Orthogonal vector algorithm to obtain the solar vector using the single-scattering Rayleigh model.

PubMed

Wang, Yinlong; Chu, Jinkui; Zhang, Ran; Shi, Chao

2018-02-01

Information obtained from a polarization pattern in the sky provides many animals like insects and birds with vital long-distance navigation cues. The solar vector can be derived from the polarization pattern using the single-scattering Rayleigh model. In this paper, an orthogonal vector algorithm, which utilizes the redundancy of the single-scattering Rayleigh model, is proposed. We use the intersection angles between the polarization vectors as the main criteria in our algorithm. The assumption that all polarization vectors can be considered coplanar is used to simplify the three-dimensional (3D) problem with respect to the polarization vectors in our simulation. The surface-normal vector of the plane, which is determined by the polarization vectors after translation, represents the solar vector. Unfortunately, the two-directionality of the polarization vectors makes the resulting solar vector ambiguous. One important result of this study is, however, that this apparent disadvantage has no effect on the complexity of the algorithm. Furthermore, two other universal least-squares algorithms were investigated and compared. A device was then constructed, which consists of five polarized-light sensors as well as a 3D attitude sensor. Both the simulation and experimental data indicate that the orthogonal vector algorithms, if used with a suitable threshold, perform equally well or better than the other two algorithms. Our experimental data reveal that if the intersection angles between the polarization vectors are close to 90°, the solar-vector angle deviations are small. The data also support the assumption of coplanarity. During the 51 min experiment, the mean of the measured solar-vector angle deviations was about 0.242°, as predicted by our theoretical model.

Floating point only SIMD instruction set architecture including compare, select, Boolean, and alignment operations

DOEpatents

Gschwind, Michael K [Chappaqua, NY

2011-03-01

Mechanisms for implementing a floating point only single instruction multiple data instruction set architecture are provided. A processor is provided that comprises an issue unit, an execution unit coupled to the issue unit, and a vector register file coupled to the execution unit. The execution unit has logic that implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA). The floating point vector registers of the vector register file store both scalar and floating point values as vectors having a plurality of vector elements. The processor may be part of a data processing system.

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.

Statistical analysis of dispersion relations in turbulent solar wind fluctuations using Cluster data

NASA Astrophysics Data System (ADS)

Perschke, C.; Narita, Y.

2012-12-01

Multi-spacecraft measurements enable us to resolve three-dimensional spatial structures without assuming Taylor's frozen-in-flow hypothesis. This is very useful to study frequency-wave vector diagram in solar wind turbulence through direct determination of three-dimensional wave vectors. The existence and evolution of dispersion relation and its role in fully-developed plasma turbulence have been drawing attention of physicists, in particular, if solar wind turbulence represents kinetic Alfvén or whistler mode as the carrier of spectral energy among different scales through wave-wave interactions. We investigate solar wind intervals of Cluster data for various flow velocities with a high-resolution wave vector analysis method, Multi-point Signal Resonator technique, at the tetrahedral separation about 100 km. Magnetic field data and ion data are used to determine the frequency- wave vector diagrams in the co-moving frame of the solar wind. We find primarily perpendicular wave vectors in solar wind turbulence which justify the earlier discussions about kinetic Alfvén or whistler wave. The frequency- wave vector diagrams confirm (a) wave vector anisotropy and (b) scattering in frequencies.

Process for structural geologic analysis of topography and point data

DOEpatents

Eliason, Jay R.; Eliason, Valerie L. C.

1987-01-01

A quantitative method of geologic structural analysis of digital terrain data is described for implementation on a computer. Assuming selected valley segments are controlled by the underlying geologic structure, topographic lows in the terrain data, defining valley bottoms, are detected, filtered and accumulated into a series line segments defining contiguous valleys. The line segments are then vectorized to produce vector segments, defining valley segments, which may be indicative of the underlying geologic structure. Coplanar analysis is performed on vector segment pairs to determine which vectors produce planes which represent underlying geologic structure. Point data such as fracture phenomena which can be related to fracture planes in 3-dimensional space can be analyzed to define common plane orientation and locations. The vectors, points, and planes are displayed in various formats for interpretation.

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.

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.

Prototype Automatic Target Screener.

DTIC Science & Technology

1980-05-19

JLIST OF TABLES I Table Page 1 PATS Modules 4 2 Vector Read/Write Command Format ( SEL4 ) 29 1 3 Read Vector Data Command Format ( SEL4 ) 30 J 4 Use Matrix...VECTOR READ/WRITE COMMAND FORMAT ( SEL4 ) S 1,4A Output 15 14 1:3 12 11 10 9 8 7 6 5 4 3 2 1 0 Da taI To VNUM VDIR V LEN InterfaceIT TNT = 1 Intensify...elements ! | 29 I TABLE 3. READ VECTOR DATA COMMAND FORMAT ( SEL4 ) SEL4 Read Vector Data Input 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 Da ta D D V To 0 A D

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

Bayesian data assimilation provides rapid decision support for vector-borne diseases.

PubMed

Jewell, Chris P; Brown, Richard G

2015-07-06

Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host-vector-pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Dynamic reduction of dimensions of a document vector in a document search and retrieval system

DOEpatents

Jiao, Yu; Potok, Thomas E.

2011-05-03

The method and system of the invention involves processing each new document (20) coming into the system into a document vector (16), and creating a document vector with reduced dimensionality (17) for comparison with the data model (15) without recomputing the data model (15). These operations are carried out by a first computer (11) while a second computer (12) updates the data model (18), which can be comprised of an initial large group of documents (19) and is premised on the computing an initial data model (13, 14, 15) to provide a reference point for determining document vectors from documents processed from the data stream (20).

Accelerating 4D flow MRI by exploiting vector field divergence regularization.

PubMed

Santelli, Claudio; Loecher, Michael; Busch, Julia; Wieben, Oliver; Schaeffter, Tobias; Kozerke, Sebastian

2016-01-01

To improve velocity vector field reconstruction from undersampled four-dimensional (4D) flow MRI by penalizing divergence of the measured flow field. Iterative image reconstruction in which magnitude and phase are regularized separately in alternating iterations was implemented. The approach allows incorporating prior knowledge of the flow field being imaged. In the present work, velocity data were regularized to reduce divergence, using either divergence-free wavelets (DFW) or a finite difference (FD) method using the ℓ1-norm of divergence and curl. The reconstruction methods were tested on a numerical phantom and in vivo data. Results of the DFW and FD approaches were compared with data obtained with standard compressed sensing (CS) reconstruction. Relative to standard CS, directional errors of vector fields and divergence were reduced by 55-60% and 38-48% for three- and six-fold undersampled data with the DFW and FD methods. Velocity vector displays of the numerical phantom and in vivo data were found to be improved upon DFW or FD reconstruction. Regularization of vector field divergence in image reconstruction from undersampled 4D flow data is a valuable approach to improve reconstruction accuracy of velocity vector fields. © 2014 Wiley Periodicals, Inc.

Matrix multiplication operations with data pre-conditioning in a high performance computing architecture

DOEpatents

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

2013-11-05

Mechanisms for performing matrix multiplication operations with data pre-conditioning in a high performance computing architecture 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 load and splat operation is performed to load an element of a second vector operand and replicating the element to each of a plurality of elements of a second target vector register. A multiply add 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 of the matrix multiplication operation is accumulated with other partial products of the matrix multiplication operation.

Bayesian data assimilation provides rapid decision support for vector-borne diseases

PubMed Central

Jewell, Chris P.; Brown, Richard G.

2015-01-01

Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host–vector–pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks. PMID:26136225

A COMPARISON OF VECTOR AND RASTER GIS METHODS FOR CALCULATING LANDSCAPE METRICS USED IN ENVIRONMENTAL ASSESSMENTS

EPA Science Inventory

GIS-based measurements that combine native raster and native vector data are commonly used to assess environmental quality. Most of these measurements can be calculated using either raster or vector data formats and processing methods. Raster processes are more commonly used beca...

A feature selection approach towards progressive vector transmission over the Internet

NASA Astrophysics Data System (ADS)

Miao, Ru; Song, Jia; Feng, Min

2017-09-01

WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

Optimal source coding, removable noise elimination, and natural coordinate system construction for general vector sources using replicator neural networks

NASA Astrophysics Data System (ADS)

Hecht-Nielsen, Robert

1997-04-01

A new universal one-chart smooth manifold model for vector information sources is introduced. Natural coordinates (a particular type of chart) for such data manifolds are then defined. Uniformly quantized natural coordinates form an optimal vector quantization code for a general vector source. Replicator neural networks (a specialized type of multilayer perceptron with three hidden layers) are the introduced. As properly configured examples of replicator networks approach minimum mean squared error (e.g., via training and architecture adjustment using randomly chosen vectors from the source), these networks automatically develop a mapping which, in the limit, produces natural coordinates for arbitrary source vectors. The new concept of removable noise (a noise model applicable to a wide variety of real-world noise processes) is then discussed. Replicator neural networks, when configured to approach minimum mean squared reconstruction error (e.g., via training and architecture adjustment on randomly chosen examples from a vector source, each with randomly chosen additive removable noise contamination), in the limit eliminate removable noise and produce natural coordinates for the data vector portions of the noise-corrupted source vectors. Consideration regarding selection of the dimension of a data manifold source model and the training/configuration of replicator neural networks are discussed.

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.

Application of information-retrieval methods to the classification of physical data

NASA Technical Reports Server (NTRS)

Mamotko, Z. N.; Khorolskaya, S. K.; Shatrovskiy, L. I.

1975-01-01

Scientific data received from satellites are characterized as a multi-dimensional time series, whose terms are vector functions of a vector of measurement conditions. Information retrieval methods are used to construct lower dimensional samples on the basis of the condition vector, in order to obtain these data and to construct partial relations. The methods are applied to the joint Soviet-French Arkad project.

Air travel and vector-borne disease movement.

PubMed

Tatem, A J; Huang, Z; Das, A; Qi, Q; Roth, J; Qiu, Y

2012-12-01

Recent decades have seen substantial expansions in the global air travel network and rapid increases in traffic volumes. The effects of this are well studied in terms of the spread of directly transmitted infections, but the role of air travel in the movement of vector-borne diseases is less well understood. Increasingly however, wider reaching surveillance for vector-borne diseases and our improving abilities to map the distributions of vectors and the diseases they carry, are providing opportunities to better our understanding of the impact of increasing air travel. Here we examine global trends in the continued expansion of air transport and its impact upon epidemiology. Novel malaria and chikungunya examples are presented, detailing how geospatial data in combination with information on air traffic can be used to predict the risks of vector-borne disease importation and establishment. Finally, we describe the development of an online tool, the Vector-Borne Disease Airline Importation Risk (VBD-Air) tool, which brings together spatial data on air traffic and vector-borne disease distributions to quantify the seasonally changing risks for importation to non-endemic regions. Such a framework provides the first steps towards an ultimate goal of adaptive management based on near real time flight data and vector-borne disease surveillance.

A recursive technique for adaptive vector quantization

NASA Technical Reports Server (NTRS)

Lindsay, Robert A.

1989-01-01

Vector Quantization (VQ) is fast becoming an accepted, if not preferred method for image compression. The VQ performs well when compressing all types of imagery including Video, Electro-Optical (EO), Infrared (IR), Synthetic Aperture Radar (SAR), Multi-Spectral (MS), and digital map data. The only requirement is to change the codebook to switch the compressor from one image sensor to another. There are several approaches for designing codebooks for a vector quantizer. Adaptive Vector Quantization is a procedure that simultaneously designs codebooks as the data is being encoded or quantized. This is done by computing the centroid as a recursive moving average where the centroids move after every vector is encoded. When computing the centroid of a fixed set of vectors the resultant centroid is identical to the previous centroid calculation. This method of centroid calculation can be easily combined with VQ encoding techniques. The defined quantizer changes after every encoded vector by recursively updating the centroid of minimum distance which is the selected by the encoder. Since the quantizer is changing definition or states after every encoded vector, the decoder must now receive updates to the codebook. This is done as side information by multiplexing bits into the compressed source data.

Identification of cardiac rhythm features by mathematical analysis of vector fields.

PubMed

Fitzgerald, Tamara N; Brooks, Dana H; Triedman, John K

2005-01-01

Automated techniques for locating cardiac arrhythmia features are limited, and cardiologists generally rely on isochronal maps to infer patterns in the cardiac activation sequence during an ablation procedure. Velocity vector mapping has been proposed as an alternative method to study cardiac activation in both clinical and research environments. In addition to the visual cues that vector maps can provide, vector fields can be analyzed using mathematical operators such as the divergence and curl. In the current study, conduction features were extracted from velocity vector fields computed from cardiac mapping data. The divergence was used to locate ectopic foci and wavefront collisions, and the curl to identify central obstacles in reentrant circuits. Both operators were applied to simulated rhythms created from a two-dimensional cellular automaton model, to measured data from an in situ experimental canine model, and to complex three-dimensional human cardiac mapping data sets. Analysis of simulated vector fields indicated that the divergence is useful in identifying ectopic foci, with a relatively small number of vectors and with errors of up to 30 degrees in the angle measurements. The curl was useful for identifying central obstacles in reentrant circuits, and the number of velocity vectors needed increased as the rhythm became more complex. The divergence was able to accurately identify canine in situ pacing sites, areas of breakthrough activation, and wavefront collisions. In data from human arrhythmias, the divergence reliably estimated origins of electrical activity and wavefront collisions, but the curl was less reliable at locating central obstacles in reentrant circuits, possibly due to the retrospective nature of data collection. The results indicate that the curl and divergence operators applied to velocity vector maps have the potential to add valuable information in cardiac mapping and can be used to supplement human pattern recognition.

Dynamic visualization of data streams

DOEpatents

Wong, Pak Chung [Richalnd, WA; Foote, Harlan P [Richland, WA; Adams, Daniel R [Kennewick, WA; Cowley, Wendy E [Richland, WA; Thomas, James J [Richland, WA

2009-07-07

One embodiment of the present invention includes a data communication subsystem to receive a data stream, and a data processing subsystem responsive to the data communication subsystem to generate a visualization output based on a group of data vectors corresponding to a first portion of the data stream. The processing subsystem is further responsive to a change in rate of receipt of the data to modify the visualization output with one or more other data vectors corresponding to a second portion of the data stream as a function of eigenspace defined with the group of data vectors. The system further includes a display device responsive to the visualization output to provide a corresponding visualization.

Tiled vector data model for the geographical features of symbolized maps.

PubMed

Li, Lin; Hu, Wei; Zhu, Haihong; Li, You; Zhang, Hang

2017-01-01

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Representation and display of vector field topology in fluid flow data sets

NASA Technical Reports Server (NTRS)

Helman, James; Hesselink, Lambertus

1989-01-01

The visualization of physical processes in general and of vector fields in particular is discussed. An approach to visualizing flow topology that is based on the physics and mathematics underlying the physical phenomenon is presented. It involves determining critical points in the flow where the velocity vector vanishes. The critical points, connected by principal lines or planes, determine the topology of the flow. The complexity of the data is reduced without sacrificing the quantitative nature of the data set. By reducing the original vector field to a set of critical points and their connections, a representation of the topology of a two-dimensional vector field that is much smaller than the original data set but retains with full precision the information pertinent to the flow topology is obtained. This representation can be displayed as a set of points and tangent curves or as a graph. Analysis (including algorithms), display, interaction, and implementation aspects are discussed.

Multi-perspective views of students’ difficulties with one-dimensional vector and two-dimensional vector

NASA Astrophysics Data System (ADS)

Fauzi, Ahmad; Ratna Kawuri, Kunthi; Pratiwi, Retno

2017-01-01

Researchers of students’ conceptual change usually collects data from written tests and interviews. Moreover, reports of conceptual change often simply refer to changes in concepts, such as on a test, without any identification of the learning processes that have taken place. Research has shown that students have difficulties with vectors in university introductory physics courses and high school physics courses. In this study, we intended to explore students’ understanding of one-dimensional and two-dimensional vector in multi perspective views. In this research, we explore students’ understanding through test perspective and interviews perspective. Our research study adopted the mixed-methodology design. The participants of this research were sixty students of third semester of physics education department. The data of this research were collected by testand interviews. In this study, we divided the students’ understanding of one-dimensional vector and two-dimensional vector in two categories, namely vector skills of the addition of one-dimensionaland two-dimensional vector and the relation between vector skills and conceptual understanding. From the investigation, only 44% of students provided correct answer for vector skills of the addition of one-dimensional and two-dimensional vector and only 27% students provided correct answer for the relation between vector skills and conceptual understanding.

Automated innovative diagnostic, data management and communication tool, for improving malaria vector control in endemic settings.

PubMed

Vontas, John; Mitsakakis, Konstantinos; Zengerle, Roland; Yewhalaw, Delenasaw; Sikaala, Chadwick Haadezu; Etang, Josiane; Fallani, Matteo; Carman, Bill; Müller, Pie; Chouaïbou, Mouhamadou; Coleman, Marlize; Coleman, Michael

2016-01-01

Malaria is a life-threatening disease that caused more than 400,000 deaths in sub-Saharan Africa in 2015. Mass prevention of the disease is best achieved by vector control which heavily relies on the use of insecticides. Monitoring mosquito vector populations is an integral component of control programs and a prerequisite for effective interventions. Several individual methods are used for this task; however, there are obstacles to their uptake, as well as challenges in organizing, interpreting and communicating vector population data. The Horizon 2020 project "DMC-MALVEC" consortium will develop a fully integrated and automated multiplex vector-diagnostic platform (LabDisk) for characterizing mosquito populations in terms of species composition, Plasmodium infections and biochemical insecticide resistance markers. The LabDisk will be interfaced with a Disease Data Management System (DDMS), a custom made data management software which will collate and manage data from routine entomological monitoring activities providing information in a timely fashion based on user needs and in a standardized way. The ResistanceSim, a serious game, a modern ICT platform that uses interactive ways of communicating guidelines and exemplifying good practices of optimal use of interventions in the health sector will also be a key element. The use of the tool will teach operational end users the value of quality data (relevant, timely and accurate) to make informed decisions. The integrated system (LabDisk, DDMS & ResistanceSim) will be evaluated in four malaria endemic countries, representative of the vector control challenges in sub-Saharan Africa, (Cameroon, Ivory Coast, Ethiopia and Zambia), highly representative of malaria settings with different levels of endemicity and vector control challenges, to support informed decision-making in vector control and disease management.

Product Quality Modelling Based on Incremental Support Vector Machine

NASA Astrophysics Data System (ADS)

Wang, J.; Zhang, W.; Qin, B.; Shi, W.

2012-05-01

Incremental Support vector machine (ISVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. It is suitable for the problem of sequentially arriving field data and has been widely used for product quality prediction and production process optimization. However, the traditional ISVM learning does not consider the quality of the incremental data which may contain noise and redundant data; it will affect the learning speed and accuracy to a great extent. In order to improve SVM training speed and accuracy, a modified incremental support vector machine (MISVM) is proposed in this paper. Firstly, the margin vectors are extracted according to the Karush-Kuhn-Tucker (KKT) condition; then the distance from the margin vectors to the final decision hyperplane is calculated to evaluate the importance of margin vectors, where the margin vectors are removed while their distance exceed the specified value; finally, the original SVs and remaining margin vectors are used to update the SVM. The proposed MISVM can not only eliminate the unimportant samples such as noise samples, but also can preserve the important samples. The MISVM has been experimented on two public data and one field data of zinc coating weight in strip hot-dip galvanizing, and the results shows that the proposed method can improve the prediction accuracy and the training speed effectively. Furthermore, it can provide the necessary decision supports and analysis tools for auto control of product quality, and also can extend to other process industries, such as chemical process and manufacturing process.

Monitoring by Use of Clusters of Sensor-Data Vectors

NASA Technical Reports Server (NTRS)

Iverson, David L.

2007-01-01

The inductive monitoring system (IMS) is a system of computer hardware and software for automated monitoring of the performance, operational condition, physical integrity, and other aspects of the health of a complex engineering system (e.g., an industrial process line or a spacecraft). The input to the IMS consists of streams of digitized readings from sensors in the monitored system. The IMS determines the type and amount of any deviation of the monitored system from a nominal or normal ( healthy ) condition on the basis of a comparison between (1) vectors constructed from the incoming sensor data and (2) corresponding vectors in a database of nominal or normal behavior. The term inductive reflects the use of a process reminiscent of traditional mathematical induction to learn about normal operation and build the nominal-condition database. The IMS offers two major advantages over prior computational monitoring systems: The computational burden of the IMS is significantly smaller, and there is no need for abnormal-condition sensor data for training the IMS to recognize abnormal conditions. The figure schematically depicts the relationships among the computational processes effected by the IMS. Training sensor data are gathered during normal operation of the monitored system, detailed computational simulation of operation of the monitored system, or both. The training data are formed into vectors that are used to generate the database. The vectors in the database are clustered into regions that represent normal or nominal operation. Once the database has been generated, the IMS compares the vectors of incoming sensor data with vectors representative of the clusters. The monitored system is deemed to be operating normally or abnormally, depending on whether the vector of incoming sensor data is or is not, respectively, sufficiently close to one of the clusters. For this purpose, a distance between two vectors is calculated by a suitable metric (e.g., Euclidean distance) and "sufficiently close" signifies lying at a distance less than a specified threshold value. It must be emphasized that although the IMS is intended to detect off-nominal or abnormal performance or health, it is not necessarily capable of performing a thorough or detailed diagnosis. Limited diagnostic information may be available under some circumstances. For example, the distance of a vector of incoming sensor data from the nearest cluster could serve as an indication of the severity of a malfunction. The identity of the nearest cluster may be a clue as to the identity of the malfunctioning component or subsystem. It is possible to decrease the IMS computation time by use of a combination of cluster-indexing and -retrieval methods. For example, in one method, the distances between each cluster and two or more reference vectors can be used for the purpose of indexing and retrieval. The clusters are sorted into a list according to these distance values, typically in ascending order of distance. When a set of input data arrives and is to be tested, the data are first arranged as an ordered set (that is, a vector). The distances from the input vector to the reference points are computed. The search of clusters from the list can then be limited to those clusters lying within a certain distance range from the input vector; the computation time is reduced by not searching the clusters at a greater distance.

The role of remote sensing and GIS for spatial prediction of vector-borne diseases transmission: a systematic review.

PubMed

Palaniyandi, M

2012-12-01

There have been several attempts made to the appreciation of remote sensing and GIS for the study of vectors, biodiversity, vector presence, vector abundance and the vector-borne diseases with respect to space and time. This study was made for reviewing and appraising the potential use of remote sensing and GIS applications for spatial prediction of vector-borne diseases transmission. The nature of the presence and the abundance of vectors and vector-borne diseases, disease infection and the disease transmission are not ubiquitous and are confined with geographical, environmental and climatic factors, and are localized. The presence of vectors and vector-borne diseases is most complex in nature, however, it is confined and fueled by the geographical, climatic and environmental factors including man-made factors. The usefulness of the present day availability of the information derived from the satellite data including vegetation indices of canopy cover and its density, soil types, soil moisture, soil texture, soil depth, etc. is integrating the information in the expert GIS engine for the spatial analysis of other geoclimatic and geoenvironmental variables. The present study gives the detailed information on the classical studies of the past and present, and the future role of remote sensing and GIS for the vector-borne diseases control. The ecological modeling directly gives us the relevant information to understand the spatial variation of the vector biodiversity, vector presence, vector abundance and the vector-borne diseases in association with geoclimatic and the environmental variables. The probability map of the geographical distribution and seasonal variations of horizontal and vertical distribution of vector abundance and its association with vector -borne diseases can be obtained with low cost remote sensing and GIS tool with reliable data and speed.

Real-time optical laboratory solution of parabolic differential equations

NASA Technical Reports Server (NTRS)

Casasent, David; Jackson, James

1988-01-01

An optical laboratory matrix-vector processor is used to solve parabolic differential equations (the transient diffusion equation with two space variables and time) by an explicit algorithm. This includes optical matrix-vector nonbase-2 encoded laboratory data, the combination of nonbase-2 and frequency-multiplexed data on such processors, a high-accuracy optical laboratory solution of a partial differential equation, new data partitioning techniques, and a discussion of a multiprocessor optical matrix-vector architecture.

A Comparison of Vector and Raster GIS Methods for Calculating Landscape Metrics Used in Environmental Assessments

Treesearch

Timothy G. Wade; James D. Wickham; Maliha S. Nash; Anne C. Neale; Kurt H. Riitters; K. Bruce Jones

2003-01-01

AbstractGIS-based measurements that combine native raster and native vector data are commonly used in environmental assessments. Most of these measurements can be calculated using either raster or vector data formats and processing methods. Raster processes are more commonly used because they can be significantly faster computationally...

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields

PubMed Central

Zhao, Henan; Bryant, Garnett W.; Griffin, Wesley; Terrill, Judith E.; Chen, Jian

2017-01-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks. PMID:28113469

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields.

PubMed

Henan Zhao; Bryant, Garnett W; Griffin, Wesley; Terrill, Judith E; Jian Chen

2017-06-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks.

Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach.

PubMed

Mitsakakis, Konstantinos; Hin, Sebastian; Müller, Pie; Wipf, Nadja; Thomsen, Edward; Coleman, Michael; Zengerle, Roland; Vontas, John; Mavridis, Konstantinos

2018-02-03

Monitoring malaria prevalence in humans, as well as vector populations, for the presence of Plasmodium , is an integral component of effective malaria control, and eventually, elimination. In the field of human diagnostics, a major challenge is the ability to define, precisely, the causative agent of fever, thereby differentiating among several candidate (also non-malaria) febrile diseases. This requires genetic-based pathogen identification and multiplexed analysis, which, in combination, are hardly provided by the current gold standard diagnostic tools. In the field of vectors, an essential component of control programs is the detection of Plasmodium species within its mosquito vectors, particularly in the salivary glands, where the infective sporozoites reside. In addition, the identification of species composition and insecticide resistance alleles within vector populations is a primary task in routine monitoring activities, aiming to support control efforts. In this context, the use of converging diagnostics is highly desirable for providing comprehensive information, including differential fever diagnosis in humans, and mosquito species composition, infection status, and resistance to insecticides of vectors. Nevertheless, the two fields of human diagnostics and vector control are rarely combined, both at the diagnostic and at the data management end, resulting in fragmented data and mis- or non-communication between various stakeholders. To this direction, molecular technologies, their integration in automated platforms, and the co-assessment of data from multiple diagnostic sources through information and communication technologies are possible pathways towards a unified human vector approach.

Converging Human and Malaria Vector Diagnostics with Data Management towards an Integrated Holistic One Health Approach

PubMed Central

Mitsakakis, Konstantinos; Hin, Sebastian; Wipf, Nadja; Coleman, Michael; Zengerle, Roland; Vontas, John; Mavridis, Konstantinos

2018-01-01

Monitoring malaria prevalence in humans, as well as vector populations, for the presence of Plasmodium, is an integral component of effective malaria control, and eventually, elimination. In the field of human diagnostics, a major challenge is the ability to define, precisely, the causative agent of fever, thereby differentiating among several candidate (also non-malaria) febrile diseases. This requires genetic-based pathogen identification and multiplexed analysis, which, in combination, are hardly provided by the current gold standard diagnostic tools. In the field of vectors, an essential component of control programs is the detection of Plasmodium species within its mosquito vectors, particularly in the salivary glands, where the infective sporozoites reside. In addition, the identification of species composition and insecticide resistance alleles within vector populations is a primary task in routine monitoring activities, aiming to support control efforts. In this context, the use of converging diagnostics is highly desirable for providing comprehensive information, including differential fever diagnosis in humans, and mosquito species composition, infection status, and resistance to insecticides of vectors. Nevertheless, the two fields of human diagnostics and vector control are rarely combined, both at the diagnostic and at the data management end, resulting in fragmented data and mis- or non-communication between various stakeholders. To this direction, molecular technologies, their integration in automated platforms, and the co-assessment of data from multiple diagnostic sources through information and communication technologies are possible pathways towards a unified human vector approach. PMID:29401670

Classification of a set of vectors using self-organizing map- and rule-based technique

NASA Astrophysics Data System (ADS)

Ae, Tadashi; Okaniwa, Kaishirou; Nosaka, Kenzaburou

2005-02-01

There exist various objects, such as pictures, music, texts, etc., around our environment. We have a view for these objects by looking, reading or listening. Our view is concerned with our behaviors deeply, and is very important to understand our behaviors. We have a view for an object, and decide the next action (data selection, etc.) with our view. Such a series of actions constructs a sequence. Therefore, we propose a method which acquires a view as a vector from several words for a view, and apply the vector to sequence generation. We focus on sequences of the data of which a user selects from a multimedia database containing pictures, music, movie, etc... These data cannot be stereotyped because user's view for them changes by each user. Therefore, we represent the structure of the multimedia database as the vector representing user's view and the stereotyped vector, and acquire sequences containing the structure as elements. Such a vector can be classified by SOM (Self-Organizing Map). Hidden Markov Model (HMM) is a method to generate sequences. Therefore, we use HMM of which a state corresponds to the representative vector of user's view, and acquire sequences containing the change of user's view. We call it Vector-state Markov Model (VMM). We introduce the rough set theory as a rule-base technique, which plays a role of classifying the sets of data such as the sets of "Tour".

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.

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

Complex matrix multiplication operations with data pre-conditioning in a high performance computing architecture

DOEpatents

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

2014-02-11

Mechanisms for performing a complex matrix multiplication operation are provided. A vector load operation is performed to load a first vector operand of the complex matrix multiplication operation to a first target vector register. The first vector operand comprises a real and imaginary part of a first complex vector value. A complex load and splat operation is performed to load a second complex vector value of a second vector operand and replicate the second complex vector value within a second target vector register. The second complex vector value has a real and imaginary part. A cross multiply add 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 complex matrix multiplication operation. The partial product is accumulated with other partial products and a resulting accumulated partial product is stored in a result vector register.

The magnetic field investigation on Cluster

NASA Technical Reports Server (NTRS)

Balogh, A.; Cowley, S. W. H.; Southwood, D. J.; Musmann, G.; Luhr, H.; Neubauer, F. M.; Glassmeier, K.-H.; Riedler, W.; Heyn, M. F.; Acuna, M. H.

1988-01-01

The magnetic field investigation of the Cluster four-spacecraft mission is designed to provide intercalibrated measurements of the B magnetic field vector. The instrumentation and data processing of the mission are discussed. The instrumentation is identical on the four spacecraft. It consists of two triaxial fluxgate sensors and of a failure tolerant data processing unit. The combined analysis of the four spacecraft data will yield such parameters as the current density vector, wave vectors, and the geometry and structure of discontinuities.

On the Impact of Widening Vector Registers on Sequence Alignment

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

Daily, Jeffrey A.; Kalyanaraman, Anantharaman; Krishnamoorthy, Sriram

2016-09-22

Vector extensions, such as SSE, have been part of the x86 since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. In this paper, we demonstrate that the trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based onmore » striped data layouts. We present a practically efficient SIMD implementation of a parallel scan based sequence alignment algorithm that can better exploit wider SIMD units. We conduct comprehensive workload and use case analyses to characterize the relative behavior of the striped and scan approaches and identify the best choice of algorithm based on input length and SIMD width.« less

Conditional Tests for Localizing Trait Genes

PubMed Central

Di, Yanming; Thompson, Elizabeth A.

2009-01-01

Background/Aims With pedigree data, genetic linkage can be detected using inheritance vector tests, which explore the discrepancy between the posterior distribution of the inheritance vectors given observed trait values and the prior distribution of the inheritance vectors. In this paper, we propose conditional inheritance vector tests for linkage localization. These conditional tests can also be used to detect additional linkage signals in the presence of previously detected causal genes. Methods For linkage localization, we propose to perform inheritance vector tests conditioning on the inheritance vectors at two positions bounding a test region. We can detect additional linkage signals by conducting a further conditional test in a region with no previously detected genes. We use randomized p values to extend the marginal and conditional tests when the inheritance vectors cannot be completely determined from genetic marker data. Results We conduct simulation studies to compare and contrast the marginal and the conditional tests and to demonstrate that randomized p values can capture both the significance and the uncertainty in the test results. Conclusions The simulation results demonstrate that the proposed conditional tests provide useful localization information, and with informative marker data, the uncertainty in randomized marginal and conditional test results is small. PMID:19439976

Exploiting Vector and Multicore Parallelsim for Recursive, Data- and Task-Parallel Programs

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

Ren, Bin; Krishnamoorthy, Sriram; Agrawal, Kunal

Modern hardware contains parallel execution resources that are well-suited for data-parallelism-vector units-and task parallelism-multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task- blocks on vector units or multicores. We show that thesemore » schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel pro- grams into task block-based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14×-108× speedup over sequential baselines.« less

Quantum Support Vector Machine for Big Data Classification

NASA Astrophysics Data System (ADS)

Rebentrost, Patrick; Mohseni, Masoud; Lloyd, Seth

2014-09-01

Supervised machine learning is the classification of new data based on already classified training examples. In this work, we show that the support vector machine, an optimized binary classifier, can be implemented on a quantum computer, with complexity logarithmic in the size of the vectors and the number of training examples. In cases where classical sampling algorithms require polynomial time, an exponential speedup is obtained. At the core of this quantum big data algorithm is a nonsparse matrix exponentiation technique for efficiently performing a matrix inversion of the training data inner-product (kernel) matrix.

A Code Generation Approach for Auto-Vectorization in the Spade Compiler

NASA Astrophysics Data System (ADS)

Wang, Huayong; Andrade, Henrique; Gedik, Buğra; Wu, Kun-Lung

We describe an auto-vectorization approach for the Spade stream processing programming language, comprising two ideas. First, we provide support for vectors as a primitive data type. Second, we provide a C++ library with architecture-specific implementations of a large number of pre-vectorized operations as the means to support language extensions. We evaluate our approach with several stream processing operators, contrasting Spade's auto-vectorization with the native auto-vectorization provided by the GNU gcc and Intel icc compilers.

Surveillance of Arthropod Vector-Borne Infectious Diseases Using Remote Sensing Techniques: A Review

PubMed Central

Kalluri, Satya; Gilruth, Peter; Rogers, David; Szczur, Martha

2007-01-01

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between remote sensing scientists and biologists, and the availability of sophisticated, statistical geographic information system and image processing algorithms in a desktop environment creates a fertile research environment. The use of remote sensing techniques to map vector-borne diseases has evolved significantly over the past 25 years. In this paper, we review the status of remote sensing studies of arthropod vector-borne diseases due to mosquitoes, ticks, blackflies, tsetse flies, and sandflies, which are responsible for the majority of vector-borne diseases in the world. Examples of simple image classification techniques that associate land use and land cover types with vector habitats, as well as complex statistical models that link satellite-derived multi-temporal meteorological observations with vector biology and abundance, are discussed here. Future improvements in remote sensing applications in epidemiology are also discussed. PMID:17967056

The Interaction between Vector Life History and Short Vector Life in Vector-Borne Disease Transmission and Control.

PubMed

Brand, Samuel P C; Rock, Kat S; Keeling, Matt J

2016-04-01

Epidemiological modelling has a vital role to play in policy planning and prediction for the control of vectors, and hence the subsequent control of vector-borne diseases. To decide between competing policies requires models that can generate accurate predictions, which in turn requires accurate knowledge of vector natural histories. Here we highlight the importance of the distribution of times between life-history events, using short-lived midge species as an example. In particular we focus on the distribution of the extrinsic incubation period (EIP) which determines the time between infection and becoming infectious, and the distribution of the length of the gonotrophic cycle which determines the time between successful bites. We show how different assumptions for these periods can radically change the basic reproductive ratio (R0) of an infection and additionally the impact of vector control on the infection. These findings highlight the need for detailed entomological data, based on laboratory experiments and field data, to correctly construct the next-generation of policy-informing models.

Analysis of structural response data using discrete modal filters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Freudinger, Lawrence C.

1991-01-01

The application of reciprocal modal vectors to the analysis of structural response data is described. Reciprocal modal vectors are constructed using an existing experimental modal model and an existing frequency response matrix of a structure, and can be assembled into a matrix that effectively transforms the data from the physical space to a modal space within a particular frequency range. In other words, the weighting matrix necessary for modal vector orthogonality (typically the mass matrix) is contained within the reciprocal model matrix. The underlying goal of this work is mostly directed toward observing the modal state responses in the presence of unknown, possibly closed loop forcing functions, thus having an impact on both operating data analysis techniques and independent modal space control techniques. This study investigates the behavior of reciprocol modal vectors as modal filters with respect to certain calculation parameters and their performance with perturbed system frequency response data.

GLOBE Observer Mosquito Habitat Mapper: Geoscience and Public Health Connections

NASA Astrophysics Data System (ADS)

Low, R.; Boger, R. A.

2017-12-01

The global health crisis posed by vector-borne diseases is so great in scope that it is clearly insurmountable without the active help of tens-or hundreds- of thousands of individuals, working to identify and eradicate risk in communities around the world. Mobile devices equipped with data collection capabilities and visualization opportunities are lowering the barrier for participation in data collection efforts. The GLOBE Observer Mosquito Habitat Mapper (MHM) provides citizen scientists with an easy to use mobile platform to identify and locate mosquito breeding sites in their community. The app also supports the identification of vector taxa in the larvae development phase via a built-in key, which provides important information for scientists and public health officials tracking the rate of range expansion of invasive vector species and associated health threats. GO Mosquito is actively working with other citizen scientist programs across the world to ensure interoperability of data through standardization of metadata fields specific to vector monitoring, and through the development of APIs that allow for data exchange and shared data display through a UN-sponsored proof of concept project, Global Mosquito Alert. Avenues of application for mosquito vector data-both directly, by public health entities, and by modelers who employ remotely sensed environmental data to project mosquito population dynamics and epidemic disease will be featured.

Non-coaxial superposition of vector vortex beams.

PubMed

Aadhi, A; Vaity, Pravin; Chithrabhanu, P; Reddy, Salla Gangi; Prabakar, Shashi; Singh, R P

2016-02-10

Vector vortex beams are classified into four types depending upon spatial variation in their polarization vector. We have generated all four of these types of vector vortex beams by using a modified polarization Sagnac interferometer with a vortex lens. Further, we have studied the non-coaxial superposition of two vector vortex beams. It is observed that the superposition of two vector vortex beams with same polarization singularity leads to a beam with another kind of polarization singularity in their interaction region. The results may be of importance in ultrahigh security of the polarization-encrypted data that utilizes vector vortex beams and multiple optical trapping with non-coaxial superposition of vector vortex beams. We verified our experimental results with theory.

Data-driven identification of potential Zika virus vectors

PubMed Central

Evans, Michelle V; Dallas, Tad A; Han, Barbara A; Murdock, Courtney C; Drake, John M

2017-01-01

Zika is an emerging virus whose rapid spread is of great public health concern. Knowledge about transmission remains incomplete, especially concerning potential transmission in geographic areas in which it has not yet been introduced. To identify unknown vectors of Zika, we developed a data-driven model linking vector species and the Zika virus via vector-virus trait combinations that confer a propensity toward associations in an ecological network connecting flaviviruses and their mosquito vectors. Our model predicts that thirty-five species may be able to transmit the virus, seven of which are found in the continental United States, including Culex quinquefasciatus and Cx. pipiens. We suggest that empirical studies prioritize these species to confirm predictions of vector competence, enabling the correct identification of populations at risk for transmission within the United States. DOI: http://dx.doi.org/10.7554/eLife.22053.001 PMID:28244371

Computational Investigation of Fluidic Counterflow Thrust Vectoring

NASA Technical Reports Server (NTRS)

Hunter, Craig A.; Deere, Karen A.

1999-01-01

A computational study of fluidic counterflow thrust vectoring has been conducted. Two-dimensional numerical simulations were run using the computational fluid dynamics code PAB3D with two-equation turbulence closure and linear Reynolds stress modeling. For validation, computational results were compared to experimental data obtained at the NASA Langley Jet Exit Test Facility. In general, computational results were in good agreement with experimental performance data, indicating that efficient thrust vectoring can be obtained with low secondary flow requirements (less than 1% of the primary flow). An examination of the computational flowfield has revealed new details about the generation of a countercurrent shear layer, its relation to secondary suction, and its role in thrust vectoring. In addition to providing new information about the physics of counterflow thrust vectoring, this work appears to be the first documented attempt to simulate the counterflow thrust vectoring problem using computational fluid dynamics.

Ice Shape Characterization Using Self-Organizing Maps

NASA Technical Reports Server (NTRS)

McClain, Stephen T.; Tino, Peter; Kreeger, Richard E.

2011-01-01

A method for characterizing ice shapes using a self-organizing map (SOM) technique is presented. Self-organizing maps are neural-network techniques for representing noisy, multi-dimensional data aligned along a lower-dimensional and possibly nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. In information processing, the intent of SOM methods is to transmit the codebook vectors, which contains far fewer elements and requires much less memory or bandwidth, than the original noisy data set. When applied to airfoil ice accretion shapes, the properties of the codebook vectors and the statistical nature of the SOM methods allows for a quantitative comparison of experimentally measured mean or average ice shapes to ice shapes predicted using computer codes such as LEWICE. The nature of the codebook vectors also enables grid generation and surface roughness descriptions for use with the discrete-element roughness approach. In the present study, SOM characterizations are applied to a rime ice shape, a glaze ice shape at an angle of attack, a bi-modal glaze ice shape, and a multi-horn glaze ice shape. Improvements and future explorations will be discussed.

BOREAS TE-20 Soils Data Over the NSA-MSA and Tower Sites in Vector Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Veldhuis, Hugo; Knapp, David

2000-01-01

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were converted to ARCANFO EXPORT files. These data cover 1-kilometer diameters around each of the NSA tower sites, and another layer covers the NSA-MSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Improvements and Advances to the Cross-Calibrated Multi-Platform (CCMP) Ocean Vector Wind Analysis (V2.0 release)

NASA Astrophysics Data System (ADS)

Scott, J. P.; Wentz, F. J.; Hoffman, R. N.; Atlas, R. M.

2016-02-01

Ocean vector wind is a valuable climate data record (CDR) useful in observing and monitoring changes in climate and air-sea interactions. Ocean surface wind stress influences such processes as heat, moisture, and momentum fluxes between the atmosphere and ocean, driving ocean currents and forcing ocean circulation. The Cross-Calibrated Multi-Platform (CCMP) ocean vector wind analysis is a quarter-degree, six-hourly global ocean wind analysis product created using the variational analysis method (VAM) [Atlas et al., 1996; Hoffman et al., 2003]. The CCMP V1.1 wind product is a highly-esteemed, widely-used data set containing the longest gap-free record of satellite-based ocean vector wind data (July 1987 to June 2012). CCMP V1.1 was considered a "first-look" data set that used the most-timely, albeit preliminary, releases of satellite, in situ, and modeled ECMWF-Operational wind background fields. The authors have been working with the original producers of CCMP V1.1 to create an updated, improved, and consistently-reprocessed CCMP V2.0 ocean vector wind analysis data set. With Remote Sensing Systems (RSS) having recently updated all passive microwave satellite instrument calibrations and retrievals to the RSS Version-7 RTM standard, the reprocessing of the CCMP data set into a higher-quality CDR using inter-calibrated satellite inputs became feasible. In addition to the use of SSM/I, SSMIS, TRMM TMI, QuikSCAT, AMSRE, and WindSat instruments, AMSR2, GMI, and ASCAT have been also included in the CCMP V2.0 data set release, which has now been extended to the beginning of 2015. Additionally, the background field has been updated to use six-hourly, quarter-degree ERA-Interim wind vector inputs, and the quality-checks on the in situ data have been carefully reviewed and improved. The goal of the release of the CCMP V2.0 ocean wind vector analysis product is to serve as a merged ocean wind vector data set for climate studies. Diligent effort has been made by the authors to minimize systematic and spurious sources of error. The authors will present a complete discussion of upgrades made to the CCMP V2.0 data set, as well as present validation work that has been completed on the CCMP V2.0 wind analysis product.

Generating and executing programs for a floating point single instruction multiple data instruction set architecture

DOEpatents

Gschwind, Michael K

2013-04-16

Mechanisms for generating and executing programs for a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA) are provided. A computer program product comprising a computer recordable medium having a computer readable program recorded thereon is provided. The computer readable program, when executed on a computing device, causes the computing device to receive one or more instructions and execute the one or more instructions using logic in an execution unit of the computing device. The logic implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA), based on data stored in a vector register file of the computing device. The vector register file is configured to store both scalar and floating point values as vectors having a plurality of vector elements.

Search for dark matter in proton-proton collisions at 8 TeV with missing transverse momentum and vector boson tagged jets

DOE PAGES

Khachatryan, Vardan

2016-12-16

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 inverse femtobarns collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. Thismore » search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. As a result, mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded.« less

Search for dark matter in proton-proton collisions at 8 TeV with missing transverse momentum and vector boson tagged jets

NASA Astrophysics Data System (ADS)

CMS Collaboration; Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Forthomme, L.; Francois, B.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Nuttens, C.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; 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.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Micanovic, S.; Sudic, L.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Calpas, B.; Kadastik, M.; Murumaa, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Peltola, T.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; 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.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schomakers, C.; Schulte, J. F.; Schulz, J.; Verlage, T.; Weber, H.; Zhukov, V.; Brodski, M.; 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.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kieseler, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Leonard, J.; Lipka, K.; Lobanov, A.; 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.; Sahin, M. Ö.; Saxena, P.; Schoerner-Sadenius, T.; Seitz, C.; Spannagel, S.; Stefaniuk, N.; Trippkewitz, K. D.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Goebel, K.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Ott, J.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Sander, C.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Barth, C.; Baus, C.; Berger, J.; Butz, E.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Lobelle Pardo, P.; Maier, B.; Mildner, H.; Mozer, M. U.; Müller, T.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wagner-Kuhr, J.; 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.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; 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.; Bahinipati, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Nishu, N.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; 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.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhowmik, S.; Dewanjee, R. K.; Ganguly, S.; 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.; Rane, A.; Sharma, S.; Behnamian, H.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Fahim, A.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; 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.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; 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.; Chiorboli, M.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; SavoyNavarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; D'imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Jorda, C.; Longo, E.; Margaroli, F.; 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.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; 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.; La Licata, C.; Schizzi, A.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Brochero Cifuentes, J. A.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Oh, S. B.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Goh, J.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Komaragiri, J. R.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Magaña Villalba, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. 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.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Voytishin, N.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; 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.; Toms, M.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Chistov, R.; Danilov, M.; Rusinov, V.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Rusakov, S. V.; 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.; 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.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras De Saa, J. R.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Guio, F.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Hammer, J.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Kousouris, K.; Krammer, M.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; 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.; Ruan, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Wardle, N.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lecomte, P.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, 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.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Yang, Y.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Tzeng, Y. M.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kara, O.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, E. A.; Yetkin, T.; Cakir, A.; Cankocak, K.; Sen, S.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; 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.; Seif El Nasr-storey, S.; 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.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Berry, E.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Breto, G.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Florent, A.; Hauser, J.; Ignatenko, M.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Malberti, M.; Olmedo Negrete, M.; Paneva, M. 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T.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; 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.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Diamond, B.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Santra, A.; Weinberg, M.; 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.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; 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.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Osherson, M.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Bowen, J.; Bruner, C.; Castle, J.; Kenny, R. P.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Knowlton, D.; Kravchenko, I.; Malta Rodrigues, A.; Meier, F.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Baumgartel, D.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Kumar, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; 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.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; 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.; Chou, J. P.; Contreras-Campana, E.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Delannoy, A. G.; 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.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2016-12-01

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 fb-1 collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. This search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. Mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded. [Figure not available: see fulltext.

Consolidating strategic planning and operational frameworks for integrated vector management in Eritrea.

PubMed

Chanda, Emmanuel; Ameneshewa, Birkinesh; Mihreteab, Selam; Berhane, Araia; Zehaie, Assefash; Ghebrat, Yohannes; Usman, Abdulmumini

2015-12-02

Contemporary malaria vector control relies on the use of insecticide-based, indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs). However, malaria-endemic countries, including Eritrea, have struggled to effectively deploy these tools due technical and operational challenges, including the selection of insecticide resistance in malaria vectors. This manuscript outlines the processes undertaken in consolidating strategic planning and operational frameworks for vector control to expedite malaria elimination in Eritrea. The effort to strengthen strategic frameworks for vector control in Eritrea was the 'case' for this study. The integrated vector management (IVM) strategy was developed in 2010 but was not well executed, resulting in a rise in malaria transmission, prompting a process to redefine and relaunch the IVM strategy with integration of other vector borne diseases (VBDs) as the focus. The information sources for this study included all available data and accessible archived documentary records on malaria vector control in Eritrea. Structured literature searches of published, peer-reviewed sources using online, scientific, bibliographic databases, Google Scholar, PubMed and WHO, and a combination of search terms were utilized to gather data. The literature was reviewed and adapted to the local context and translated into the consolidated strategic framework. In Eritrea, communities are grappling with the challenge of VBDs posing public health concerns, including malaria. The global fund financed the scale-up of IRS and LLIN programmes in 2014. Eritrea is transitioning towards malaria elimination and strategic frameworks for vector control have been consolidated by: developing an integrated vector management (IVM) strategy (2015-2019); updating IRS and larval source management (LSM) guidelines; developing training manuals for IRS and LSM; training of national staff in malaria entomology and vector control, including insecticide resistance monitoring techniques; initiating the global plan for insecticide resistance management; conducting needs' assessments and developing standard operating procedure for insectaries; developing a guidance document on malaria vector control based on eco-epidemiological strata, a vector surveillance plan and harmonized mapping, data collection and reporting tools. Eritrea has successfully consolidated strategic frameworks for vector control. Rational decision-making remains critical to ensure that the interventions are effective and their choice is evidence-based, and to optimize the use of resources for vector control. Implementation of effective IVM requires proper collaboration and coordination, consistent technical and financial capacity and support to offer greater benefits.

Analysis of Genetic Algorithm for Rule-Set Production (GARP) modeling approach for predicting distributions of fleas implicated as vectors of plague, Yersinia pestis, in California.

PubMed

Adjemian, Jennifer C Z; Girvetz, Evan H; Beckett, Laurel; Foley, Janet E

2006-01-01

More than 20 species of fleas in California are implicated as potential vectors of Yersinia pestis. Extremely limited spatial data exist for plague vectors-a key component to understanding where the greatest risks for human, domestic animal, and wildlife health exist. This study increases the spatial data available for 13 potential plague vectors by using the ecological niche modeling system Genetic Algorithm for Rule-Set Production (GARP) to predict their respective distributions. Because the available sample sizes in our data set varied greatly from one species to another, we also performed an analysis of the robustness of GARP by using the data available for flea Oropsylla montana (Baker) to quantify the effects that sample size and the chosen explanatory variables have on the final species distribution map. GARP effectively modeled the distributions of 13 vector species. Furthermore, our analyses show that all of these modeled ranges are robust, with a sample size of six fleas or greater not significantly impacting the percentage of the in-state area where the flea was predicted to be found, or the testing accuracy of the model. The results of this study will help guide the sampling efforts of future studies focusing on plague vectors.

Pairwise Sequence Alignment Library

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

Jeff Daily, PNNL

2015-05-20

Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, amore » novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.« less

An investigation for the development of an integrated optical data preprocessor. [preprocessing remote sensor outputs

NASA Technical Reports Server (NTRS)

Verber, C. M.; Kenan, R. P.; Hartman, N. F.; Chapman, C. M.

1980-01-01

A laboratory model of a 16 channel integrated optical data preprocessor was fabricated and tested in response to a need for a device to evaluate the outputs of a set of remote sensors. It does this by accepting the outputs of these sensors, in parallel, as the components of a multidimensional vector descriptive of the data and comparing this vector to one or more reference vectors which are used to classify the data set. The comparison is performed by taking the difference between the signal and reference vectors. The preprocessor is wholly integrated upon the surface of a LiNbO3 single crystal with the exceptions of the source and the detector. He-Ne laser light is coupled in and out of the waveguide by prism couplers. The integrated optical circuit consists of a titanium infused waveguide pattern, electrode structures and grating beam splitters. The waveguide and electrode patterns, by virtue of their complexity, make the vector subtraction device the most complex integrated optical structure fabricated to date.

Development of a S/w System for Relative Positioning Using GPS Carrier Phase

NASA Astrophysics Data System (ADS)

Ahn, Yong-Won; Kim, Chun-Hwey; Park, Pil-Ho; Park, Jong-Uk; Jo, Jeong-Ho

1997-12-01

We developed a GPS phase data processing S/W system which calculates baseline vectors and distances between two points located in the surface of the Earth. For this development a Double-Difference method and L1 carrier phase data from GPS(Global Positioning System) were used. This S/W system consists of four main parts : satellite position calculation, Single-Difference equation, Double-Difference equation, and correlation. To verify our S/W, we fixed KAO(N36.37, E127.37, H77.61m), one of the International GPS Services for Geodynamics, which is located at Tae-Jon, and we measured baseline vectors and relative distances with data from observations at approximate baseline distances of 2.7, 42.1, 81.1, 146.6km. Then we compared the vectors and distances with the data which we obtained from the GPSurvery S/W system, with the L1/L2 ION-Free method and broadcast ephemeris. From the comparison of the vectors and distances with the data from the GPSurvey S/W system, we found baseline vectors X, Y, Z and baseline distances matched well within the extent of 50cm and 10cm, respectively.

Aircraft attitude measurement using a vector magnetometer

NASA Technical Reports Server (NTRS)

Peitila, R.; Dunn, W. R., Jr.

1977-01-01

The feasibility of a vector magnetometer system was investigated by developing a technique to determine attitude given magnetic field components. Sample calculations are then made using the earth's magnetic field data acquired during actual flight conditions. Results of these calculations are compared graphically with measured attitude data acquired simultaneously with the magnetic data. The role and possible implementation of various reference angles are discussed along with other pertinent considerations. Finally, it is concluded that the earth's magnetic field as measured by modern vector magnetometers can play a significant role in attitude control systems.

Temporo-spatial distribution of insecticide-resistance in Indian malaria vectors in the last quarter-century: Need for regular resistance monitoring and management.

PubMed

Raghavendra, Kamaraju; Velamuri, Poonam Sharma; Verma, Vaishali; Elamathi, Natarajan; Barik, Tapan Kumar; Bhatt, Rajendra Mohan; Dash, Aditya Prasad

2017-01-01

The Indian vector control programme similar to other programmes in the world is still reliant on chemical insecticides. Anopheles culicifacies is the major vector out of six primary malaria vectors in India and alone contributes about 2/3 malaria cases annually; and per se its control is actually control of malaria in India. For effective management of vectors, current information on their susceptibility status to different insecticides is essential. In this review, an attempt was made to compile and present the available data on the susceptibility status of different malaria vector species in India from the last 2.5 decades. Literature search was conducted by different means mainly web and library search; susceptibility data was collated from 62 sources for the nine malaria vector species from 145 districts in 21 states and two union territories between 1991 and 2016. Interpretation of the susceptibility/resistance status was made on basis of the recent WHO criteria. Comprehensive analysis of the data indicated that An. culicifacies, a major vector species was resistant to at least one insecticide in 70% (101/145) of the districts. It was reported mostly resistant to DDT and malathion whereas, its resistant status against deltamethrin varied across the districts. The major threat for the malaria control programmes is multiple-insecticide-resistance in An. culicifacies which needs immediate attention for resistance management in order to sustain the gains achieved so far, as the programmes have targeted malaria elimination by 2030.

Bayesian Kernel Methods for Non-Gaussian Distributions: Binary and Multi-class Classification Problems

DTIC Science & Technology

2013-05-28

those of the support vector machine and relevance vector machine, and the model runs more quickly than the other algorithms . When one class occurs...incremental support vector machine algorithm for online learning when fewer than 50 data points are available. (a) Papers published in peer-reviewed journals...learning environments, where data processing occurs one observation at a time and the classification algorithm improves over time with new

The morphing of geographical features by Fourier transformation.

PubMed

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

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.

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

Khachatryan, Vardan

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 inverse femtobarns collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. Thismore » search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. As a result, mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded.« less

Estimation of the chemical rank for the three-way data: a principal norm vector orthogonal projection approach.

PubMed

Hong-Ping, Xie; Jian-Hui, Jiang; Guo-Li, Shen; Ru-Qin, Yu

2002-01-01

A new approach for estimating the chemical rank of the three-way array called the principal norm vector orthogonal projection method has been proposed. The method is based on the fact that the chemical rank of the three-way data array is equal to one of the column space of the unfolded matrix along the spectral or chromatographic mode. A vector with maximum Frobenius norm is selected among all the column vectors of the unfolded matrix as the principal norm vector (PNV). A transformation is conducted for the column vectors with an orthogonal projection matrix formulated by PNV. The mathematical rank of the column space of the residual matrix thus obtained should decrease by one. Such orthogonal projection is carried out repeatedly till the contribution of chemical species to the signal data is all deleted. At this time the decrease of the mathematical rank would equal that of the chemical rank, and the remaining residual subspace would entirely be due to the noise contribution. The chemical rank can be estimated easily by using an F-test. The method has been used successfully to the simulated HPLC-DAD type three-way data array and two real excitation-emission fluorescence data sets of amino acid mixtures and dye mixtures. The simulation with added relatively high level noise shows that the method is robust in resisting the heteroscedastic noise. The proposed algorithm is simple and easy to program with quite light computational burden.

MosquitoMap and the Mal-area calculator: new web tools to relate mosquito species distribution with vector borne disease

PubMed Central

2010-01-01

Background Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. Results A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. Conclusion MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases. PMID:20167090

MosquitoMap and the Mal-area calculator: new web tools to relate mosquito species distribution with vector borne disease.

PubMed

Foley, Desmond H; Wilkerson, Richard C; Birney, Ian; Harrison, Stanley; Christensen, Jamie; Rueda, Leopoldo M

2010-02-18

Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases.

Measurements of Solar Vector Magnetic Fields

NASA Technical Reports Server (NTRS)

Hagyard, M. J. (Editor)

1985-01-01

Various aspects of the measurement of solar magnetic fields are presented. The four major subdivisions of the study are: (1) theoretical understanding of solar vector magnetic fields; (3) techniques for interpretation of observational data; and (4) techniques for data display.

Chromosomal integration of adenoviral vector DNA in vivo.

PubMed

Stephen, Sam Laurel; Montini, Eugenio; Sivanandam, Vijayshankar Ganesh; Al-Dhalimy, Muhseen; Kestler, Hans A; Finegold, Milton; Grompe, Markus; Kochanek, Stefan

2010-10-01

So far there has been no report of any clinical or preclinical evidence for chromosomal vector integration following adenovirus (Ad) vector-mediated gene transfer in vivo. We used liver gene transfer with high-capacity Ad vectors in the FAH(Deltaexon5) mouse model to analyze homologous and heterologous recombination events between vector and chromosomal DNA. Intravenous injection of Ad vectors either expressing a fumarylacetoacetate hydrolase (FAH) cDNA or carrying part of the FAH genomic locus resulted in liver nodules of FAH-expressing hepatocytes, demonstrating chromosomal vector integration. Analysis of junctions between vector and chromosomal DNA following heterologous recombination indicated integration of the vector genome through its termini. Heterologous recombination occurred with a median frequency of 6.72 x 10(-5) per transduced hepatocyte, while homologous recombination occurred more rarely with a median frequency of 3.88 x 10(-7). This study has established quantitative and qualitative data on recombination of adenoviral vector DNA with genomic DNA in vivo, contributing to a risk-benefit assessment of the biosafety of Ad vector-mediated gene transfer.

What is the risk for exposure to vector-borne pathogens in United States national parks?

PubMed

Eisen, Lars; Wong, David; Shelus, Victoria; Eisen, Rebecca J

2013-03-01

United States national parks attract > 275 million visitors annually and collectively present risk of exposure for staff and visitors to a wide range of arthropod vector species (most notably fleas, mosquitoes, and ticks) and their associated bacterial, protozoan, or viral pathogens. We assessed the current state of knowledge for risk of exposure to vector-borne pathogens in national parks through a review of relevant literature, including internal National Park Service documents and organismal databases. We conclude that, because of lack of systematic surveillance for vector-borne pathogens in national parks, the risk of pathogen exposure for staff and visitors is unclear. Existing data for vectors within national parks were not based on systematic collections and rarely include evaluation for pathogen infection. Extrapolation of human-based surveillance data from neighboring communities likely provides inaccurate estimates for national parks because landscape differences impact transmission of vector-borne pathogens and human-vector contact rates likely differ inside versus outside the parks because of differences in activities or behaviors. Vector-based pathogen surveillance holds promise to define when and where within national parks the risk of exposure to infected vectors is elevated. A pilot effort, including 5-10 strategic national parks, would greatly improve our understanding of the scope and magnitude of vector-borne pathogen transmission in these high-use public settings. Such efforts also will support messaging to promote personal protection measures and inform park visitors and staff of their responsibility for personal protection, which the National Park Service preservation mission dictates as the core strategy to reduce exposure to vector-borne pathogens in national parks.

Analysis of vector wind change with respect to time for Cape Kennedy, Florida: Wind aloft profile change vs. time, phase 1

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1977-01-01

Wind vector change with respect to time at Cape Kennedy, Florida, is examined according to the theory of multivariate normality. The joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from fifteen years of twice daily Rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, the joint distribution of wind component changes is bivariate normal, and the modulus of vector wind change is Rayleigh, has been tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from one to five hours, calculated from Jimsphere data, are presented.

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

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

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

Sine Rotation Vector Method for Attitude Estimation of an Underwater Robot

PubMed Central

Ko, Nak Yong; Jeong, Seokki; Bae, Youngchul

2016-01-01

This paper describes a method for estimating the attitude of an underwater robot. The method employs a new concept of sine rotation vector and uses both an attitude heading and reference system (AHRS) and a Doppler velocity log (DVL) for the purpose of measurement. First, the acceleration and magnetic-field measurements are transformed into sine rotation vectors and combined. The combined sine rotation vector is then transformed into the differences between the Euler angles of the measured attitude and the predicted attitude; the differences are used to correct the predicted attitude. The method was evaluated according to field-test data and simulation data and compared to existing methods that calculate angular differences directly without a preceding sine rotation vector transformation. The comparison verifies that the proposed method improves the attitude estimation performance. PMID:27490549

Content based image retrieval using local binary pattern operator and data mining techniques.

PubMed

Vatamanu, Oana Astrid; Frandeş, Mirela; Lungeanu, Diana; Mihalaş, Gheorghe-Ioan

2015-01-01

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology

NASA Astrophysics Data System (ADS)

Gao, Wei; Zhu, Linli; Wang, Kaiyun

2015-12-01

Ontology, a model of knowledge representation and storage, has had extensive applications in pharmaceutics, social science, chemistry and biology. In the age of “big data”, the constructed concepts are often represented as higher-dimensional data by scholars, and thus the sparse learning techniques are introduced into ontology algorithms. In this paper, based on the alternating direction augmented Lagrangian method, we present an ontology optimization algorithm for ontological sparse vector learning, and a fast version of such ontology technologies. The optimal sparse vector is obtained by an iterative procedure, and the ontology function is then obtained from the sparse vector. Four simulation experiments show that our ontological sparse vector learning model has a higher precision ratio on plant ontology, humanoid robotics ontology, biology ontology and physics education ontology data for similarity measuring and ontology mapping applications.

Aerial images visual localization on a vector map using color-texture segmentation

NASA Astrophysics Data System (ADS)

Kunina, I. A.; Teplyakov, L. M.; Gladkov, A. P.; Khanipov, T. M.; Nikolaev, D. P.

2018-04-01

In this paper we study the problem of combining UAV obtained optical data and a coastal vector map in absence of satellite navigation data. The method is based on presenting the territory as a set of segments produced by color-texture image segmentation. We then find such geometric transform which gives the best match between these segments and land and water areas of the georeferenced vector map. We calculate transform consisting of an arbitrary shift relatively to the vector map and bound rotation and scaling. These parameters are estimated using the RANSAC algorithm which matches the segments contours and the contours of land and water areas of the vector map. To implement this matching we suggest computing shape descriptors robust to rotation and scaling. We performed numerical experiments demonstrating the practical applicability of the proposed method.

Fast support vector data descriptions for novelty detection.

PubMed

Liu, Yi-Hung; Liu, Yan-Chen; Chen, Yen-Jen

2010-08-01

Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems. However, the decision function of SVDD is expressed in terms of the kernel expansion, which results in a run-time complexity linear in the number of support vectors. For applications where fast real-time response is needed, how to speed up the decision function is crucial. This paper aims at dealing with the issue of reducing the testing time complexity of SVDD. A method called fast SVDD (F-SVDD) is proposed. Unlike the traditional methods which all try to compress a kernel expansion into one with fewer terms, the proposed F-SVDD directly finds the preimage of a feature vector, and then uses a simple relationship between this feature vector and the SVDD sphere center to re-express the center with a single vector. The decision function of F-SVDD contains only one kernel term, and thus the decision boundary of F-SVDD is only spherical in the original space. Hence, the run-time complexity of the F-SVDD decision function is no longer linear in the support vectors, but is a constant, no matter how large the training set size is. In this paper, we also propose a novel direct preimage-finding method, which is noniterative and involves no free parameters. The unique preimage can be obtained in real time by the proposed direct method without taking trial-and-error. For demonstration, several real-world data sets and a large-scale data set, the extended MIT face data set, are used in experiments. In addition, a practical industry example regarding liquid crystal display micro-defect inspection is also used to compare the applicability of SVDD and our proposed F-SVDD when faced with mass data input. The results are very encouraging.

Vector Acoustics, Vector Sensors, and 3D Underwater Imaging

NASA Astrophysics Data System (ADS)

Lindwall, D.

2007-12-01

Vector acoustic data has two more dimensions of information than pressure data and may allow for 3D underwater imaging with much less data than with hydrophone data. The vector acoustic sensors measures the particle motions due to passing sound waves and, in conjunction with a collocated hydrophone, the direction of travel of the sound waves. When using a controlled source with known source and sensor locations, the reflection points of the sound field can be determined with a simple trigonometric calculation. I demonstrate this concept with an experiment that used an accelerometer based vector acoustic sensor in a water tank with a short-pulse source and passive scattering targets. The sensor consists of a three-axis accelerometer and a matched hydrophone. The sound source was a standard transducer driven by a short 7 kHz pulse. The sensor was suspended in a fixed location and the hydrophone was moved about the tank by a robotic arm to insonify the tank from many locations. Several floats were placed in the tank as acoustic targets at diagonal ranges of approximately one meter. The accelerometer data show the direct source wave as well as the target scattered waves and reflections from the nearby water surface, tank bottom and sides. Without resorting to the usual methods of seismic imaging, which in this case is only two dimensional and relied entirely on the use of a synthetic source aperture, the two targets, the tank walls, the tank bottom, and the water surface were imaged. A directional ambiguity inherent to vector sensors is removed by using collocated hydrophone data. Although this experiment was in a very simple environment, it suggests that 3-D seismic surveys may be achieved with vector sensors using the same logistics as a 2-D survey that uses conventional hydrophones. This work was supported by the Office of Naval Research, program element 61153N.

A MODELING APPROACH FOR ESTIMATING WATERSHED IMPERVIOUS SURFACE AREA FROM NATIONAL LAND COVER DATA 92

EPA Science Inventory

We used National Land Cover Data 92 (NLCD92), vector impervious surface data, and raster GIS overlay methods to derive impervious surface coefficients per NLCD92 class in portions of the Nfid-Atlantic physiographic region. The methods involve a vector to raster conversion of the ...

The use of digital spaceborne SAR data for the delineation of surface features indicative of malaria vector breeding habitats

NASA Technical Reports Server (NTRS)

Imhoff, M. L.; Vermillion, C. H.; Khan, F. A.

1984-01-01

An investigation to examine the utility of spaceborne radar image data to malaria vector control programs is described. Specific tasks involve an analysis of radar illumination geometry vs information content, the synergy of radar and multispectral data mergers, and automated information extraction techniques.

Application of Bred Vectors To Data Assimilation

NASA Astrophysics Data System (ADS)

Corazza, M.; Kalnay, E.; Patil, Dj

We introduced a statistic, the BV-dimension, to measure the effective local finite-time dimensionality of the atmosphere. We show that this dimension is often quite low, and suggest that this finding has important implications for data assimilation and the accuracy of weather forecasting (Patil et al, 2001). The original database for this study was the forecasts of the NCEP global ensemble forecasting system. The initial differences between the control forecast and the per- turbed forecasts are called bred vectors. The control and perturbed initial conditions valid at time t=n(t are evolved using the forecast model until time t=(n+1) (t. The differences between the perturbed and the control forecasts are scaled down to their initial amplitude, and constitute the bred vectors valid at (n+1) (t. Their growth rate is typically about 1.5/day. The bred vectors are similar by construction to leading Lya- punov vectors except that they have small but finite amplitude, and they are valid at finite times. The original NCEP ensemble data set has 5 independent bred vectors. We define a local bred vector at each grid point by choosing the 5 by 5 grid points centered at the grid point (a region of about 1100km by 1100km), and using the north-south and east- west velocity components at 500mb pressure level to form a 50 dimensional column vector. Since we have k=5 global bred vectors, we also have k local bred vectors at each grid point. We estimate the effective dimensionality of the subspace spanned by the local bred vectors by performing a singular value decomposition (EOF analysis). The k local bred vector columns form a 50xk matrix M. The singular values s(i) of M measure the extent to which the k column unit vectors making up the matrix M point in the direction of v(i). We define the bred vector dimension as BVDIM={Sum[s(i)]}^2/{Sum[s(i)]^2} For example, if 4 out of the 5 vectors lie along v, and one lies along v, the BV- dimension would be BVDIM[sqrt(4), 1, 0,0,0]=1.8, less than 2 because one direction is more dominant than the other in representing the original data. The results (Patil et al, 2001) show that there are large regions where the bred vectors span a subspace of substantially lower dimension than that of the full space. These low dimensionality regions are dominant in the baroclinic extratropics, typically have a lifetime of 3-7 days, have a well-defined horizontal and vertical structure that spans 1 most of the atmosphere, and tend to move eastward. New results with a large number of ensemble members confirm these results and indicate that the low dimensionality regions are quite robust, and depend only on the verification time (i.e., the underlying flow). Corazza et al (2001) have performed experiments with a data assimilation system based on a quasi-geostrophic model and simulated observations (Morss, 1999, Hamill et al, 2000). A 3D-variational data assimilation scheme for a quasi-geostrophic chan- nel model is used to study the structure of the background error and its relationship to the corresponding bred vectors. The "true" evolution of the model atmosphere is defined by an integration of the model and "rawinsonde observations" are simulated by randomly perturbing the true state at fixed locations. It is found that after 3-5 days the bred vectors develop well organized structures which are very similar for the two different norms considered in this paper (potential vorticity norm and streamfunction norm). The results show that the bred vectors do indeed represent well the characteristics of the data assimilation forecast errors, and that the subspace of bred vectors contains most of the forecast error, except in areas where the forecast errors are small. For example, the angle between the 6hr forecast error and the subspace spanned by 10 bred vectors is less than 10o over 90% of the domain, indicating a pattern correlation of more than 98.5% between the forecast error and its projection onto the bred vector subspace. The presence of low-dimensional regions in the perturbations of the basic flow has important implications for data assimilation. At any given time, there is a difference between the true atmospheric state and the model forecast. Assuming that model er- rors are not the dominant source of errors, in a region of low BV-dimensionality the difference between the true state and the forecast should lie substantially in the low dimensional unstable subspace of the few bred vectors that contribute most strongly to the low BV-dimension. This information should yield a substantial improvement in the forecast: the data assimilation algorithm should correct the model state by moving it closer to the observations along the unstable subspace, since this is where the true state most likely lies. Preliminary experiments have been conducted with the quasi-geostrophic data assim- ilation system testing whether it is possible to add "errors of the day" based on bred vectors to the standard (constant) 3D-Var background error covariance in order to capture these important errors. The results are extremely encouraging, indicating a significant reduction (about 40%) in the analysis errors at a very low computational cost. References: 2 Corazza, M., E. Kalnay, DJ Patil, R. Morss, M Cai, I. Szunyogh, BR Hunt, E Ott and JA Yorke, 2001: Use of the breeding technique to estimate the structure of the analysis "errors of the day". Submitted to Nonlinear Processes in Geophysics. Hamill, T.M., Snyder, C., and Morss, R.E., 2000: A Comparison of Probabilistic Fore- casts from Bred, Singular-Vector and Perturbed Observation Ensembles, Mon. Wea. Rev., 128, 1835­1851. Kalnay, E., and Z. Toth, 1994: Removing growing errors in the analysis cycle. Preprints of the Tenth Conference on Numerical Weather Prediction, Amer. Meteor. Soc., 1994, 212-215. Morss, R. E., 1999: Adaptive observations: Idealized sampling strategies for improv- ing numerical weather prediction. PHD thesis, Massachussetts Institute of technology, 225pp. Patil, D. J. S., B. R. Hunt, E. Kalnay, J. A. Yorke, and E. Ott., 2001: Local Low Dimensionality of Atmospheric Dynamics. Phys. Rev. Lett., 86, 5878. 3

Justification of Fuzzy Declustering Vector Quantization Modeling in Classification of Genotype-Image Phenotypes

NASA Astrophysics Data System (ADS)

Ng, Theam Foo; Pham, Tuan D.; Zhou, Xiaobo

2010-01-01

With the fast development of multi-dimensional data compression and pattern classification techniques, vector quantization (VQ) has become a system that allows large reduction of data storage and computational effort. One of the most recent VQ techniques that handle the poor estimation of vector centroids due to biased data from undersampling is to use fuzzy declustering-based vector quantization (FDVQ) technique. Therefore, in this paper, we are motivated to propose a justification of FDVQ based hidden Markov model (HMM) for investigating its effectiveness and efficiency in classification of genotype-image phenotypes. The performance evaluation and comparison of the recognition accuracy between a proposed FDVQ based HMM (FDVQ-HMM) and a well-known LBG (Linde, Buzo, Gray) vector quantization based HMM (LBG-HMM) will be carried out. The experimental results show that the performances of both FDVQ-HMM and LBG-HMM are almost similar. Finally, we have justified the competitiveness of FDVQ-HMM in classification of cellular phenotype image database by using hypotheses t-test. As a result, we have validated that the FDVQ algorithm is a robust and an efficient classification technique in the application of RNAi genome-wide screening image data.

Method for predicting peptide detection in mass spectrometry

DOEpatents

Kangas, Lars [West Richland, WA; Smith, Richard D [Richland, WA; Petritis, Konstantinos [Richland, WA

2010-07-13

A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.

Vector and Axial-Vector Current Correlators Within the Instanton Model of QCD Vacuum

NASA Astrophysics Data System (ADS)

Dorokhov, A. E.

2005-08-01

The pion electric polarizability, α {π ^ ± }E , the leading order hadronic contribution to the muon anomalous magnetic moment, aμ hvp(1) , and the ratio of the V - A and V + A correlators are found within the instanton model of QCD vacuum. The results are compared with phenomenological estimates of these quantities from the ALEPH and OPAL data on vector and axial-vector spectral densities.

Vector species richness increases haemorrhagic disease prevalence through functional diversity modulating the duration of seasonal transmission.

PubMed

Park, Andrew W; Cleveland, Christopher A; Dallas, Tad A; Corn, Joseph L

2016-06-01

Although many parasites are transmitted between hosts by a suite of arthropod vectors, the impact of vector biodiversity on parasite transmission is poorly understood. Positive relationships between host infection prevalence and vector species richness (SR) may operate through multiple mechanisms, including (i) increased vector abundance, (ii) a sampling effect in which species of high vectorial capacity are more likely to occur in species-rich communities, and (iii) functional diversity whereby communities comprised species with distinct phenologies may extend the duration of seasonal transmission. Teasing such mechanisms apart is impeded by a lack of appropriate data, yet could highlight a neglected role for functional diversity in parasite transmission. We used statistical modelling of extensive host, vector and microparasite data to test the hypothesis that functional diversity leading to longer seasonal transmission explained variable levels of disease in a wildlife population. We additionally developed a simple transmission model to guide our expectation of how an increased transmission season translates to infection prevalence. Our study demonstrates that vector SR is associated with increased levels of disease reporting, but not via increases in vector abundance or via a sampling effect. Rather, the relationship operates by extending the length of seasonal transmission, in line with theoretical predictions.

The morphing of geographical features by Fourier transformation

PubMed Central

Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. PMID:29351344

A vector scanning processing technique for pulsed laser velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1989-01-01

Pulsed-laser-sheet velocimetry yields two-dimensional velocity vectors across an extended planar region of a flow. Current processing techniques offer high-precision (1-percent) velocity estimates, but can require hours of processing time on specialized array processors. Sometimes, however, a less accurate (about 5 percent) data-reduction technique which also gives unambiguous velocity vector information is acceptable. Here, a direct space-domain processing technique is described and shown to be far superior to previous methods in achieving these objectives. It uses a novel data coding and reduction technique and has no 180-deg directional ambiguity. A complex convection vortex flow was recorded and completely processed in under 2 min on an 80386-based PC, producing a two-dimensional velocity-vector map of the flowfield. Pulsed-laser velocimetry data can thus be reduced quickly and reasonably accurately, without specialized array processing hardware.

An examination of techniques for reformatting digital cartographic data/part 1: the raster-to- vector process.

USGS Publications Warehouse

Peuquet, D.J.

1981-01-01

Current graphic devices suitable for high-speed computer input and output of cartographic data are tending more and more to be raster-oriented, such as the rotating drum scanner and the color raster display. However, the majority of commonly used manipulative techniques in computer-assisted cartography and automated spatial data handling continue to require that the data be in vector format. This situation has recently precipitated the requirement for very fast techniques for converting digital cartographic data from raster to vector format for processing, and then back into raster format for plotting. The current article is part 1 of a 2 part paper concerned with examining the state-of-the-art in these conversion techniques. -from Author

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 adaptive vector quantization scheme

NASA Technical Reports Server (NTRS)

Cheung, K.-M.

1990-01-01

Vector quantization is known to be an effective compression scheme to achieve a low bit rate so as to minimize communication channel bandwidth and also to reduce digital memory storage while maintaining the necessary fidelity of the data. However, the large number of computations required in vector quantizers has been a handicap in using vector quantization for low-rate source coding. An adaptive vector quantization algorithm is introduced that is inherently suitable for simple hardware implementation because it has a simple architecture. It allows fast encoding and decoding because it requires only addition and subtraction operations.

An efficient and portable SIMD algorithm for charge/current deposition in Particle-In-Cell codes

DOE PAGES

Vincenti, H.; Lobet, M.; Lehe, R.; ...

2016-09-19

In current computer architectures, data movement (from die to network) is by far the most energy consuming part of an algorithm (≈20pJ/word on-die to ≈10,000 pJ/word on the network). To increase memory locality at the hardware level and reduce energy consumption related to data movement, future exascale computers tend to use many-core processors on each compute nodes that will have a reduced clock speed to allow for efficient cooling. To compensate for frequency decrease, machine vendors are making use of long SIMD instruction registers that are able to process multiple data with one arithmetic operator in one clock cycle. SIMD registermore » length is expected to double every four years. As a consequence, Particle-In-Cell (PIC) codes will have to achieve good vectorization to fully take advantage of these upcoming architectures. In this paper, we present a new algorithm that allows for efficient and portable SIMD vectorization of current/charge deposition routines that are, along with the field gathering routines, among the most time consuming parts of the PIC algorithm. Our new algorithm uses a particular data structure that takes into account memory alignment constraints and avoids gather/scat;ter instructions that can significantly affect vectorization performances on current CPUs. The new algorithm was successfully implemented in the 3D skeleton PIC code PICSAR and tested on Haswell Xeon processors (AVX2-256 bits wide data registers). Results show a factor of ×2 to ×2.5 speed-up in double precision for particle shape factor of orders 1–3. The new algorithm can be applied as is on future KNL (Knights Landing) architectures that will include AVX-512 instruction sets with 512 bits register lengths (8 doubles/16 singles). Program summary Program Title: vec_deposition Program Files doi:http://dx.doi.org/10.17632/nh77fv9k8c.1 Licensing provisions: BSD 3-Clause Programming language: Fortran 90 External routines/libraries:  OpenMP > 4.0 Nature of problem: Exascale architectures will have many-core processors per node with long vector data registers capable of performing one single instruction on multiple data during one clock cycle. Data register lengths are expected to double every four years and this pushes for new portable solutions for efficiently vectorizing Particle-In-Cell codes on these future many-core architectures. One of the main hotspot routines of the PIC algorithm is the current/charge deposition for which there is no efficient and portable vector algorithm. Solution method: Here we provide an efficient and portable vector algorithm of current/charge deposition routines that uses a new data structure, which significantly reduces gather/scatter operations. Vectorization is controlled using OpenMP 4.0 compiler directives for vectorization which ensures portability across different architectures. Restrictions: Here we do not provide the full PIC algorithm with an executable but only vector routines for current/charge deposition. These scalar/vector routines can be used as library routines in your 3D Particle-In-Cell code. However, to get the best performances out of vector routines you have to satisfy the two following requirements: (1) Your code should implement particle tiling (as explained in the manuscript) to allow for maximized cache reuse and reduce memory accesses that can hinder vector performances. The routines can be used directly on each particle tile. (2) You should compile your code with a Fortran 90 compiler (e.g Intel, gnu or cray) and provide proper alignment flags and compiler alignment directives (more details in README file).« less

An efficient and portable SIMD algorithm for charge/current deposition in Particle-In-Cell codes

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

Vincenti, H.; Lobet, M.; Lehe, R.

In current computer architectures, data movement (from die to network) is by far the most energy consuming part of an algorithm (≈20pJ/word on-die to ≈10,000 pJ/word on the network). To increase memory locality at the hardware level and reduce energy consumption related to data movement, future exascale computers tend to use many-core processors on each compute nodes that will have a reduced clock speed to allow for efficient cooling. To compensate for frequency decrease, machine vendors are making use of long SIMD instruction registers that are able to process multiple data with one arithmetic operator in one clock cycle. SIMD registermore » length is expected to double every four years. As a consequence, Particle-In-Cell (PIC) codes will have to achieve good vectorization to fully take advantage of these upcoming architectures. In this paper, we present a new algorithm that allows for efficient and portable SIMD vectorization of current/charge deposition routines that are, along with the field gathering routines, among the most time consuming parts of the PIC algorithm. Our new algorithm uses a particular data structure that takes into account memory alignment constraints and avoids gather/scat;ter instructions that can significantly affect vectorization performances on current CPUs. The new algorithm was successfully implemented in the 3D skeleton PIC code PICSAR and tested on Haswell Xeon processors (AVX2-256 bits wide data registers). Results show a factor of ×2 to ×2.5 speed-up in double precision for particle shape factor of orders 1–3. The new algorithm can be applied as is on future KNL (Knights Landing) architectures that will include AVX-512 instruction sets with 512 bits register lengths (8 doubles/16 singles). Program summary Program Title: vec_deposition Program Files doi:http://dx.doi.org/10.17632/nh77fv9k8c.1 Licensing provisions: BSD 3-Clause Programming language: Fortran 90 External routines/libraries:  OpenMP > 4.0 Nature of problem: Exascale architectures will have many-core processors per node with long vector data registers capable of performing one single instruction on multiple data during one clock cycle. Data register lengths are expected to double every four years and this pushes for new portable solutions for efficiently vectorizing Particle-In-Cell codes on these future many-core architectures. One of the main hotspot routines of the PIC algorithm is the current/charge deposition for which there is no efficient and portable vector algorithm. Solution method: Here we provide an efficient and portable vector algorithm of current/charge deposition routines that uses a new data structure, which significantly reduces gather/scatter operations. Vectorization is controlled using OpenMP 4.0 compiler directives for vectorization which ensures portability across different architectures. Restrictions: Here we do not provide the full PIC algorithm with an executable but only vector routines for current/charge deposition. These scalar/vector routines can be used as library routines in your 3D Particle-In-Cell code. However, to get the best performances out of vector routines you have to satisfy the two following requirements: (1) Your code should implement particle tiling (as explained in the manuscript) to allow for maximized cache reuse and reduce memory accesses that can hinder vector performances. The routines can be used directly on each particle tile. (2) You should compile your code with a Fortran 90 compiler (e.g Intel, gnu or cray) and provide proper alignment flags and compiler alignment directives (more details in README file).« less

Reconstruction of interatomic vectors by principle component analysis of nuclear magnetic resonance data in multiple alignments

NASA Astrophysics Data System (ADS)

Hus, Jean-Christophe; Bruschweiler, Rafael

2002-07-01

A general method is presented for the reconstruction of interatomic vector orientations from nuclear magnetic resonance (NMR) spectroscopic data of tensor interactions of rank 2, such as dipolar coupling and chemical shielding anisotropy interactions, in solids and partially aligned liquid-state systems. The method, called PRIMA, is based on a principal component analysis of the covariance matrix of the NMR parameters collected for multiple alignments. The five nonzero eigenvalues and their eigenvectors efficiently allow the approximate reconstruction of the vector orientations of the underlying interactions. The method is demonstrated for an isotropic distribution of sample orientations as well as for finite sets of orientations and internuclear vectors encountered in protein systems.

VISA--Vector Integration Site Analysis server: a web-based server to rapidly identify retroviral integration sites from next-generation sequencing.

PubMed

Hocum, Jonah D; Battrell, Logan R; Maynard, Ryan; Adair, Jennifer E; Beard, Brian C; Rawlings, David J; Kiem, Hans-Peter; Miller, Daniel G; Trobridge, Grant D

2015-07-07

Analyzing the integration profile of retroviral vectors is a vital step in determining their potential genotoxic effects and developing safer vectors for therapeutic use. Identifying retroviral vector integration sites is also important for retroviral mutagenesis screens. We developed VISA, a vector integration site analysis server, to analyze next-generation sequencing data for retroviral vector integration sites. Sequence reads that contain a provirus are mapped to the human genome, sequence reads that cannot be localized to a unique location in the genome are filtered out, and then unique retroviral vector integration sites are determined based on the alignment scores of the remaining sequence reads. VISA offers a simple web interface to upload sequence files and results are returned in a concise tabular format to allow rapid analysis of retroviral vector integration sites.

The Coordinate Transformation Method of High Resolution dem Data

NASA Astrophysics Data System (ADS)

Yan, Chaode; Guo, Wang; Li, Aimin

2018-04-01

Coordinate transformation methods of DEM data can be divided into two categories. One reconstruct based on original vector elevation data. The other transforms DEM data blocks by transforming parameters. But the former doesn't work in the absence of original vector data, and the later may cause errors at joint places between adjoining blocks of high resolution DEM data. In view of this problem, a method dealing with high resolution DEM data coordinate transformation is proposed. The method transforms DEM data into discrete vector elevation points, and then adjusts positions of points by bi-linear interpolation respectively. Finally, a TIN is generated by transformed points, and the new DEM data in target coordinate system is reconstructed based on TIN. An algorithm which can find blocks and transform automatically is given in this paper. The method is tested in different terrains and proved to be feasible and valid.

Limits on the Efficiency of Event-Based Algorithms for Monte Carlo Neutron Transport

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

Romano, Paul K.; Siegel, Andrew R.

The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each individual particle history is considered a unit of work, does not lend itself well to data-level parallelism. Event-based algorithms, which were originally used for simulations on vector processors, may offer a path toward better utilizing data-level parallelism in modern computer architectures. In this study, a simple model is developed for estimating the efficiency of the event-based particle transport algorithm under two sets of assumptions. Data collected from simulations of four reactor problems using OpenMC was then used in conjunction with the models to calculate the speedup duemore » to vectorization as a function of the size of the particle bank and the vector width. When each event type is assumed to have constant execution time, the achievable speedup is directly related to the particle bank size. We observed that the bank size generally needs to be at least 20 times greater than vector size to achieve vector efficiency greater than 90%. Lastly, when the execution times for events are allowed to vary, the vector speedup is also limited by differences in execution time for events being carried out in a single event-iteration.« less

Limits on the Efficiency of Event-Based Algorithms for Monte Carlo Neutron Transport

DOE PAGES

Romano, Paul K.; Siegel, Andrew R.

2017-07-01

The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each individual particle history is considered a unit of work, does not lend itself well to data-level parallelism. Event-based algorithms, which were originally used for simulations on vector processors, may offer a path toward better utilizing data-level parallelism in modern computer architectures. In this study, a simple model is developed for estimating the efficiency of the event-based particle transport algorithm under two sets of assumptions. Data collected from simulations of four reactor problems using OpenMC was then used in conjunction with the models to calculate the speedup duemore » to vectorization as a function of the size of the particle bank and the vector width. When each event type is assumed to have constant execution time, the achievable speedup is directly related to the particle bank size. We observed that the bank size generally needs to be at least 20 times greater than vector size to achieve vector efficiency greater than 90%. Lastly, when the execution times for events are allowed to vary, the vector speedup is also limited by differences in execution time for events being carried out in a single event-iteration.« less

A vector scanning processing technique for pulsed laser velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1989-01-01

Pulsed laser sheet velocimetry yields nonintrusive measurements of two-dimensional velocity vectors across an extended planar region of a flow. Current processing techniques offer high precision (1 pct) velocity estimates, but can require several hours of processing time on specialized array processors. Under some circumstances, a simple, fast, less accurate (approx. 5 pct), data reduction technique which also gives unambiguous velocity vector information is acceptable. A direct space domain processing technique was examined. The direct space domain processing technique was found to be far superior to any other techniques known, in achieving the objectives listed above. It employs a new data coding and reduction technique, where the particle time history information is used directly. Further, it has no 180 deg directional ambiguity. A complex convection vortex flow was recorded and completely processed in under 2 minutes on an 80386 based PC, producing a 2-D velocity vector map of the flow field. Hence, using this new space domain vector scanning (VS) technique, pulsed laser velocimetry data can be reduced quickly and reasonably accurately, without specialized array processing hardware.

Thrust Vectoring on the NASA F-18 High Alpha Research Vehicle

NASA Technical Reports Server (NTRS)

Bowers, Albion H.; Pahle, Joseph W.

1996-01-01

Investigations into a multiaxis thrust-vectoring system have been conducted on an F-18 configuration. These investigations include ground-based scale-model tests, ground-based full-scale testing, and flight testing. This thrust-vectoring system has been tested on the NASA F-18 High Alpha Research Vehicle (HARV). The system provides thrust vectoring in pitch and yaw axes. Ground-based subscale test data have been gathered as background to the flight phase of the program. Tests investigated aerodynamic interaction and vane control effectiveness. The ground-based full-scale data were gathered from static engine runs with image analysis to determine relative thrust-vectoring effectiveness. Flight tests have been conducted at the NASA Dryden Flight Research Center. Parameter identification input techniques have been developed. Individual vanes were not directly controlled because of a mixer-predictor function built into the flight control laws. Combined effects of the vanes have been measured in flight and compared to combined effects of the vanes as predicted by the cold-jet test data. Very good agreement has been found in the linearized effectiveness derivatives.

What is the Risk for Exposure to Vector-Borne Pathogens in United States National Parks?

PubMed Central

EISEN, LARS; WONG, DAVID; SHELUS, VICTORIA; EISEN, REBECCA J.

2015-01-01

United States national parks attract >275 million visitors annually and collectively present risk of exposure for staff and visitors to a wide range of arthropod vector species (most notably fleas, mosquitoes, and ticks) and their associated bacterial, protozoan, or viral pathogens. We assessed the current state of knowledge for risk of exposure to vector-borne pathogens in national parks through a review of relevant literature, including internal National Park Service documents and organismal databases. We conclude that, because of lack of systematic surveillance for vector-borne pathogens in national parks, the risk of pathogen exposure for staff and visitors is unclear. Existing data for vectors within national parks were not based on systematic collections and rarely include evaluation for pathogen infection. Extrapolation of human-based surveillance data from neighboring communities likely provides inaccurate estimates for national parks because landscape differences impact transmission of vector-borne pathogens and human-vector contact rates likely differ inside versus outside the parks because of differences in activities or behaviors. Vector-based pathogen surveillance holds promise to define when and where within national parks the risk of exposure to infected vectors is elevated. A pilot effort, including 5–10 strategic national parks, would greatly improve our understanding of the scope and magnitude of vector-borne pathogen transmission in these high-use public settings. Such efforts also will support messaging to promote personal protection measures and inform park visitors and staff of their responsibility for personal protection, which the National Park Service preservation mission dictates as the core strategy to reduce exposure to vector-borne pathogens in national parks. PMID:23540107

Tensor Sparse Coding for Positive Definite Matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikos

2013-08-02

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for e.g., image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Tensor sparse coding for positive definite matrices.

PubMed

Sivalingam, Ravishankar; Boley, Daniel; Morellas, Vassilios; Papanikolopoulos, Nikolaos

2014-03-01

In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for example, image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This paper proposes a novel sparse coding technique for positive definite matrices, which respects the structure of the Riemannian manifold and preserves the positivity of their eigenvalues, without resorting to vectorization. Synthetic and real-world computer vision experiments with region covariance descriptors demonstrate the need for and the applicability of the new sparse coding model. This work serves to bridge the gap between the sparse modeling paradigm and the space of positive definite matrices.

Vector representation of user's view using self-organizing map

NASA Astrophysics Data System (ADS)

Ae, Tadashi; Yamaguchi, Tomohisa; Monden, Eri; Kawabata, Shunji; Kamitani, Motoki

2004-05-01

There exist various objects, such as pictures, music, texts, etc., around our environment. We have a view for these objects by looking, reading or listening. Our view is concerned with our behaviors deeply, and is very important to understand our behaviors. Therefore, we propose a method which acquires a view as a vector, and apply the vector to sequence generation. We focus on sequences of the data of which a user selects from a multimedia database containing pictures, music, movie, etc.. These data cannot be stereotyped because user's view for them changes by each user. Therefore, we represent the structure of the multimedia database as the vector representing user's view and the stereotyped vector, and acquire sequences containing the structure as elements. We demonstrate a city-sequence generation system which reflects user's intension as an application of sequence generation containing user's view. We apply the self-organizing map to this system to represent user's view.

Inclusive τ lepton hadronic decay in vector and axial-vector channels within dispersive approach to QCD

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

Nesterenko, A. V.

The dispersive approach to QCD, which properly embodies the intrinsically nonperturbative constraints originating in the kinematic restrictions on relevant physical processes and extends the applicability range of perturbation theory towards the infrared domain, is briefly overviewed. The study of OPAL (update 2012) and ALEPH (update 2014) experimental data on inclusive τ lepton hadronic decay in vector and axial-vector channels within dispersive approach is presented.

Vecuum: identification and filtration of false somatic variants caused by recombinant vector contamination.

PubMed

Kim, Junho; Maeng, Ju Heon; Lim, Jae Seok; Son, Hyeonju; Lee, Junehawk; Lee, Jeong Ho; Kim, Sangwoo

2016-10-15

Advances in sequencing technologies have remarkably lowered the detection limit of somatic variants to a low frequency. However, calling mutations at this range is still confounded by many factors including environmental contamination. Vector contamination is a continuously occurring issue and is especially problematic since vector inserts are hardly distinguishable from the sample sequences. Such inserts, which may harbor polymorphisms and engineered functional mutations, can result in calling false variants at corresponding sites. Numerous vector-screening methods have been developed, but none could handle contamination from inserts because they are focusing on vector backbone sequences alone. We developed a novel method-Vecuum-that identifies vector-originated reads and resultant false variants. Since vector inserts are generally constructed from intron-less cDNAs, Vecuum identifies vector-originated reads by inspecting the clipping patterns at exon junctions. False variant calls are further detected based on the biased distribution of mutant alleles to vector-originated reads. Tests on simulated and spike-in experimental data validated that Vecuum could detect 93% of vector contaminants and could remove up to 87% of variant-like false calls with 100% precision. Application to public sequence datasets demonstrated the utility of Vecuum in detecting false variants resulting from various types of external contamination. Java-based implementation of the method is available at http://vecuum.sourceforge.net/ CONTACT: swkim@yuhs.acSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predictiveness of Disease Risk in a Global Outreach Tourist Setting in Thailand Using Meteorological Data and Vector-Borne Disease Incidences

PubMed Central

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-01-01

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate. PMID:25325356

Predictiveness of disease risk in a global outreach tourist setting in Thailand using meteorological data and vector-borne disease incidences.

PubMed

Ninphanomchai, Suwannapa; Chansang, Chitti; Hii, Yien Ling; Rocklöv, Joacim; Kittayapong, Pattamaporn

2014-10-16

Dengue and malaria are vector-borne diseases and major public health problems worldwide. Changes in climatic factors influence incidences of these diseases. The objective of this study was to investigate the relationship between vector-borne disease incidences and meteorological data, and hence to predict disease risk in a global outreach tourist setting. The retrospective data of dengue and malaria incidences together with local meteorological factors (temperature, rainfall, humidity) registered from 2001 to 2011 on Koh Chang, Thailand were used in this study. Seasonal distribution of disease incidences and its correlation with local climatic factors were analyzed. Seasonal patterns in disease transmission differed between dengue and malaria. Monthly meteorological data and reported disease incidences showed good predictive ability of disease transmission patterns. These findings provide a rational basis for identifying the predictive ability of local meteorological factors on disease incidence that may be useful for the implementation of disease prevention and vector control programs on the tourism island, where climatic factors fluctuate.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

Chaibub Neto, Elias

2015-01-01

In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965

Vectorized Rebinning Algorithm for Fast Data Down-Sampling

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Jeffrey

2013-01-01

A vectorized rebinning (down-sampling) algorithm, applicable to N-dimensional data sets, has been developed that offers a significant reduction in computer run time when compared to conventional rebinning algorithms. For clarity, a two-dimensional version of the algorithm is discussed to illustrate some specific details of the algorithm content, and using the language of image processing, 2D data will be referred to as "images," and each value in an image as a "pixel." The new approach is fully vectorized, i.e., the down-sampling procedure is done as a single step over all image rows, and then as a single step over all image columns. Data rebinning (or down-sampling) is a procedure that uses a discretely sampled N-dimensional data set to create a representation of the same data, but with fewer discrete samples. Such data down-sampling is fundamental to digital signal processing, e.g., for data compression applications.

Analysis of vector wind change with respect to time for Cape Kennedy, Florida

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1978-01-01

Multivariate analysis was used to determine the joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from 15 years of twice-daily rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, that the joint distribution of wind component change with respect to time is univariate normal, that the joint distribution of wind component changes is bivariate normal, and that the modulus of vector wind change is Rayleigh are tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from 1 to 5 hours, calculated from Jimsphere data, are presented. Extension of the theoretical prediction (based on rawinsonde data) of wind component change standard deviation to time periods of 1 to 5 hours falls (with a few exceptions) within the 95 percentile confidence band of the population estimate obtained from the Jimsphere sample data. The joint distributions of wind change components, conditional wind components, and 1 km vector wind shear change components are illustrated by probability ellipses at the 95 percentile level.

A simple method of equine limb force vector analysis and its potential applications.

PubMed

Hobbs, Sarah Jane; Robinson, Mark A; Clayton, Hilary M

2018-01-01

Ground reaction forces (GRF) measured during equine gait analysis are typically evaluated by analyzing discrete values obtained from continuous force-time data for the vertical, longitudinal and transverse GRF components. This paper describes a simple, temporo-spatial method of displaying and analyzing sagittal plane GRF vectors. In addition, the application of statistical parametric mapping (SPM) is introduced to analyse differences between contra-lateral fore and hindlimb force-time curves throughout the stance phase. The overall aim of the study was to demonstrate alternative methods of evaluating functional (a)symmetry within horses. GRF and kinematic data were collected from 10 horses trotting over a series of four force plates (120 Hz). The kinematic data were used to determine clean hoof contacts. The stance phase of each hoof was determined using a 50 N threshold. Vertical and longitudinal GRF for each stance phase were plotted both as force-time curves and as force vector diagrams in which vectors originating at the centre of pressure on the force plate were drawn at intervals of 8.3 ms for the duration of stance. Visual evaluation was facilitated by overlay of the vector diagrams for different limbs. Summary vectors representing the magnitude (VecMag) and direction (VecAng) of the mean force over the entire stance phase were superimposed on the force vector diagram. Typical measurements extracted from the force-time curves (peak forces, impulses) were compared with VecMag and VecAng using partial correlation (controlling for speed). Paired samples t -tests (left v. right diagonal pair comparison and high v. low vertical force diagonal pair comparison) were performed on discrete and vector variables using traditional methods and Hotelling's T 2 tests on normalized stance phase data using SPM. Evidence from traditional statistical tests suggested that VecMag is more influenced by the vertical force and impulse, whereas VecAng is more influenced by the longitudinal force and impulse. When used to evaluate mean data from the group of ten sound horses, SPM did not identify differences between the left and right contralateral limb pairs or between limb pairs classified according to directional asymmetry. When evaluating a single horse, three periods were identified during which differences in the forces between the left and right forelimbs exceeded the critical threshold ( p  < .01). Traditional statistical analysis of 2D GRF peak values, summary vector variables and visual evaluation of force vector diagrams gave harmonious results and both methods identified the same inter-limb asymmetries. As alpha was more tightly controlled using SPM, significance was only found in the individual horse although T 2 plots followed the same trends as discrete analysis for the group. The techniques of force vector analysis and SPM hold promise for investigations of sidedness and asymmetry in horses.

User's Guide for Monthly Vector Wind Profile Model

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1999-01-01

The background, theoretical concepts, and methodology for construction of vector wind profiles based on a statistical model are presented. The derived monthly vector wind profiles are to be applied by the launch vehicle design community for establishing realistic estimates of critical vehicle design parameter dispersions related to wind profile dispersions. During initial studies a number of months are used to establish the model profiles that produce the largest monthly dispersions of ascent vehicle aerodynamic load indicators. The largest monthly dispersions for wind, which occur during the winter high-wind months, are used for establishing the design reference dispersions for the aerodynamic load indicators. This document includes a description of the computational process for the vector wind model including specification of input data, parameter settings, and output data formats. Sample output data listings are provided to aid the user in the verification of test output.

Wind Field Extractions from SAR Sentinel-1 Images Using Electromagnetic Models

NASA Astrophysics Data System (ADS)

La, Tran Vu; Khenchaf, Ali; Comblet, Fabrice; Nahum, Carole

2016-08-01

Among available wind sources, i.e. measured data, numeric weather models, the retrieval of wind vectors from Synthetic Aperture Radar (SAR) data / images is particularly preferred due to a lot of SAR systems (available data in most meteorological conditions, revisit mode, high resolution, etc.). For this purpose, the retrieval of wind vectors is principally based on the empirical (EP) models, e.g. CMOD series in C-band. Little studies have been reported about the use of the electromagnetic (EM) models for wind vector retrieval, since it is quite complicated to invert. However, the EM models can be applied for most cases of polarization, frequency and wind regime. In order to evaluate the advantages and limits of the EM models for wind vector retrieval, we compare in this study estimated results by the EM and EP models for both cases of polarization (vertical-vertical, or VV-pol and horizontal- horizontal, or HH-pol).

A Mathematical Motivation for Complex-Valued Convolutional Networks.

PubMed

Tygert, Mark; Bruna, Joan; Chintala, Soumith; LeCun, Yann; Piantino, Serkan; Szlam, Arthur

2016-05-01

A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with complex-valued vectors, followed by (2) taking the absolute value of every entry of the resulting vectors, followed by (3) local averaging. For processing real-valued random vectors, complex-valued convnets can be viewed as data-driven multiscale windowed power spectra, data-driven multiscale windowed absolute spectra, data-driven multiwavelet absolute values, or (in their most general configuration) data-driven nonlinear multiwavelet packets. Indeed, complex-valued convnets can calculate multiscale windowed spectra when the convnet filters are windowed complex-valued exponentials. Standard real-valued convnets, using rectified linear units (ReLUs), sigmoidal (e.g., logistic or tanh) nonlinearities, or max pooling, for example, do not obviously exhibit the same exact correspondence with data-driven wavelets (whereas for complex-valued convnets, the correspondence is much more than just a vague analogy). Courtesy of the exact correspondence, the remarkably rich and rigorous body of mathematical analysis for wavelets applies directly to (complex-valued) convnets.

Discriminant analysis for fast multiclass data classification through regularized kernel function approximation.

PubMed

Ghorai, Santanu; Mukherjee, Anirban; Dutta, Pranab K

2010-06-01

In this brief we have proposed the multiclass data classification by computationally inexpensive discriminant analysis through vector-valued regularized kernel function approximation (VVRKFA). VVRKFA being an extension of fast regularized kernel function approximation (FRKFA), provides the vector-valued response at single step. The VVRKFA finds a linear operator and a bias vector by using a reduced kernel that maps a pattern from feature space into the low dimensional label space. The classification of patterns is carried out in this low dimensional label subspace. A test pattern is classified depending on its proximity to class centroids. The effectiveness of the proposed method is experimentally verified and compared with multiclass support vector machine (SVM) on several benchmark data sets as well as on gene microarray data for multi-category cancer classification. The results indicate the significant improvement in both training and testing time compared to that of multiclass SVM with comparable testing accuracy principally in large data sets. Experiments in this brief also serve as comparison of performance of VVRKFA with stratified random sampling and sub-sampling.

Characteristic vector analysis as a technique for signature extraction of remote ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1977-01-01

Characteristic vector analysis is being used to extract spectral signatures of suspended matter in the ocean from remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor), a multispectral scanner. Spectral signatures appear to be obtainable either directly from characteristic vectors or through a transformation of these eigenvectors. Quantification of the suspended matter associated with each resulting signature seems feasible using associated coefficients generated by the technique. This paper presents eigenvectors associated with algae, 'sediment', acid waste, sewage sludge, and oil. The results suggest an efficient method of transmitting from satellites multispectral data of pollution in our oceans.

An accelerated training method for back propagation networks

NASA Technical Reports Server (NTRS)

Shelton, Robert O. (Inventor)

1993-01-01

The principal objective is to provide a training procedure for a feed forward, back propagation neural network which greatly accelerates the training process. A set of orthogonal singular vectors are determined from the input matrix such that the standard deviations of the projections of the input vectors along these singular vectors, as a set, are substantially maximized, thus providing an optimal means of presenting the input data. Novelty exists in the method of extracting from the set of input data, a set of features which can serve to represent the input data in a simplified manner, thus greatly reducing the time/expense to training the system.

Optimization of Control Strategies for Non-Domiciliated Triatoma dimidiata, Chagas Disease Vector in the Yucatán Peninsula, Mexico

PubMed Central

Barbu, Corentin; Dumonteil, Eric; Gourbière, Sébastien

2009-01-01

Background Chagas disease is the most important vector-borne disease in Latin America. Regional initiatives based on residual insecticide spraying have successfully controlled domiciliated vectors in many regions. Non-domiciliated vectors remain responsible for a significant transmission risk, and their control is now a key challenge for disease control. Methodology/Principal Findings A mathematical model was developed to predict the temporal variations in abundance of non-domiciliated vectors inside houses. Demographic parameters were estimated by fitting the model to two years of field data from the Yucatan peninsula, Mexico. The predictive value of the model was tested on an independent data set before simulations examined the efficacy of control strategies based on residual insecticide spraying, insect screens, and bednets. The model accurately fitted and predicted field data in the absence and presence of insecticide spraying. Pyrethroid spraying was found effective when 50 mg/m2 were applied yearly within a two-month period matching the immigration season. The >80% reduction in bug abundance was not improved by larger doses or more frequent interventions, and it decreased drastically for different timing and lower frequencies of intervention. Alternatively, the use of insect screens consistently reduced bug abundance proportionally to the reduction of the vector immigration rate. Conclusion/Significance Control of non-domiciliated vectors can hardly be achieved by insecticide spraying, because it would require yearly application and an accurate understanding of the temporal pattern of immigration. Insect screens appear to offer an effective and sustainable alternative, which may be part of multi-disease interventions for the integrated control of neglected vector-borne diseases. PMID:19365542

Agriculture Canada Central Saskatchewan Vector Soils Data

NASA Technical Reports Server (NTRS)

Knapp, David; Hall, Forrest G. (Editor); Rostad, Harold

2000-01-01

This data set consists of GIS layers that describe the soils of the BOREAS SSA. These original data layers were submitted as vector data in ARC/INFO EXPORT format. These data also include the soil name and soil layer files, which provide additional information about the soils. There are three sets of attributes that include information on the primary, secondary, and tertiary soil type within each polygon. Thus, there is a total of nine main attributes in this data set.

Identifying saltcedar with hyperspectral data and support vector machines

USDA-ARS?s Scientific Manuscript database

Saltcedar (Tamarix spp.) are a group of dense phreatophytic shrubs and trees that are invasive to riparian areas throughout the United States. This study determined the feasibility of using hyperspectral data and a support vector machine (SVM) classifier to discriminate saltcedar from other cover t...

Genetic modification of hematopoietic cells using retroviral and lentiviral vectors: safety considerations for vector design and delivery into target cells.

PubMed

Dropulic, Boro

2005-07-01

The recent development of leukemia in three patients following retroviral vector gene transfer in hematopoietic stem cells, resulting in the death of one patient, has raised safety concerns for the use of integrating gene transfer vectors for human gene therapy. This review discusses these serious adverse events from the perspective of whether restrictions on vector design and vector-modified target cells are warranted at this time. A case is made against presently establishing specific restrictions for vector design and transduced cells; rather, their safety should be ascertained by empiric evaluation in appropriate preclinical models on a case-by-case basis. Such preclinical data, coupled with proper informed patient consent and a risk-benefit ratio analysis, provide the best available prospective evaluation of gene transfer vectors prior to their translation into the clinic.

Evaluation of the SPAR thermal analyzer on the CYBER-203 computer

NASA Technical Reports Server (NTRS)

Robinson, J. C.; Riley, K. M.; Haftka, R. T.

1982-01-01

The use of the CYBER 203 vector computer for thermal analysis is investigated. Strengths of the CYBER 203 include the ability to perform, in vector mode using a 64 bit word, 50 million floating point operations per second (MFLOPS) for addition and subtraction, 25 MFLOPS for multiplication and 12.5 MFLOPS for division. The speed of scalar operation is comparable to that of a CDC 7600 and is some 2 to 3 times faster than Langley's CYBER 175s. The CYBER 203 has 1,048,576 64-bit words of real memory with an 80 nanosecond (nsec) access time. Memory is bit addressable and provides single error correction, double error detection (SECDED) capability. The virtual memory capability handles data in either 512 or 65,536 word pages. The machine has 256 registers with a 40 nsec access time. The weaknesses of the CYBER 203 include the amount of vector operation overhead and some data storage limitations. In vector operations there is a considerable amount of time before a single result is produced so that vector calculation speed is slower than scalar operation for short vectors.

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.

Photoproduction of vector mesons in proton-proton ultraperipheral collisions at the CERN Large Hadron Collider

NASA Astrophysics Data System (ADS)

Xie, Ya-Ping; Chen, Xurong

2018-05-01

Photoproduction of vector mesons is computed with dipole model in proton-proton ultraperipheral collisions (UPCs) at the CERN Large Hadron Collider (LHC). The dipole model framework is employed in the calculations of vector mesons production in diffractive processes. Parameters of the bCGC model are refitted with the latest inclusive deep inelastic scattering experimental data. Employing the bCGC model and boosted Gaussian light-cone wave function for vector mesons, we obtain the prediction of rapidity distributions of J/ψ and ψ(2s) mesons in proton-proton ultraperipheral collisions at the LHC. The predictions give a good description of the experimental data of LHCb. Predictions of ϕ and ω mesons are also evaluated in this paper.

Applying Genomic and Bioinformatic Resources to Human Adenovirus Genomes for Use in Vaccine Development and for Applications in Vector Development for Gene Delivery

PubMed Central

Seto, Jason; Walsh, Michael P.; Mahadevan, Padmanabhan; Zhang, Qiwei; Seto, Donald

2010-01-01

Technological advances and increasingly cost-effect methodologies in DNA sequencing and computational analysis are providing genome and proteome data for human adenovirus research. Applying these tools, data and derived knowledge to the development of vaccines against these pathogens will provide effective prophylactics. The same data and approaches can be applied to vector development for gene delivery in gene therapy and vaccine delivery protocols. Examination of several field strain genomes and their analyses provide examples of data that are available using these approaches. An example of the development of HAdV-B3 both as a vaccine and also as a vector is presented. PMID:21994597

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

NASA Technical Reports Server (NTRS)

Jaggi, S.

1993-01-01

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Insulated Foamy Viral Vectors

PubMed Central

Browning, Diana L.; Collins, Casey P.; Hocum, Jonah D.; Leap, David J.; Rae, Dustin T.; Trobridge, Grant D.

2016-01-01

Retroviral vector-mediated gene therapy is promising, but genotoxicity has limited its use in the clinic. Genotoxicity is highly dependent on the retroviral vector used, and foamy viral (FV) vectors appear relatively safe. However, internal promoters may still potentially activate nearby genes. We developed insulated FV vectors, using four previously described insulators: a version of the well-studied chicken hypersensitivity site 4 insulator (650cHS4), two synthetic CCCTC-binding factor (CTCF)-based insulators, and an insulator based on the CCAAT box-binding transcription factor/nuclear factor I (7xCTF/NF1). We directly compared these insulators for enhancer-blocking activity, effect on FV vector titer, and fidelity of transfer to both proviral long terminal repeats. The synthetic CTCF-based insulators had the strongest insulating activity, but reduced titers significantly. The 7xCTF/NF1 insulator did not reduce titers but had weak insulating activity. The 650cHS4-insulated FV vector was identified as the overall most promising vector. Uninsulated and 650cHS4-insulated FV vectors were both significantly less genotoxic than gammaretroviral vectors. Integration sites were evaluated in cord blood CD34+ cells and the 650cHS4-insulated FV vector had fewer hotspots compared with an uninsulated FV vector. These data suggest that insulated FV vectors are promising for hematopoietic stem cell gene therapy. PMID:26715244

Contingency Pest and Vector Surveillance

DTIC Science & Technology

2013-11-01

Baseline Survey - conducted to determine the types of vectors and pests occurring in the area of operations, their respective breeding sites or...source habitat, and seasonal activity patterns. Operational Survey - data collected in an operational survey are used specifically to aid pest...management personnel in making decisions on when to start or stop control measures. Operational survey data is compared to baseline data and the

Strengthening tactical planning and operational frameworks for vector control: the roadmap for malaria elimination in Namibia.

PubMed

Chanda, Emmanuel; Ameneshewa, Birkinesh; Angula, Hans A; Iitula, Iitula; Uusiku, Pentrina; Trune, Desta; Islam, Quazi M; Govere, John M

2015-08-05

Namibia has made tremendous gains in malaria control and the epidemiological trend of the disease has changed significantly over the past years. In 2010, the country reoriented from the objective of reducing disease morbidity and mortality to the goal of achieving malaria elimination by 2020. This manuscript outlines the processes undertaken in strengthening tactical planning and operational frameworks for vector control to facilitate expeditious malaria elimination in Namibia. The information sources for this study included all available data and accessible archived documentary records on malaria vector control in Namibia. A methodical assessment of published and unpublished documents was conducted via a literature search of online electronic databases, Google Scholar, PubMed and WHO, using a combination of search terms. To attain the goal of elimination in Namibia, systems are being strengthened to identify and clear all infections, and significantly reduce human-mosquito contact. Particularly, consolidating vector control for reducing transmission at the identified malaria foci will be critical for accelerated malaria elimination. Thus, guarding against potential challenges and the need for evidence-based and sustainable vector control instigated the strengthening of strategic frameworks by: adopting the integrated vector management (IVM) strategy; initiating implementation of the global plan for insecticide resistance management (GPIRM); intensifying malaria vector surveillance; improving data collection and reporting systems on DDT; updating the indoor residual spraying (IRS) data collection and reporting tool; and, improving geographical reconnaissance using geographical information system-based satellite imagery. Universal coverage with IRS and long-lasting insecticidal nets, supplemented by larval source management in the context of IVM and guided by vector surveillance coupled with rational operationalization of the GPIRM, will enable expeditious attainment of elimination in Namibia. However, national capacity to plan, implement, monitor and evaluate interventions will require adequate and sustained support for technical, physical infrastructure, and human and financial resources for entomology and vector control operations.

Self-Organizing-Map Program for Analyzing Multivariate Data

NASA Technical Reports Server (NTRS)

Li, P. Peggy; Jacob, Joseph C.; Block, Gary L.; Braverman, Amy J.

2005-01-01

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

The Application of a Technique for Vector Correlation to Problems in Meteorology and Oceanography.

NASA Astrophysics Data System (ADS)

Breaker, L. C.; Gemmill, W. H.; Crosby, D. S.

1994-11-01

In a recent study, Crosby et al. proposed a definition for vector correlation that has not been commonly used in meteorology or oceanography. This definition has both a firm theoretical basis and a rather complete set of desirable statistical properties. In this study, the authors apply the definition to practical problems arising in meteorology and oceanography. In the first of two case studies, vector correlations were calculated between subsurface currents for five locations along the southeastern shore of Lake Erie. Vector correlations for one sample size were calculated for all current meter combinations, first including the seiche frequency and then with the seiche frequency removed. Removal of the seiche frequency, which was easily detected in the current spectra, had only a small effect on the vector correlations. Under reasonable assumptions, the vector correlations were in most cases statistically significant and revealed considerable fine structure in the vector correlation sequences. In some cases, major variations in vector correlation coincided with changes in surface wind. The vector correlations for the various current meter combinations decreased rapidly with increasing spatial separation. For one current meter combination, canonical correlations were also calculated; the first canonical correlation tended to retain the underlying trend, whereas the second canonical correlation retained the peaks in the vector correlations.In the second case study, vector correlations were calculated between marine surface winds derived from the National Meteorological Center's Global Data Assimilation System and observed winds acquired from the network of National Data Buoy Center buoys that are located off the continental United States and in the Gulf of Alaska. Results of this comparison indicated that 1) there was a significant decrease in correlation between the predicted and observed winds with increasing forecast interval out to 72 h, 2) the technique provides a sensitive indicator for detecting bad buoy reports, and 3) there was no obvious seasonal cycle in the monthly vector correlations for the period of observation.

Impact of Short Interval SMS Digital Data on Wind Vector Determination for a Severe Local Storms Area

NASA Technical Reports Server (NTRS)

Peslen, C. A.

1979-01-01

The impact of 5 minute interval SMS-2 visible digital image data in analyzing severe local storms is examined using wind vectors derived from cloud tracking on time lapsed sequence of geosynchronous satellite images. The cloud tracking areas are located in the Central Plains, where on 6 May 1975, hail-producing thunderstorms occurred ahead of a well defined dry line. The results demonstrate that satellite-derived wind vectors and their associated divergence fields complement conventional meteorological analyses in describing the conditions preceding severe local storm development.

Estimation of Target Angular Position Under Mainbeam Jamming Conditions,

DTIC Science & Technology

1995-12-01

technique, Multiple Signal Classification ( MUSIC ), is used to estimate the target Direction Of Arrival (DOA) from the processed data vectors. The model...used in the MUSIC technique takes into account the fact that the jammer has been cancelled in the target data vector. The performance of this algorithm

Comparison of Support Vector Machine, Neural Network, and CART Algorithms for the Land-Cover Classification Using Limited Training Data Points

EPA Science Inventory

Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data. Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity). The results were compared to two convention...

Malaria entomological profile in Tanzania from 1950 to 2010: a review of mosquito distribution, vectorial capacity and insecticide resistance.

PubMed

Kabula, Bilali; Derua, Yahya A; Tungui, Patrick; Massue, Dennis J; Sambu, Edward; Stanley, Grades; Mosha, Franklin W; Kisinza, William N

2011-12-01

In Sub Saharan Africa where most of the malaria cases and deaths occur, members of the Anopheles gambiae species complex and Anophelesfunestus species group are the important malaria vectors. Control efforts against these vectors in Tanzania like in most other Sub Saharan countries have failed to achieve the set objectives of eliminating transmission due to scarcity of information about the enormous diversity of Anopheles mosquito species and their susceptibility status to insecticides used for malaria vector control. Understanding the diversity and insecticide susceptibility status of these vectors and other factors relating to their importance as vectors (such as malaria transmission dynamics, vector biology, ecology, behaviour and population genetics) is crucial to developing a better and sound intervention strategies that will reduce man-vector contact and also manage the emergency of insecticide resistance early and hence .a success in malaria control. The objective of this review was therefore to obtain the information from published and unpublished documents on spatial distribution and composition of malaria vectors, key features of their behaviour, transmission indices and susceptibility status to insecticides in Tanzania. All data available were collated into a database. Details recorded for each data source were the locality, latitude/longitude, time/period of study, species, abundance, sampling/collection methods, species identification methods, insecticide resistance status, including evidence of the kdr allele, and Plasmodium falciparum sporozoite rate. This collation resulted in a total of 368 publications, encompassing 806,273 Anopheles mosquitoes from 157 georeferenced locations being collected and identified across Tanzania from 1950s to 2010. Overall, the vector species most often reported included An. gambiae complex (66.8%), An. funestus complex (21.8%), An. gambiae s.s. (2.1%) and An. arabiensis (9%). A variety of sampling/ collection and species identification methods were used with an increase in molecular techniques in recent decades. Only 32.2% and 8.4% of the data sets reported on sporozoite analysis and entomological inoculation rate (EIR), respectively which highlights the paucity of such important information in the country. Studies demonstrated efficacy of all four major classes of insecticides against malaria vectors in Tanzania with focal points showing phenotypic resistance. About 95% of malaria entomological data was obtained from northeastern Tanzania. This shows the disproportionate nature of the available information with the western part of the country having none. Therefore it is important for the country to establish entomological surveillance system with state of the art to capture all vitally important entomological indices including vector bionomics in areas of Tanzania where very few or no studies have been done. This is vital in planning and implementing evidence based malaria vector control programmes as well as in monitoring the current malaria control interventions.

Dengue and climate change in Australia: predictions for the future should incorporate knowledge from the past.

PubMed

Russell, Richard C; Currie, Bart J; Lindsay, Michael D; Mackenzie, John S; Ritchie, Scott A; Whelan, Peter I

2009-03-02

Dengue transmission in Australia is currently restricted to Queensland, where the vector mosquito Aedes aegypti is established. Locally acquired infections have been reported only from urban areas in the north-east of the state, where the vector is most abundant. Considerable attention has been drawn to the potential impact of climate change on dengue distribution within Australia, with projections for substantial rises in incidence and distribution associated with increasing temperatures. However, historical data show that much of Australia has previously sustained both the vector mosquito and dengue viruses. Although current vector distribution is restricted to Queensland, the area inhabited by A. aegypti is larger than the disease-transmission areas, and is not restricted by temperature (or vector-control programs); thus, it is unlikely that rising temperatures alone will bring increased vector or virus distribution. Factors likely to be important to dengue and vector distribution in the future include increased dengue activity in Asian and Pacific nations that would raise rates of virus importation by travellers, importation of vectors via international ports to regions without A. aegypti, higher rates of domestic collection and storage of water that would provide habitat in urban areas, and growing human populations in northern Australia. Past and recent successful control initiatives in Australia lend support to the idea that well resourced and functioning surveillance programs, and effective public health intervention capabilities, are essential to counter threats from dengue and other mosquito-borne diseases. Models projecting future activity of dengue (or other vector-borne disease) with climate change should carefully consider the local historical and contemporary data on the ecology and distribution of the vector and local virus transmission.

Three-Dimensional Analysis of Long-Term Midface Volume Change After Vertical Vector Deep-Plane Rhytidectomy.

PubMed

Jacono, Andrew A; Malone, Melanie H; Talei, Benjamin

2015-07-01

Facial aging is a complicated process that includes volume loss and soft tissue descent. This study provides quantitative 3-dimensional (3D) data on the long-term effect of vertical vector deep-plane rhytidectomy on restoring volume to the midface. To determine if primary vertical vector deep-plane rhytidectomy resulted in long-term volume change in the midface. We performed a prospective study on patients undergoing primary vertical vector deep-plane rhytidectomy to quantitate 3D volume changes in the midface. Quantitative analysis of volume changes was made using the Vectra 3D imaging software (Canfield Scientific, Inc, Fairfield, New Jersey) at a minimum follow-up of 1 year. Forty-three patients (86 hemifaces) were analyzed. The average volume gained in each hemi-midface after vertical vector deep-plane rhytidectomy was 3.2 mL. Vertical vector deep-plane rhytidectomy provides significant long-term augmentation of volume in the midface. These quantitative data demonstrate that some midface volume loss is related to gravitational descent of the cheek fat compartments and that vertical vector deep-plane rhytidectomy may obviate the need for other volumization procedures such as autologous fat grafting in selected cases. 4 Therapeutic. © 2015 The American Society for Aesthetic Plastic Surgery, Inc. Reprints and permission: journals.permissions@oup.com.

Estimating locations and total magnetization vectors of compact magnetic sources from scalar, vector, or tensor magnetic measurements through combined Helbig and Euler analysis

USGS Publications Warehouse

Phillips, J.D.; Nabighian, M.N.; Smith, D.V.; Li, Y.

2007-01-01

The Helbig method for estimating total magnetization directions of compact sources from magnetic vector components is extended so that tensor magnetic gradient components can be used instead. Depths of the compact sources can be estimated using the Euler equation, and their dipole moment magnitudes can be estimated using a least squares fit to the vector component or tensor gradient component data. ?? 2007 Society of Exploration Geophysicists.

Thrust Vector Control of an Overexpanded Supersonic Nozzle Using Pin Insertion and Rotating Airfoils

DTIC Science & Technology

1991-12-01

12 THRUST VECTOR CONTROL OP AN OVEREXPANDED 3UPfRSONIC NOZZLE USING PIN INSERTION AND ROTATINO AIRFOILS THESIS Presented to the Faculty of the School...gather data that would aid in the evaluation of thrust vector control mechanisms for nozzle applications. I would like to thank my thesis advisor, Dr... Control Nozzle. MS Thesis . Air Force Institute of Technology (AU), Wright- Patterson AFB OH, December 1988. 4. Herup, Eric J. Confined Jet Thrust Vector

Assessment of ICount software, a precise and fast egg counting tool for the mosquito vector Aedes aegypti.

PubMed

Gaburro, Julie; Duchemin, Jean-Bernard; Paradkar, Prasad N; Nahavandi, Saeid; Bhatti, Asim

2016-11-18

Widespread in the tropics, the mosquito Aedes aegypti is an important vector of many viruses, posing a significant threat to human health. Vector monitoring often requires fecundity estimation by counting eggs laid by female mosquitoes. Traditionally, manual data analyses have been used but this requires a lot of effort and is the methods are prone to errors. An easy tool to assess the number of eggs laid would facilitate experimentation and vector control operations. This study introduces a built-in software called ICount allowing automatic egg counting of the mosquito vector, Aedes aegypti. ICount egg estimation compared to manual counting is statistically equivalent, making the software effective for automatic and semi-automatic data analysis. This technique also allows rapid analysis compared to manual methods. Finally, the software has been used to assess p-cresol oviposition choices under laboratory conditions in order to test the system with different egg densities. ICount is a powerful tool for fast and precise egg count analysis, freeing experimenters from manual data processing. Software access is free and its user-friendly interface allows easy use by non-experts. Its efficiency has been tested in our laboratory with oviposition dual choices of Aedes aegypti females. The next step will be the development of a mobile application, based on the ICount platform, for vector monitoring surveys in the field.

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Anthropogenic disturbance and the risk of flea-borne disease transmission

Treesearch

Megan M. Friggens; Paul Beier

2010-01-01

Anthropogenic disturbance may lead to the spread of vector-borne diseases through effects on pathogens, vectors, and hosts. Identifying the type and extent of vector response to habitat change will enable better and more accurate management strategies for anthropogenic disease spread. We compiled and analyzed data from published empirical studies to test for patterns...

Multigrid Equation Solvers for Large Scale Nonlinear Finite Element Simulations

DTIC Science & Technology

1999-01-01

purpose of the second partitioning phase , on each SMP, is to minimize the communication within the SMP; even if a multi - threaded matrix vector product...8.7 Comparison of model with experimental data for send phase of matrix vector product on ne grid...140 8.4 Matrix vector product phase times : : : : : : : : : : : : : : : : : : : : : : : 145 9.1 Flat and

Limits on the Efficiency of Event-Based Algorithms for Monte Carlo Neutron Transport

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

Romano, Paul K.; Siegel, Andrew R.

The traditional form of parallelism in Monte Carlo particle transport simulations, wherein each individual particle history is considered a unit of work, does not lend itself well to data-level parallelism. Event-based algorithms, which were originally used for simulations on vector processors, may offer a path toward better utilizing data-level parallelism in modern computer architectures. In this study, a simple model is developed for estimating the efficiency of the event-based particle transport algorithm under two sets of assumptions. Data collected from simulations of four reactor problems using OpenMC was then used in conjunction with the models to calculate the speedup duemore » to vectorization as a function of two parameters: the size of the particle bank and the vector width. When each event type is assumed to have constant execution time, the achievable speedup is directly related to the particle bank size. We observed that the bank size generally needs to be at least 20 times greater than vector size in order to achieve vector efficiency greater than 90%. When the execution times for events are allowed to vary, however, the vector speedup is also limited by differences in execution time for events being carried out in a single event-iteration. For some problems, this implies that vector effciencies over 50% may not be attainable. While there are many factors impacting performance of an event-based algorithm that are not captured by our model, it nevertheless provides insights into factors that may be limiting in a real implementation.« less

Remote Sensing as a Landscape Epidemiologic Tool to Identify Villages at High Risk for Malaria Transmission

NASA Technical Reports Server (NTRS)

Beck, Louisa R.; Rodriquez, Mario H.; Dister, Sheri W.; Rodriquez, Americo D.; Rejmankova, Eliska; Ulloa, Armando; Meza, Rosa A.; Roberts, Donald R.; Paris, Jack F.; Spanner, Michael A.;

Multi-Parent Clustering Algorithms from Stochastic Grammar Data Models

NASA Technical Reports Server (NTRS)

Mjoisness, Eric; Castano, Rebecca; Gray, Alexander

1999-01-01

We introduce a statistical data model and an associated optimization-based clustering algorithm which allows data vectors to belong to zero, one or several "parent" clusters. For each data vector the algorithm makes a discrete decision among these alternatives. Thus, a recursive version of this algorithm would place data clusters in a Directed Acyclic Graph rather than a tree. We test the algorithm with synthetic data generated according to the statistical data model. We also illustrate the algorithm using real data from large-scale gene expression assays.

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.

Magsat vector magnetometer calibration using Magsat geomagnetic field measurements

NASA Technical Reports Server (NTRS)

Lancaster, E. R.; Jennings, T.; Morrissey, M.; Langel, R. A.

1980-01-01

From the time of its launch on Oct. 30, 1979 into a nearly polar, Sun synchronous orbit, until it reentered the Earth's atmosphere on June 11, 1980, Magsat measured and transmitted more than three complete sets of global magnetic field data. The data obtained from the mission will be used primarily to compute a currently accurate model of the Earth's main magnetic field, to update and refine world and regional magnetic charts, and to develop a global scalar and vector crustal magnetic anomaly map. The in-flight calibration procecure used for 39 vector magnetometer system parameters is described as well as results obtained from some data sets and the numerical studies designed to evaluate the results.

Vector wind, horizontal divergence, wind stress and wind stress curl from SEASAT-SASS at one degree resolution

NASA Technical Reports Server (NTRS)

Pierson, W. J., Jr.; Sylvester, W. B.; Salfi, R. E.

1984-01-01

Conventional data obtained in 1983 are contrasted with SEASAT-A scatterometer and scanning multichannel microwave radiometer (SMMR) data to show how observations at a single station can be extended to an area of about 150,000 square km by means of remotely sensed data obtained in nine minutes. Superobservations at a one degree resolution for the vector winds were estimated along with their standard deviations. From these superobservations, the horizontal divergence, vector wind stress, and the curl of the wind stress can be found. Weather forecasting theory is discussed and meteorological charts of the North Pacific Ocean are presented. Synoptic meteorology as a technique is examined.

Communication systems, transceivers, and methods for generating data based on channel characteristics

DOEpatents

Forman, Michael A; Young, Derek

2012-09-18

Examples of methods for generating data based on a communications channel are described. In one such example, a processing unit may generate a first vector representation based in part on at least two characteristics of a communications channel. A constellation having at least two dimensions may be addressed with the first vector representation to identify a first symbol associated with the first vector representation. The constellation represents a plurality of regions, each region associated with a respective symbol. The symbol may be used to generate data, which may stored in an electronic storage medium and used as a cryptographic key or a spreading code or hopping sequence in a modulation technique.

Road Damage Extraction from Post-Earthquake Uav Images Assisted by Vector Data

NASA Astrophysics Data System (ADS)

Chen, Z.; Dou, A.

2018-04-01

Extraction of road damage information after earthquake has been regarded as urgent mission. To collect information about stricken areas, Unmanned Aerial Vehicle can be used to obtain images rapidly. This paper put forward a novel method to detect road damage and bring forward a coefficient to assess road accessibility. With the assistance of vector road data, image data of the Jiuzhaigou Ms7.0 Earthquake is tested. In the first, the image is clipped according to vector buffer. Then a large-scale segmentation is applied to remove irrelevant objects. Thirdly, statistics of road features are analysed, and damage information is extracted. Combining with the on-filed investigation, the extraction result is effective.

Vector Autoregression, Structural Equation Modeling, and Their Synthesis in Neuroimaging Data Analysis

PubMed Central

Chen, Gang; Glen, Daniel R.; Saad, Ziad S.; Hamilton, J. Paul; Thomason, Moriah E.; Gotlib, Ian H.; Cox, Robert W.

2011-01-01

Vector autoregression (VAR) and structural equation modeling (SEM) are two popular brain-network modeling tools. VAR, which is a data-driven approach, assumes that connected regions exert time-lagged influences on one another. In contrast, the hypothesis-driven SEM is used to validate an existing connectivity model where connected regions have contemporaneous interactions among them. We present the two models in detail and discuss their applicability to FMRI data, and interpretational limits. We also propose a unified approach that models both lagged and contemporaneous effects. The unifying model, structural vector autoregression (SVAR), may improve statistical and explanatory power, and avoids some prevalent pitfalls that can occur when VAR and SEM are utilized separately. PMID:21975109

Aeroservoelastic Modeling and Validation of a Thrust-Vectoring F/A-18 Aircraft

NASA Technical Reports Server (NTRS)

Brenner, Martin J.

1996-01-01

An F/A-18 aircraft was modified to perform flight research at high angles of attack (AOA) using thrust vectoring and advanced control law concepts for agility and performance enhancement and to provide a testbed for the computational fluid dynamics community. Aeroservoelastic (ASE) characteristics had changed considerably from the baseline F/A-18 aircraft because of structural and flight control system amendments, so analyses and flight tests were performed to verify structural stability at high AOA. Detailed actuator models that consider the physical, electrical, and mechanical elements of actuation and its installation on the airframe were employed in the analysis to accurately model the coupled dynamics of the airframe, actuators, and control surfaces. This report describes the ASE modeling procedure, ground test validation, flight test clearance, and test data analysis for the reconfigured F/A-18 aircraft. Multivariable ASE stability margins are calculated from flight data and compared to analytical margins. Because this thrust-vectoring configuration uses exhaust vanes to vector the thrust, the modeling issues are nearly identical for modem multi-axis nozzle configurations. This report correlates analysis results with flight test data and makes observations concerning the application of the linear predictions to thrust-vectoring and high-AOA flight.

TreeVector: scalable, interactive, phylogenetic trees for the web.

PubMed

Pethica, Ralph; Barker, Gary; Kovacs, Tim; Gough, Julian

2010-01-28

Phylogenetic trees are complex data forms that need to be graphically displayed to be human-readable. Traditional techniques of plotting phylogenetic trees focus on rendering a single static image, but increases in the production of biological data and large-scale analyses demand scalable, browsable, and interactive trees. We introduce TreeVector, a Scalable Vector Graphics-and Java-based method that allows trees to be integrated and viewed seamlessly in standard web browsers with no extra software required, and can be modified and linked using standard web technologies. There are now many bioinformatics servers and databases with a range of dynamic processes and updates to cope with the increasing volume of data. TreeVector is designed as a framework to integrate with these processes and produce user-customized phylogenies automatically. We also address the strengths of phylogenetic trees as part of a linked-in browsing process rather than an end graphic for print. TreeVector is fast and easy to use and is available to download precompiled, but is also open source. It can also be run from the web server listed below or the user's own web server. It has already been deployed on two recognized and widely used database Web sites.

Digital TV processing system

NASA Technical Reports Server (NTRS)

1975-01-01

Two digital video data compression systems directly applicable to the Space Shuttle TV Communication System were described: (1) For the uplink, a low rate monochrome data compressor is used. The compression is achieved by using a motion detection technique in the Hadamard domain. To transform the variable source rate into a fixed rate, an adaptive rate buffer is provided. (2) For the downlink, a color data compressor is considered. The compression is achieved first by intra-color transformation of the original signal vector, into a vector which has lower information entropy. Then two-dimensional data compression techniques are applied to the Hadamard transformed components of this last vector. Mathematical models and data reliability analyses were also provided for the above video data compression techniques transmitted over a channel encoded Gaussian channel. It was shown that substantial gains can be achieved by the combination of video source and channel coding.

Anopheles atroparvus density modeling using MODIS NDVI in a former malarious area in Portugal.

PubMed

Lourenço, Pedro M; Sousa, Carla A; Seixas, Júlia; Lopes, Pedro; Novo, Maria T; Almeida, A Paulo G

2011-12-01

Malaria is dependent on environmental factors and considered as potentially re-emerging in temperate regions. Remote sensing data have been used successfully for monitoring environmental conditions that influence the patterns of such arthropod vector-borne diseases. Anopheles atroparvus density data were collected from 2002 to 2005, on a bimonthly basis, at three sites in a former malarial area in Southern Portugal. The development of the Remote Vector Model (RVM) was based upon two main variables: temperature and the Normalized Differential Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite. Temperature influences the mosquito life cycle and affects its intra-annual prevalence, and MODIS NDVI was used as a proxy for suitable habitat conditions. Mosquito data were used for calibration and validation of the model. For areas with high mosquito density, the model validation demonstrated a Pearson correlation of 0.68 (p<0.05) and a modelling efficiency/Nash-Sutcliffe of 0.44 representing the model's ability to predict intra- and inter-annual vector density trends. RVM estimates the density of the former malarial vector An. atroparvus as a function of temperature and of MODIS NDVI. RVM is a satellite data-based assimilation algorithm that uses temperature fields to predict the intra- and inter-annual densities of this mosquito species using MODIS NDVI. RVM is a relevant tool for vector density estimation, contributing to the risk assessment of transmission of mosquito-borne diseases and can be part of the early warning system and contingency plans providing support to the decision making process of relevant authorities. © 2011 The Society for Vector Ecology.

Application of Hyperspectal Techniques to Monitoring & Management of Invasive Plant Species Infestation

DTIC Science & Technology

2008-01-09

The image data as acquired from the sensor is a data cloud in multi- dimensional space with each band generating an axis of dimension. When the data... The color of a material is defined by the direction of its unit vector in n- dimensional spectral space . The length of the vector relates only to how...to n- dimensional space . SAM determines the similarity

Digital photogrammetry at the U.S. Geological Survey

USGS Publications Warehouse

Greve, Clifford W.

1995-01-01

The U.S. Geological Survey is converting its primary map production and revision operations to use digital photogrammetric techniques. The primary source of data for these operations is the digital orthophoto quadrangle derived from National Aerial Photography Program images. These digital orthophotos are used on workstations that permit comparison of existing vector and raster data with the orthophoto and interactive collection and revision of the vector data.

Genetic Testing Registry

MedlinePlus

... Splign Vector Alignment Search Tool (VAST) All Data & Software Resources... Domains & Structures BioSystems Cn3D Conserved Domain Database (CDD) Conserved Domain Search Service (CD Search) Structure (Molecular Modeling Database) Vector Alignment ...

[Comparison of classical 2D measurement of scoliosis and 3D measurement using vertebral vectors; advantages for prognosis and treatment evaluation].

PubMed

Illés, Tamás

2011-03-01

The EOS system is a new medical imaging device based on low-dose X-rays, gaseous detectors and dedicated software for 3D reconstruction. It was developed by Nobel prizewinner Georges Charpak. A new concept--the vertebral vector--is used to facilitate the interpretation of EOS data, especially in the horizontal plane. We studied 95 cases of idiopathic scoliosis before and after surgery by means of classical methods and using vertebral vectors, in order to compare the accuracy of the two approaches. The vertebral vector permits simultaneous analysis of the scoliotic curvature in the frontal, sagittal and horizontal planes, as precisely as classical methods. The use of the vertebral vector simplifies and facilitates the interpretation of the mass of information provided by EOS. After analyzing the horizontal data, the first goal of corrective intervention would be to reduce the lateral vertebral deviation. The reduction in vertebral rotation seems less important. This is a new element in the therapeutic management of spinal deformations.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.

PubMed

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝ d , and the dictionary is learned from the training data using the vector space structure of ℝ d and its Euclidean L 2 -metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis.

On A Nonlinear Generalization of Sparse Coding and Dictionary Learning

PubMed Central

Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba

2013-01-01

Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝd, and the dictionary is learned from the training data using the vector space structure of ℝd and its Euclidean L2-metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis. PMID:24129583

Analyzing neural responses with vector fields.

PubMed

Buneo, Christopher A

2011-04-15

Analyzing changes in the shape and scale of single cell response fields is a key component of many neurophysiological studies. Typical analyses of shape change involve correlating firing rates between experimental conditions or "cross-correlating" single cell tuning curves by shifting them with respect to one another and correlating the overlapping data. Such shifting results in a loss of data, making interpretation of the resulting correlation coefficients problematic. The problem is particularly acute for two dimensional response fields, which require shifting along two axes. Here, an alternative method for quantifying response field shape and scale based on correlation of vector field representations is introduced. The merits and limitations of the methods are illustrated using both simulated and experimental data. It is shown that vector correlation provides more information on response field changes than scalar correlation without requiring field shifting and concomitant data loss. An extension of this vector field approach is also demonstrated which can be used to identify the manner in which experimental variables are encoded in studies of neural reference frames. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

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

Estimating the Crustal Power Spectrum From Vector Magsat Data: Crustal Power Spectrum

NASA Technical Reports Server (NTRS)

Lowe, David A. J.; Parker, Robert L.; Purucker, Michael E.; Constable, Catherine G.

2000-01-01

The Earth's magnetic field can be subdivided into core and crustal components and we seek to characterize the crustal part through its spatial power spectrum (R(sub l)). We process vector Magsat data to isolate the crustal field and then invert power spectral densities of flight-local components along-track for R(sub l) following O'Brien et al. [1999]. Our model (LPPC) is accurate up to approximately degree 45 (lambda=900 km) - this is the resolution limit of our data and suggests that global crustal anomaly maps constructed from vector Magsat data should not contain features with wavelengths less than 900 km. We find continental power spectra to be greater than oceanic ones and attribute this to the relative thicknesses of continental and oceanic crust.

A simple method of equine limb force vector analysis and its potential applications

PubMed Central

Robinson, Mark A.; Clayton, Hilary M.

2018-01-01

Background Ground reaction forces (GRF) measured during equine gait analysis are typically evaluated by analyzing discrete values obtained from continuous force-time data for the vertical, longitudinal and transverse GRF components. This paper describes a simple, temporo-spatial method of displaying and analyzing sagittal plane GRF vectors. In addition, the application of statistical parametric mapping (SPM) is introduced to analyse differences between contra-lateral fore and hindlimb force-time curves throughout the stance phase. The overall aim of the study was to demonstrate alternative methods of evaluating functional (a)symmetry within horses. Methods GRF and kinematic data were collected from 10 horses trotting over a series of four force plates (120 Hz). The kinematic data were used to determine clean hoof contacts. The stance phase of each hoof was determined using a 50 N threshold. Vertical and longitudinal GRF for each stance phase were plotted both as force-time curves and as force vector diagrams in which vectors originating at the centre of pressure on the force plate were drawn at intervals of 8.3 ms for the duration of stance. Visual evaluation was facilitated by overlay of the vector diagrams for different limbs. Summary vectors representing the magnitude (VecMag) and direction (VecAng) of the mean force over the entire stance phase were superimposed on the force vector diagram. Typical measurements extracted from the force-time curves (peak forces, impulses) were compared with VecMag and VecAng using partial correlation (controlling for speed). Paired samples t-tests (left v. right diagonal pair comparison and high v. low vertical force diagonal pair comparison) were performed on discrete and vector variables using traditional methods and Hotelling’s T2 tests on normalized stance phase data using SPM. Results Evidence from traditional statistical tests suggested that VecMag is more influenced by the vertical force and impulse, whereas VecAng is more influenced by the longitudinal force and impulse. When used to evaluate mean data from the group of ten sound horses, SPM did not identify differences between the left and right contralateral limb pairs or between limb pairs classified according to directional asymmetry. When evaluating a single horse, three periods were identified during which differences in the forces between the left and right forelimbs exceeded the critical threshold (p < .01). Discussion Traditional statistical analysis of 2D GRF peak values, summary vector variables and visual evaluation of force vector diagrams gave harmonious results and both methods identified the same inter-limb asymmetries. As alpha was more tightly controlled using SPM, significance was only found in the individual horse although T2 plots followed the same trends as discrete analysis for the group. Conclusions The techniques of force vector analysis and SPM hold promise for investigations of sidedness and asymmetry in horses. PMID:29492341

Balancing aggregation and smoothing errors in inverse models

DOE PAGES

Turner, A. J.; Jacob, D. J.

2015-06-30

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function ofmore » state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.« less

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-01-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D. J.

2015-06-01

Inverse models use observations of a system (observation vector) to quantify the variables driving that system (state vector) by statistical optimization. When the observation vector is large, such as with satellite data, selecting a suitable dimension for the state vector is a challenge. A state vector that is too large cannot be effectively constrained by the observations, leading to smoothing error. However, reducing the dimension of the state vector leads to aggregation error as prior relationships between state vector elements are imposed rather than optimized. Here we present a method for quantifying aggregation and smoothing errors as a function of state vector dimension, so that a suitable dimension can be selected by minimizing the combined error. Reducing the state vector within the aggregation error constraints can have the added advantage of enabling analytical solution to the inverse problem with full error characterization. We compare three methods for reducing the dimension of the state vector from its native resolution: (1) merging adjacent elements (grid coarsening), (2) clustering with principal component analysis (PCA), and (3) applying a Gaussian mixture model (GMM) with Gaussian pdfs as state vector elements on which the native-resolution state vector elements are projected using radial basis functions (RBFs). The GMM method leads to somewhat lower aggregation error than the other methods, but more importantly it retains resolution of major local features in the state vector while smoothing weak and broad features.

Prince Albert National Park Forest Cover Data in Vector Format

NASA Technical Reports Server (NTRS)

Fitzsimmons, Michael; Nickeson, Jaime; Hall, Forrest G. (Editor)

2000-01-01

This data set provides detailed canopy, understory, and ground cover height, density, and condition information for PANP in the western portion of the BOReal Ecosystem-Atmosphere Study (BOREAS) Southern Study Area (SSA) in vector form. The original biophysical resource data set was produced in 1978 based on aerial photographs taken in 1968 and field work conducted in the mid-1970s, and PANP's update/revision of the data set was completed in 1994. The data are stored in an ARC/INFO export file.

Modeling Malaria Vector Distribution under Climate Change Scenarios in Kenya

NASA Astrophysics Data System (ADS)

Ngaina, J. N.

2017-12-01

Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control strategies for sustaining elimination and preventing reintroduction of malaria. However, in Kenya, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of future climate change on locally dominant Anopheles vectors including Anopheles gambiae, Anopheles arabiensis, Anopheles merus, Anopheles funestus, Anopheles pharoensis and Anopheles nili. Environmental data (Climate, Land cover and elevation) and primary empirical geo-located species-presence data were identified. The principle of maximum entropy (Maxent) was used to model the species' potential distribution area under paleoclimate, current and future climates. The Maxent model was highly accurate with a statistically significant AUC value. Simulation-based estimates suggest that the environmentally suitable area (ESA) for Anopheles gambiae, An. arabiensis, An. funestus and An. pharoensis would increase under all two scenarios for mid-century (2016-2045), but decrease for end century (2071-2100). An increase in ESA of An. Funestus was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios for mid-century. Our findings can be applied in various ways such as the identification of additional localities where Anopheles malaria vectors may already exist, but has not yet been detected and the recognition of localities where it is likely to spread to. Moreover, it will help guide future sampling location decisions, help with the planning of vector control suites nationally and encourage broader research inquiry into vector species niche modeling

Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.

PubMed

Liang, Junli; Yu, Guoyang; Chen, Badong; Zhao, Minghua

2016-11-01

This paper develops a novel decentralized dimensionality reduction algorithm for the distributed tensor data across sensor networks. The main contributions of this paper are as follows. First, conventional centralized methods, which utilize entire data to simultaneously determine all the vectors of the projection matrix along each tensor mode, are not suitable for the network environment. Here, we relax the simultaneous processing manner into the one-vector-by-one-vector (OVBOV) manner, i.e., determining the projection vectors (PVs) related to each tensor mode one by one. Second, we prove that in the OVBOV manner each PV can be determined without modifying any tensor data, which simplifies corresponding computations. Third, we cast the decentralized PV determination problem as a set of subproblems with consensus constraints, so that it can be solved in the network environment only by local computations and information communications among neighboring nodes. Fourth, we introduce the null space and transform the PV determination problem with complex orthogonality constraints into an equivalent hidden convex one without any orthogonality constraint, which can be solved by the Lagrange multiplier method. Finally, experimental results are given to show that the proposed algorithm is an effective dimensionality reduction scheme for the distributed tensor data across the sensor networks.

Extraction and classification of 3D objects from volumetric CT data

NASA Astrophysics Data System (ADS)

Song, Samuel M.; Kwon, Junghyun; Ely, Austin; Enyeart, John; Johnson, Chad; Lee, Jongkyu; Kim, Namho; Boyd, Douglas P.

2016-05-01

We propose an Automatic Threat Detection (ATD) algorithm for Explosive Detection System (EDS) using our multistage Segmentation Carving (SC) followed by Support Vector Machine (SVM) classifier. The multi-stage Segmentation and Carving (SC) step extracts all suspect 3-D objects. The feature vector is then constructed for all extracted objects and the feature vector is classified by the Support Vector Machine (SVM) previously learned using a set of ground truth threat and benign objects. The learned SVM classifier has shown to be effective in classification of different types of threat materials. The proposed ATD algorithm robustly deals with CT data that are prone to artifacts due to scatter, beam hardening as well as other systematic idiosyncrasies of the CT data. Furthermore, the proposed ATD algorithm is amenable for including newly emerging threat materials as well as for accommodating data from newly developing sensor technologies. Efficacy of the proposed ATD algorithm with the SVM classifier is demonstrated by the Receiver Operating Characteristics (ROC) curve that relates Probability of Detection (PD) as a function of Probability of False Alarm (PFA). The tests performed using CT data of passenger bags shows excellent performance characteristics.

Comparison of scoliosis measurements based on three-dimensional vertebra vectors and conventional two-dimensional measurements: advantages in evaluation of prognosis and surgical results.

PubMed

Illés, Tamás; Somoskeöy, Szabolcs

2013-06-01

A new concept of vertebra vectors based on spinal three-dimensional (3D) reconstructions of images from the EOS system, a new low-dose X-ray imaging device, was recently proposed to facilitate interpretation of EOS 3D data, especially with regard to horizontal plane images. This retrospective study was aimed at the evaluation of the spinal layout visualized by EOS 3D and vertebra vectors before and after surgical correction, the comparison of scoliotic spine measurement values based on 3D vertebra vectors with measurements using conventional two-dimensional (2D) methods, and an evaluation of horizontal plane vector parameters for their relationship with the magnitude of scoliotic deformity. 95 patients with adolescent idiopathic scoliosis operated according to the Cotrel-Dubousset principle were subjected to EOS X-ray examinations pre- and postoperatively, followed by 3D reconstructions and generation of vertebra vectors in a calibrated coordinate system to calculate vector coordinates and parameters, as published earlier. Differences in values of conventional 2D Cobb methods and methods based on vertebra vectors were evaluated by means comparison T test and relationship of corresponding parameters was analysed by bivariate correlation. Relationship of horizontal plane vector parameters with the magnitude of scoliotic deformities and results of surgical correction were analysed by Pearson correlation and linear regression. In comparison to manual 2D methods, a very close relationship was detectable in vertebra vector-based curvature data for coronal curves (preop r 0.950, postop r 0.935) and thoracic kyphosis (preop r 0.893, postop r 0.896), while the found small difference in L1-L5 lordosis values (preop r 0.763, postop r 0.809) was shown to be strongly related to the magnitude of corresponding L5 wedge. The correlation analysis results revealed strong correlation between the magnitude of scoliosis and the lateral translation of apical vertebra in horizontal plane. The horizontal plane coordinates of the terminal and initial points of apical vertebra vectors represent this (r 0.701; r 0.667). Less strong correlation was detected in the axial rotation of apical vertebras and the magnitudes of the frontal curves (r 0.459). Vertebra vectors provide a key opportunity to visualize spinal deformities in all three planes simultaneously. Measurement methods based on vertebral vectors proved to be just as accurate and reliable as conventional measurement methods for coronal and sagittal plane parameters. In addition, the horizontal plane display of the curves can be studied using the same vertebra vectors. Based on the vertebra vectors data, during the surgical treatment of spinal deformities, the diminution of the lateral translation of the vertebras seems to be more important in the results of the surgical correction than the correction of the axial rotation.

From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.

PubMed

Eckhoff, Philip A; Bever, Caitlin A; Gerardin, Jaline; Wenger, Edward A; Smith, David L

2015-08-01

Since the original Ross-Macdonald formulations of vector-borne disease transmission, there has been a broad proliferation of mathematical models of vector-borne disease, but many of these models retain most to all of the simplifying assumptions of the original formulations. Recently, there has been a new expansion of mathematical frameworks that contain explicit representations of the vector life cycle including aquatic stages, multiple vector species, host heterogeneity in biting rate, realistic vector feeding behavior, and spatial heterogeneity. In particular, there are now multiple frameworks for spatially explicit dynamics with movements of vector, host, or both. These frameworks are flexible and powerful, but require additional data to take advantage of these features. For a given question posed, utilizing a range of models with varying complexity and assumptions can provide a deeper understanding of the answers derived from models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Development of Novel Adenoviral Vectors to Overcome Challenges Observed With HAdV-5–based Constructs

PubMed Central

Alonso-Padilla, Julio; Papp, Tibor; Kaján, Győző L; Benkő, Mária; Havenga, Menzo; Lemckert, Angelique; Harrach, Balázs; Baker, Andrew H

2016-01-01

Recombinant vectors based on human adenovirus serotype 5 (HAdV-5) have been extensively studied in preclinical models and clinical trials over the past two decades. However, the thorough understanding of the HAdV-5 interaction with human subjects has uncovered major concerns about its product applicability. High vector-associated toxicity and widespread preexisting immunity have been shown to significantly impede the effectiveness of HAdV-5–mediated gene transfer. It is therefore that the in-depth knowledge attained working on HAdV-5 is currently being used to develop alternative vectors. Here, we provide a comprehensive overview of data obtained in recent years disqualifying the HAdV-5 vector for systemic gene delivery as well as novel strategies being pursued to overcome the limitations observed with particular emphasis on the ongoing vectorization efforts to obtain vectors based on alternative serotypes. PMID:26478249

Models for discrete-time self-similar vector processes with application to network traffic

NASA Astrophysics Data System (ADS)

Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

2003-07-01

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Ontology for Vector Surveillance and Management

PubMed Central

LOZANO-FUENTES, SAUL; BANDYOPADHYAY, ARITRA; COWELL, LINDSAY G.; GOLDFAIN, ALBERT; EISEN, LARS

2013-01-01

Ontologies, which are made up by standardized and defined controlled vocabulary terms and their interrelationships, are comprehensive and readily searchable repositories for knowledge in a given domain. The Open Biomedical Ontologies (OBO) Foundry was initiated in 2001 with the aims of becoming an “umbrella” for life-science ontologies and promoting the use of ontology development best practices. A software application (OBO-Edit; *.obo file format) was developed to facilitate ontology development and editing. The OBO Foundry now comprises over 100 ontologies and candidate ontologies, including the NCBI organismal classification ontology (NCBITaxon), the Mosquito Insecticide Resistance Ontology (MIRO), the Infectious Disease Ontology (IDO), the IDOMAL malaria ontology, and ontologies for mosquito gross anatomy and tick gross anatomy. We previously developed a disease data management system for dengue and malaria control programs, which incorporated a set of information trees built upon ontological principles, including a “term tree” to promote the use of standardized terms. In the course of doing so, we realized that there were substantial gaps in existing ontologies with regards to concepts, processes, and, especially, physical entities (e.g., vector species, pathogen species, and vector surveillance and management equipment) in the domain of surveillance and management of vectors and vector-borne pathogens. We therefore produced an ontology for vector surveillance and management, focusing on arthropod vectors and vector-borne pathogens with relevance to humans or domestic animals, and with special emphasis on content to support operational activities through inclusion in databases, data management systems, or decision support systems. The Vector Surveillance and Management Ontology (VSMO) includes >2,200 unique terms, of which the vast majority (>80%) were newly generated during the development of this ontology. One core feature of the VSMO is the linkage, through the has_vector relation, of arthropod species to the pathogenic microorganisms for which they serve as biological vectors. We also recognized and addressed a potential roadblock for use of the VSMO by the vector-borne disease community: the difficulty in extracting information from OBO-Edit ontology files (*.obo files) and exporting the information to other file formats. A novel ontology explorer tool was developed to facilitate extraction and export of information from the VSMO *.obo file into lists of terms and their associated unique IDs in *.txt or *.csv file formats. These lists can then be imported into a database or data management system for use as select lists with predefined terms. This is an important step to ensure that the knowledge contained in our ontology can be put into practical use. PMID:23427646

Ontology for vector surveillance and management.

PubMed

Lozano-Fuentes, Saul; Bandyopadhyay, Aritra; Cowell, Lindsay G; Goldfain, Albert; Eisen, Lars

2013-01-01

Ontologies, which are made up by standardized and defined controlled vocabulary terms and their interrelationships, are comprehensive and readily searchable repositories for knowledge in a given domain. The Open Biomedical Ontologies (OBO) Foundry was initiated in 2001 with the aims of becoming an "umbrella" for life-science ontologies and promoting the use of ontology development best practices. A software application (OBO-Edit; *.obo file format) was developed to facilitate ontology development and editing. The OBO Foundry now comprises over 100 ontologies and candidate ontologies, including the NCBI organismal classification ontology (NCBITaxon), the Mosquito Insecticide Resistance Ontology (MIRO), the Infectious Disease Ontology (IDO), the IDOMAL malaria ontology, and ontologies for mosquito gross anatomy and tick gross anatomy. We previously developed a disease data management system for dengue and malaria control programs, which incorporated a set of information trees built upon ontological principles, including a "term tree" to promote the use of standardized terms. In the course of doing so, we realized that there were substantial gaps in existing ontologies with regards to concepts, processes, and, especially, physical entities (e.g., vector species, pathogen species, and vector surveillance and management equipment) in the domain of surveillance and management of vectors and vector-borne pathogens. We therefore produced an ontology for vector surveillance and management, focusing on arthropod vectors and vector-borne pathogens with relevance to humans or domestic animals, and with special emphasis on content to support operational activities through inclusion in databases, data management systems, or decision support systems. The Vector Surveillance and Management Ontology (VSMO) includes >2,200 unique terms, of which the vast majority (>80%) were newly generated during the development of this ontology. One core feature of the VSMO is the linkage, through the has vector relation, of arthropod species to the pathogenic microorganisms for which they serve as biological vectors. We also recognized and addressed a potential roadblock for use of the VSMO by the vector-borne disease community: the difficulty in extracting information from OBO-Edit ontology files (*.obo files) and exporting the information to other file formats. A novel ontology explorer tool was developed to facilitate extraction and export of information from the VSMO*.obo file into lists of terms and their associated unique IDs in *.txt or *.csv file formats. These lists can then be imported into a database or data management system for use as select lists with predefined terms. This is an important step to ensure that the knowledge contained in our ontology can be put into practical use.

National Center for Biotechnology Information

MedlinePlus

... Splign Vector Alignment Search Tool (VAST) All Data & Software Resources... Domains & Structures BioSystems Cn3D Conserved Domain Database (CDD) Conserved Domain Search Service (CD Search) Structure (Molecular Modeling Database) Vector Alignment ...

A hybrid approach to select features and classify diseases based on medical data

NASA Astrophysics Data System (ADS)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

A remote sensing and geographic information system approach to sampling malaria vector habitats in Chiapas, Mexico

NASA Astrophysics Data System (ADS)

Beck, L.; Wood, B.; Whitney, S.; Rossi, R.; Spanner, M.; Rodriguez, M.; Rodriguez-Ramirez, A.; Salute, J.; Legters, L.; Roberts, D.; Rejmankova, E.; Washino, R.

1993-08-01

This paper describes a procedure whereby remote sensing and geographic information system (GIS) technologies are used in a sample design to study the habitat of Anopheles albimanus, one of the principle vectors of malaria in Central America. This procedure incorporates Landsat-derived land cover maps with digital elevation and road network data to identify a random selection of larval habitats accessible for field sampling. At the conclusion of the sampling season, the larval counts will be used to determine habitat productivity, and then integrated with information on human settlement to assess where people are at high risk of malaria. This aproach would be appropriate in areas where land cover information is lacking and problems of access constrain field sampling. The use of a GIS also permits other data (such as insecticide spraying data) to the incorporated in the sample design as they arise. This approach would also be pertinent for other tropical vector-borne diseases, particularly where human activities impact disease vector habitat.

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.

The synoptic maps of Br from HMI observations

NASA Astrophysics Data System (ADS)

Hayashi, Keiji; Hoeksema, J. Todd; Liu, Sun; Yang, Xudong; Centeno, Rebecca; Leka, K. D.; Barnes, Graham

2012-03-01

The vector magnetic field measurement can, in principal, give the "true" radial component of the magnetic field. We prepare 4 types of synoptic maps of the radial photospheric magnetic field, from the vector magnetic field data disambiguated by means of the minimum energy method developed at NWRA/CoRA, the vector data determined under the potential-field acute assumption, and the vector data determined under the radial-acute assumption, and the standard line-of-sight magnetogram. The models of the global corona, the MHD and the PFSS, are applied to different types of maps. Although the three-dimensional structures of the global coronal magnetic field with different maps are similar and overall agreeing well the AIA full-disk images, noticeable differences among the model outputs are found especially in the high latitude regions. We will show details of these test maps and discuss the issues in determining the radial component of the photospheric magnetic field near the poles and limb.

Jupiter Environment Tool

NASA Technical Reports Server (NTRS)

Sturm, Erick J.; Monahue, Kenneth M.; Biehl, James P.; Kokorowski, Michael; Ngalande, Cedrick,; Boedeker, Jordan

2012-01-01

The Jupiter Environment Tool (JET) is a custom UI plug-in for STK that provides an interface to Jupiter environment models for visualization and analysis. Users can visualize the different magnetic field models of Jupiter through various rendering methods, which are fully integrated within STK s 3D Window. This allows users to take snapshots and make animations of their scenarios with magnetic field visualizations. Analytical data can be accessed in the form of custom vectors. Given these custom vectors, users have access to magnetic field data in custom reports, graphs, access constraints, coverage analysis, and anywhere else vectors are used within STK.

Evaluation Method for Service Branding Using Word-of-Mouth Data

NASA Astrophysics Data System (ADS)

Shirahada, Kunio; Kosaka, Michitaka

Development and spread of internet technology contributes service firms to obtaining the high capability of brand information transmission as well as relative customer feedback data collection. In this paper, we propose a new evaluation method for service branding using firms and consumers data on the internet. Based on service marketing 7Ps (Product, Price, Place, Promotion, People, Physical evidence, Process) which are the key viewpoints for branding, we develop a brand evaluation system including coding methods for Word-of-Mouth (WoM) and corporate introductory information on the internet to identify both customer's service value recognition vector and firm's service value proposition vector. Our system quantitatively clarify both customer's service value recognition of the firm and firm's strength in service value proposition, thereby analyzing service brand communication gaps between firm and consumers. We applied this system to Japanese Ryokan hotel industry. Using six ryokan-hotels' data on Jyaran-net and Rakuten travel, we made totally 983 codes from WoM information and analyzed their service brand value according to three price based categories. As a result, we found that the characteristics of customers' service value recognition vector differ according to the price categories. In addition, the system clarified that there is a firm that has a different service value proposition vector from customers' recognition vector. This helps to analyze corporate service brand strategy and has a significance as a system technology supporting service management.

The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis

PubMed Central

2011-01-01

Background The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed. Results Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented. Conclusions This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps. PMID:21612587

The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis.

PubMed

Sinka, Marianne E; Bangs, Michael J; Manguin, Sylvie; Chareonviriyaphap, Theeraphap; Patil, Anand P; Temperley, William H; Gething, Peter W; Elyazar, Iqbal R F; Kabaria, Caroline W; Harbach, Ralph E; Hay, Simon I

2011-05-25

The final article in a series of three publications examining the global distribution of 41 dominant vector species (DVS) of malaria is presented here. The first publication examined the DVS from the Americas, with the second covering those species present in Africa, Europe and the Middle East. Here we discuss the 19 DVS of the Asian-Pacific region. This region experiences a high diversity of vector species, many occurring sympatrically, which, combined with the occurrence of a high number of species complexes and suspected species complexes, and behavioural plasticity of many of these major vectors, adds a level of entomological complexity not comparable elsewhere globally. To try and untangle the intricacy of the vectors of this region and to increase the effectiveness of vector control interventions, an understanding of the contemporary distribution of each species, combined with a synthesis of the current knowledge of their behaviour and ecology is needed. Expert opinion (EO) range maps, created with the most up-to-date expert knowledge of each DVS distribution, were combined with a contemporary database of occurrence data and a suite of open access, environmental and climatic variables. Using the Boosted Regression Tree (BRT) modelling method, distribution maps of each DVS were produced. The occurrence data were abstracted from the formal, published literature, plus other relevant sources, resulting in the collation of DVS occurrence at 10116 locations across 31 countries, of which 8853 were successfully geo-referenced and 7430 were resolved to spatial areas that could be included in the BRT model. A detailed summary of the information on the bionomics of each species and species complex is also presented. This article concludes a project aimed to establish the contemporary global distribution of the DVS of malaria. The three articles produced are intended as a detailed reference for scientists continuing research into the aspects of taxonomy, biology and ecology relevant to species-specific vector control. This research is particularly relevant to help unravel the complicated taxonomic status, ecology and epidemiology of the vectors of the Asia-Pacific region. All the occurrence data, predictive maps and EO-shape files generated during the production of these publications will be made available in the public domain. We hope that this will encourage data sharing to improve future iterations of the distribution maps.

A Comprehensive Optimization Strategy for Real-time Spatial Feature Sharing and Visual Analytics in Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Li, W.; Shao, H.

2017-12-01

For geospatial cyberinfrastructure enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for the vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: 1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance (ADT) to meet various visualization requirements, and at the same time speed up simplification efficiency; 2) a progressive attribute transmission method to reduce data size and therefore the service response time; 3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to widen the use of web service providing vector data to support real-time spatial feature sharing, visual analytics and decision-making.

Lsiviewer 2.0 - a Client-Oriented Online Visualization Tool for Geospatial Vector Data

NASA Astrophysics Data System (ADS)

Manikanta, K.; Rajan, K. S.

2017-09-01

Geospatial data visualization systems have been predominantly through applications that are installed and run in a desktop environment. Over the last decade, with the advent of web technologies and its adoption by Geospatial community, the server-client model for data handling, data rendering and visualization respectively has been the most prevalent approach in Web-GIS. While the client devices have become functionally more powerful over the recent years, the above model has largely ignored it and is still in a mode of serverdominant computing paradigm. In this paper, an attempt has been made to develop and demonstrate LSIViewer - a simple, easy-to-use and robust online geospatial data visualisation system for the user's own data that harness the client's capabilities for data rendering and user-interactive styling, with a reduced load on the server. The developed system can support multiple geospatial vector formats and can be integrated with other web-based systems like WMS, WFS, etc. The technology stack used to build this system is Node.js on the server side and HTML5 Canvas and JavaScript on the client side. Various tests run on a range of vector datasets, upto 35 MB, showed that the time taken to render the vector data using LSIViewer is comparable to a desktop GIS application, QGIS, over an identical system.

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.

Characteristic vector analysis of inflection ratio spectra: New technique for analysis of ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1985-01-01

Characteristic vector analysis applied to inflection ratio spectra is a new approach to analyzing spectral data. The technique applied to remote data collected with the multichannel ocean color sensor (MOCS), a passive sensor, simultaneously maps the distribution of two different phytopigments, chlorophyll alpha and phycoerythrin, the ocean. The data set presented is from a series of warm core ring missions conducted during 1982. The data compare favorably with a theoretical model and with data collected on the same mission by an active sensor, the airborne oceanographic lidar (AOL).

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.

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

PubMed Central

2012-01-01

Background Over the past century, the size and complexity of the air travel network has increased dramatically. Nowadays, there are 29.6 million scheduled flights per year and around 2.7 billion passengers are transported annually. The rapid expansion of the network increasingly connects regions of endemic vector-borne disease with the rest of the world, resulting in challenges to health systems worldwide in terms of vector-borne pathogen importation and disease vector invasion events. Here we describe the development of a user-friendly Web-based GIS tool: the Vector-Borne Disease Airline Importation Risk Tool (VBD-AIR), to help better define the roles of airports and airlines in the transmission and spread of vector-borne diseases. Methods Spatial datasets on modeled global disease and vector distributions, as well as climatic and air network traffic data were assembled. These were combined to derive relative risk metrics via air travel for imported infections, imported vectors and onward transmission, and incorporated into a three-tier server architecture in a Model-View-Controller framework with distributed GIS components. A user-friendly web-portal was built that enables dynamic querying of the spatial databases to provide relevant information. Results The VBD-AIR tool constructed enables the user to explore the interrelationships among modeled global distributions of vector-borne infectious diseases (malaria. dengue, yellow fever and chikungunya) and international air service routes to quantify seasonally changing risks of vector and vector-borne disease importation and spread by air travel, forming an evidence base to help plan mitigation strategies. The VBD-AIR tool is available at http://www.vbd-air.com. Conclusions VBD-AIR supports a data flow that generates analytical results from disparate but complementary datasets into an organized cartographical presentation on a web map for the assessment of vector-borne disease movements on the air travel network. The framework built provides a flexible and robust informatics infrastructure by separating the modules of functionality through an ontological model for vector-borne disease. The VBD‒AIR tool is designed as an evidence base for visualizing the risks of vector-borne disease by air travel for a wide range of users, including planners and decisions makers based in state and local government, and in particular, those at international and domestic airports tasked with planning for health risks and allocating limited resources. PMID:22892045

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

PubMed

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

2012-08-14

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

Inductive monitoring system constructed from nominal system data and its use in real-time system monitoring

NASA Technical Reports Server (NTRS)

Iverson, David L. (Inventor)

2008-01-01

The present invention relates to an Inductive Monitoring System (IMS), its software implementations, hardware embodiments and applications. Training data is received, typically nominal system data acquired from sensors in normally operating systems or from detailed system simulations. The training data is formed into vectors that are used to generate a knowledge database having clusters of nominal operating regions therein. IMS monitors a system's performance or health by comparing cluster parameters in the knowledge database with incoming sensor data from a monitored-system formed into vectors. Nominal performance is concluded when a monitored-system vector is determined to lie within a nominal operating region cluster or lies sufficiently close to a such a cluster as determined by a threshold value and a distance metric. Some embodiments of IMS include cluster indexing and retrieval methods that increase the execution speed of IMS.

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.

Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation

ERIC Educational Resources Information Center

Hinton, Geoffrey; Osindero, Simon; Welling, Max; Teh, Yee-Whye

2006-01-01

We describe a way of modeling high-dimensional data vectors by using an unsupervised, nonlinear, multilayer neural network in which the activity of each neuron-like unit makes an additive contribution to a global energy score that indicates how surprised the network is by the data vector. The connection weights that determine how the activity of…

Divide and Recombine for Large Complex Data

DTIC Science & Technology

2017-12-01

Empirical Methods in Natural Language Processing , October 2014 Keywords Enter keywords for the publication. URL Enter the URL...low-latency data processing systems. Declarative Languages for Interactive Visualization: The Reactive Vega Stack Another thread of XDATA research...for array processing operations embedded in the R programming language . Vector virtual machines work well for long vectors. One of the most

Long-term modulation of cosmic rays during solar cycle 21

NASA Technical Reports Server (NTRS)

Fenton, A. G.; Fenton, K. B.; Humble, J. E.

1985-01-01

A preliminary result concerning the rigidity dependence of the longer-term solar cycle modulation is reported. The long-term modulation, using monthly mean intensities and referred to November 1977 as a normalizing level, appear to be in accordance with the exponent gamma = 1, provided only Brisbane and Hobart data are used. Darwin data do not conform to this pattern except perhaps during the early years of the cycle until about the end of 1980, since when the Darwin long-term intensity has been largely steady, apart from Forbush-type decreases and the as yet unidentified vector from the observed SI vector. The true SI vector of galactic origin can be obtained. The resultant vector has the amplitude of 0.031% and the phase of 2.3h. The present result seems to be consistent with those so far reported.

Predicted Distribution of Visceral Leishmaniasis Vectors (Diptera: Psychodidae; Phlebotominae) in Iran: A Niche Model Study.

PubMed

Hanafi-Bojd, A A; Rassi, Y; Yaghoobi-Ershadi, M R; Haghdoost, A A; Akhavan, A A; Charrahy, Z; Karimi, A

2015-12-01

Visceral leishmaniasis (VL) is an important vector-borne disease in Iran. Till now, Leishmania infantum has been detected from five species of sand flies in the country including Phlebotomus kandelakii, Phlebotomus major s.l., Phlebotomus perfiliewi, Phlebotomus alexandri and Phlebotomus tobbi. Also, Phlebotomus keshishiani was found to be infected with Leishmania parasites. This study aimed at predicting the probable niches and distribution of vectors of visceral leishmaniasis in Iran. Data on spatial distribution studies of sand flies were obtained from Iranian database on sand flies. Sample points were included in data from faunistic studies on sand flies conducted during 1995-2013. MaxEnt software was used to predict the appropriate ecological niches for given species, using climatic and topographical data. Distribution maps were prepared and classified in ArcGIS to find main ecological niches of the vectors and hot spots for VL transmission in Iran. Phlebotomus kandelakii, Ph. major s.l. and Ph. alexandri seem to have played a more important role in VL transmission in Iran, so this study focuses on them. Representations of MaxEnt model for probability of distribution of the studied sand flies showed high contribution of climatological and topographical variables to predict the potential distribution of three vector species. Isothermality was found to be an environmental variable with the highest gain when used in isolation for Ph. kandelakii and Ph. major s.l., while for Ph. alexandri, the most effective variable was precipitation of the coldest quarter. The results of this study present the first prediction on distribution of sand fly vectors of VL in Iran. The predicted distributions were matched with the disease-endemic areas in the country, while it was found that there were some unaffected areas with the potential transmission. More comprehensive studies are recommended on the ecology and vector competence of VL vectors in the country. © 2015 Blackwell Verlag GmbH.

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.

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

Bhatia, Harsh

This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields—an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single “correct” reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thusmore » creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of “correctness” of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (timeindependent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty visualization of unavoidable discretization errors. Together, the two main contributions of this dissertation address two important concerns regarding feature extraction from scientific data: correctness and precision. The work presented here also opens new avenues for further research by exploring more-general reference frames and more-sophisticated domain discretizations.« 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.

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.

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

USGS Publications Warehouse

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

2012-01-01

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

Studies of Solar Helicity Using Vector Magnetograms

NASA Technical Reports Server (NTRS)

Hagyard, Mona J.; Pevstov, Alexei A.

1999-01-01

observations of photospheric magnetic fields made with vector magnetographs have been used recently to study solar helicity. In this paper we indicate what can and cannot be derived from vector magnetograms, and point out some potential problems in these data that could affect the calculations of 'helicity'. Among these problems are magnetic saturation, Faraday rotation, low spectral resolution, and the method of resolving the ambiguity in the azimuth.

Two-Dimensional Supersonic Nozzle Thrust Vectoring Using Staggered Ramps

NASA Astrophysics Data System (ADS)

Montes, Carlos Fernando

A novel mechanism for vectoring the thrust of a supersonic, air-breathing engine was analyzed numerically using ANSYS Fluent. The mechanism uses two asymmetrically staggered ramps; one placed at the throat, the other positioned at the exit lip of the nozzle. The nozzle was designed using published flow data, isentropic relationships, and piecewise quartic splines. The design was verified numerically and was in fair agreement with the analytical data. Using the steady-state pressure-based solver, along with the realizable kappa - epsilon turbulence model, a total of eighteen simulations were conducted: three ramp lengths at three angles, using two sets of inlet boundary conditions (non-afterburning and afterburning). The vectoring simulations showed that the afterburning flow yields a lower flow deflection distribution, shown by the calculated average deflection angle and area-weighted integrals of the distributions. The data implies that an aircraft can achieve an average thrust vectoring angle of approximately 30° in a given direction with the longest ramp length and largest ramp angle configuration. With increasing ramp angle, the static pressure across the nozzle inlet increased, causing concern for potential negative effects on the engine's turbine. The mechanism, for which a provisional patent application has been filed, will require further work to investigate the maximum possible thrust vectoring angle, including experiments.

Interplanetary medium data book, appendix

NASA Technical Reports Server (NTRS)

King, J. H.

1977-01-01

Computer generated listings of hourly average interplanetary plasma and magnetic field parameters are given. Parameters include proton temperature, proton density, bulk speed, an identifier of the source of the plasma data for the hour, average magnetic field magnitude and cartesian components of the magnetic field. Also included are longitude and latitude angles of the vector made up of the average field components, a vector standard deviation, and an identifier of the source of magnetic field data.

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

Mapping of Malaria Vectors at District Level in India: Changing Scenario and Identified Gaps.

PubMed

Singh, Poonam; Lingala, Mercy Aparna L; Sarkar, Soma; Dhiman, Ramesh C

2017-02-01

Malaria is one of the six major vector-borne diseases in India, the endemicity of which changes with changes in ecological, climatic, and sociodevelopmental conditions. The anopheline vectors are greatly affected by ecological conditions such as deforestation, urbanization, climate and lifestyle. Despite the advent of tools such as Geographic Information System (GIS), the updated information on the distribution of anopheline vectors of malaria is not available. In India, the plan for vector control is organized at subcentral level but information about vectors is unavailable even at the district level. Therefore, a systematic presentation of vector distribution has been made to provide maps in respect of major vector species. A search of the literature for major vector species, that is, Anopheles culicifacies, Anopheles fluviatilis, Anopheles stephensi, Anopheles minimus, and Anopheles dirus sensu lato, since 1927 till 2015 was carried out. Data have been presented as present, absent, and no information about vector species during pre-eradication (1927-1958), posteradication (1959-1999), and current scenario (2000-2015). Vectors' distribution and malaria endemicity were mapped using Arc GIS. Of 630 districts of India, major vectors An. culicifacies, An. fluviatilis, and An. stephensi were present in 420, 241, and 243 districts, respectively. In 183 districts, there is no information on any major malaria vector species although 27 of them from the states of Arunachal Pradesh, Jharkhand, Manipur, and Mizoram are highly endemic for malaria, having incidences of 2-40 cases/1000/year. The identified gaps in vector distribution, particularly in malaria endemic areas, necessitate further surveys so as to generate the missing information.

Data-driven probability concentration and sampling on manifold

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

Soize, C., E-mail: christian.soize@univ-paris-est.fr; Ghanem, R., E-mail: ghanem@usc.edu

2016-09-15

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a dataset of observations of this vector. The probability distribution of this random vector, while a priori not known, is presumed to be concentrated on an unknown subset of the Euclidean space. A random matrix is introduced whose columns are independent copies of the random vector and for which the number of columns is the number of data points in the dataset. The approach is based on the use of (i) the multidimensional kernel-density estimation methodmore » for estimating the probability distribution of the random matrix, (ii) a MCMC method for generating realizations for the random matrix, (iii) the diffusion-maps approach for discovering and characterizing the geometry and the structure of the dataset, and (iv) a reduced-order representation of the random matrix, which is constructed using the diffusion-maps vectors associated with the first eigenvalues of the transition matrix relative to the given dataset. The convergence aspects of the proposed methodology are analyzed and a numerical validation is explored through three applications of increasing complexity. The proposed method is found to be robust to noise levels and data complexity as well as to the intrinsic dimension of data and the size of experimental datasets. Both the methodology and the underlying mathematical framework presented in this paper contribute new capabilities and perspectives at the interface of uncertainty quantification, statistical data analysis, stochastic modeling and associated statistical inverse problems.« less

Incoherent vector mesons production in PbPb ultraperipheral collisions at the LHC

NASA Astrophysics Data System (ADS)

Xie, Ya-Ping; Chen, Xurong

2017-03-01

The incoherent rapidity distributions of vector mesons are computed in dipole model in PbPb ultraperipheral collisions at the CERN Large Hadron Collider (LHC). The IIM model fitted from newer data is employed in the dipole amplitude. The Boosted Gaussian and Gaus-LC wave functions for vector mesons are implemented in the calculations as well. Predictions for the J / ψ, ψ (2 s), ρ and ϕ incoherent rapidity distributions are evaluated and compared with experimental data and other theoretical predictions in this paper. We obtain closer predictions of the incoherent rapidity distributions for J / ψ than previous calculations in the IIM model.

Mathematical modeling of Chikungunya fever control

NASA Astrophysics Data System (ADS)

Hincapié-Palacio, Doracelly; Ospina, Juan

2015-05-01

Chikungunya fever is a global concern due to the occurrence of large outbreaks, the presence of persistent arthropathy and its rapid expansion throughout various continents. Globalization and climate change have contributed to the expansion of the geographical areas where mosquitoes Aedes aegypti and Aedes albopictus (Stegomyia) remain. It is necessary to improve the techniques of vector control in the presence of large outbreaks in The American Region. We derive measures of disease control, using a mathematical model of mosquito-human interaction, by means of three scenarios: a) a single vector b) two vectors, c) two vectors and human and non-human reservoirs. The basic reproductive number and critical control measures were deduced by using computer algebra with Maple (Maplesoft Inc, Ontario Canada). Control measures were simulated with parameter values obtained from published data. According to the number of households in high risk areas, the goals of effective vector control to reduce the likelihood of mosquito-human transmission would be established. Besides the two vectors, if presence of other non-human reservoirs were reported, the monthly target of effective elimination of the vector would be approximately double compared to the presence of a single vector. The model shows the need to periodically evaluate the effectiveness of vector control measures.

On the Prognostic Efficiency of Topological Descriptors for Magnetograms of Active Regions

NASA Astrophysics Data System (ADS)

Knyazeva, I. S.; Urtiev, F. A.; Makarenko, N. G.

2017-12-01

Solar flare prediction remains an important practical task of space weather. An increase in the amount and quality of observational data and the development of machine-learning methods has led to an improvement in prediction techniques. Additional information has been retrieved from the vector magnetograms; these have been recently supplemented by traditional line-of-sight (LOS) magnetograms. In this work, the problem of the comparative prognostic efficiency of features obtained on the basis of vector data and LOS magnetograms is discussed. Invariants obtained from a topological analysis of LOS magnetograms are used as complexity characteristics of magnetic patterns. Alternatively, the so-called SHARP parameters were used; they were calculated by the data analysis group of the Stanford University Laboratory on the basis of HMI/SDO vector magnetograms and are available online at the website (http://jsoc.stanford.edu/) with the solar dynamics observatory (SDO) database for the entire history of SDO observations. It has been found that the efficiency of large-flare prediction based on topological descriptors of LOS magnetograms in epignosis mode is at least s no worse than the results of prognostic schemes based on vector features. The advantages of the use of topological invariants based on LOS data are discussed.

Sparse kernel methods for high-dimensional survival data.

PubMed

Evers, Ludger; Messow, Claudia-Martina

2008-07-15

Sparse kernel methods like support vector machines (SVM) have been applied with great success to classification and (standard) regression settings. Existing support vector classification and regression techniques however are not suitable for partly censored survival data, which are typically analysed using Cox's proportional hazards model. As the partial likelihood of the proportional hazards model only depends on the covariates through inner products, it can be 'kernelized'. The kernelized proportional hazards model however yields a solution that is dense, i.e. the solution depends on all observations. One of the key features of an SVM is that it yields a sparse solution, depending only on a small fraction of the training data. We propose two methods. One is based on a geometric idea, where-akin to support vector classification-the margin between the failed observation and the observations currently at risk is maximised. The other approach is based on obtaining a sparse model by adding observations one after another akin to the Import Vector Machine (IVM). Data examples studied suggest that both methods can outperform competing approaches. Software is available under the GNU Public License as an R package and can be obtained from the first author's website http://www.maths.bris.ac.uk/~maxle/software.html.

Predictions of malaria vector distribution in Belize based on multispectral satellite data.

PubMed

Roberts, D R; Paris, J F; Manguin, S; Harbach, R E; Woodruff, R; Rejmankova, E; Polanco, J; Wullschleger, B; Legters, L J

1996-03-01

Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

Predictions of malaria vector distribution in Belize based on multispectral satellite data

NASA Technical Reports Server (NTRS)

Roberts, D. R.; Paris, J. F.; Manguin, S.; Harbach, R. E.; Woodruff, R.; Rejmankova, E.; Polanco, J.; Wullschleger, B.; Legters, L. J.

1996-01-01

Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

BOREAS Regional Soils Data in Raster Format and AEAC Projection

NASA Technical Reports Server (NTRS)

Monette, Bryan; Knapp, David; Hall, Forrest G. (Editor); Nickeson, Jaime (Editor)

2000-01-01

This data set was gridded by BOREAS Information System (BORIS) Staff from a vector data set received from the Canadian Soil Information System (CanSIS). The original data came in two parts that covered Saskatchewan and Manitoba. The data were gridded and merged into one data set of 84 files covering the BOREAS region. The data were gridded into the AEAC projection. Because the mapping of the two provinces was done separately in the original vector data, there may be discontinuities in some of the soil layers because of different interpretations of certain soil properties. The data are stored in binary, image format files.

Effects of Circular DNA Length on Transfection Efficiency by Electroporation into HeLa Cells.

PubMed

Hornstein, Benjamin D; Roman, Dany; Arévalo-Soliz, Lirio M; Engevik, Melinda A; Zechiedrich, Lynn

2016-01-01

The ability to produce extremely small and circular supercoiled vectors has opened new territory for improving non-viral gene therapy vectors. In this work, we compared transfection of supercoiled DNA vectors ranging from 383 to 4,548 bp, each encoding shRNA against GFP under control of the H1 promoter. We assessed knockdown of GFP by electroporation into HeLa cells. All of our vectors entered cells in comparable numbers when electroporated with equal moles of DNA. Despite similar cell entry, we found length-dependent differences in how efficiently the vectors knocked down GFP. As vector length increased up to 1,869 bp, GFP knockdown efficiency per mole of transfected DNA increased. From 1,869 to 4,257 bp, GFP knockdown efficiency per mole was steady, then decreased with increasing vector length. In comparing GFP knockdown with equal masses of vectors, we found that the shorter vectors transfect more efficiently per nanogram of DNA transfected. Our results rule out cell entry and DNA mass as determining factors for gene knockdown efficiency via electroporation. The length-dependent effects we have uncovered are likely explained by differences in nuclear translocation or transcription. These data add an important step towards clinical applications of non-viral vector delivery.

Effects of Circular DNA Length on Transfection Efficiency by Electroporation into HeLa Cells

PubMed Central

Hornstein, Benjamin D.; Roman, Dany; Arévalo-Soliz, Lirio M.; Engevik, Melinda A.

2016-01-01

The ability to produce extremely small and circular supercoiled vectors has opened new territory for improving non-viral gene therapy vectors. In this work, we compared transfection of supercoiled DNA vectors ranging from 383 to 4,548 bp, each encoding shRNA against GFP under control of the H1 promoter. We assessed knockdown of GFP by electroporation into HeLa cells. All of our vectors entered cells in comparable numbers when electroporated with equal moles of DNA. Despite similar cell entry, we found length-dependent differences in how efficiently the vectors knocked down GFP. As vector length increased up to 1,869 bp, GFP knockdown efficiency per mole of transfected DNA increased. From 1,869 to 4,257 bp, GFP knockdown efficiency per mole was steady, then decreased with increasing vector length. In comparing GFP knockdown with equal masses of vectors, we found that the shorter vectors transfect more efficiently per nanogram of DNA transfected. Our results rule out cell entry and DNA mass as determining factors for gene knockdown efficiency via electroporation. The length-dependent effects we have uncovered are likely explained by differences in nuclear translocation or transcription. These data add an important step towards clinical applications of non-viral vector delivery. PMID:27918590

Estimation of relative order tensors, and reconstruction of vectors in space using unassigned RDC data and its application

NASA Astrophysics Data System (ADS)

Miao, Xijiang; Mukhopadhyay, Rishi; Valafar, Homayoun

2008-10-01

Advances in NMR instrumentation and pulse sequence design have resulted in easier acquisition of Residual Dipolar Coupling (RDC) data. However, computational and theoretical analysis of this type of data has continued to challenge the international community of investigators because of their complexity and rich information content. Contemporary use of RDC data has required a-priori assignment, which significantly increases the overall cost of structural analysis. This article introduces a novel algorithm that utilizes unassigned RDC data acquired from multiple alignment media ( nD-RDC, n ⩾ 3) for simultaneous extraction of the relative order tensor matrices and reconstruction of the interacting vectors in space. Estimation of the relative order tensors and reconstruction of the interacting vectors can be invaluable in a number of endeavors. An example application has been presented where the reconstructed vectors have been used to quantify the fitness of a template protein structure to the unknown protein structure. This work has other important direct applications such as verification of the novelty of an unknown protein and validation of the accuracy of an available protein structure model in drug design. More importantly, the presented work has the potential to bridge the gap between experimental and computational methods of structure determination.

Spacebased Estimation of Moisture Transport in Marine Atmosphere Using Support Vector Regression

NASA Technical Reports Server (NTRS)

Xie, Xiaosu; Liu, W. Timothy; Tang, Benyang

2007-01-01

An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.

Integrated pest management and allocation of control efforts for vector-borne diseases

USGS Publications Warehouse

Ginsberg, H.S.

2001-01-01

Applications of various control methods were evaluated to determine how to integrate methods so as to minimize the number of human cases of vector-borne diseases. These diseases can be controlled by lowering the number of vector-human contacts (e.g., by pesticide applications or use of repellents), or by lowering the proportion of vectors infected with pathogens (e.g., by lowering or vaccinating reservoir host populations). Control methods should be combined in such a way as to most efficiently lower the probability of human encounter with an infected vector. Simulations using a simple probabilistic model of pathogen transmission suggest that the most efficient way to integrate different control methods is to combine methods that have the same effect (e.g., combine treatments that lower the vector population; or combine treatments that lower pathogen prevalence in vectors). Combining techniques that have different effects (e.g., a technique that lowers vector populations with a technique that lowers pathogen prevalence in vectors) will be less efficient than combining two techniques that both lower vector populations or combining two techniques that both lower pathogen prevalence, costs being the same. Costs of alternative control methods generally differ, so the efficiency of various combinations at lowering human contact with infected vectors should be estimated at available funding levels. Data should be collected from initial trials to improve the effects of subsequent interventions on the number of human cases.

Vector Doppler: spatial sampling analysis and presentation techniques for real-time systems

NASA Astrophysics Data System (ADS)

Capineri, Lorenzo; Scabia, Marco; Masotti, Leonardo F.

2001-05-01

The aim of the vector Doppler (VD) technique is the quantitative reconstruction of a velocity field independently of the ultrasonic probe axis to flow angle. In particular vector Doppler is interesting for studying vascular pathologies related to complex blood flow conditions. Clinical applications require a real-time operating mode and the capability to perform Doppler measurements over a defined volume. The combination of these two characteristics produces a real-time vector velocity map. In previous works the authors investigated the theory of pulsed wave (PW) vector Doppler and developed an experimental system capable of producing off-line 3D vector velocity maps. Afterwards, for producing dynamic velocity vector maps, we realized a new 2D vector Doppler system based on a modified commercial echograph. The measurement and presentation of a vector velocity field requires a correct spatial sampling that must satisfy the Shannon criterion. In this work we tackled this problem, establishing a relationship between sampling steps and scanning system characteristics. Another problem posed by the vector Doppler technique is the data representation in real-time that should be easy to interpret for the physician. With this in mine we attempted a multimedia solution that uses both interpolated images and sound to represent the information of the measured vector velocity map. These presentation techniques were experimented for real-time scanning on flow phantoms and preliminary measurements in vivo on a human carotid artery.

High-performance computing — an overview

NASA Astrophysics Data System (ADS)

Marksteiner, Peter

1996-08-01

An overview of high-performance computing (HPC) is given. Different types of computer architectures used in HPC are discussed: vector supercomputers, high-performance RISC processors, various parallel computers like symmetric multiprocessors, workstation clusters, massively parallel processors. Software tools and programming techniques used in HPC are reviewed: vectorizing compilers, optimization and vector tuning, optimization for RISC processors; parallel programming techniques like shared-memory parallelism, message passing and data parallelism; and numerical libraries.

Cross-Service Investigation of Geographical Information Systems

DTIC Science & Technology

2004-03-01

Figure 8 illustrates the combined layers. Information for the layers is stored in a database format. The two types of storage are vector and...raster models. In a vector model, the image and information are stored as geometric objects such as points, lines, or polygons. In a raster model...DNCs are a vector -based digital database with selected maritime significant physical features from hydrographic charts. Layers within the DNC are data

Rotation invariants of vector fields from orthogonal moments

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

Yang, Bo; Kostková, Jitka; Flusser, Jan

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Rate determination from vector observations

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.

1993-01-01

Vector observations are a common class of attitude data provided by a wide variety of attitude sensors. Attitude determination from vector observations is a well-understood process and numerous algorithms such as the TRIAD algorithm exist. These algorithms require measurement of the line of site (LOS) vector to reference objects and knowledge of the LOS directions in some predetermined reference frame. Once attitude is determined, it is a simple matter to synthesize vehicle rate using some form of lead-lag filter, and then, use it for vehicle stabilization. Many situations arise, however, in which rate knowledge is required but knowledge of the nominal LOS directions are not available. This paper presents two methods for determining spacecraft angular rates from vector observations without a priori knowledge of the vector directions. The first approach uses an extended Kalman filter with a spacecraft dynamic model and a kinematic model representing the motion of the observed LOS vectors. The second approach uses a 'differential' TRIAD algorithm to compute the incremental direction cosine matrix, from which vehicle rate is then derived.

Rotation invariants of vector fields from orthogonal moments

DOE PAGES

Yang, Bo; Kostková, Jitka; Flusser, Jan; ...

2017-09-11

Vector field images are a type of new multidimensional data that appear in many engineering areas. Although the vector fields can be visualized as images, they differ from graylevel and color images in several aspects. In order to analyze them, special methods and algorithms must be originally developed or substantially adapted from the traditional image processing area. Here, we propose a method for the description and matching of vector field patterns under an unknown rotation of the field. Rotation of a vector field is so-called total rotation, where the action is applied not only on the spatial coordinates but alsomore » on the field values. Invariants of vector fields with respect to total rotation constructed from orthogonal Gaussian–Hermite moments and Zernike moments are introduced. Their numerical stability is shown to be better than that of the invariants published so far. We demonstrate their usefulness in a real world template matching application of rotated vector fields.« less

Extracting remanent magnetization from magnetic data inversion

NASA Astrophysics Data System (ADS)

Liu, S.; Fedi, M.; Baniamerian, J.; Hu, X.

2017-12-01

Remanent magnetization is an important vector parameter of rocks' and ores' magnetism, which is related to the intensity and direction of primary geomagnetic fields at all geological periods and hence shows critical evidences of geological tectonic movement and sedimentary evolution. We extract the remanence information from the distributions of the inverted magnetization vector. Firstly, directions of total magnetization vector are estimated from reduced-to-pole anomaly (max-min algorithm) and by its correlations with other magnitude magnetic transforms such as magnitude magnetic anomaly and normalized source strength. Then we invert data for the magnetization intensity and finally the intensity and direction of the remanent magnetization are separated from the total magnetization vector with a generalized formula of the apparent susceptibility based on a priori information on the Koenigsberger ratio. Our approach is used to investigate the targeted resources and geologic processes of the mining areas in China.

Rank-Optimized Logistic Matrix Regression toward Improved Matrix Data Classification.

PubMed

Zhang, Jianguang; Jiang, Jianmin

2018-02-01

While existing logistic regression suffers from overfitting and often fails in considering structural information, we propose a novel matrix-based logistic regression to overcome the weakness. In the proposed method, 2D matrices are directly used to learn two groups of parameter vectors along each dimension without vectorization, which allows the proposed method to fully exploit the underlying structural information embedded inside the 2D matrices. Further, we add a joint [Formula: see text]-norm on two parameter matrices, which are organized by aligning each group of parameter vectors in columns. This added co-regularization term has two roles-enhancing the effect of regularization and optimizing the rank during the learning process. With our proposed fast iterative solution, we carried out extensive experiments. The results show that in comparison to both the traditional tensor-based methods and the vector-based regression methods, our proposed solution achieves better performance for matrix data classifications.

A VLSI chip set for real time vector quantization of image sequences

NASA Technical Reports Server (NTRS)

Baker, Richard L.

1989-01-01

The architecture and implementation of a VLSI chip set that vector quantizes (VQ) image sequences in real time is described. The chip set forms a programmable Single-Instruction, Multiple-Data (SIMD) machine which can implement various vector quantization encoding structures. Its VQ codebook may contain unlimited number of codevectors, N, having dimension up to K = 64. Under a weighted least squared error criterion, the engine locates at video rates the best code vector in full-searched or large tree searched VQ codebooks. The ability to manipulate tree structured codebooks, coupled with parallelism and pipelining, permits searches in as short as O (log N) cycles. A full codebook search results in O(N) performance, compared to O(KN) for a Single-Instruction, Single-Data (SISD) machine. With this VLSI chip set, an entire video code can be built on a single board that permits realtime experimentation with very large codebooks.

Method for enhanced accuracy in predicting peptides using liquid separations or chromatography

DOEpatents

Kangas, Lars J.; Auberry, Kenneth J.; Anderson, Gordon A.; Smith, Richard D.

2006-11-14

A method for predicting the elution time of a peptide in chromatographic and electrophoretic separations by first providing a data set of known elution times of known peptides, then creating a plurality of vectors, each vector having a plurality of dimensions, and each dimension representing the elution time of amino acids present in each of these known peptides from the data set. The elution time of any protein is then be predicted by first creating a vector by assigning dimensional values for the elution time of amino acids of at least one hypothetical peptide and then calculating a predicted elution time for the vector by performing a multivariate regression of the dimensional values of the hypothetical peptide using the dimensional values of the known peptides. Preferably, the multivariate regression is accomplished by the use of an artificial neural network and the elution times are first normalized using a transfer function.

Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

NASA Technical Reports Server (NTRS)

Shen, Han-Wei; Johnson, Christopher R.; Ma, Kwan-Liu

1996-01-01

We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

Visualization and manipulating the image of a formal data structure (FDS)-based database

NASA Astrophysics Data System (ADS)

Verdiesen, Franc; de Hoop, Sylvia; Molenaar, Martien

1994-08-01

A vector map is a terrain representation with a vector-structured geometry. Molenaar formulated an object-oriented formal data structure for 3D single valued vector maps. This FDS is implemented in a database (Oracle). In this study we describe a methodology for visualizing a FDS-based database and manipulating the image. A data set retrieved by querying the database is converted into an import file for a drawing application. An objective of this study is that an end-user can alter and add terrain objects in the image. The drawing application creates an export file, that is compared with the import file. Differences between these files result in updating the database which involves checks on consistency. In this study Autocad is used for visualizing and manipulating the image of the data set. A computer program has been written for the data exchange and conversion between Oracle and Autocad. The data structure of the FDS is compared to the data structure of Autocad and the data of the FDS is converted into the structure of Autocad equal to the FDS.

The Absolute Vector Magnetometers on Board Swarm, Lessons Learned From Two Years in Space.

NASA Astrophysics Data System (ADS)

Hulot, G.; Leger, J. M.; Vigneron, P.; Brocco, L.; Olsen, N.; Jager, T.; Bertrand, F.; Fratter, I.; Sirol, O.; Lalanne, X.

2015-12-01

ESA's Swarm satellites carry 4He absolute magnetometers (ASM), designed by CEA-Léti and developed in partnership with CNES. These instruments are the first-ever space-born magnetometers to use a common sensor to simultaneously deliver 1Hz independent absolute scalar and vector readings of the magnetic field. They have provided the very high accuracy scalar field data nominally required by the mission (for both science and calibration purposes, since each satellite also carries a low noise high frequency fluxgate magnetometer designed by DTU), but also very useful experimental absolute vector data. In this presentation, we will report on the status of the instruments, as well as on the various tests and investigations carried out using these experimental data since launch in November 2013. In particular, we will illustrate the advantages of flying ASM instruments on space-born magnetic missions for nominal data quality checks, geomagnetic field modeling and science objectives.

Statistical distribution of wind speeds and directions globally observed by NSCAT

NASA Astrophysics Data System (ADS)

Ebuchi, Naoto

1999-05-01

In order to validate wind vectors derived from the NASA scatterometer (NSCAT), statistical distributions of wind speeds and directions over the global oceans are investigated by comparing with European Centre for Medium-Range Weather Forecasts (ECMWF) wind data. Histograms of wind speeds and directions are calculated from the preliminary and reprocessed NSCAT data products for a period of 8 weeks. For wind speed of the preliminary data products, excessive low wind distribution is pointed out through comparison with ECMWF winds. A hump at the lower wind speed side of the peak in the wind speed histogram is discernible. The shape of the hump varies with incidence angle. Incompleteness of the prelaunch geophysical model function, SASS 2, tentatively used to retrieve wind vectors of the preliminary data products, is considered to cause the skew of the wind speed distribution. On the contrary, histograms of wind speeds of the reprocessed data products show consistent features over the whole range of incidence angles. Frequency distribution of wind directions relative to spacecraft flight direction is calculated to assess self-consistency of the wind directions. It is found that wind vectors of the preliminary data products exhibit systematic directional preference relative to antenna beams. This artificial directivity is also considered to be caused by imperfections in the geophysical model function. The directional distributions of the reprocessed wind vectors show less directivity and consistent features, except for very low wind cases.

QuickMap: a public tool for large-scale gene therapy vector insertion site mapping and analysis.

PubMed

Appelt, J-U; Giordano, F A; Ecker, M; Roeder, I; Grund, N; Hotz-Wagenblatt, A; Opelz, G; Zeller, W J; Allgayer, H; Fruehauf, S; Laufs, S

2009-07-01

Several events of insertional mutagenesis in pre-clinical and clinical gene therapy studies have created intense interest in assessing the genomic insertion profiles of gene therapy vectors. For the construction of such profiles, vector-flanking sequences detected by inverse PCR, linear amplification-mediated-PCR or ligation-mediated-PCR need to be mapped to the host cell's genome and compared to a reference set. Although remarkable progress has been achieved in mapping gene therapy vector insertion sites, public reference sets are lacking, as are the possibilities to quickly detect non-random patterns in experimental data. We developed a tool termed QuickMap, which uniformly maps and analyzes human and murine vector-flanking sequences within seconds (available at www.gtsg.org). Besides information about hits in chromosomes and fragile sites, QuickMap automatically determines insertion frequencies in +/- 250 kb adjacency to genes, cancer genes, pseudogenes, transcription factor and (post-transcriptional) miRNA binding sites, CpG islands and repetitive elements (short interspersed nuclear elements (SINE), long interspersed nuclear elements (LINE), Type II elements and LTR elements). Additionally, all experimental frequencies are compared with the data obtained from a reference set, containing 1 000 000 random integrations ('random set'). Thus, for the first time a tool allowing high-throughput profiling of gene therapy vector insertion sites is available. It provides a basis for large-scale insertion site analyses, which is now urgently needed to discover novel gene therapy vectors with 'safe' insertion profiles.

Participatory Risk Mapping of Malaria Vector Exposure in Northern South America using Environmental and Population Data

PubMed Central

Fuller, D.O.; Troyo, A.; Alimi, T.O.; Beier, J.C.

2014-01-01

Malaria elimination remains a major public health challenge in many tropical regions, including large areas of northern South America. In this study, we present a new high spatial resolution (90 × 90 m) risk map for Colombia and surrounding areas based on environmental and human population data. The map was created through a participatory multi-criteria decision analysis in which expert opinion was solicited to determine key environmental and population risk factors, different fuzzy functions to standardize risk factor inputs, and variable factor weights to combine risk factors in a geographic information system. The new risk map was compared to a map of malaria cases in which cases were aggregated to the municipio (municipality) level. The relationship between mean municipio risk scores and total cases by muncípio showed a weak correlation. However, the relationship between pixel-level risk scores and vector occurrence points for two dominant vector species, Anopheles albimanus and An. darlingi, was significantly different (p < 0.05) from a random point distribution, as was a pooled point distribution for these two vector species and An. nuneztovari. Thus, we conclude that the new risk map derived based on expert opinion provides an accurate spatial representation of risk of potential vector exposure rather than malaria transmission as shown by the pattern of malaria cases, and therefore it may be used to inform public health authorities as to where vector control measures should be prioritized to limit human-vector contact in future malaria outbreaks. PMID:24976656

A cost-function approach to rival penalized competitive learning (RPCL).

PubMed

Ma, Jinwen; Wang, Taijun

2006-08-01

Rival penalized competitive learning (RPCL) has been shown to be a useful tool for clustering on a set of sample data in which the number of clusters is unknown. However, the RPCL algorithm was proposed heuristically and is still in lack of a mathematical theory to describe its convergence behavior. In order to solve the convergence problem, we investigate it via a cost-function approach. By theoretical analysis, we prove that a general form of RPCL, called distance-sensitive RPCL (DSRPCL), is associated with the minimization of a cost function on the weight vectors of a competitive learning network. As a DSRPCL process decreases the cost to a local minimum, a number of weight vectors eventually fall into a hypersphere surrounding the sample data, while the other weight vectors diverge to infinity. Moreover, it is shown by the theoretical analysis and simulation experiments that if the cost reduces into the global minimum, a correct number of weight vectors is automatically selected and located around the centers of the actual clusters, respectively. Finally, we apply the DSRPCL algorithms to unsupervised color image segmentation and classification of the wine data.

Estimation of 3-D conduction velocity vector fields from cardiac mapping data.

PubMed

Barnette, A R; Bayly, P V; Zhang, S; Walcott, G P; Ideker, R E; Smith, W M

2000-08-01

A method to estimate three-dimensional (3-D) conduction velocity vector fields in cardiac tissue is presented. The speed and direction of propagation are found from polynomial "surfaces" fitted to space-time (x, y, z, t) coordinates of cardiac activity. The technique is applied to sinus rhythm and paced rhythm mapped with plunge needles at 396-466 sites in the canine myocardium. The method was validated on simulated 3-D plane and spherical waves. For simulated data, conduction velocities were estimated with an accuracy of 1%-2%. In experimental data, estimates of conduction speeds during paced rhythm were slower than those found during normal sinus rhythm. Vector directions were also found to differ between different types of beats. The technique was able to distinguish between premature ventricular contractions and sinus beats and between sinus and paced beats. The proposed approach to computing velocity vector fields provides an automated, physiological, and quantitative description of local electrical activity in 3-D tissue. This method may provide insight into abnormal conduction associated with fatal ventricular arrhythmias.

Prediction of hourly PM2.5 using a space-time support vector regression model

NASA Astrophysics Data System (ADS)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

Elastic and acoustic wavefield decompositions and application to reverse time migrations

NASA Astrophysics Data System (ADS)

Wang, Wenlong

P- and S-waves coexist in elastic wavefields, and separation between them is an essential step in elastic reverse-time migrations (RTMs). Unlike the traditional separation methods that use curl and divergence operators, which do not preserve the wavefield vector component information, we propose and compare two vector decomposition methods, which preserve the same vector components that exist in the input elastic wavefield. The amplitude and phase information is automatically preserved, so no amplitude or phase corrections are required. The decoupled propagation method is extended from elastic to viscoelastic wavefields. To use the decomposed P and S vector wavefields and generate PP and PS images, we create a new 2D migration context for isotropic, elastic RTM which includes PS vector decomposition; the propagation directions of both incident and reflected P- and S-waves are calculated directly from the stress and particle velocity definitions of the decomposed P- and S-wave Poynting vectors. Then an excitation-amplitude image condition that scales the receiver wavelet by the source vector magnitude produces angle-dependent images of PP and PS reflection coefficients with the correct polarities, polarization, and amplitudes. It thus simplifies the process of obtaining PP and PS angle-domain common-image gathers (ADCIGs); it is less effort to generate ADCIGs from vector data than from scalar data. Besides P- and S-waves decomposition, separations of up- and down-going waves are also a part of processing of multi-component recorded data and propagating wavefields. A complex trace based up/down separation approach is extended from acoustic to elastic, and combined with P- and S-wave decomposition by decoupled propagation. This eliminates the need for a Fourier transform over time, thereby significantly reducing the storage cost and improving computational efficiency. Wavefield decomposition is applied to both synthetic elastic VSP data and propagating wavefield snapshots. Poynting vectors obtained from the particle-velocity and stress fields after P/S and up/down decompositions are much more accurate than those without. The up/down separation algorithm is also applicable in acoustic RTMs, where both (forward-time extrapolated) source and (reverse-time extrapolated) receiver wavefields are decomposed into up-going and down-going parts. Together with the crosscorrelation imaging condition, four images (down-up, up-down, up-up and down-down) are generated, which facilitate the analysis of artifacts and the imaging ability of the four images. Artifacts may exist in all the decomposed images, but their positions and types are different. The causes of artifacts in different images are explained and illustrated with sketches and numerical tests.

INTERIM ANALYSIS OF THE CONTRIBUTION OF HIGH-LEVEL EVIDENCE FOR DENGUE VECTOR CONTROL.

PubMed

Horstick, Olaf; Ranzinger, Silvia Runge

2015-01-01

This interim analysis reviews the available systematic literature for dengue vector control on three levels: 1) single and combined vector control methods, with existing work on peridomestic space spraying and on Bacillus thuringiensis israelensis; further work is available soon on the use of Temephos, Copepods and larvivorous fish; 2) or for a specific purpose, like outbreak control, and 3) on a strategic level, as for example decentralization vs centralization, with a systematic review on vector control organization. Clear best practice guidelines for methodology of entomological studies are needed. There is a need to include measuring dengue transmission data. The following recommendations emerge: Although vector control can be effective, implementation remains an issue; Single interventions are probably not useful; Combinations of interventions have mixed results; Careful implementation of vector control measures may be most important; Outbreak interventions are often applied with questionable effectiveness.

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.

New Methods For Interpretation Of Magnetic Gradient Tensor Data Using Eigenalysis And The Normalized Source Strength

NASA Astrophysics Data System (ADS)

Clark, D.

2012-12-01

In the future, acquisition of magnetic gradient tensor data is likely to become routine. New methods developed for analysis of magnetic gradient tensor data can also be applied to high quality conventional TMI surveys that have been processed using Fourier filtering techniques, or otherwise, to calculate magnetic vector and tensor components. This approach is, in fact, the only practical way at present to analyze vector component data, as measurements of vector components are seriously afflicted by motion noise, which is not as serious a problem for gradient components. In many circumstances, an optimal approach to extracting maximum information from magnetic surveys would be to combine analysis of measured gradient tensor data with vector components calculated from TMI measurements. New methods for inverting gradient tensor surveys to obtain source parameters have been developed for a number of elementary, but useful, models. These include point dipole (sphere), vertical line of dipoles (narrow vertical pipe), line of dipoles (horizontal cylinder), thin dipping sheet, horizontal line current and contact models. A key simplification is the use of eigenvalues and associated eigenvectors of the tensor. The normalized source strength (NSS), calculated from the eigenvalues, is a particularly useful rotational invariant that peaks directly over 3D compact sources, 2D compact sources, thin sheets and contacts, and is independent of magnetization direction for these sources (and only very weakly dependent on magnetization direction in general). In combination the NSS and its vector gradient enable estimation of the Euler structural index, thereby constraining source geometry, and determine source locations uniquely. NSS analysis can be extended to other useful models, such as vertical pipes, by calculating eigenvalues of the vertical derivative of the gradient tensor. Once source locations are determined, information of source magnetizations can be obtained by simple linear inversion of measured or calculated vector and/or tensor data. Inversions based on the vector gradient of the NSS over the Tallawang magnetite deposit in central New South Wales obtained good agreement between the inferred geometry of the tabular magnetite skarn body and drill hole intersections. Inverted magnetizations are consistent with magnetic property measurements on drill core samples from this deposit. Similarly, inversions of calculated tensor data over the Mount Leyshold gold-mineralized porphyry system in Queensland yield good estimates of the centroid location, total magnetic moment and magnetization direction of the magnetite-bearing potassic alteration zone that are consistent with geological and petrophysical information.

System balance analysis for vector computers

NASA Technical Reports Server (NTRS)

Knight, J. C.; Poole, W. G., Jr.; Voight, R. G.

1975-01-01

The availability of vector processors capable of sustaining computing rates of 10 to the 8th power arithmetic results pers second raised the question of whether peripheral storage devices representing current technology can keep such processors supplied with data. By examining the solution of a large banded linear system on these computers, it was found that even under ideal conditions, the processors will frequently be waiting for problem data.

An examination of techniques for reformatting digital cartographic data. Part 2: the vector-to raster process.

USGS Publications Warehouse

Peuquet, D.J.

1981-01-01

Current graphic devices suitable for high-speed computer input and output of cartographic data are tending more and more to be raster-oriented, such as the rotating drum scanner and the color raster display. However, the majority of commonly used manipulative techniques in computer-assisted cartography and automated spatial data handling continue to require that the data be in vector format. The current article is the second part of a two-part paper that examines the state of the art in these conversion techniques. - from Author

Application of satellite data in variational analysis for global cyclonic systems

NASA Technical Reports Server (NTRS)

Achtemeier, G. L.

1987-01-01

The research goal was a variational data assimilation method that incorporates as dynamical constraints, the primitive equations for a moist, convectively unstable atmosphere and the radiative transfer equation. Variables to be adjusted include the three-dimensional vector wind, height, temperature, and moisture from rawinsonde data, and cloud-wind vectors, moisture, and radiance from satellite data. This presents a formidable mathematical problem. In order to facilitate thorough analysis of each of the model components, four variational models that divide the problem naturally according to increasing complexity are defined. Each model is summarized.

Search for dark matter produced with an energetic jet or a hadronically decaying W or Z boson at $$\\sqrt{s}=13 $$ TeV

DOE PAGES

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

2017-07-05

A search for dark matter particles is performed using events with large missing transverse momentum, at least one energetic jet, and no leptons, in proton-proton collisions atmore » $$ \\sqrt{s}=13 $$ TeV collected with the CMS detector at the LHC. The data sample corresponds to an integrated luminosity of 12.9 fb -1. The search includes events with jets from the hadronic decays of a W or Z boson. The data are found to be in agreement with the predicted background contributions from standard model processes. The results are presented in terms of simplified models in which dark matter particles are produced through interactions involving a vector, axial-vector, scalar, or pseudoscalar mediator. Vector and axial-vector mediator particles with masses up to 1.95 TeV, and scalar and pseudoscalar mediator particles with masses up to 100 and 430 GeV respectively, are excluded at 95% confidence level. The results are also interpreted in terms of the invisible decays of the Higgs boson, yielding an observed (expected) 95% confidence level upper limit of 0.44 (0.56) on the corresponding branching fraction. The results of this search provide the strongest constraints on the dark matter pair production cross section through vector and axial-vector mediators at a particle collider. When compared to the direct detection experiments, the limits obtained from this search provide stronger constraints for dark matter masses less than 5, 9, and 550 GeV, assuming vector, scalar, and axial-vector mediators, respectively. In conclusion, the search yields stronger constraints for dark matter masses less than 200 GeV, assuming a pseudoscalar mediator, when compared to the indirect detection results from Fermi-LAT.« less

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

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

A search for dark matter particles is performed using events with large missing transverse momentum, at least one energetic jet, and no leptons, in proton-proton collisions atmore » $$ \\sqrt{s}=13 $$ TeV collected with the CMS detector at the LHC. The data sample corresponds to an integrated luminosity of 12.9 fb -1. The search includes events with jets from the hadronic decays of a W or Z boson. The data are found to be in agreement with the predicted background contributions from standard model processes. The results are presented in terms of simplified models in which dark matter particles are produced through interactions involving a vector, axial-vector, scalar, or pseudoscalar mediator. Vector and axial-vector mediator particles with masses up to 1.95 TeV, and scalar and pseudoscalar mediator particles with masses up to 100 and 430 GeV respectively, are excluded at 95% confidence level. The results are also interpreted in terms of the invisible decays of the Higgs boson, yielding an observed (expected) 95% confidence level upper limit of 0.44 (0.56) on the corresponding branching fraction. The results of this search provide the strongest constraints on the dark matter pair production cross section through vector and axial-vector mediators at a particle collider. When compared to the direct detection experiments, the limits obtained from this search provide stronger constraints for dark matter masses less than 5, 9, and 550 GeV, assuming vector, scalar, and axial-vector mediators, respectively. In conclusion, the search yields stronger constraints for dark matter masses less than 200 GeV, assuming a pseudoscalar mediator, when compared to the indirect detection results from Fermi-LAT.« less

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.

International solar polar mission: The vector helium magnetometer

NASA Technical Reports Server (NTRS)

1982-01-01

The functional requirements for the vector helium magnetometer (VHM) on the Solar Polar spacecraft are presented. The VHM is one of the two magnetometers on board that will measure the vector magnetic field along the Earth to Jupiter transfer trajectory, as well as in the vicinity of Jupiter and along the solar polar orbit following the Jupiter encounter. The interconnection between these two magnetometers and their shared data processing unit is illustrated.

United States Air Force Guide to Operational Surveillance of Medically Important Vectors and Pests Operational Entomology

DTIC Science & Technology

2006-08-15

Programs Section 3. Sampling Equipment Sampling Equipment Solid-State Army Miniature (SSAM) trap ABC style trap Encephalitis Vector Survey Trap CDC...Baseline Survey - these are conducted to determine the types of vectors and pests occurring in the area of operations, their respective breeding sites...or source habitat, and seasonal activity patterns. Operational Survey - data collected in an operational survey are used specifically to aid pest

Data catalog for JPL Physical Oceanography Distributed Active Archive Center (PO.DAAC)

NASA Technical Reports Server (NTRS)

Digby, Susan

1995-01-01

The Physical Oceanography Distributed Active Archive Center (PO.DAAC) archive at the Jet Propulsion Laboratory contains satellite data sets and ancillary in-situ data for the ocean sciences and global-change research to facilitate multidisciplinary use of satellite ocean data. Geophysical parameters available from the archive include sea-surface height, surface-wind vector, surface-wind speed, surface-wind stress vector, sea-surface temperature, atmospheric liquid water, integrated water vapor, phytoplankton pigment concentration, heat flux, and in-situ data. PO.DAAC is an element of the Earth Observing System Data and Information System and is the United States distribution site for TOPEX/POSEIDON data and metadata.

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

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

Paulsson, Bjorn N.P.; Thornburg, Jon A.; He, Ruiqing

2015-04-21

Seismic techniques are the dominant geophysical techniques for the characterization of subsurface structures and stratigraphy. The seismic techniques also dominate the monitoring and mapping of reservoir injection and production processes. Borehole seismology, of all the seismic techniques, despite its current shortcomings, has been shown to provide the highest resolution characterization and most precise monitoring results because it generates higher signal to noise ratio and higher frequency data than surface seismic techniques. The operational environments for borehole seismic instruments are however much more demanding than for surface seismic instruments making both the instruments and the installation much more expensive. The currentmore » state-of-the-art borehole seismic instruments have not been robust enough for long term monitoring compounding the problems with expensive instruments and installations. Furthermore, they have also not been able to record the large bandwidth data available in boreholes or having the sensitivity allowing them to record small high frequency micro seismic events with high vector fidelity. To reliably achieve high resolution characterization and long term monitoring of Enhanced Geothermal Systems (EGS) sites a new generation of borehole seismic instruments must therefore be developed and deployed. To address the critical site characterization and monitoring needs for EGS programs, US Department of Energy (DOE) funded Paulsson, Inc. in 2010 to develop a fiber optic based ultra-large bandwidth clamped borehole seismic vector array capable of deploying up to one thousand 3C sensor pods suitable for deployment into ultra-high temperature and high pressure boreholes. Tests of the fiber optic seismic vector sensors developed on the DOE funding have shown that the new borehole seismic sensor technology is capable of generating outstanding high vector fidelity data with extremely large bandwidth: 0.01 – 6,000 Hz. Field tests have shown that the system can record events at magnitudes much smaller than M-2.6 at frequencies up to 2,000 Hz. The sensors have also proved to be about 100 times more sensitive than the regular coil geophones that are used in borehole seismic systems today. The fiber optic seismic sensors have furthermore been qualified to operate at temperatures over 300°C (572°F). Simultaneously with the fiber optic based seismic 3C vector sensors we are using the lead-in fiber to acquire Distributed Acoustic Sensor (DAS) data from the surface to the bottom of the vector array. While the DAS data is of much lower quality than the vector sensor data it provides a 1 m spatial sampling of the downgoing wavefield which will be used to build the high resolution velocity model which is an essential component in high resolution imaging and monitoring.« less

Initial geomagnetic field model from Magsat vector data

NASA Technical Reports Server (NTRS)

Langel, R. A.; Mead, G. D.; Lancaster, E. R.; Estes, R. H.; Fabiano, E. B.

1980-01-01

Magsat data from the magnetically quiet days of November 5-6, 1979, were used to derive a thirteenth degree and order spherical harmonic geomagnetic field model, MGST(6/80). The model utilized both scalar and high-accuracy vector data and fit that data with root-mean-square deviations of 8.2, 6.9, 7.6 and 7.4 nT for the scalar magnitude, B(r), B(theta), and B(phi), respectively. The model includes the three first-order coefficients of the external field. Comparison with averaged Dst indicates that zero Dst corresponds with 25 nT of horizontal field from external sources. When compared with earlier models, the earth's dipole moment continues to decrease at a rate of about 26 nT/yr. Evaluation of earlier models with Magsat data shows that the scalar field at the Magsat epoch is best predicted by the POGO(2/72) model but that the WC80, AWC/75 and IGS/75 are better for predicting vector fields.

Spatial Risk Assessments Based on Vector-Borne Disease Epidemiologic Data: Importance of Scale for West Nile Virus Disease in Colorado

PubMed Central

Winters, Anna M.; Eisen, Rebecca J.; Delorey, Mark J.; Fischer, Marc; Nasci, Roger S.; Zielinski-Gutierrez, Emily; Moore, Chester G.; Pape, W. John; Eisen, Lars

2010-01-01

We used epidemiologic data for human West Nile virus (WNV) disease in Colorado from 2003 and 2007 to determine 1) the degree to which estimates of vector-borne disease occurrence is influenced by spatial scale of data aggregation (county versus census tract), and 2) the extent of concordance between spatial risk patterns based on case counts versus incidence. Statistical analyses showed that county, compared with census tract, accounted for approximately 50% of the overall variance in WNV disease incidence, and approximately 33% for the subset of cases classified as West Nile neuroinvasive disease. These findings indicate that sub-county scale presentation provides valuable risk information for stakeholders. There was high concordance between spatial patterns of WNV disease incidence and case counts for census tract (83%) but not for county (50%) or zip code (31%). We discuss how these findings impact on practices to develop spatial epidemiologic data for vector-borne diseases and present data to stakeholders. PMID:20439980

A collaborative framework for Distributed Privacy-Preserving Support Vector Machine learning.

PubMed

Que, Jialan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

A Support Vector Machine (SVM) is a popular tool for decision support. The traditional way to build an SVM model is to estimate parameters based on a centralized repository of data. However, in the field of biomedicine, patient data are sometimes stored in local repositories or institutions where they were collected, and may not be easily shared due to privacy concerns. This creates a substantial barrier for researchers to effectively learn from the distributed data using machine learning tools like SVMs. To overcome this difficulty and promote efficient information exchange without sharing sensitive raw data, we developed a Distributed Privacy Preserving Support Vector Machine (DPP-SVM). The DPP-SVM enables privacy-preserving collaborative learning, in which a trusted server integrates "privacy-insensitive" intermediary results. The globally learned model is guaranteed to be exactly the same as learned from combined data. We also provide a free web-service (http://privacy.ucsd.edu:8080/ppsvm/) for multiple participants to collaborate and complete the SVM-learning task in an efficient and privacy-preserving manner.

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.

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.

Progress toward a circulation atlas for application to coastal water siting problems

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.; Gordon, H. H.

1978-01-01

Circulation data needed to resolve coastal siting problems are assembled from historical hydrographic and remote sensing studies in the form of a Circulation Atlas. Empirical data are used instead of numerical model simulations to achieve fine resolution and include fronts and convergence zones. Eulerian and Langrangian data are collected, transformed, and combined into trajectory maps and current vector maps as a function of tidal phase and wind vector. Initial Atlas development is centered on the Elizabeth River, Hampton Roads, Virgina.

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

Vectors into the Future of Mass and Interpersonal Communication Research: Big Data, Social Media, and Computational Social Science.

PubMed

Cappella, Joseph N

2017-10-01

Simultaneous developments in big data, social media, and computational social science have set the stage for how we think about and understand interpersonal and mass communication. This article explores some of the ways that these developments generate 4 hypothetical "vectors" - directions - into the next generation of communication research. These vectors include developments in network analysis, modeling interpersonal and social influence, recommendation systems, and the blurring of distinctions between interpersonal and mass audiences through narrowcasting and broadcasting. The methods and research in these arenas are occurring in areas outside the typical boundaries of the communication discipline but engage classic, substantive questions in mass and interpersonal communication.

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.

Major vectors and vector-borne diseases in small ruminants in Ethiopia: A systematic review.

PubMed

Asmare, Kassahun; Abayneh, Takele; Sibhat, Berhanu; Shiferaw, Dessie; Szonyi, Barbara; Krontveit, Randi I; Skjerve, Eystein; Wieland, Barbara

2017-06-01

Vector-borne diseases are among major health constraints of small ruminant in Ethiopia. While various studies on single vector-borne diseases or presence of vectors have been conducted, no summarized evidence is available on the occurrence of these diseases and the related vectors. This systematic literature review provides a comprehensive summary on major vectors and vector-borne diseases in small ruminants in Ethiopia. Search for published and unpublished literature was conducted between 8th of January and 25th of June 2015. The search was both manual and electronic. The databases used in electronic search were PubMed, Web of Science, CAB Direct and AJOL. For most of the vector-borne diseases, the summary was limited to narrative synthesis due to lack of sufficient data. Meta-analysis was computed for trypanosomosis and dermatophilosis while meta-regression and sensitivity analysis was done only for trypanososmosis due to lack of sufficient reports on dermatophilosis. Owing emphasis to their vector role, ticks and flies were summarized narratively at genera/species level. In line with inclusion criteria, out of 106 initially identified research reports 43 peer-reviewed articles passed the quality assessment. Data on 7 vector-borne diseases were extracted at species and region level from each source. Accordingly, the pooled prevalence estimate of trypanosomosis was 3.7% with 95% confidence interval (CI) 2.8, 4.9), while that of dermatophilosis was 3.1% (95% CI: 1.6, 6.0). The in-between study variance noted for trypanosomosis was statistically significant (p<0.05). Among the three covariates considered for meta-regression, only one (species) fitted the final model significantly (p<0.05) and explained 65.44% of the between studies variance (R 2 ). The prevalence in sheep (5.5%) increased nearly by 34% compared to goats (2.9%). The parasitic presence in blood was documented for babesiosis (3.7% in goats); and anaplasmosis (3.9% in sheep). Serological evidence was retrieved for bluetongue ranging from 34.1% to 46.67% in sheep, and coxiellosis was 10.4% in goats. There was also molecular evidence on the presence of theileriosis in sheep (93%, n=160) and goats (1.9%, n=265). Regarding vectors of veterinary importance, 14 species of ticks in five genera, four species of Glossina and 4 genera of biting flies were reported. Despite the evidence on presence of various vectors including ticks, flies, mosquitoes and midges, studies on vector-borne diseases in Ethiopia are surprisingly rare, especially considering risks related to climate change, which is likely to affect distribution of vectors. Thus better evidence on the current situation is urgently needed in order to prevent spread and to model future distribution scenarios. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PlasmoGEM, a database supporting a community resource for large-scale experimental genetics in malaria parasites.

PubMed

Schwach, Frank; Bushell, Ellen; Gomes, Ana Rita; Anar, Burcu; Girling, Gareth; Herd, Colin; Rayner, Julian C; Billker, Oliver

2015-01-01

The Plasmodium Genetic Modification (PlasmoGEM) database (http://plasmogem.sanger.ac.uk) provides access to a resource of modular, versatile and adaptable vectors for genome modification of Plasmodium spp. parasites. PlasmoGEM currently consists of >2000 plasmids designed to modify the genome of Plasmodium berghei, a malaria parasite of rodents, which can be requested by non-profit research organisations free of charge. PlasmoGEM vectors are designed with long homology arms for efficient genome integration and carry gene specific barcodes to identify individual mutants. They can be used for a wide array of applications, including protein localisation, gene interaction studies and high-throughput genetic screens. The vector production pipeline is supported by a custom software suite that automates both the vector design process and quality control by full-length sequencing of the finished vectors. The PlasmoGEM web interface allows users to search a database of finished knock-out and gene tagging vectors, view details of their designs, download vector sequence in different formats and view available quality control data as well as suggested genotyping strategies. We also make gDNA library clones and intermediate vectors available for researchers to produce vectors for themselves. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Novel Vaccine Approach for Chagas Disease Using Rare Adenovirus Serotype 48 Vectors

PubMed Central

Farrow, Anitra L.; Peng, Binghao J.; Gu, Linlin; Krendelchtchikov, Alexandre; Matthews, Qiana L.

2016-01-01

Due to the increasing amount of people afflicted worldwide with Chagas disease and an increasing prevalence in the United States, there is a greater need to develop a safe and effective vaccine for this neglected disease. Adenovirus serotype 5 (Ad5) is the most common adenovirus vector used for gene therapy and vaccine approaches, but its efficacy is limited by preexisting vector immunity in humans resulting from natural infections. Therefore, we have employed rare serotype adenovirus 48 (Ad48) as an alternative choice for adenovirus/Chagas vaccine therapy. In this study, we modified Ad5 and Ad48 vectors to contain T. cruzi’s amastigote surface protein 2 (ASP-2) in the adenoviral early gene. We also modified Ad5 and Ad48 vectors to utilize the “Antigen Capsid-Incorporation” strategy by adding T. cruzi epitopes to protein IX (pIX). Mice that were immunized with the modified vectors were able to elicit T. cruzi-specific humoral and cellular responses. This study indicates that Ad48-modified vectors function comparable to or even premium to Ad5-modified vectors. This study provides novel data demonstrating that Ad48 can be used as a potential adenovirus vaccine vector against Chagas disease. PMID:26978385

Host structural carbohydrate induces vector transmission of a bacterial plant pathogen.

PubMed

Killiny, Nabil; Almeida, Rodrigo P P

2009-12-29

Many insect-borne pathogens have complex life histories because they must colonize both hosts and vectors for successful dissemination. In addition, the transition from host to vector environments may require changes in gene expression before the pathogen's departure from the host. Xylella fastidiosa is a xylem-limited plant-pathogenic bacterium transmitted by leafhopper vectors that causes diseases in a number of economically important plants. We hypothesized that factors of host origin, such as plant structural polysaccharides, are important in regulating X. fastidiosa gene expression and mediating vector transmission of this pathogen. The addition of pectin and glucan to a simple defined medium resulted in dramatic changes in X. fastidiosa's phenotype and gene-expression profile. Cells grown in the presence of pectin became more adhesive than in other media tested. In addition, the presence of pectin and glucan in media resulted in significant changes in the expression of several genes previously identified as important for X. fastidiosa's pathogenicity in plants. Furthermore, vector transmission of X. fastidiosa was induced in the presence of both polysaccharides. Our data show that host structural polysaccharides mediate gene regulation in X. fastidiosa, which results in phenotypic changes required for vector transmission. A better understanding of how vector-borne pathogens transition from host to vector, and vice versa, may lead to previously undiscovered disease-control strategies.

Effects of Cucumber mosaic virus infection on vector and non-vector herbivores of squash.

PubMed

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

2010-11-01

Plant chemicals mediating interactions with insect herbivores seem a likely target for manipulation by insectvectored plant pathogens. Yet, little is currently known about the chemical ecology of insect-vectored diseases or their effects on the ecology of vector and nonvector insects. We recently reported that a widespread plant pathogen, Cucumber mosaic virus (CMV), greatly reduces the quality of host-plants (squash) for aphid vectors, but that aphids are nevertheless attracted to the odors of infected plants-which exhibit elevated emissions of a volatile blend otherwise similar to the odor of healthy plants. This finding suggests that exaggerating existing host-location cues can be a viable vector attraction strategy for pathogens that otherwise reduce host quality for vectors. Here we report additional data regarding the effects of CMV infection on plant interactions with a common nonvector herbivore, the squash bug, Anasa tristis, which is a pest in this system. We found that adult A. tristis females preferred to oviposit on healthy plants in the field, and that healthy plants supported higher populations of nymphs. Collectively, our recent findings suggest that CMV-induced changes in host plant chemistry influence the behavior of both vector and non-vector herbivores, with significant implications both for disease spread and for broader community-level interactions.

3D magnetization vector inversion based on fuzzy clustering: inversion algorithm, uncertainty analysis, and application to geology differentiation

NASA Astrophysics Data System (ADS)

Sun, J.; Li, Y.

2017-12-01

Magnetic data contain important information about the subsurface rocks that were magnetized in the geological history, which provides an important avenue to the study of the crustal heterogeneities associated with magmatic and hydrothermal activities. Interpretation of magnetic data has been widely used in mineral exploration, basement characterization and large scale crustal studies for several decades. However, interpreting magnetic data has been often complicated by the presence of remanent magnetizations with unknown magnetization directions. Researchers have developed different methods to deal with the challenges posed by remanence. We have developed a new and effective approach to inverting magnetic data for magnetization vector distributions characterized by region-wise consistency in the magnetization directions. This approach combines the classical Tikhonov inversion scheme with fuzzy C-means clustering algorithm, and constrains the estimated magnetization vectors to a specified small number of possible directions while fitting the observed magnetic data to within noise level. Our magnetization vector inversion recovers both the magnitudes and the directions of the magnetizations in the subsurface. Magnetization directions reflect the unique geological or hydrothermal processes applied to each geological unit, and therefore, can potentially be used for the purpose of differentiating various geological units. We have developed a practically convenient and effective way of assessing the uncertainty associated with the inverted magnetization directions (Figure 1), and investigated how geological differentiation results might be affected (Figure 2). The algorithm and procedures we have developed for magnetization vector inversion and uncertainty analysis open up new possibilities of extracting useful information from magnetic data affected by remanence. We will use a field data example from exploration of an iron-oxide-copper-gold (IOCG) deposit in Brazil to illustrate how to solve the inverse problem, assess uncertainty, and perform geology differentiation in practice. We will also discuss the potential applications of this new method to large scale crustal studies.

Zika mosquito vectors: the jury is still out.

PubMed

Leal, Walter S

2016-01-01

After a 40-year hiatus, the International Congress of Entomology (ICE 2016) convened in Orlando, Florida (September 25-30, 2016). One of the symposia at ICE 2016, the Zika Symposium, covered multiple aspects of the Zika epidemic, including epidemiology, sexual transmission, genetic tools for reducing transmission, and particularly vector competence. While there was a consensus among participants that the yellow fever mosquito, Aedes aegypti , is a vector of the Zika virus, there is growing evidence indicating that the range of mosquito vectors might be wider than anticipated. In particular, three independent groups from Canada, China, and Brazil presented and discussed laboratory and field data strongly suggesting that the southern house mosquito, Culex quinquefasciatus , also known as the common mosquito, is highly likely to be a vector in certain environments.

VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy.

PubMed

Juanes, José M; Gallego, Asunción; Tárraga, Joaquín; Chaves, Felipe J; Marín-Garcia, Pablo; Medina, Ignacio; Arnau, Vicente; Dopazo, Joaquín

2017-09-20

The possibility of integrating viral vectors to become a persistent part of the host genome makes them a crucial element of clinical gene therapy. However, viral integration has associated risks, such as the unintentional activation of oncogenes that can result in cancer. Therefore, the analysis of integration sites of retroviral vectors is a crucial step in developing safer vectors for therapeutic use. Here we present VISMapper, a vector integration site analysis web server, to analyze next-generation sequencing data for retroviral vector integration sites. VISMapper can be found at: http://vismapper.babelomics.org . Because it uses novel mapping algorithms VISMapper is remarkably faster than previous available programs. It also provides a useful graphical interface to analyze the integration sites found in the genomic context.

Geosmithia associated with bark beetles and woodborers in the western USA: taxonomic diversity and vector specificity.

PubMed

Kolařík, Miroslav; Hulcr, Jiri; Tisserat, Ned; De Beer, Wilhelm; Kostovčík, Martin; Kolaříková, Zuzana; Seybold, Steven J; Rizzo, David M

2017-01-01

Fungi in the genus Geosmithia (Ascomycota: Hypocreales) are frequent associates of bark beetles and woodborers that colonize hardwood and coniferous trees. One species, Geosmithia morbida, is an economically damaging invasive species. The authors surveyed the Geosmithia species of California and Colorado, USA, to (i) provide baseline data on taxonomy of Geosmithia and beetle vector specificity across the western USA; (ii) investigate the subcortical beetle fauna for alternative vectors of the invasive G. morbida; and (iii) interpret the community composition of this region within the emerging global biogeography of Geosmithia. Geosmithia was detected in 87% of 126 beetle samples obtained from 39 plant species. Twenty-nine species of Geosmithia were distinguished, of which 13 may be new species. Bark beetles from hardwoods, Cupressus, and Sequoia appear to be regular vectors, with Geosmithia present in all beetle gallery systems examined. Other subcortical insects appear to vector Geosmithia at lower frequencies. Overall, most Geosmithia have a distinct level of vector specificity (mostly high, sometimes low) enabling their separation to generalists and specialists. Plant pathogenic Geosmithia morbida was not found in association with any other beetle besides Pityophthorus juglandis. However, four additional Geosmithia species were found in P. juglandis galleries. When integrated with recent data from other continents, a global pattern of Geosmithia distribution across continents, latitudes, and vectors is emerging: of the 29 Geosmithia species found in the western USA, 12 have not been reported outside of the USA. The most frequently encountered species with the widest global distribution also had the broadest range of beetle vectors. Several Geosmithia spp. with very narrow vector ranges in Europe exhibited the similar degree of specialization in the USA. Such strong canalization in association could reflect an ancient origin of each individual association, or a recent origin and a subsequent diversification in North America.

Contrasting Effects of Human, Canine, and Hybrid Adenovirus Vectors on the Phenotypical and Functional Maturation of Human Dendritic Cells: Implications for Clinical Efficacy▿

PubMed Central

Perreau, Matthieu; Mennechet, Franck; Serratrice, Nicolas; Glasgow, Joel N.; Curiel, David T.; Wodrich, Harald; Kremer, Eric J.

2007-01-01

Antipathogen immune responses create a balance between immunity, tolerance, and immune evasion. However, during gene therapy most viral vectors are delivered in substantial doses and are incapable of expressing gene products that reduce the host's ability to detect transduced cells. Gene transfer efficacy is also modified by the in vivo transduction of dendritic cells (DC), which notably increases the immunogenicity of virions and vector-encoded genes. In this study, we evaluated parameters that are relevant to the use of canine adenovirus serotype 2 (CAV-2) vectors in the clinical setting by assaying their effect on human monocyte-derived DC (hMoDC). We compared CAV-2 to human adenovirus (HAd) vectors containing the wild-type virion, functional deletions in the penton base RGD motif, and the CAV-2 fiber knob. In contrast to the HAd type 5 (HAd5)-based vectors, CAV-2 poorly transduced hMoDC, provoked minimal upregulation of major histocompatibility complex class I/II and costimulatory molecules (CD40, CD80, and CD86), and induced negligible morphological changes indicative of DC maturation. Functional maturation assay results (e.g., reduced antigen uptake; tumor necrosis factor alpha, interleukin-1β [IL-1β], gamma interferon [IFN-γ], IL-10, IL-12, and IFN-α/β secretion; and stimulation of heterologous T-cell proliferation) were also significantly lower for CAV-2. Our data suggested that this was due, in part, to the use of an alternative receptor and a block in vesicular escape. Additionally, HAd5 vector-induced hMoDC maturation was independent of the aforementioned cytokines. Paradoxically, an HAd5/CAV-2 hybrid vector induced the greatest phenotypical and functional maturation of hMoDC. Our data suggest that CAV-2 and the HAd5/CAV-2 vector may be the antithesis of Adenoviridae immunogenicity and that each may have specific clinical advantages. PMID:17229706

Polynomial chaos representation of databases on manifolds

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

Soize, C., E-mail: christian.soize@univ-paris-est.fr; Ghanem, R., E-mail: ghanem@usc.edu

2017-04-15

Characterizing the polynomial chaos expansion (PCE) of a vector-valued random variable with probability distribution concentrated on a manifold is a relevant problem in data-driven settings. The probability distribution of such random vectors is multimodal in general, leading to potentially very slow convergence of the PCE. In this paper, we build on a recent development for estimating and sampling from probabilities concentrated on a diffusion manifold. The proposed methodology constructs a PCE of the random vector together with an associated generator that samples from the target probability distribution which is estimated from data concentrated in the neighborhood of the manifold. Themore » method is robust and remains efficient for high dimension and large datasets. The resulting polynomial chaos construction on manifolds permits the adaptation of many uncertainty quantification and statistical tools to emerging questions motivated by data-driven queries.« less

Geometric Representations of Condition Queries on Three-Dimensional Vector Fields

NASA Technical Reports Server (NTRS)

Henze, Chris

1999-01-01

Condition queries on distributed data ask where particular conditions are satisfied. It is possible to represent condition queries as geometric objects by plotting field data in various spaces derived from the data, and by selecting loci within these derived spaces which signify the desired conditions. Rather simple geometric partitions of derived spaces can represent complex condition queries because much complexity can be encapsulated in the derived space mapping itself A geometric view of condition queries provides a useful conceptual unification, allowing one to intuitively understand many existing vector field feature detection algorithms -- and to design new ones -- as variations on a common theme. A geometric representation of condition queries also provides a simple and coherent basis for computer implementation, reducing a wide variety of existing and potential vector field feature detection techniques to a few simple geometric operations.

A Field Trial of Alternative Targeted Screening Strategies for Chagas Disease in Arequipa, Peru

PubMed Central

Hunter, Gabrielle C.; Borrini-Mayorí, Katty; Ancca Juárez, Jenny; Castillo Neyra, Ricardo; Verastegui, Manuela R.; Malaga Chavez, Fernando S.; Cornejo del Carpio, Juan Geny; Córdova Benzaquen, Eleazar; Náquira, César; Gilman, Robert H.; Bern, Caryn; Levy, Michael Z.

2012-01-01

Background Chagas disease is endemic in the rural areas of southern Peru and a growing urban problem in the regional capital of Arequipa, population ∼860,000. It is unclear how to implement cost-effective screening programs across a large urban and periurban environment. Methods We compared four alternative screening strategies in 18 periurban communities, testing individuals in houses with 1) infected vectors; 2) high vector densities; 3) low vector densities; and 4) no vectors. Vector data were obtained from routine Ministry of Health insecticide application campaigns. We performed ring case detection (radius of 15 m) around seropositive individuals, and collected data on costs of implementation for each strategy. Results Infection was detected in 21 of 923 (2.28%) participants. Cases had lived more time on average in rural places than non-cases (7.20 years versus 3.31 years, respectively). Significant risk factors on univariate logistic regression for infection were age (OR 1.02; p = 0.041), time lived in a rural location (OR 1.04; p = 0.022), and time lived in an infested area (OR 1.04; p = 0.008). No multivariate model with these variables fit the data better than a simple model including only the time lived in an area with triatomine bugs. There was no significant difference in prevalence across the screening strategies; however a self-assessment of disease risk may have biased participation, inflating prevalence among residents of houses where no infestation was detected. Testing houses with infected-vectors was least expensive. Ring case detection yielded four secondary cases in only one community, possibly due to vector-borne transmission in this community, apparently absent in the others. Conclusions Targeted screening for urban Chagas disease is promising in areas with ongoing vector-borne transmission; however, these pockets of epidemic transmission remain difficult to detect a priori. The flexibility to adapt to the epidemiology that emerges during screening is key to an efficient case detection intervention. In heterogeneous urban environments, self-assessments of risk and simple residence history questionnaires may be useful to identify those at highest risk for Chagas disease to guide diagnostic efforts. PMID:22253939

A field trial of alternative targeted screening strategies for Chagas disease in Arequipa, Peru.

PubMed

Hunter, Gabrielle C; Borrini-Mayorí, Katty; Ancca Juárez, Jenny; Castillo Neyra, Ricardo; Verastegui, Manuela R; Malaga Chavez, Fernando S; Cornejo del Carpio, Juan Geny; Córdova Benzaquen, Eleazar; Náquira, César; Gilman, Robert H; Bern, Caryn; Levy, Michael Z

2012-01-01

Chagas disease is endemic in the rural areas of southern Peru and a growing urban problem in the regional capital of Arequipa, population ∼860,000. It is unclear how to implement cost-effective screening programs across a large urban and periurban environment. We compared four alternative screening strategies in 18 periurban communities, testing individuals in houses with 1) infected vectors; 2) high vector densities; 3) low vector densities; and 4) no vectors. Vector data were obtained from routine Ministry of Health insecticide application campaigns. We performed ring case detection (radius of 15 m) around seropositive individuals, and collected data on costs of implementation for each strategy. Infection was detected in 21 of 923 (2.28%) participants. Cases had lived more time on average in rural places than non-cases (7.20 years versus 3.31 years, respectively). Significant risk factors on univariate logistic regression for infection were age (OR 1.02; p = 0.041), time lived in a rural location (OR 1.04; p = 0.022), and time lived in an infested area (OR 1.04; p = 0.008). No multivariate model with these variables fit the data better than a simple model including only the time lived in an area with triatomine bugs. There was no significant difference in prevalence across the screening strategies; however a self-assessment of disease risk may have biased participation, inflating prevalence among residents of houses where no infestation was detected. Testing houses with infected-vectors was least expensive. Ring case detection yielded four secondary cases in only one community, possibly due to vector-borne transmission in this community, apparently absent in the others. Targeted screening for urban Chagas disease is promising in areas with ongoing vector-borne transmission; however, these pockets of epidemic transmission remain difficult to detect a priori. The flexibility to adapt to the epidemiology that emerges during screening is key to an efficient case detection intervention. In heterogeneous urban environments, self-assessments of risk and simple residence history questionnaires may be useful to identify those at highest risk for Chagas disease to guide diagnostic efforts.

Transcriptome of the adult female malaria mosquito vector Anopheles albimanus.

PubMed

Martínez-Barnetche, Jesús; Gómez-Barreto, Rosa E; Ovilla-Muñoz, Marbella; Téllez-Sosa, Juan; García López, David E; Dinglasan, Rhoel R; Ubaida Mohien, Ceereena; MacCallum, Robert M; Redmond, Seth N; Gibbons, John G; Rokas, Antonis; Machado, Carlos A; Cazares-Raga, Febe E; González-Cerón, Lilia; Hernández-Martínez, Salvador; Rodríguez López, Mario H

2012-05-30

Human Malaria is transmitted by mosquitoes of the genus Anopheles. Transmission is a complex phenomenon involving biological and environmental factors of humans, parasites and mosquitoes. Among more than 500 anopheline species, only a few species from different branches of the mosquito evolutionary tree transmit malaria, suggesting that their vectorial capacity has evolved independently. Anopheles albimanus (subgenus Nyssorhynchus) is an important malaria vector in the Americas. The divergence time between Anopheles gambiae, the main malaria vector in Africa, and the Neotropical vectors has been estimated to be 100 My. To better understand the biological basis of malaria transmission and to develop novel and effective means of vector control, there is a need to explore the mosquito biology beyond the An. gambiae complex. We sequenced the transcriptome of the An. albimanus adult female. By combining Sanger, 454 and Illumina sequences from cDNA libraries derived from the midgut, cuticular fat body, dorsal vessel, salivary gland and whole body, we generated a single, high-quality assembly containing 16,669 transcripts, 92% of which mapped to the An. darlingi genome and covered 90% of the core eukaryotic genome. Bidirectional comparisons between the An. gambiae, An. darlingi and An. albimanus predicted proteomes allowed the identification of 3,772 putative orthologs. More than half of the transcripts had a match to proteins in other insect vectors and had an InterPro annotation. We identified several protein families that may be relevant to the study of Plasmodium-mosquito interaction. An open source transcript annotation browser called GDAV (Genome-Delinked Annotation Viewer) was developed to facilitate public access to the data generated by this and future transcriptome projects. We have explored the adult female transcriptome of one important New World malaria vector, An. albimanus. We identified protein-coding transcripts involved in biological processes that may be relevant to the Plasmodium lifecycle and can serve as the starting point for searching targets for novel control strategies. Our data increase the available genomic information regarding An. albimanus several hundred-fold, and will facilitate molecular research in medical entomology, evolutionary biology, genomics and proteomics of anopheline mosquito vectors. The data reported in this manuscript is accessible to the community via the VectorBase website (http://www.vectorbase.org/Other/AdditionalOrganisms/).

Administration of helper-dependent adenoviral vectors and sequential delivery of different vector serotype for long-term liver-directed gene transfer in baboons

PubMed Central

Morral, Núria; O’Neal, Wanda; Rice, Karen; Leland, Michele; Kaplan, Johanne; Piedra, Pedro A.; Zhou, Heshan; Parks, Robin J.; Velji, Rizwan; Aguilar-Córdova, Estuardo; Wadsworth, Samuel; Graham, Frank L.; Kochanek, Stefan; Carey, K. Dee; Beaudet, Arthur L.

1999-01-01

The efficiency of first-generation adenoviral vectors as gene delivery tools is often limited by the short duration of transgene expression, which can be related to immune responses and to toxic effects of viral proteins. In addition, readministration is usually ineffective unless the animals are immunocompromised or a different adenovirus serotype is used. Recently, adenoviral vectors devoid of all viral coding sequences (helper-dependent or gutless vectors) have been developed to avoid expression of viral proteins. In mice, liver-directed gene transfer with AdSTK109, a helper-dependent adenoviral (Ad) vector containing the human α1-antitrypsin (hAAT) gene, resulted in sustained expression for longer than 10 months with negligible toxicity to the liver. In the present report, we have examined the duration of expression of AdSTK109 in the liver of baboons and compared it to first-generation vectors expressing hAAT. Transgene expression was limited to approximately 3–5 months with the first-generation vectors. In contrast, administration of AdSTK109 resulted in transgene expression for longer than a year in two of three baboons. We have also investigated the feasibility of circumventing the humoral response to the virus by sequential administration of vectors of different serotypes. We found that the ineffectiveness of readministration due to the humoral response to an Ad5 first-generation vector was overcome by use of an Ad2-based vector expressing hAAT. These data suggest that long-term expression of transgenes should be possible by combining the reduced immunogenicity and toxicity of helper-dependent vectors with sequential delivery of vectors of different serotypes. PMID:10536005

Co-occurrence of viruses and mosquitoes at the vectors' optimal climate range: An underestimated risk to temperate regions?

PubMed

Blagrove, Marcus S C; Caminade, Cyril; Waldmann, Elisabeth; Sutton, Elizabeth R; Wardeh, Maya; Baylis, Matthew

2017-06-01

Mosquito-borne viruses have been estimated to cause over 100 million cases of human disease annually. Many methodologies have been developed to help identify areas most at risk from transmission of these viruses. However, generally, these methodologies focus predominantly on the effects of climate on either the vectors or the pathogens they spread, and do not consider the dynamic interaction between the optimal conditions for both vector and virus. Here, we use a new approach that considers the complex interplay between the optimal temperature for virus transmission, and the optimal climate for the mosquito vectors. Using published geolocated data we identified temperature and rainfall ranges in which a number of mosquito vectors have been observed to co-occur with West Nile virus, dengue virus or chikungunya virus. We then investigated whether the optimal climate for co-occurrence of vector and virus varies between "warmer" and "cooler" adapted vectors for the same virus. We found that different mosquito vectors co-occur with the same virus at different temperatures, despite significant overlap in vector temperature ranges. Specifically, we found that co-occurrence correlates with the optimal climatic conditions for the respective vector; cooler-adapted mosquitoes tend to co-occur with the same virus in cooler conditions than their warmer-adapted counterparts. We conclude that mosquitoes appear to be most able to transmit virus in the mosquitoes' optimal climate range, and hypothesise that this may be due to proportionally over-extended vector longevity, and other increased fitness attributes, within this optimal range. These results suggest that the threat posed by vector-competent mosquito species indigenous to temperate regions may have been underestimated, whilst the threat arising from invasive tropical vectors moving to cooler temperate regions may be overestimated.

Measured pressure distributions inside nonaxisymmetric nozzles with partially deployed thrust reversers

NASA Technical Reports Server (NTRS)

Green, Robert S.; Carson, George T., Jr.

1987-01-01

An investigation was conducted in the Langley 16-Foot Transonic Tunnel at static conditions to measure the pressure distributions inside a nonaxisymmetric nozzle with simultaneous partial thrust reversing (50-percent deployment) and thrust vectoring of the primary (forward-thrust) nozzle flow. Geometric forward-thrust-vector angles of 0 and 15 deg. were tested. Test data were obtained at static conditions while nozzle pressure ratio was varied from 2.0 to 4.0. Results indicate that, unlike the 0 deg. vector angle nozzle, a complicated, asymmetric exhaust flow pattern exists in the primary-flow exhaust duct of the 15 deg. vectored nozzle.

Molecular phylogeny of the Anopheles gambiae complex suggests genetic introgression between principal malaria vectors.

PubMed Central

Besansky, N J; Powell, J R; Caccone, A; Hamm, D M; Scott, J A; Collins, F H

1994-01-01

The six Afrotropical species of mosquitoes comprising the Anopheles gambiae complex include the most efficient vectors of malaria in the world as well as a nonvector species. The accepted interpretation of evolutionary relationships among these species is based on chromosomal inversions and suggests that the two principal vectors, A. gambiae and Anopheles arabiensis, are on distant branches of the phylogenetic tree. However, DNA sequence data indicate that these two species are sister taxa and suggest gene flow between them. These results have important implications for malaria control strategies involving the replacement of vector with nonvector populations. Images PMID:8041714

Method and system for efficiently searching an encoded vector index

DOEpatents

Bui, Thuan Quang; Egan, Randy Lynn; Kathmann, Kevin James

2001-09-04

Method and system aspects for efficiently searching an encoded vector index are provided. The aspects include the translation of a search query into a candidate bitmap, and the mapping of data from the candidate bitmap into a search result bitmap according to entry values in the encoded vector index. Further, the translation includes the setting of a bit in the candidate bitmap for each entry in a symbol table that corresponds to candidate of the search query. Also included in the mapping is the identification of a bit value in the candidate bitmap pointed to by an entry in an encoded vector.

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

PubMed

Bisenius, Sandrine; Mueller, Karsten; Diehl-Schmid, Janine; Fassbender, Klaus; Grimmer, Timo; Jessen, Frank; Kassubek, Jan; Kornhuber, Johannes; Landwehrmeyer, Bernhard; Ludolph, Albert; Schneider, Anja; Anderl-Straub, Sarah; Stuke, Katharina; Danek, Adrian; Otto, Markus; Schroeter, Matthias L

2017-01-01

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.

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.

Design Enhancements of the Two-Dimensional, Dual Throat Fluidic Thrust Vectoring Nozzle Concept

NASA Technical Reports Server (NTRS)

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

2006-01-01

A Dual Throat Nozzle fluidic thrust vectoring technique that achieves higher thrust-vectoring efficiencies than other fluidic techniques, without sacrificing thrust efficiency has been developed at NASA Langley Research Center. The nozzle concept was designed with the aid of the structured-grid, Reynolds-averaged Navier-Stokes computational fluidic dynamics code PAB3D. This new concept combines the thrust efficiency of sonic-plane skewing with increased thrust-vectoring efficiencies obtained by maximizing pressure differentials in a separated cavity located downstream of the nozzle throat. By injecting secondary flow asymmetrically at the upstream minimum area, a new aerodynamic minimum area is formed downstream of the geometric minimum and the sonic line is skewed, thus vectoring the exhaust flow. The nozzle was tested in the NASA Langley Research Center Jet Exit Test Facility. Internal nozzle performance characteristics were defined for nozzle pressure ratios up to 10, with a range of secondary injection flow rates up to 10 percent of the primary flow rate. Most of the data included in this paper shows the effect of secondary injection rate at a nozzle pressure ratio of 4. The effects of modifying cavity divergence angle, convergence angle and cavity shape on internal nozzle performance were investigated, as were effects of injection geometry, hole or slot. In agreement with computationally predicted data, experimental data verified that decreasing cavity divergence angle had a negative impact and increasing cavity convergence angle had a positive impact on thrust vector angle and thrust efficiency. A curved cavity apex provided improved thrust ratios at some injection rates. However, overall nozzle performance suffered with no secondary injection. Injection holes were more efficient than the injection slot over the range of injection rates, but the slot generated larger thrust vector angles for injection rates less than 4 percent of the primary flow rate.

Effective data compaction algorithm for vector scan EB writing system

NASA Astrophysics Data System (ADS)

Ueki, Shinichi; Ashida, Isao; Kawahira, Hiroichi

2001-01-01

We have developed a new mask data compaction algorithm dedicated to vector scan electron beam (EB) writing systems for 0.13 μm device generation. Large mask data size has become a significant problem at mask data processing for which data compaction is an important technique. In our new mask data compaction, 'array' representation and 'cell' representation are used. The mask data format for the EB writing system with vector scan supports these representations. The array representation has a pitch and a number of repetitions in both X and Y direction. The cell representation has a definition of figure group and its reference. The new data compaction method has the following three steps. (1) Search arrays of figures by selecting pitches of array so that a number of figures are included. (2) Find out same arrays that have same repetitive pitch and number of figures. (3) Search cells of figures, where the figures in each cell take identical positional relationship. By this new method for the mask data of a 4M-DRAM block gate layer with peripheral circuits, 202 Mbytes without compaction was highly compacted to 6.7 Mbytes in 20 minutes on a 500 MHz PC.

Development of a NEW Vector Magnetograph at Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

West, Edward; Hagyard, Mona; Gary, Allen; Smith, James; Adams, Mitzi; Rose, M. Franklin (Technical Monitor)

2001-01-01

This paper will describe the Experimental Vector Magnetograph that has been developed at the Marshall Space Flight Center (MSFC). This instrument was designed to improve linear polarization measurements by replacing electro-optic and rotating waveplate modulators with a rotating linear analyzer. Our paper will describe the motivation for developing this magnetograph, compare this instrument with traditional magnetograph designs, and present a comparison of the data acquired by this instrument and original MSFC vector magnetograph.

Compressing interpreted satellite imagery for geographic information systems applications over extensive regions

USGS Publications Warehouse

Miller, Stephan W.

1981-01-01

A second set of related problems deals with how this format and other representations of spatial entities, such as vector formats for point and line features, can be interrelated for manipulation, retrieval, and analysis by a spatial database management subsystem. Methods have been developed for interrelating areal data sets in the raster format with point and line data in a vector format and these are described.

Search for vector-like quark production in the lepton+jets and dilepton+jets final states using 5.4 fb -1 of Run II data

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

Caughron, Seth

2011-01-01

The Standard Model of particle physics provides an excellent description of particle interactions at energies up to ~1 TeV, but it is expected to fail above that scale. Multiple models developed to describe phenomena above the TeV scale predict the existence of very massive, vector-like quarks. A search for single electroweak production of such particles in pmore » $$\\bar{p}$$ collisions at a center-of-mass energy of 1.96 TeV is performed in the W+jets and Z+jets channels. The data were collected by the DØ detector at the Fermilab Tevatron Collider and correspond to an integrated luminosity of 5.4 fb -1. Events consistent with a heavy object decaying to a vector boson and a jet are selected. We observe no significant excess in comparison to the background prediction and set 95% confidence level upper limits on production cross sections for vector-like quarks decaying to W+jet and Z+jet. Assuming a vector-like quark -- standard model quark coupling parameter $$\\tilde{κ}$$ qQ of unity, we exclude vector-like quarks with mass below 693 GeV for decays to W+jet and mass below 449 GeV for decays to Z+jet. These represent the most sensitive limits to date.« less

Surveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement.

PubMed

Minuzzi-Souza, Thaís Tâmara Castro; Nitz, Nadjar; Cuba, César Augusto Cuba; Hagström, Luciana; Hecht, Mariana Machado; Santana, Camila; Ribeiro, Marcelle; Vital, Tamires Emanuele; Santalucia, Marcelo; Knox, Monique; Obara, Marcos Takashi; Abad-Franch, Fernando; Gurgel-Gonçalves, Rodrigo

2018-01-09

Vector-borne pathogens threaten human health worldwide. Despite their critical role in disease prevention, routine surveillance systems often rely on low-complexity pathogen detection tests of uncertain accuracy. In Chagas disease surveillance, optical microscopy (OM) is routinely used for detecting Trypanosoma cruzi in its vectors. Here, we use replicate T. cruzi detection data and hierarchical site-occupancy models to assess the reliability of OM-based T. cruzi surveillance while explicitly accounting for false-negative and false-positive results. We investigated 841 triatomines with OM slides (1194 fresh, 1192 Giemsa-stained) plus conventional (cPCR, 841 assays) and quantitative PCR (qPCR, 1682 assays). Detections were considered unambiguous only when parasitologists unmistakably identified T. cruzi in Giemsa-stained slides. qPCR was >99% sensitive and specific, whereas cPCR was ~100% specific but only ~55% sensitive. In routine surveillance, examination of a single OM slide per vector missed ~50-75% of infections and wrongly scored as infected ~7% of the bugs. qPCR-based and model-based infection frequency estimates were nearly three times higher, on average, than OM-based indices. We conclude that the risk of vector-borne Chagas disease may be substantially higher than routine surveillance data suggest. The hierarchical modelling approach we illustrate can help enhance vector-borne disease surveillance systems when pathogen detection is imperfect.

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.

Mapping Neglected Swimming Pools from Satellite Data for Urban Vector Control

NASA Astrophysics Data System (ADS)

Barker, C. M.; Melton, F. S.; Reisen, W. K.

2010-12-01

Neglected swimming pools provide suitable breeding habit for mosquitoes, can contain thousands of mosquito larvae, and present both a significant nuisance and public health risk due to their inherent proximity to urban and suburban populations. The rapid increase and sustained rate of foreclosures in California associated with the recent recession presents a challenge for vector control districts seeking to identify, treat, and monitor neglected pools. Commercial high resolution satellite imagery offers some promise for mapping potential neglected pools, and for mapping pools for which routine maintenance has been reestablished. We present progress on unsupervised classification techniques for mapping both neglected pools and clean pools using high resolution commercial satellite data and discuss the potential uses and limitations of this data source in support of vector control efforts. An unsupervised classification scheme that utilizes image segmentation, band thresholds, and a change detection approach was implemented for sample regions in Coachella Valley, CA and the greater Los Angeles area. Comparison with field data collected by vector control personal was used to assess the accuracy of the estimates. The results suggest that the current system may provide some utility for early detection, or cost effective and time efficient annual monitoring, but additional work is required to address spectral and spatial limitations of current commercial satellite sensors for this purpose.

Intercomparison of Registration Techniques and Interactive 3D Visualization of Differential LiDAR from the 2010 El Mayor-Cucapah Earthquake

NASA Astrophysics Data System (ADS)

Banesh, D.; Oskin, M. E.; Mu, A.; Vu, C.; Westerteiger, R.; Krishnan, A.; Hamann, B.; Glennie, C. L.; Hinojosa, A.; Borsa, A. A.

2013-12-01

Differential LiDAR provides unprecedented images of the near-field ground deformation and fault slip due to earthquakes. Here we examine the performance of the Iterative Closest Point (ICP) technique for data registration between pre- and post-earthquake LiDAR point clouds of varying density. We use the 2010 El Mayor-Cucapah data set as our region of interest since this earthquake produced different types of surface ruptures, yielding a variety of deformation styles for analysis. We also test a more simplistic, Chi-Squared minimization approach and find that it produces good results when compared to ICP. We present different techniques for visualizing large vector fields, and show how each method highlights a unique feature in the data set. Dense vector fields are useful when analyzing smaller deformations in the surface. A sparse, averaged vector field analyzes the bigger, overall shifts without interference caused by small details. Flow-based visualizations like Line Integral Convolution (LIC) graphs, provide insight into particular artifacts of data collection, such as distortions due to uncorrected pitch and yaw of the aircraft during the survey. Animations of the vector field establish the direction of movement in the landscape, quickly highlighting areas of interest.

MISR Level 3 Cloud Motion Vector

Atmospheric Science Data Center

2013-07-10

... 2012 A new version, F02_0002, of the MISR L3 CMV (Cloud Motion Vector) data product is now available. This new release ... CMV products for the full mission time period of March 2000 - September 2012 are now available for ordering.   Information ...

Extreme Weather Events and Impacts on Vector-borne Diseases and Agriculture

USDA-ARS?s Scientific Manuscript database

Extreme weather events during the period 2010-2012 impacted agriculture and vector-borne disease throughout the world. We evaluated specific weather events with satellite remotely sensed environmental data and evaluated crop production and diseases associated with these events. Significant droughts ...

The effectiveness of problem-based learning on students’ problem solving ability in vector analysis course

NASA Astrophysics Data System (ADS)

Mushlihuddin, R.; Nurafifah; Irvan

2018-01-01

The student’s low ability in mathematics problem solving proved to the less effective of a learning process in the classroom. Effective learning was a learning that affects student’s math skills, one of which is problem-solving abilities. Problem-solving capability consisted of several stages: understanding the problem, planning the settlement, solving the problem as planned, re-examining the procedure and the outcome. The purpose of this research was to know: (1) was there any influence of PBL model in improving ability Problem solving of student math in a subject of vector analysis?; (2) was the PBL model effective in improving students’ mathematical problem-solving skills in vector analysis courses? This research was a quasi-experiment research. The data analysis techniques performed from the test stages of data description, a prerequisite test is the normality test, and hypothesis test using the ANCOVA test and Gain test. The results showed that: (1) there was an influence of PBL model in improving students’ math problem-solving abilities in vector analysis courses; (2) the PBL model was effective in improving students’ problem-solving skills in vector analysis courses with a medium category.

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. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Burns, D.; Sanchez, M. Calderon De La Barca; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Shirazi, S. M. A. Ghiasi; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Negrete, M. Olmedo; Paneva, M. I.; Shrinivas, A.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Macneill, I.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Della Porta, G. Zevi; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Sevilla, M. Franco; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. 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.

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.

Breathing motion compensated reconstruction for C-arm cone beam CT imaging: initial experience based on animal data

NASA Astrophysics Data System (ADS)

Schäfer, D.; Lin, M.; Rao, P. P.; Loffroy, R.; Liapi, E.; Noordhoek, N.; Eshuis, P.; Radaelli, A.; Grass, M.; Geschwind, J.-F. H.

2012-03-01

C-arm based tomographic 3D imaging is applied in an increasing number of minimal invasive procedures. Due to the limited acquisition speed for a complete projection data set required for tomographic reconstruction, breathing motion is a potential source of artifacts. This is the case for patients who cannot comply breathing commands (e.g. due to anesthesia). Intra-scan motion estimation and compensation is required. Here, a scheme for projection based local breathing motion estimation is combined with an anatomy adapted interpolation strategy and subsequent motion compensated filtered back projection. The breathing motion vector is measured as a displacement vector on the projections of a tomographic short scan acquisition using the diaphragm as a landmark. Scaling of the displacement to the acquisition iso-center and anatomy adapted volumetric motion vector field interpolation delivers a 3D motion vector per voxel. Motion compensated filtered back projection incorporates this motion vector field in the image reconstruction process. This approach is applied in animal experiments on a flat panel C-arm system delivering improved image quality (lower artifact levels, improved tumor delineation) in 3D liver tumor imaging.

Bayesian anomaly detection in monitoring data applying relevance vector machine

NASA Astrophysics Data System (ADS)

Saito, Tomoo

2011-04-01

A method for automatically classifying the monitoring data into two categories, normal and anomaly, is developed in order to remove anomalous data included in the enormous amount of monitoring data, applying the relevance vector machine (RVM) to a probabilistic discriminative model with basis functions and their weight parameters whose posterior PDF (probabilistic density function) conditional on the learning data set is given by Bayes' theorem. The proposed framework is applied to actual monitoring data sets containing some anomalous data collected at two buildings in Tokyo, Japan, which shows that the trained models discriminate anomalous data from normal data very clearly, giving high probabilities of being normal to normal data and low probabilities of being normal to anomalous data.

A multi-label learning based kernel automatic recommendation method for support vector machine.

PubMed

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

PubMed Central

Zhang, Xueying; Song, Qinbao

2015-01-01

Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance. PMID:25893896

[Climate change - a pioneer for the expansion of canine vector-borne diseases?].

PubMed

Krämer, F; Mencke, N

2011-01-01

Vector-transmitted diseases are one of the major contributors to the global burden of disease in humans and animals. Climate change is consistently held responsible for the spread of parasitic acarid and insect vectors such as ticks, fleas, sand flies and mosquitoes, and their transmitted pathogens (in the case of the dog the so-called canine vector-borne diseases [CVBD]). Currently, there is only insufficient data available to prove whether climate change is a major driving force for vector and disease expansion, but the evidence is growing. Other reasons, such as ecological, demographic and socio-economic factors, e.g. pet travel into and pet import from endemic areas, also play a role in this development. Apart from all the controversial discussion of the factors leading to vector and disease expansion, preventative measures should include dog owners' education as they are responsible for individual parasite protection as well as for the minimisation of adverse risk behaviour, e.g. regarding pet travel. Broad-spectrum vector control should be practised by using parasiticides that repel and kill blood feeders in order to minimize the risk of CVBD-pathogen transmission.

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

DOE PAGES

Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; ...

2015-05-22

The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The modelmore » has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. Lastly, this work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.« less

Orthonormal vector polynomials in a unit circle, Part I: Basis set derived from gradients of Zernike polynomials.

PubMed

Zhao, Chunyu; Burge, James H

2007-12-24

Zernike polynomials provide a well known, orthogonal set of scalar functions over a circular domain, and are commonly used to represent wavefront phase or surface irregularity. A related set of orthogonal functions is given here which represent vector quantities, such as mapping distortion or wavefront gradient. These functions are generated from gradients of Zernike polynomials, made orthonormal using the Gram- Schmidt technique. This set provides a complete basis for representing vector fields that can be defined as a gradient of some scalar function. It is then efficient to transform from the coefficients of the vector functions to the scalar Zernike polynomials that represent the function whose gradient was fit. These new vector functions have immediate application for fitting data from a Shack-Hartmann wavefront sensor or for fitting mapping distortion for optical testing. A subsequent paper gives an additional set of vector functions consisting only of rotational terms with zero divergence. The two sets together provide a complete basis that can represent all vector distributions in a circular domain.

How random is a random vector?

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2015-12-01

Over 80 years ago Samuel Wilks proposed that the "generalized variance" of a random vector is the determinant of its covariance matrix. To date, the notion and use of the generalized variance is confined only to very specific niches in statistics. In this paper we establish that the "Wilks standard deviation" -the square root of the generalized variance-is indeed the standard deviation of a random vector. We further establish that the "uncorrelation index" -a derivative of the Wilks standard deviation-is a measure of the overall correlation between the components of a random vector. Both the Wilks standard deviation and the uncorrelation index are, respectively, special cases of two general notions that we introduce: "randomness measures" and "independence indices" of random vectors. In turn, these general notions give rise to "randomness diagrams"-tangible planar visualizations that answer the question: How random is a random vector? The notion of "independence indices" yields a novel measure of correlation for Lévy laws. In general, the concepts and results presented in this paper are applicable to any field of science and engineering with random-vectors empirical data.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Wavefront analysis from its slope data

NASA Astrophysics Data System (ADS)

Mahajan, Virendra N.; Acosta, Eva

2017-08-01

In the aberration analysis of a wavefront over a certain domain, the polynomials that are orthogonal over and represent balanced wave aberrations for this domain are used. For example, Zernike circle polynomials are used for the analysis of a circular wavefront. Similarly, the annular polynomials are used to analyze the annular wavefronts for systems with annular pupils, as in a rotationally symmetric two-mirror system, such as the Hubble space telescope. However, when the data available for analysis are the slopes of a wavefront, as, for example, in a Shack- Hartmann sensor, we can integrate the slope data to obtain the wavefront data, and then use the orthogonal polynomials to obtain the aberration coefficients. An alternative is to find vector functions that are orthogonal to the gradients of the wavefront polynomials, and obtain the aberration coefficients directly as the inner products of these functions with the slope data. In this paper, we show that an infinite number of vector functions can be obtained in this manner. We show further that the vector functions that are irrotational are unique and propagate minimum uncorrelated additive random noise from the slope data to the aberration coefficients.

Modelling strategies to break transmission of lymphatic filariasis--aggregation, adherence and vector competence greatly alter elimination.

PubMed

Irvine, M A; Reimer, L J; Njenga, S M; Gunawardena, S; Kelly-Hope, L; Bockarie, M; Hollingsworth, T D

2015-10-22

With ambitious targets to eliminate lymphatic filariasis over the coming years, there is a need to identify optimal strategies to achieve them in areas with different baseline prevalence and stages of control. Modelling can assist in identifying what data should be collected and what strategies are best for which scenarios. We develop a new individual-based, stochastic mathematical model of the transmission of lymphatic filariasis. We validate the model by fitting to a first time point and predicting future timepoints from surveillance data in Kenya and Sri Lanka, which have different vectors and different stages of the control programme. We then simulate different treatment scenarios in low, medium and high transmission settings, comparing once yearly mass drug administration (MDA) with more frequent MDA and higher coverage. We investigate the potential impact that vector control, systematic non-compliance and different levels of aggregation have on the dynamics of transmission and control. In all settings, increasing coverage from 65 to 80 % has a similar impact on control to treating twice a year at 65 % coverage, for fewer drug treatments being distributed. Vector control has a large impact, even at moderate levels. The extent of aggregation of parasite loads amongst a small portion of the population, which has been estimated to be highly variable in different settings, can undermine the success of a programme, particularly if high risk sub-communities are not accessing interventions. Even moderate levels of vector control have a large impact both on the reduction in prevalence and the maintenance of gains made during MDA, even when parasite loads are highly aggregated, and use of vector control is at moderate levels. For the same prevalence, differences in aggregation and adherence can result in very different dynamics. The novel analysis of a small amount of surveillance data and resulting simulations highlight the need for more individual level data to be analysed to effectively tailor programmes in the drive for elimination.

Meta-analyses of the proportion of Japanese encephalitis virus infection in vectors and vertebrate hosts.

PubMed

Oliveira, Ana R S; Cohnstaedt, Lee W; Strathe, Erin; Hernández, Luciana Etcheverry; McVey, D Scott; Piaggio, José; Cernicchiaro, Natalia

2017-09-07

Japanese encephalitis (JE) is a zoonosis in Southeast Asia vectored by mosquitoes infected with the Japanese encephalitis virus (JEV). Japanese encephalitis is considered an emerging exotic infectious disease with potential for introduction in currently JEV-free countries. Pigs and ardeid birds are reservoir hosts and play a major role on the transmission dynamics of the disease. The objective of the study was to quantitatively summarize the proportion of JEV infection in vectors and vertebrate hosts from data pertaining to observational studies obtained in a systematic review of the literature on vector and host competence for JEV, using meta-analyses. Data gathered in this study pertained to three outcomes: proportion of JEV infection in vectors, proportion of JEV infection in vertebrate hosts, and minimum infection rate (MIR) in vectors. Random-effects subgroup meta-analysis models were fitted by species (mosquito or vertebrate host species) to estimate pooled summary measures, as well as to compute the variance between studies. Meta-regression models were fitted to assess the association between different predictors and the outcomes of interest and to identify sources of heterogeneity among studies. Predictors included in all models were mosquito/vertebrate host species, diagnostic methods, mosquito capture methods, season, country/region, age category, and number of mosquitos per pool. Mosquito species, diagnostic method, country, and capture method represented important sources of heterogeneity associated with the proportion of JEV infection; host species and region were considered sources of heterogeneity associated with the proportion of JEV infection in hosts; and diagnostic and mosquito capture methods were deemed important contributors of heterogeneity for the MIR outcome. Our findings provide reference pooled summary estimates of vector competence for JEV for some mosquito species, as well as of sources of variability for these outcomes. Moreover, this work provides useful guidelines when interpreting vector and host infection proportions or prevalence from observational studies, and contributes to further our understanding of vector and vertebrate host competence for JEV, elucidating information on the relative importance of vectors and hosts on JEV introduction and transmission.

Internal and external potential-field estimation from regional vector data at varying satellite altitude

NASA Astrophysics Data System (ADS)

Plattner, Alain; Simons, Frederik J.

2017-10-01

When modelling satellite data to recover a global planetary magnetic or gravitational potential field, the method of choice remains their analysis in terms of spherical harmonics. When only regional data are available, or when data quality varies strongly with geographic location, the inversion problem becomes severely ill-posed. In those cases, adopting explicitly local methods is to be preferred over adapting global ones (e.g. by regularization). Here, we develop the theory behind a procedure to invert for planetary potential fields from vector observations collected within a spatially bounded region at varying satellite altitude. Our method relies on the construction of spatiospectrally localized bases of functions that mitigate the noise amplification caused by downward continuation (from the satellite altitude to the source) while balancing the conflicting demands for spatial concentration and spectral limitation. The `altitude-cognizant' gradient vector Slepian functions (AC-GVSF) enjoy a noise tolerance under downward continuation that is much improved relative to the `classical' gradient vector Slepian functions (CL-GVSF), which do not factor satellite altitude into their construction. Furthermore, venturing beyond the realm of their first application, published in a preceding paper, in the present article we extend the theory to being able to handle both internal and external potential-field estimation. Solving simultaneously for internal and external fields under the limitation of regional data availability reduces internal-field artefacts introduced by downward-continuing unmodelled external fields, as we show with numerical examples. We explain our solution strategies on the basis of analytic expressions for the behaviour of the estimation bias and variance of models for which signal and noise are uncorrelated, (essentially) space- and band-limited, and spectrally (almost) white. The AC-GVSF are optimal linear combinations of vector spherical harmonics. Their construction is not altogether very computationally demanding when the concentration domains (the regions of spatial concentration) have circular symmetry, for example, on spherical caps or rings—even when the spherical-harmonic bandwidth is large. Data inversion proceeds by solving for the expansion coefficients of truncated function sequences, by least-squares analysis in a reduced-dimensional space. Hence, our method brings high-resolution regional potential-field modelling from incomplete and noisy vector-valued satellite data within reach of contemporary desktop machines.

A generic model for a single strain mosquito-transmitted disease with memory on the host and the vector.

PubMed

Sardar, Tridip; Rana, Sourav; Bhattacharya, Sabyasachi; Al-Khaled, Kamel; Chattopadhyay, Joydev

2015-05-01

In the present investigation, three mathematical models on a common single strain mosquito-transmitted diseases are considered. The first one is based on ordinary differential equations, and other two models are based on fractional order differential equations. The proposed models are validated using published monthly dengue incidence data from two provinces of Venezuela during the period 1999-2002. We estimate several parameters of these models like the order of the fractional derivatives (in case of two fractional order systems), the biting rate of mosquito, two probabilities of infection, mosquito recruitment and mortality rates, etc., from the data. The basic reproduction number, R0, for the ODE system is estimated using the data. For two fractional order systems, an upper bound for, R0, is derived and its value is obtained using the published data. The force of infection, and the effective reproduction number, R(t), for the three models are estimated using the data. Sensitivity analysis of the mosquito memory parameter with some important responses is worked out. We use Akaike Information Criterion (AIC) to identify the best model among the three proposed models. It is observed that the model with memory in both the host, and the vector population provides a better agreement with epidemic data. Finally, we provide a control strategy for the vector-borne disease, dengue, using the memory of the host, and the vector. Copyright © 2015 Elsevier Inc. All rights reserved.

Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains

NASA Astrophysics Data System (ADS)

Koulouri, Alexandra; Brookes, Mike; Rimpiläinen, Ville

2017-01-01

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In this paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field.

Stability of Lentiviral Vector-Mediated Transgene Expression in the Brain in the Presence of Systemic Antivector Immune Responses

PubMed Central

ABORDO-ADESIDA, EVELYN; FOLLENZI, ANTONIA; BARCIA, CARLOS; SCIASCIA, SANDRA; CASTRO, MARIA G.; NALDINI, LUIGI; LOWENSTEIN, PEDRO R.

2009-01-01

Lentiviral vectors are promising tools for gene therapy in the CNS. It is therefore important to characterize their interactions with the immune system in the CNS. This work characterizes transgene expression and brain inflammation in the presence or absence of immune responses generated after systemic immunization with lentiviral vectors. We characterized transduction with SIN-LV vectors in the CNS. A dose—response curve using SIN-LV-GFP demonstrated detectable transgene expression in the striatum at a dose of 102, and maximum expression at 106, transducing units of lentiviral vector, with minimal increase in inflammatory markers between the lowest and highest dose of vector injected. Our studies demonstrate that injection of a lentiviral vector into the CNS did not cause a measurable inflammatory response. Systemic immunization after CNS injection, with the lentiviral vector expressing the same transgene as a vector injected into the CNS, caused a decrease in transgene expression in the CNS, concomitantly with an infiltration of inflammatory cells into the CNS parenchyma at the injection site. However, peripheral immunization with a lentiviral vector carrying a different transgene did not diminish transgene expression, or cause CNS inflammation. Systemic immunization preceding injection of lentiviral vectors into the CNS determined that preexisting antilentiviral immunity, regardless of the transgene, did not affect transgene expression. Furthermore, we showed that the transgene, but not the virion or vector components, is responsible for providing antigenic epitopes to the activated immune system, on systemic immunization with lentivirus. Low immunogenicity and prolonged transgene expression in the presence of preexisting lentiviral immunity are encouraging data for the future use of lentiviral vectors in CNS gene therapy. In summary, the lentiviral vectors tested induced undetectable activation of innate immune responses, and stimulation of adaptive immune responses against lentiviral vectors was effective in causing a decrease in transgene expression only if the immune response was directed against the transgene. A systemic immune response against vector components alone did not cause brain inflammation, possibly because vector-derived epitopes were not being presented in the CNS. PMID:15960605

CanSIS Regional Soils Data in Vector Format

NASA Technical Reports Server (NTRS)

Monette, Bryan; Knapp, David; Hall, Forrest G. (Editor)

2000-01-01

This data set is the original vector data set received from Canada Soil Information System (CanSIS). The data include the provinces of Saskatchewan and Manitoba. Attribute tables provide the various soil data for the polygons; there is one attribute table for Saskatchewan and one for Manitoba. The data are stored in ARC/INFO export format files. Based on agreements made with Agriculture Canada, these data are available only to individuals and groups that have an official relationship with the BOREAS project. These data are not included on the BOReal Ecosystem-Atmosphere Study (BOREAS) CD-ROM set. A raster version of this data set titled 'BOREAS Regional Soils Data in Raster Format and AEAC Projection' is publicly available and is included on the BOREAS CD-ROM set.

Naive Bayes Bearing Fault Diagnosis Based on Enhanced Independence of Data

PubMed Central

Zhang, Nannan; Wu, Lifeng; Yang, Jing; Guan, Yong

2018-01-01

The bearing is the key component of rotating machinery, and its performance directly determines the reliability and safety of the system. Data-based bearing fault diagnosis has become a research hotspot. Naive Bayes (NB), which is based on independent presumption, is widely used in fault diagnosis. However, the bearing data are not completely independent, which reduces the performance of NB algorithms. In order to solve this problem, we propose a NB bearing fault diagnosis method based on enhanced independence of data. The method deals with data vector from two aspects: the attribute feature and the sample dimension. After processing, the classification limitation of NB is reduced by the independence hypothesis. First, we extract the statistical characteristics of the original signal of the bearings effectively. Then, the Decision Tree algorithm is used to select the important features of the time domain signal, and the low correlation features is selected. Next, the Selective Support Vector Machine (SSVM) is used to prune the dimension data and remove redundant vectors. Finally, we use NB to diagnose the fault with the low correlation data. The experimental results show that the independent enhancement of data is effective for bearing fault diagnosis. PMID:29401730

Combining Vector Quantization and Histogram Equalization.

ERIC Educational Resources Information Center

Cosman, Pamela C.; And Others

1992-01-01

Discussion of contrast enhancement techniques focuses on the use of histogram equalization with a data compression technique, i.e., tree-structured vector quantization. The enhancement technique of intensity windowing is described, and the use of enhancement techniques for medical images is explained, including adaptive histogram equalization.…

Recent weather extremes and impact agricultural production and vector-borne disease patterns

USDA-ARS?s Scientific Manuscript database

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA’s satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to ...

Stable Local Volatility Calibration Using Kernel Splines

NASA Astrophysics Data System (ADS)

Coleman, Thomas F.; Li, Yuying; Wang, Cheng

2010-09-01

We propose an optimization formulation using L1 norm to ensure accuracy and stability in calibrating a local volatility function for option pricing. Using a regularization parameter, the proposed objective function balances the calibration accuracy with the model complexity. Motivated by the support vector machine learning, the unknown local volatility function is represented by a kernel function generating splines and the model complexity is controlled by minimizing the 1-norm of the kernel coefficient vector. In the context of the support vector regression for function estimation based on a finite set of observations, this corresponds to minimizing the number of support vectors for predictability. We illustrate the ability of the proposed approach to reconstruct the local volatility function in a synthetic market. In addition, based on S&P 500 market index option data, we demonstrate that the calibrated local volatility surface is simple and resembles the observed implied volatility surface in shape. Stability is illustrated by calibrating local volatility functions using market option data from different dates.

Index formulas for higher order Loewner vector fields

NASA Astrophysics Data System (ADS)

Broad, Steven

Let ∂ be the Cauchy-Riemann operator and f be a C real-valued function in a neighborhood of 0 in R in which ∂z¯nf≠0 for all z≠0. In such cases, ∂z¯nf is known as a Loewner vector field due to its connection with Loewner's conjecture that the index of such a vector field is bounded above by n. The n=2 case of Loewner's conjecture implies Carathéodory's conjecture that any C-immersion of S into R must have at least two umbilics. Recent work of F. Xavier produced a formula for computing the index of Loewner vector fields when n=2 using data about the Hessian of f. In this paper, we extend this result and establish an index formula for ∂z¯nf for all n⩾2. Structurally, our index formula provides a defect term, which contains geometric data extracted from Hessian-like objects associated with higher order derivatives of f.

Motion direction estimation based on active RFID with changing environment

NASA Astrophysics Data System (ADS)

Jie, Wu; Minghua, Zhu; Wei, He

2018-05-01

The gate system is used to estimate the direction of RFID tags carriers when they are going through the gate. Normally, it is difficult to achieve and keep a high accuracy in estimating motion direction of RFID tags because the received signal strength of tag changes sharply according to the changing electromagnetic environment. In this paper, a method of motion direction estimation for RFID tags is presented. To improve estimation accuracy, the machine leaning algorithm is used to get the fitting function of the received data by readers which are deployed inside and outside gate respectively. Then the fitted data are sampled to get the standard vector. We compare the stand vector with template vectors to get the motion direction estimation result. Then the corresponding template vector is updated according to the surrounding environment. We conducted the simulation and implement of the proposed method and the result shows that the proposed method in this work can improve and keep a high accuracy under the condition of the constantly changing environment.

Cubic-panorama image dataset analysis for storage and transmission

NASA Astrophysics Data System (ADS)

Salehi, Saeed; Dubois, Eric

2013-02-01

In this paper we address the problem of disparity estimation required for free navigation in acquired cubicpanorama image datasets. A client server based scheme is assumed and a remote user is assumed to seek information at each navigation step. The initial compression of such image datasets for storage as well as the transmission of the required data is addressed in this work. Regarding the compression of such data for storage, a fast method that uses properties of the epipolar geometry together with the cubic format of panoramas is used to estimate disparity vectors efficiently. Assuming the use of B pictures, the concept of forward and backward prediction is addressed. Regarding the transmission stage, a new disparity vector transcoding-like scheme is introduced and a frame conversion scenario is addressed. Details on how to pick the best vector among candidate disparity vectors is explained. In all the above mentioned cases, results are compared both visually through error images as well as using the objective measure of Peak Signal to Noise Ratio (PSNR) versus time.

Study of the modifications needed for efficient operation of NASTRAN on the Control Data Corporation STAR-100 computer

NASA Technical Reports Server (NTRS)

1975-01-01

NASA structural analysis (NASTRAN) computer program is operational on three series of third generation computers. The problem and difficulties involved in adapting NASTRAN to a fourth generation computer, namely, the Control Data STAR-100, are discussed. The salient features which distinguish Control Data STAR-100 from third generation computers are hardware vector processing capability and virtual memory. A feasible method is presented for transferring NASTRAN to Control Data STAR-100 system while retaining much of the machine-independent code. Basic matrix operations are noted for optimization for vector processing.

BOREAS TE-1 Soils Data Over The SSA Tower Sites in Raster Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Anderson, Darwin; Knapp, David E.

2000-01-01

The BOREAS TE-1 team collected various data to characterize the soil-plant systems in the BOREAS SSA. This data set was gridded from vector layers of soil maps that were received from Dr. Darwin Anderson (TE-1), who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the tower sites in the SSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Efficient Kriging via Fast Matrix-Vector Products

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Raykar, Vikas C.; Duraiswami, Ramani; Mount, David M.

2008-01-01

Interpolating scattered data points is a problem of wide ranging interest. Ordinary kriging is an optimal scattered data estimator, widely used in geosciences and remote sensing. A generalized version of this technique, called cokriging, can be used for image fusion of remotely sensed data. However, it is computationally very expensive for large data sets. We demonstrate the time efficiency and accuracy of approximating ordinary kriging through the use of fast matrixvector products combined with iterative methods. We used methods based on the fast Multipole methods and nearest neighbor searching techniques for implementations of the fast matrix-vector products.

Development of a 300°C 3C Fiber Optic Downhole Seismic Receiver Array for Surveying and Monitoring of Geothermal Reservoirs

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

Paulsson, Bjorn N.P.

2016-06-29

To address the critical site characterization and monitoring needs for Enhance Geothermal Systems (EGS) programs, US Department of Energy (DOE) awarded Paulsson, Inc. in 2011 a contract to design, build and test a high temperature fiber optic based ultra-large bandwidth clamped borehole seismic vector array capable of deploying a large number of 3C sensor pods suitable for deployment into high temperature and high pressure boreholes. Paulsson, Inc. has completed a design or a unique borehole seismic system consisting of a novel drill pipe based deployment system that includes a hydraulic clamping mechanism for the sensor pods, a new sensor podmore » design and most important – a unique fiber optic seismic vector sensor with technical specifications and capabilities that far exceed the state of the art seismic sensor technologies. These novel technologies were all applied to the new borehole seismic system. In combination these technologies will allow for the deployment of up to 1,000 3C sensor pods in vertical, deviated or horizontal wells. Laboratory tests of the fiber optic seismic vector sensors developed during this project have shown that the new borehole seismic sensor technology is capable of generating outstanding high vector fidelity data with extremely large bandwidth: 0.01 – 6,000 Hz. Field tests have shown that the system can record events at magnitudes much smaller than M-4.0 at frequencies over 2,000 Hz. The sensors have also proved to be about 100 times more sensitive than the regular coil geophones that are used in borehole seismic systems today. The fiber optic seismic sensors have furthermore been qualified to operate at temperatures over 300°C (572°F). The data telemetry fibers used for the seismic vector sensors in the system are also used to simultaneously record Distributed Temperature Sensor (DTS) and Distributed Acoustic Sensor (DAS) data allowing additional value added data to be recorded simultaneously with the seismic vector sensor data.« less

Principle component analysis to separate deformation signals from multiple sources during a 2015 intrusive sequence at Kīlauea Volcano

NASA Astrophysics Data System (ADS)

Johanson, I. A.; Miklius, A.; Poland, M. P.

2016-12-01

A sequence of magmatic events in April-May 2015 at Kīlauea Volcano produced a complex deformation pattern that can be described by multiple deforming sources, active simultaneously. The 2015 intrusive sequence began with inflation in the volcano's summit caldera near Halema`uma`u (HMM) Crater, which continued over a few weeks, followed by rapid deflation of the HMM source and inflation of a source in the south caldera region during the next few days. In Kīlauea Volcano's summit area, multiple deformation centers are active at varying times, and all contribute to the overall pattern observed with GPS, tiltmeters, and InSAR. Isolating the contribution of different signals related to each source is a challenge and complicates the determination of optimal source geometry for the underlying magma bodies. We used principle component analysis of continuous GPS time series from the 2015 intrusion sequence to determine three basis vectors which together account for 83% of the variance in the data set. The three basis vectors are non-orthogonal and not strictly the principle components of the data set. In addition to separating deformation sources in the continuous GPS data, the basis vectors provide a means to scale the contribution of each source in a given interferogram. This provides an additional constraint in a joint model of GPS and InSAR data (COSMO-SkyMed and Sentinel-1A) to determine source geometry. The first basis vector corresponds with inflation in the south caldera region, an area long recognized as the location of a long-term storage reservoir. The second vector represents deformation of the HMM source, which is in the same location as a previously modeled shallow reservoir, however InSAR data suggest a more complicated source. Preliminary modeling of the deformation attributed to the third basis vector shows that it is consistent with inflation of a steeply dipping ellipsoid centered below Keanakāko`i crater, southeast of HMM. Keanakāko`i crater is the locus of a known, intermittently active deformation source, which was not previously recognized to have been active during the 2015 event.

Geospatial Analysis and Seasonal Distribution of West Nile Virus Vectors (Diptera: Culicidae) in Southern Ontario, Canada

PubMed Central

Turner, Kevin W.; Hunter, Fiona F.

2018-01-01

The purpose of this study was to establish geospatial and seasonal distributions of West Nile virus vectors in southern Ontario, Canada using historical surveillance data from 2002 to 2014. We set out to produce mosquito abundance prediction surfaces for each of Ontario’s thirteen West Nile virus vectors. We also set out to determine whether elevation and proximity to conservation areas and provincial parks, wetlands, and population centres could be used to improve our model. Our results indicated that the data sets for Anopheles quadrimaculatus, Anopheles punctipennis, Anopheles walkeri, Culex salinarius, Culex tarsalis, Ochlerotatus stimulans, and Ochlerotatus triseriatus were not suitable for geospatial modelling because they are randomly distributed throughout Ontario. Spatial prediction surfaces were created for Aedes japonicus and proximity to wetlands, Aedes vexans and proximity to population centres, Culex pipiens/restuans and proximity to population centres, Ochlerotatus canadensis and elevation, and Ochlerotatus trivittatus and proximity to population centres using kriging. Seasonal distributions are presented for all thirteen species. We have identified both when and where vector species are most abundant in southern Ontario. These data have the potential to contribute to a more efficient and focused larvicide program and West Nile virus awareness campaigns. PMID:29597256

Comparing WSA coronal and solar wind model predictions driven by line-of-sight and vector HMI ADAPT maps

NASA Astrophysics Data System (ADS)

Arge, C. N.; Henney, C. J.; Shurkin, K.; Wallace, S.

2017-12-01

As the primary input to nearly all coronal models, reliable estimates of the global solar photospheric magnetic field distribution are critical for accurate modeling and understanding of solar and heliospheric magnetic fields. The Air Force Data Assimilative Photospheric flux Transport (ADAPT) model generates synchronic (i.e., globally instantaneous) maps by evolving observed solar magnetic flux using relatively well understood transport processes when measurements are not available and then updating modeled flux with new observations (available from both the Earth and the far-side of the Sun) using data assimilation methods that rigorously take into account model and observational uncertainties. ADAPT is capable of assimilating line-of-sight and vector magnetic field data from all observatory sources including the expected photospheric vector magnetograms from the Polarimetric and Helioseismic Imager (PHI) on the Solar Orbiter, as well as those generated using helioseismic methods. This paper compares Wang-Sheeley-Arge (WSA) coronal and solar wind modeling results at Earth and STEREO A & B using ADAPT input model maps derived from both line-of-site and vector SDO/HMI magnetograms that include methods for incorporating observations of a large, newly emerged (July 2010) far-side active region (AR11087).

Insecticide resistance in Bemisia tabaci Gennadius (Homoptera: Aleyrodidae) and Anopheles gambiae Giles (Diptera: Culicidae) could compromise the sustainability of malaria vector control strategies in West Africa.

PubMed

Gnankiné, Olivier; Bassolé, Imael H N; Chandre, Fabrice; Glitho, Isabelle; Akogbeto, Martin; Dabiré, Roch K; Martin, Thibaud

2013-10-01

Insecticides from the organophosphate (OP) and pyrethroid (PY) chemical families, have respectively, been in use for 50 and 30 years in West Africa, mainly against agricultural pests, but also against vectors of human disease. The selection pressure, with practically the same molecules year after year (mainly on cotton), has caused insecticide resistance in pest populations such as Bemisia tabaci, vector of harmful phytoviruses on vegetables. The evolution toward insecticide resistance in malaria vectors such as Anopheles gambiae sensus lato (s.l.) is probably related to the current use of these insecticides in agriculture. Thus, successful pest and vector control in West Africa requires an investigation of insect susceptibility, in relation to the identification of species and sub species, such as molecular forms or biotypes. Identification of knock down resistance (kdr) and acetylcholinesterase gene (Ace1) mutations modifying insecticide targets in individual insects and measure of enzymes activity typically involved in insecticide metabolism (oxidase, esterase and glutathion-S-transferase) are indispensable in understanding the mechanisms of resistance. Insecticide resistance is a good example in which genotype-phenotype links have been made successfully. Insecticides used in agriculture continue to select new resistant populations of B. tabaci that could be from different biotype vectors of plant viruses. As well, the evolution of insecticide resistance in An. gambiae threatens the management of malaria vectors in West Africa. It raises the question of priority in the use of insecticides in health and/or agriculture, and more generally, the question of sustainability of crop protection and vector control strategies in the region. Here, we review the susceptibility tests, biochemical and molecular assays data for B. tabaci, a major pest in cotton and vegetable crops, and An. gambiae, main vector of malaria. The data reviewed was collected in Benin and Burkina Faso between 2008 and 2010 under the Corus 6015 research program. This review aims to show: (i) the insecticide resistance in B. tabaci as well as in An. gambiae; and (ii) due to this, the impact of selection of resistant populations on malaria vector control strategies. Some measures that could be beneficial for crop protection and vector control strategies in West Africa are proposed. Copyright © 2013 Elsevier B.V. All rights reserved.

A vector autopilot system. [aircraft attitude determination with three-axis magnetometer

NASA Technical Reports Server (NTRS)

Pietila, R.; Dunn, W. R., Jr.

1976-01-01

Current technology has evolved low cost, highly reliable solid state vector magnetometers with excellent angular resolution. This paper discusses the role of a three-axis magnetometer as a new instrument for aircraft attitude determination. Using flight data acquired by an instrumented aircraft, attitude is calculated using the earth's magnetic field vector and compared to measured attitudes. The magnetic field alone is not adequate to resolve all attitude variations and the need for a second reference angle or vector is discussed. A system combining the functions of heading determination and attitude measurement is presented to show that both functions can be implemented with essentially the same component count required to measure heading alone. It is concluded that with the correlation achieved in calculated and measured attitude there is a potential application of vector magnetometry in attitude measurement systems.

Challenging assumptions of notational transparency: the case of vectors in engineering mathematics

NASA Astrophysics Data System (ADS)

Craig, Tracy S.

2017-11-01

The notation for vector analysis has a contentious nineteenth century history, with many different notations describing the same or similar concepts competing for use. While the twentieth century has seen a great deal of unification in vector analysis notation, variation still remains. In this paper, the two primary notations used for expressing the components of a vector are discussed in historical and current context. Popular mathematical texts use the two notations as if they are transparent and interchangeable. In this research project, engineering students' proficiency at vector analysis was assessed and the data were analyzed using the Rasch measurement method. Results indicate that the students found items expressed in unit vector notation more difficult than those expressed in parenthesis notation. The expert experience of notation as transparent and unproblematically symbolic of underlying processes independent of notation is shown to contrast with the student experience where the less familiar notation is experienced as harder to work with.

Membrane-bound SIV envelope trimers are immunogenic in ferrets after intranasal vaccination with a replication-competent canine distemper virus vector.

PubMed

Zhang, Xinsheng; Wallace, Olivia; Wright, Kevin J; Backer, Martin; Coleman, John W; Koehnke, Rebecca; Frenk, Esther; Domi, Arban; Chiuchiolo, Maria J; DeStefano, Joanne; Narpala, Sandeep; Powell, Rebecca; Morrow, Gavin; Boggiano, Cesar; Zamb, Timothy J; Richter King, C; Parks, Christopher L

2013-11-01

We are investigating canine distemper virus (CDV) as a vaccine vector for the delivery of HIV envelope (Env) that closely resembles the native trimeric spike. We selected CDV because it will promote vaccine delivery to lymphoid tissues, and because human exposure is infrequent, reducing potential effects of pre-existing immunity. Using SIV Env as a model, we tested a number of vector and gene insert designs. Vectors containing a gene inserted between the CDV H and L genes, which encoded Env lacking most of its cytoplasmic tail, propagated efficiently in Vero cells, expressed the immunogen on the cell surface, and incorporated the SIV glycoprotein into progeny virus particles. When ferrets were vaccinated intranasally, there were no signs of distress, vector replication was observed in the gut-associated lymphoid tissues, and the animals produced anti-SIV Env antibodies. These data show that live CDV-SIV Env vectors can safely induce anti-Env immune responses following intranasal vaccination. © 2013 Elsevier Inc. All rights reserved.

A Search for Vector Magnetic Field Variations Associated with the M-Class Flares of 1991 June 10 in AR 6659

NASA Technical Reports Server (NTRS)

Hagyard, Mona J.; Stark, B. A.; Venkatakrishnan, P.

1998-01-01

A careful analysis of a 6-hour time sequence of vector magnetograms of AR 6659, observed on 1991 June 10 with the MSFC vector magnetograph, has revealed only minor changes in the vector magnetic field azimuths in the vicinity of two M-class flares, and the association of these changes with the flares is not unambiguous. In this paper we present our analysis of the data which includes comparison of vector magnetograms prior to and during the flares, calculation of distributions of the rms variation of the azimuth at each pixel in the field of view of the active region, and examination of the variation with time of the azimuths at every pixel covered by the main flare emissions as observed with the H-alpha telescope coaligned with the vector magnetograph. We also present results of an analysis of evolutionary changes in the azimuth over the field of view of the active region.

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.

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.

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

The maximum vector-angular margin classifier and its fast training on large datasets using a core vector machine.

PubMed

Hu, Wenjun; Chung, Fu-Lai; Wang, Shitong

2012-03-01

Although pattern classification has been extensively studied in the past decades, how to effectively solve the corresponding training on large datasets is a problem that still requires particular attention. Many kernelized classification methods, such as SVM and SVDD, can be formulated as the corresponding quadratic programming (QP) problems, but computing the associated kernel matrices requires O(n2)(or even up to O(n3)) computational complexity, where n is the size of the training patterns, which heavily limits the applicability of these methods for large datasets. In this paper, a new classification method called the maximum vector-angular margin classifier (MAMC) is first proposed based on the vector-angular margin to find an optimal vector c in the pattern feature space, and all the testing patterns can be classified in terms of the maximum vector-angular margin ρ, between the vector c and all the training data points. Accordingly, it is proved that the kernelized MAMC can be equivalently formulated as the kernelized Minimum Enclosing Ball (MEB), which leads to a distinctive merit of MAMC, i.e., it has the flexibility of controlling the sum of support vectors like v-SVC and may be extended to a maximum vector-angular margin core vector machine (MAMCVM) by connecting the core vector machine (CVM) method with MAMC such that the corresponding fast training on large datasets can be effectively achieved. Experimental results on artificial and real datasets are provided to validate the power of the proposed methods. Copyright © 2011 Elsevier Ltd. All rights reserved.

Wess-Zumino current and the structure of the decay tau- -->K- pi- K+ nu tau.

PubMed

Coan, T E; Gao, Y S; Liu, F; Stroynowski, R; Artuso, M; Boulahouache, C; Blusk, S; Butt, J; Dambasuren, E; Dorjkhaidav, O; Haynes, J; Menaa, N; Mountain, R; Muramatsu, H; Nandakumar, R; Redjimi, R; Sia, R; Skwarnicki, T; Stone, S; Wang, J C; Zhang, Kevin; Mahmood, A H; Csorna, S E; Bonvicini, G; Cinabro, D; Dubrovin, M; Bornheim, A; Lipeles, E; Pappas, S P; Shapiro, A; Weinstein, A J; Briere, R A; Chen, G P; Ferguson, T; Tatishvili, G; Vogel, H; Watkins, M E; Adam, N E; Alexander, J P; Berkelman, K; Boisvert, V; Cassel, D G; Duboscq, J E; Ecklund, K M; Ehrlich, R; Galik, R S; Gibbons, L; Gittelman, B; Gray, S W; Hartill, D L; Heltsley, B K; Hsu, L; Jones, C D; Kandaswamy, J; Kreinick, D L; Kuznetsov, V E; Magerkurth, A; Mahlke-Krüger, H; Meyer, T O; Patterson, J R; Pedlar, T K; Peterson, D; Pivarski, J; Riley, D; Sadoff, A J; Schwarthoff, H; Shepherd, M R; Sun, W M; Thayer, J G; Urner, D; Wilksen, T; Weinberger, M; Athar, S B; Avery, P; Breva-Newell, L; Potlia, V; Stoeck, H; Yelton, J; Eisenstein, B I; Gollin, G D; Karliner, I; Lowrey, N; Naik, P; Sedlack, C; Selen, M; Thaler, J J; Williams, J; Edwards, K W; Besson, D; Gao, K Y; Gong, D T; Kubota, Y; Li, S Z; Poling, R; Scott, A W; Smith, A; Stepaniak, C J; Urheim, J; Metreveli, Z; Seth, K K; Tomaradze, A; Zweber, P; Arms, K; Eckhart, E; Gan, K K; Gwon, C; Severini, H; Skubic, P; Asner, D M; Dytman, S A; Mehrabyan, S; Mueller, J A; Nam, S; Savinov, V; Huang, G S; Miller, D H; Pavlunin, V; Sanghi, B; Shibata, E I; Shipsey, I P J; Adams, G S; Chasse, M; Cummings, J P; Danko, I; Napolitano, J; Cronin-Hennessy, D; Park, C S; Park, W; Thayer, J B; Thorndike, E H

2004-06-11

We present the first study of the vector (Wess-Zumino) current in tau(-)-->K-pi-K+nu(tau) decay using data collected with the CLEO III detector at the Cornell Electron Storage Ring. We determine the quantitative contributions to the decay width from the vector and axial vector currents. Within the framework of a model by Kühn and Mirkes, we identify the quantitative contributions to the total decay rate from the intermediate states omegapi, rho(')pi, and K*K.

Optical implementation of systolic array processing

NASA Technical Reports Server (NTRS)

Caulfield, H. J.; Rhodes, W. T.; Foster, M. J.; Horvitz, S.

1981-01-01

Algorithms for matrix vector multiplication are implemented using acousto-optic cells for multiplication and input data transfer and using charge coupled devices detector arrays for accumulation and output of the results. No two dimensional matrix mask is required; matrix changes are implemented electronically. A system for multiplying a 50 component nonnegative real vector by a 50 by 50 nonnegative real matrix is described. Modifications for bipolar real and complex valued processing are possible, as are extensions to matrix-matrix multiplication and multiplication of a vector by multiple matrices.

Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality

NASA Astrophysics Data System (ADS)

Cherukuru, Nihanth Wagmi

Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars. Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona's Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as a few earth science datasets for education and outreach activities.

BOREAS TE-20 Soils Data Over the NSA-MSA and Tower Sites in Raster Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Veldhuis, Hugo; Knapp, David; Veldhuis, Hugo

2000-01-01

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set was gridded from vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were gridded into raster files that cover the NSA-MSA and tower sites. The data are stored in binary, image format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Method and apparatus for second-rank tensor generation

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor)

1991-01-01

A method and apparatus are disclosed for generation of second-rank tensors using a photorefractive crystal to perform the outer-product between two vectors via four-wave mixing, thereby taking 2n input data to a control n squared output data points. Two orthogonal amplitude modulated coherent vector beams x and y are expanded and then parallel sides of the photorefractive crystal in exact opposition. A beamsplitter is used to direct a coherent pumping beam onto the crystal at an appropriate angle so as to produce a conjugate beam that is the matrix product of the vector beam that propagates in the exact opposite direction from the pumping beam. The conjugate beam thus separated is the tensor output xy (sup T).

Discrete Data Transfer Technique for Fluid-Structure Interaction

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2007-01-01

This paper presents a general three-dimensional algorithm for data transfer between dissimilar meshes. The algorithm is suitable for applications of fluid-structure interaction and other high-fidelity multidisciplinary analysis and optimization. Because the algorithm is independent of the mesh topology, we can treat structured and unstructured meshes in the same manner. The algorithm is fast and accurate for transfer of scalar or vector fields between dissimilar surface meshes. The algorithm is also applicable for the integration of a scalar field (e.g., coefficients of pressure) on one mesh and injection of the resulting vectors (e.g., force vectors) onto another mesh. The author has implemented the algorithm in a C++ computer code. This paper contains a complete formulation of the algorithm with a few selected results.

nu-Anomica: A Fast Support Vector Based Novelty Detection Technique

NASA Technical Reports Server (NTRS)

Das, Santanu; Bhaduri, Kanishka; Oza, Nikunj C.; Srivastava, Ashok N.

2009-01-01

In this paper we propose nu-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared to the benchmark one-class Support Vector Machines algorithm. In -Anomica, the idea is to train the machine such that it can provide a close approximation to the exact decision plane using fewer training points and without losing much of the generalization performance of the classical approach. We have tested the proposed algorithm on a variety of continuous data sets under different conditions. We show that under all test conditions the developed procedure closely preserves the accuracy of standard one-class Support Vector Machines while reducing both the training time and the test time by 5 - 20 times.

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.

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

Receptor-mediated gene transfer vectors: progress towards genetic pharmaceuticals.

PubMed

Molas, M; Gómez-Valadés, A G; Vidal-Alabró, A; Miguel-Turu, M; Bermudez, J; Bartrons, R; Perales, J C

2003-10-01

Although specific delivery to tissues and unique cell types in vivo has been demonstrated for many non-viral vectors, current methods are still inadequate for human applications, mainly because of limitations on their efficiencies. All the steps required for an efficient receptor-mediated gene transfer process may in principle be exploited to enhance targeted gene delivery. These steps are: DNA/vector binding, internalization, subcellular trafficking, vesicular escape, nuclear import, and unpacking either for transcription or other functions (i.e., antisense, RNA interference, etc.). The large variety of vector designs that are currently available, usually aimed at improving the efficiency of these steps, has complicated the evaluation of data obtained from specific derivatives of such vectors. The importance of the structure of the final vector and the consequences of design decisions at specific steps on the overall efficiency of the vector will be discussed in detail. We emphasize in this review that stability in serum and thus, proper bioavailability of vectors to their specific receptors may be the single greatest limiting factor on the overall gene transfer efficiency in vivo. We discuss current approaches to overcome the intrinsic instability of synthetic vectors in the blood. In this regard, a summary of the structural features of the vectors obtained from current protocols will be presented and their functional characteristics evaluated. Dissecting information on molecular conjugates obtained by such methodologies, when carefully evaluated, should provide important guidelines for the creation of effective, targeted and safe DNA therapeutics.

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

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

Cross-entropy embedding of high-dimensional data using the neural gas model.

PubMed

Estévez, Pablo A; Figueroa, Cristián J; Saito, Kazumi

2005-01-01

A cross-entropy approach to mapping high-dimensional data into a low-dimensional space embedding is presented. The method allows to project simultaneously the input data and the codebook vectors, obtained with the Neural Gas (NG) quantizer algorithm, into a low-dimensional output space. The aim of this approach is to preserve the relationship defined by the NG neighborhood function for each pair of input and codebook vectors. A cost function based on the cross-entropy between input and output probabilities is minimized by using a Newton-Raphson method. The new approach is compared with Sammon's non-linear mapping (NLM) and the hierarchical approach of combining a vector quantizer such as the self-organizing feature map (SOM) or NG with the NLM recall algorithm. In comparison with these techniques, our method delivers a clear visualization of both data points and codebooks, and it achieves a better mapping quality in terms of the topology preservation measure q(m).

"Triplet" polycistronic vectors encoding Gata4, Mef2c, and Tbx5 enhances postinfarct ventricular functional improvement compared with singlet vectors.

PubMed

Mathison, Megumi; Singh, Vivek P; Gersch, Robert P; Ramirez, Maricela O; Cooney, Austin; Kaminsky, Stephen M; Chiuchiolo, Maria J; Nasser, Ahmed; Yang, Jianchang; Crystal, Ronald G; Rosengart, Todd K

2014-10-01

The in situ reprogramming of cardiac fibroblasts into induced cardiomyocytes by the administration of gene transfer vectors encoding Gata4 (G), Mef2c (M), and Tbx5 (T) has been shown to improve ventricular function in myocardial infarction models. The efficacy of this strategy could, however, be limited by the need for fibroblast targets to be infected 3 times--once by each of the 3 transgene vectors. We hypothesized that a polycistronic "triplet" vector encoding all 3 transgenes would enhance postinfarct ventricular function compared with use of "singlet" vectors. After validation of the polycistronic vector expression in vitro, adult male Fischer 344 rats (n=6) underwent coronary ligation with or without intramyocardial administration of an adenovirus encoding all 3 major vascular endothelial growth factor (VEGF) isoforms (AdVEGF-All6A positive), followed 3 weeks later by the administration to AdVEGF-All6A-positive treated rats of singlet lentivirus encoding G, M, or T (1×10(5) transducing units each) or the same total dose of a GMT "triplet" lentivirus vector. Western blots demonstrated that triplet and singlet vectors yielded equivalent GMT transgene expression, and fluorescence activated cell sorting demonstrated that triplet vectors were nearly twice as potent as singlet vectors in generating induced cardiomyocytes from cardiac fibroblasts. Echocardiography demonstrated that GMT triplet vectors were more effective than the 3 combined singlet vectors in enhancing ventricular function from postinfarct baselines (triplet, 37%±10%; singlet, 13%±7%; negative control, 9%±5%; P<.05). These data have confirmed that the in situ administration of G, M, and T induces postinfarct ventricular functional improvement and that GMT polycistronic vectors enhance the efficacy of this strategy. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

An age-structured extension to the vectorial capacity model.

PubMed

Novoseltsev, Vasiliy N; Michalski, Anatoli I; Novoseltseva, Janna A; Yashin, Anatoliy I; Carey, James R; Ellis, Alicia M

2012-01-01

Vectorial capacity and the basic reproductive number (R(0)) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention. Based on survival analysis we derived new equations for vectorial capacity and R(0) that are valid for any pattern of age-dependent (or age-independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies. Accounting for age-dependent vector mortality in estimates of vectorial capacity and R(0) was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R(0) is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R(0) ∼ 1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field.

An Age-Structured Extension to the Vectorial Capacity Model

PubMed Central

Novoseltsev, Vasiliy N.; Michalski, Anatoli I.; Novoseltseva, Janna A.; Yashin, Anatoliy I.; Carey, James R.; Ellis, Alicia M.

2012-01-01

Background Vectorial capacity and the basic reproductive number (R0) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention. Methodology/Principal Findings Based on survival analysis we derived new equations for vectorial capacity and R0 that are valid for any pattern of age-dependent (or age–independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies. Conclusions/Significance Accounting for age-dependent vector mortality in estimates of vectorial capacity and R0 was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R0 is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R0∼1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field. PMID:22724022

Vector Topographic Map Data over the BOREAS NSA and SSA in SIF Format

NASA Technical Reports Server (NTRS)

Knapp, David; Nickeson, Jaime; Hall, Forrest G. (Editor)

2000-01-01

This data set contains vector contours and other features of individual topographic map sheets from the National Topographic Series (NTS). The map sheet files were received in Standard Interchange Format (SIF) and cover the BOReal Ecosystem-Atmosphere Study (BOREAS) Northern Study Area (NSA) and Southern Study Area (SSA) at scales of 1:50,000 and 1:250,000. The individual files are stored in compressed Unix tar archives.

Sparse matrix-vector multiplication on network-on-chip

NASA Astrophysics Data System (ADS)

Sun, C.-C.; Götze, J.; Jheng, H.-Y.; Ruan, S.-J.

2010-12-01

In this paper, we present an idea for performing matrix-vector multiplication by using Network-on-Chip (NoC) architecture. In traditional IC design on-chip communications have been designed with dedicated point-to-point interconnections. Therefore, regular local data transfer is the major concept of many parallel implementations. However, when dealing with the parallel implementation of sparse matrix-vector multiplication (SMVM), which is the main step of all iterative algorithms for solving systems of linear equation, the required data transfers depend on the sparsity structure of the matrix and can be extremely irregular. Using the NoC architecture makes it possible to deal with arbitrary structure of the data transfers; i.e. with the irregular structure of the sparse matrices. So far, we have already implemented the proposed SMVM-NoC architecture with the size 4×4 and 5×5 in IEEE 754 single float point precision using FPGA.

Vector and Tensor Analyzing Powers in Deuteron-Proton Breakup

NASA Astrophysics Data System (ADS)

Stephan, E.; Kistryn, St.; Kalantar-Nayestanaki, N.; Biegun, A.; Bodek, K.; Ciepał, I.; Deltuva, A.; Eslami-Kalantari, M.; Fonseca, A. C.; Gasparić, I.; Golak, J.; Jamróz, B.; Joulaeizadeh, L.; Kamada, H.; Kiš, M.; Kłos, B.; Kozela, A.; Mahjour-Shafiei, M.; Mardanpour, H.; Messchendorp, J.; Micherdzińska, A.; Moeini, H.; Nogga, A.; Ramazani-Moghaddam-Arani, A.; Skibiński, R.; Sworst, R.; Witała, H.; Zejma, J.

2011-05-01

High precision data for vector and tensor analyzing powers of the {^1{H}({d},{{pp}}){n}} breakup reaction at 130 and 100 MeV deuteron beam energies have been measured in a large fraction of the phase space. They are compared to the theoretical predictions based on various approaches to describe the three nucleon (3N) system dynamics. Theoretical predictions describe very well the vector analyzing power data, with no need to include any three-nucleon force effects for these observables. Tensor analyzing powers can be also very well reproduced by calculations in most of the studied region, but locally certain discrepancies are observed. At 130 MeV for A xy such discrepancies usually appear, or are enhanced, when model 3N forces are included. Predicted effects of 3NFs are much lower at 100 MeV and at this energy equally good consistency between the data and the calculations is obtained with or without 3NFs.

Indicator Development for Potential Presence of Schistosomiasis Japonicum's Vector in Lake and Marshland Regions- A Case Study of Poyang Lake, Jiangxi Province, P.R. China

NASA Astrophysics Data System (ADS)

Marie, Tiphanie; Yesou, Herve; Huber, Claire; De Fraipont, Paul; Uribe, Carlos; Lacaux, Jean-Pierre; Lafaye, Murielle; Lai, Xijun; Desnos, Yves-Louis

2013-01-01

Earth observation data and bibliography on environmental parameters were used for mapping Oncomelania hupensis distribution, the Schistosomiasis japonicum’s intermediate host snail, within Poyang Lake (Jiangxi Province, P.R. China). Areas suitable for the development of O. hupensis, the vector of schistosomiasis, were derived from submersion time parameters and vegetation community indicators. ENVISAT time series data acquired from 2000 to 2009 were used for submersion times mapping, and 5 Beijing-1 data acquired during the dry season between 2006 and 2008 were used to map suitable vegetation for vector development. Yearly maps obtained indicate four principally potential endemic areas: the Gan Delta, the bank of the Fu He River, the Dalianzi Hu sector and the Poyang Lake Nature Reserve. Monthly maps from December 2005 to December 2008 show the dynamic of potential O. hupensis presence areas.

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.

In Vivo Zinc Finger Nuclease-mediated Targeted Integration of a Glucose-6-phosphatase Transgene Promotes Survival in Mice With Glycogen Storage Disease Type IA

PubMed Central

Landau, Dustin J; Brooks, Elizabeth Drake; Perez-Pinera, Pablo; Amarasekara, Hiruni; Mefferd, Adam; Li, Songtao; Bird, Andrew; Gersbach, Charles A; Koeberl, Dwight D

2016-01-01

Glycogen storage disease type Ia (GSD Ia) is caused by glucose-6-phosphatase (G6Pase) deficiency in association with severe, life-threatening hypoglycemia that necessitates lifelong dietary therapy. Here we show that use of a zinc-finger nuclease (ZFN) targeted to the ROSA26 safe harbor locus and a ROSA26-targeting vector containing a G6PC donor transgene, both delivered with adeno-associated virus (AAV) vectors, markedly improved survival of G6Pase knockout (G6Pase-KO) mice compared with mice receiving the donor vector alone (P < 0.04). Furthermore, transgene integration has been confirmed by sequencing in the majority of the mice treated with both vectors. Targeted alleles were 4.6-fold more common in livers of mice with GSD Ia, as compared with normal littermates, at 8 months following vector administration (P < 0.02). This suggests a selective advantage for vector-transduced hepatocytes following ZFN-mediated integration of the G6Pase vector. A short-term experiment also showed that 3-month-old mice receiving the ZFN had significantly-improved biochemical correction, in comparison with mice that received the donor vector alone. These data suggest that the use of ZFNs to drive integration of G6Pase at a safe harbor locus might improve vector persistence and efficacy, and lower mortality in GSD Ia. PMID:26865405

Reduction of solar vector magnetograph data using a microMSP array processor

NASA Technical Reports Server (NTRS)

Kineke, Jack

1990-01-01

The processing of raw data obtained by the solar vector magnetograph at NASA-Marshall requires extensive arithmetic operations on large arrays of real numbers. The objectives of this summer faculty fellowship study are to: (1) learn the programming language of the MicroMSP Array Processor and adapt some existing data reduction routines to exploit its capabilities; and (2) identify other applications and/or existing programs which lend themselves to array processor utilization which can be developed by undergraduate student programmers under the provisions of project JOVE.

Progressive Vector Quantization on a massively parallel SIMD machine with application to multispectral image data

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1994-01-01

A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.

A Statistical Comparison between Photospheric Vector Magnetograms Obtained by SDO/HMI and Hinode/SP

NASA Astrophysics Data System (ADS)

Sainz Dalda, Alberto

2017-12-01

Since 2010 May 1, we have been able to study (almost) continuously the vector magnetic field in the Sun, thanks to two space-based observatories: the Solar Dynamics Observatory (SDO) and Hinode. Both are equipped with instruments able to measure the Stokes parameters of Zeeman-induced polarization of photospheric line radiation. But the observation modes; the spectral lines; the spatial, spectral, and temporal sampling; and even the inversion codes used to recover magnetic and thermodynamic information from the Stokes profiles are different. We compare the vector magnetic fields derived from observations with the HMI instrument on board SDO with those observed by the SP instrument on Hinode. We have obtained relationships between components of magnetic vectors in the umbra, penumbra, and plage observed in 14 maps of NOAA Active Region 11084. Importantly, we have transformed SP data into observables comparable to those of HMI, to explore possible influences of the different modes of operation of the two instruments and the inversion schemes used to infer the magnetic fields. The assumed filling factor (fraction of each pixel containing a Zeeman signature) produces the most significant differences in derived magnetic properties, especially in the plage. The spectral and angular samplings have the next-largest effects. We suggest to treat the disambiguation in the same way in the data provided by HMI and SP. That would make the relationship between the vector magnetic field recovered from these data stronger, which would favor the simultaneous or complementary use of both instruments.

Remote Sensing the Patterns of Vector-borne Disease in El Nino and non-El Nino Years

NASA Technical Reports Server (NTRS)

Wood, B. L.; Chang, J.; Lobitz, B.; Beck, L.; DAntoni, Hector (Technical Monitor)

1997-01-01

The relationship between El Nino and non-El Nino and the patterns of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are long term predictions of changing precipitation and temperature patterns at continental and global scales. At the opposite extreme are the local or site specific ecological changes associated with the long term events. In order to understand and address the human health consequences of El Nino events, especially the patterns of vector-borne diseases, it is necessary to combine both scales of observation. At a local or regional scale the patterns of vector-borne diseases are determined by temperature, precipitation, and habitat availability. These factors, as well as disease incidence can be altered by El Nino events. Remote sensing data such as that acquired by the NOAA AVHRR and Landsat TM sensors can be used to characterize and monitor changing ecological conditions and therefore predict vector-borne disease patterns. The authors present the results of preliminary work on the analysis of historical AVHRR and TM data acquired during El Nino and nonfatal Nino years to characterize ecological conditions in Peru on a monthly basis. This information will then be combined with disease data to determine the relationship between changes in ecological conditions and disease incidence. Our goal is to produce a sequence of remotely sensed images which can be used to show the ecological and disease patterns associated with long term El Nino events and predictions.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

The Support Vector Machine is a powerful algorithm, useful in classifying data in to species. The Support Vector Machines implemented in this research were used as classifiers for the final stage in a Multistage Autonomous Target Recognition system. A single kernel SVM known as SVMlight, and a modified version known as a Support Vector Machine with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SMV as a method for classification. From trial to trial, SVM produces consistent results

TRAC Searchable Research Library

DTIC Science & Technology

2016-05-01

network accessible document repository for technical documents and similar document artifacts. We used a model-based approach using the Vector...demonstration and model refinement. 14. SUBJECT TERMS Knowledge Management, Document Repository , Digital Library, Vector Directional Data Model...27 Figure D1. Administrator Repository Upload Page. ................................................................... D-2 Figure D2

Statistical learning algorithms for identifying contrasting tillage practices with landsat thematic mapper data

USDA-ARS?s Scientific Manuscript database

Tillage management practices have direct impact on water holding capacity, evaporation, carbon sequestration, and water quality. This study examines the feasibility of two statistical learning algorithms, such as Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM), for cla...

Spatial orientation of caloric nystagmus in semicircular canal-plugged monkeys.

PubMed

Arai, Yasuko; Yakushin, Sergei B; Cohen, Bernard; Suzuki, Jun-Ichi; Raphan, Theodore

2002-08-01

We studied caloric nystagmus before and after plugging all six semicircular canals to determine whether velocity storage contributed to the spatial orientation of caloric nystagmus. Monkeys were stimulated unilaterally with cold ( approximately 20 degrees C) water while upright, supine, prone, right-side down, and left-side down. The decline in the slow phase velocity vector was determined over the last 37% of the nystagmus, at a time when the response was largely due to activation of velocity storage. Before plugging, yaw components varied with the convective flow of endolymph in the lateral canals in all head orientations. Plugging blocked endolymph flow, eliminating convection currents. Despite this, caloric nystagmus was readily elicited, but the horizontal component was always toward the stimulated (ipsilateral) side, regardless of head position relative to gravity. When upright, the slow phase velocity vector was close to the yaw and spatial vertical axes. Roll components became stronger in supine and prone positions, and vertical components were enhanced in side down positions. In each case, this brought the velocity vectors toward alignment with the spatial vertical. Consistent with principles governing the orientation of velocity storage, when the yaw component of the velocity vector was positive, the cross-coupled pitch or roll components brought the vector upward in space. Conversely, when yaw eye velocity vector was downward in the head coordinate frame, i.e., negative, pitch and roll were downward in space. The data could not be modeled simply by a reduction in activity in the ipsilateral vestibular nerve, which would direct the velocity vector along the roll direction. Since there is no cross coupling from roll to yaw, velocity storage alone could not rotate the vector to fit the data. We postulated, therefore, that cooling had caused contraction of the endolymph in the plugged canals. This contraction would deflect the cupula toward the plug, simulating ampullofugal flow of endolymph. Inhibition and excitation induced by such cupula deflection fit the data well in the upright position but not in lateral or prone/supine conditions. Data fits in these positions required the addition of a spatially orientated, velocity storage component. We conclude, therefore, that three factors produce cold caloric nystagmus after canal plugging: inhibition of activity in ampullary nerves, contraction of endolymph in the stimulated canals, and orientation of eye velocity to gravity through velocity storage. Although the response to convection currents dominates the normal response to caloric stimulation, velocity storage probably also contributes to the orientation of eye velocity.

GIS based Cadastral level Forest Information System using World View-II data in Bir Hisar (Haryana)

NASA Astrophysics Data System (ADS)

Mothi Kumar, K. E.; Singh, S.; Attri, P.; Kumar, R.; Kumar, A.; Sarika; Hooda, R. S.; Sapra, R. K.; Garg, V.; Kumar, V.; Nivedita

2014-11-01

Identification and demarcation of Forest lands on the ground remains a major challenge in Forest administration and management. Cadastral forest mapping deals with forestlands boundary delineation and their associated characterization (forest/non forest). The present study is an application of high resolution World View-II data for digitization of Protected Forest boundary at cadastral level with integration of Records of Right (ROR) data. Cadastral vector data was generated by digitization of spatial data using scanned mussavies in ArcGIS environment. Ortho-images were created from World View-II digital stereo data with Universal Transverse Mercator coordinate system with WGS 84 datum. Cadastral vector data of Bir Hisar (Hisar district, Haryana) and adjacent villages was spatially adjusted over ortho-image using ArcGIS software. Edge matching of village boundaries was done with respect to khasra boundaries of individual village. The notified forest grids were identified on ortho-image and grid vector data was extracted from georeferenced cadastral data. Cadastral forest boundary vectors were digitized from ortho-images. Accuracy of cadastral data was checked by comparison of randomly selected geo-coordinates points, tie lines and boundary measurements of randomly selected parcels generated from image data set with that of actual field measurements. Area comparison was done between cadastral map area, the image map area and RoR area. The area covered under Protected Forest was compared with ROR data and within an accuracy of less than 1 % from ROR area was accepted. The methodology presented in this paper is useful to update the cadastral forest maps. The produced GIS databases and large-scale Forest Maps may serve as a data foundation towards a land register of forests. The study introduces the use of very high resolution satellite data to develop a method for cadastral surveying through on - screen digitization in a less time as compared to the old fashioned cadastral parcel boundaries surveying method.

Real time display Fourier-domain OCT using multi-thread parallel computing with data vectorization

NASA Astrophysics Data System (ADS)

Eom, Tae Joong; Kim, Hoon Seop; Kim, Chul Min; Lee, Yeung Lak; Choi, Eun-Seo

2011-03-01

We demonstrate a real-time display of processed OCT images using multi-thread parallel computing with a quad-core CPU of a personal computer. The data of each A-line are treated as one vector to maximize the data translation rate between the cores of the CPU and RAM stored image data. A display rate of 29.9 frames/sec for processed OCT data (4096 FFT-size x 500 A-scans) is achieved in our system using a wavelength swept source with 52-kHz swept frequency. The data processing times of the OCT image and a Doppler OCT image with a 4-time average are 23.8 msec and 91.4 msec.

Assessing the potential for AAV vector genotoxicity in a murine model

PubMed Central

Li, Hojun; Malani, Nirav; Hamilton, Shari R.; Schlachterman, Alexander; Bussadori, Giulio; Edmonson, Shyrie E.; Shah, Rachel; Arruda, Valder R.; Mingozzi, Federico; Fraser Wright, J.; Bushman, Frederic D.

2011-01-01

Gene transfer using adeno-associated virus (AAV) vectors has great potential for treating human disease. Recently, questions have arisen about the safety of AAV vectors, specifically, whether integration of vector DNA in transduced cell genomes promotes tumor formation. This study addresses these questions with high-dose liver-directed AAV-mediated gene transfer in the adult mouse as a model (80 AAV-injected mice and 52 controls). After 18 months of follow-up, AAV-injected mice did not show a significantly higher rate of hepatocellular carcinoma compared with controls. Tumors in mice treated with AAV vectors did not have significantly different amounts of vector DNA compared with adjacent normal tissue. A novel high-throughput method for identifying AAV vector integration sites was developed and used to clone 1029 integrants. Integration patterns in tumor tissue and adjacent normal tissue were similar to each other, showing preferences for active genes, cytosine-phosphate-guanosine islands, and guanosine/cysteine-rich regions. Gene expression data showed that genes near integration sites did not show significant changes in expression patterns compared with genes more distal to integration sites. No integration events were identified as causing increased oncogene expression. Thus, we did not find evidence that AAV vectors cause insertional activation of oncogenes and subsequent tumor formation. PMID:21106988

Detection of osteoclastic cell-cell fusion through retroviral vector packaging.

PubMed

Kondo, Takako; Ikeda, Kyoji; Matsuo, Koichi

2004-11-01

Cell-cell fusion generates multinucleated cells such as osteoclasts in bone, myotubes in muscle, and trophoblasts in placenta. Molecular details governing these fusion processes are still largely unknown. As a step toward identification of fusogenic genes, we tested the concept that retroviral vectors can be packaged as a result of cell-cell fusion. First, we introduced replication-deficient retroviral vectors expressing mCAT-1, which mediates fusogenic interaction with the retroviral envelope protein Env, into Chinese hamster ovary (CHO) cells to generate vector cells. Plasmids expressing virion proteins Gag, Pol, and Env were introduced into a separate culture of CHO cells to generate packaging cells. Co-culturing vector and packaging cells resulted in production of infectious retroviruses carrying the mCAT-1 gene as a consequence of cell-cell fusion. Second, we introduced a retroviral vector into primary osteoclast precursors and co-cultured them with established osteoclast precursor RAW264.7 cells, which turned out to harbor packaging activity. Packaged retroviral vector was detected in culture supernatants only where the osteoclast differentiation factor receptor activator for NF-kappaB ligand (RANKL) induced fusion between these two cell types. These data suggest that retrovirus production can occur as a result of cell-cell fusion. This provides a novel approach for isolating and characterizing fusogenic genes using retroviral expression vectors.

Incremental classification learning for anomaly detection in medical images

NASA Astrophysics Data System (ADS)

Giritharan, Balathasan; Yuan, Xiaohui; Liu, Jianguo

2009-02-01

Computer-aided diagnosis usually screens thousands of instances to find only a few positive cases that indicate probable presence of disease.The amount of patient data increases consistently all the time. In diagnosis of new instances, disagreement occurs between a CAD system and physicians, which suggests inaccurate classifiers. Intuitively, misclassified instances and the previously acquired data should be used to retrain the classifier. This, however, is very time consuming and, in some cases where dataset is too large, becomes infeasible. In addition, among the patient data, only a small percentile shows positive sign, which is known as imbalanced data.We present an incremental Support Vector Machines(SVM) as a solution for the class imbalance problem in classification of anomaly in medical images. The support vectors provide a concise representation of the distribution of the training data. Here we use bootstrapping to identify potential candidate support vectors for future iterations. Experiments were conducted using images from endoscopy videos, and the sensitivity and specificity were close to that of SVM trained using all samples available at a given incremental step with significantly improved efficiency in training the classifier.

A Collaborative Framework for Distributed Privacy-Preserving Support Vector Machine Learning

PubMed Central

Que, Jialan; Jiang, Xiaoqian; Ohno-Machado, Lucila

2012-01-01

A Support Vector Machine (SVM) is a popular tool for decision support. The traditional way to build an SVM model is to estimate parameters based on a centralized repository of data. However, in the field of biomedicine, patient data are sometimes stored in local repositories or institutions where they were collected, and may not be easily shared due to privacy concerns. This creates a substantial barrier for researchers to effectively learn from the distributed data using machine learning tools like SVMs. To overcome this difficulty and promote efficient information exchange without sharing sensitive raw data, we developed a Distributed Privacy Preserving Support Vector Machine (DPP-SVM). The DPP-SVM enables privacy-preserving collaborative learning, in which a trusted server integrates “privacy-insensitive” intermediary results. The globally learned model is guaranteed to be exactly the same as learned from combined data. We also provide a free web-service (http://privacy.ucsd.edu:8080/ppsvm/) for multiple participants to collaborate and complete the SVM-learning task in an efficient and privacy-preserving manner. PMID:23304414

Gaussian statistics for palaeomagnetic vectors

USGS Publications Warehouse

Love, J.J.; Constable, C.G.

2003-01-01

With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to formulate the inverse problem, and how to estimate the mean and variance of the magnetic vector field, even when the data consist of mixed combinations of directions and intensities. We examine palaeomagnetic secular-variation data from Hawaii and Re??union, and although these two sites are on almost opposite latitudes, we find significant differences in the mean vector and differences in the local vectorial variances, with the Hawaiian data being particularly anisotropic. These observations are inconsistent with a description of the mean field as being a simple geocentric axial dipole and with secular variation being statistically symmetrical with respect to reflection through the equatorial plane. Finally, our analysis of palaeomagnetic acquisition data from the 1960 Kilauea flow in Hawaii and the Holocene Xitle flow in Mexico, is consistent with the widely held suspicion that directional data are more accurate than intensity data.

Gaussian statistics for palaeomagnetic vectors

NASA Astrophysics Data System (ADS)

Love, J. J.; Constable, C. G.

2003-03-01

With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimodal) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to formulate the inverse problem, and how to estimate the mean and variance of the magnetic vector field, even when the data consist of mixed combinations of directions and intensities. We examine palaeomagnetic secular-variation data from Hawaii and Réunion, and although these two sites are on almost opposite latitudes, we find significant differences in the mean vector and differences in the local vectorial variances, with the Hawaiian data being particularly anisotropic. These observations are inconsistent with a description of the mean field as being a simple geocentric axial dipole and with secular variation being statistically symmetrical with respect to reflection through the equatorial plane. Finally, our analysis of palaeomagnetic acquisition data from the 1960 Kilauea flow in Hawaii and the Holocene Xitle flow in Mexico, is consistent with the widely held suspicion that directional data are more accurate than intensity data.

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.

Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

Autonomous learning derived from experimental modeling of physical laws.

PubMed

Grabec, Igor

2013-05-01

This article deals with experimental description of physical laws by probability density function of measured data. The Gaussian mixture model specified by representative data and related probabilities is utilized for this purpose. The information cost function of the model is described in terms of information entropy by the sum of the estimation error and redundancy. A new method is proposed for searching the minimum of the cost function. The number of the resulting prototype data depends on the accuracy of measurement. Their adaptation resembles a self-organized, highly non-linear cooperation between neurons in an artificial NN. A prototype datum corresponds to the memorized content, while the related probability corresponds to the excitability of the neuron. The method does not include any free parameters except objectively determined accuracy of the measurement system and is therefore convenient for autonomous execution. Since representative data are generally less numerous than the measured ones, the method is applicable for a rather general and objective compression of overwhelming experimental data in automatic data-acquisition systems. Such compression is demonstrated on analytically determined random noise and measured traffic flow data. The flow over a day is described by a vector of 24 components. The set of 365 vectors measured over one year is compressed by autonomous learning to just 4 representative vectors and related probabilities. These vectors represent the flow in normal working days and weekends or holidays, while the related probabilities correspond to relative frequencies of these days. This example reveals that autonomous learning yields a new basis for interpretation of representative data and the optimal model structure. Copyright © 2012 Elsevier Ltd. All rights reserved.

Measuring and Modeling Shared Visual Attention

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.; Gontar, Patrick

2016-01-01

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval. We present two methods for comparing sequences of this sort, one based on computing the time-varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions. We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of "activities," each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. We have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Haslbeck, Gontar & Schubert, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Measuring and Modeling Shared Visual Attention

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

2016-01-01

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval. We present two methods for comparing sequences of this sort, one based on computing the time-varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions.We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of activities, each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates.We have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Haslbeck, Gontar Schubert, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Role of geospatial technology in identifying natural habitat of malarial vectors in South Andaman, India.

PubMed

Shankar, Shiva; Agrawal, Deepak Kumar

2016-03-01

Malaria is a serious disease which has repeatedly threatened Andaman, an island territory of India. Uncharted dense vegetation and inaccessibility are the salient features of the area and the major areas are covered by remotely sensed data to identify the malaria vector's natural habitat. The present investigation appraises the role of geospatial technologies in identifying the natural habitat of malarial vectors. The base map was prepared from Survey of India's toposheets, the landuse map was prepared from indices techniques like normalised difference vegetation index (NDVI), normalised difference water index (NDWI), modified normalised difference water index (MNDWI), normalised difference pond index (NDPI), and normalized difference turbidity index (NDTI) in conjugation with visual interpretation. The soil moisture content map was reproduced from the soil atlas of Andaman and Nicobar Islands followed by generation of an aspect profile from ASTER-GDEM satellite data. Both the landuse map and aspect profile were validated for accuracy in the field. A weighted overlay analysis of the classes like landuse, soil moisture and aspect profile of the study area resulted in identification of the potential natural habitat map of malaria vector surrounding the areas of Tushnabad, Garacharma, Manglutan, Chouldari, Ferrargunj and Wimberlygunj hamlets. The natural habitat of malaria vector indicated that Tushnabad, Garacharma, Manglutan, Chouldari, Ferrargunj and Wimberlygunj hamlets are within the proximity of 2.5 km from the prime habitat location with more number of malaria positive cases. Also these hamlets are surrounded by dense evergreen forest and the land surface is draped by clay loam and clay soil texture exhibiting high soil moisture content warranting high rates of survival and proliferation of the vector ensuring resurgence of malaria every year. It is thus concluded that application of geospatial technologies plays an important role in identifying the natural habitat of malaria vector.

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

Support vector machines classifiers of physical activities in preschoolers

USDA-ARS?s Scientific Manuscript database

The goal of this study is to develop, test, and compare multinomial logistic regression (MLR) and support vector machines (SVM) in classifying preschool-aged children physical activity data acquired from an accelerometer. In this study, 69 children aged 3-5 years old were asked to participate in a s...

Complete genome sequence of a Klebsiella pneumoniae strain isolated from a known cotton insect boll vector

USDA-ARS?s Scientific Manuscript database

Klebsiella pneumoniae (associated with bacterial pneumonia) was previously isolated from Nezara viridula, a significant vector of cotton boll-rot pathogens. We provide the first annotated genome sequence of the cotton opportunistic strain K. pneumoniae 5-1. This data provides guidance to study the...

Analysis of vector wind change with respect to time for Vandenberg Air Force Base, California

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1978-01-01

A statistical analysis of the temporal variability of wind vectors at 1 km altitude intervals from 0 to 27 km altitude taken from a 10-year data sample of twice-daily rawinsode wind measurements over Vandenberg Air Force Base, California is presented.

Evaluation of spray droplet spectrum of sprayers used for vector control

USDA-ARS?s Scientific Manuscript database

Droplet spectra data were collected from spray equipment intended for use in vector control by the US Department of Defense pest management programs to determine if they produce droplets in the ultra-low volume (ULV) spectrum. Droplets generated by 26 sprayers utilizing water + non-ionic surfactant...

Novel, Post-Stall, Thrust-Vectored F-15 RPVs: Laboratory and Flight Tests

DTIC Science & Technology

1990-04-24

Flight Tests Program Manager : Douglas Bowers 1ST-Year Report Principal Investigator: Benjamin 6al-Or April 24, 1990 DTIC.LECTE AUG201990 i/ E...constructed. The geometry, dimensions and preliminary wind-tunnel test data for such a design are provided In Appendix A. If funded, such a 3rd...Preliminary Calibration Flight Test Data Obtained from the Onboard Computer ........ 33 Talless, PST-RaNPAS, Roll-Yaw-Pitch, Thrust-Vectored, PST F-15 (Cf. ADp

User's guide for vectorized code EQUIL for calculating equilibrium chemistry on Control Data STAR-100 computer

NASA Technical Reports Server (NTRS)

Kumar, A.; Graves, R. A., Jr.; Weilmuenster, K. J.

1980-01-01

A vectorized code, EQUIL, was developed for calculating the equilibrium chemistry of a reacting gas mixture on the Control Data STAR-100 computer. The code provides species mole fractions, mass fractions, and thermodynamic and transport properties of the mixture for given temperature, pressure, and elemental mass fractions. The code is set up for the electrons H, He, C, O, N system of elements. In all, 24 chemical species are included.

Investigating the Magnetic Imprints of Major Solar Eruptions with SDO /HMI High-cadence Vector Magnetograms

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

Sun Xudong; Hoeksema, J. Todd; Liu Yang

The solar active region photospheric magnetic field evolves rapidly during major eruptive events, suggesting appreciable feedback from the corona. Previous studies of these “magnetic imprints” are mostly based on line of sight only or lower-cadence vector observations; a temporally resolved depiction of the vector field evolution is hitherto lacking. Here, we introduce the high-cadence (90 s or 135 s) vector magnetogram data set from the Helioseismic and Magnetic Imager, which is well suited for investigating the phenomenon. These observations allow quantitative characterization of the permanent, step-like changes that are most pronounced in the horizontal field component (B {sub h}). Amore » highly structured pattern emerges from analysis of an archetypical event, SOL2011-02-15T01:56, where B {sub h} near the main polarity inversion line increases significantly during the earlier phase of the associated flare with a timescale of several minutes, while B {sub h} in the periphery decreases at later times with smaller magnitudes and a slightly longer timescale. The data set also allows effective identification of the “magnetic transient” artifact, where enhanced flare emission alters the Stokes profiles and the inferred magnetic field becomes unreliable. Our results provide insights on the momentum processes in solar eruptions. The data set may also be useful to the study of sunquakes and data-driven modeling of the corona.« less

Extending R packages to support 64-bit compiled code: An illustration with spam64 and GIMMS NDVI3g data

NASA Astrophysics Data System (ADS)

Gerber, Florian; Mösinger, Kaspar; Furrer, Reinhard

2017-07-01

Software packages for spatial data often implement a hybrid approach of interpreted and compiled programming languages. The compiled parts are usually written in C, C++, or Fortran, and are efficient in terms of computational speed and memory usage. Conversely, the interpreted part serves as a convenient user-interface and calls the compiled code for computationally demanding operations. The price paid for the user friendliness of the interpreted component is-besides performance-the limited access to low level and optimized code. An example of such a restriction is the 64-bit vector support of the widely used statistical language R. On the R side, users do not need to change existing code and may not even notice the extension. On the other hand, interfacing 64-bit compiled code efficiently is challenging. Since many R packages for spatial data could benefit from 64-bit vectors, we investigate strategies to efficiently pass 64-bit vectors to compiled languages. More precisely, we show how to simply extend existing R packages using the foreign function interface to seamlessly support 64-bit vectors. This extension is shown with the sparse matrix algebra R package spam. The new capabilities are illustrated with an example of GIMMS NDVI3g data featuring a parametric modeling approach for a non-stationary covariance matrix.

Dryden/Edwards 1994 Thrust-Vectoring Aircraft Fleet - F-18 HARV, X-31, F-16 MATV

NASA Technical Reports Server (NTRS)

1994-01-01

The three thrust-vectoring aircraft at Edwards, California, each capable of flying at extreme angles of attack, cruise over the California desert in formation during flight in March 1994. They are, from left, NASA's F-18 High Alpha Research Vehicle (HARV), flown by the NASA Dryden Flight Research Center; the X-31, flown by the X-31 International Test Organization (ITO) at Dryden; and the Air Force F-16 Multi-Axis Thrust Vectoring (MATV) aircraft. All three aircraft were flown in different programs and were developed independently. The NASA F-18 HARV was a testbed to produce aerodynamic data at high angles of attack to validate computer codes and wind tunnel research. The X-31 was used to study thrust vectoring to enhance close-in air combat maneuvering, while the F-16 MATV was a demonstration of how thrust vectoring could be applied to operational aircraft.

Current status of Plasmodium knowlesi vectors: a public health concern?

PubMed

Vythilingam, I; Wong, M L; Wan-Yussof, W S

2018-01-01

Plasmodium knowlesi a simian malaria parasite is currently affecting humans in Southeast Asia. Malaysia has reported the most number of cases and P. knowlesi is the predominant species occurring in humans. The vectors of P. knowlesi belong to the Leucosphyrus group of Anopheles mosquitoes. These are generally described as forest-dwelling mosquitoes. With deforestation and changes in land-use, some species have become predominant in farms and villages. However, knowledge on the distribution of these vectors in the country is sparse. From a public health point of view it is important to know the vectors, so that risk factors towards knowlesi malaria can be identified and control measures instituted where possible. Here, we review what is known about the knowlesi malaria vectors and ascertain the gaps in knowledge, so that future studies could concentrate on this paucity of data in-order to address this zoonotic problem.

Feeding profile of Mepraia spinolai, a sylvatic vector of Chagas disease in Chile.

PubMed

Chacón, F; Bacigalupo, A; Quiroga, J F; Ferreira, A; Cattan, P E; Ramírez-Toloza, G

2016-10-01

American trypanosomiasis is a chronic disease transmitted mainly by vectors. The hematophagous triatomine vectors transmit Trypanosoma cruzi to a wide variety of mammals, which usually are their food source. This study determined the feeding profile of Mepraia spinolai, a sylvatic triatomine vector, present in endemic areas of Chile. Vectors were captured in the north-central area of Chile. Samples of intestinal contents were analyzed by an Enzyme-linked immunosorbent assay (ELISA) that identifies and discriminates the presence of serum antigens from Homo sapiens and nine animal species (Canis familiaris, Felis catus, Capra hircus, Mus musculus, Gallus gallus, Octodon degus, Thylamys elegans, Phyllotis darwini and Oryctolagus cuniculus). Our data indicate the most frequent feeding source in this area was P. darwini, followed by O. degus, O. cuniculus, M. musculus, G. gallus, T. elegans, C. familiaris, F. catus and C. hircus. Mixed food sources were also identified. Copyright © 2016 Elsevier B.V. All rights reserved.

Curing genetic disease with gene therapy.

PubMed

Williams, David A

2014-01-01

Development of viral vectors that allow high efficiency gene transfer into mammalian cells in the early 1980s foresaw the treatment of severe monogenic diseases in humans. The application of gene transfer using viral vectors has been successful in diseases of the blood and immune systems, albeit with several curative studies also showing serious adverse events (SAEs). In children with X-linked severe combined immunodeficiency (SCID-X1), chronic granulomatous disease, and Wiskott-Aldrich syndrome, these SAEs were caused by inappropriate activation of oncogenes. Subsequent studies have defined the vector sequences responsible for these transforming events. Members of the Transatlantic Gene Therapy Consortium [TAGTC] have collaboratively developed new vectors that have proven safer in preclinical studies and used these vectors in new clinical trials in SCID-X1. These trials have shown evidence of early efficacy and preliminary integration analysis data from the SCID-X1 trial suggest an improved safety profile.

Ecohealth Interventions Limit Triatomine Reinfestation following Insecticide Spraying in La Brea, Guatemala

PubMed Central

Lucero, David E.; Morrissey, Leslie A.; Rizzo, Donna M.; Rodas, Antonieta; Garnica, Roberto; Stevens, Lori; Bustamante, Dulce M.; Monroy, Maria Carlota

2013-01-01

In this study, we evaluate the effect of participatory Ecohealth interventions on domestic reinfestation of the Chagas disease vector Triatoma dimidiata after village-wide suppression of the vector population using a residual insecticide. The study was conducted in the rural community of La Brea, Guatemala between 2002 and 2009 where vector infestation was analyzed within a spatial data framework based on entomological and socio-economic surveys of homesteads within the village. Participatory interventions focused on community awareness and low-cost home improvements using local materials to limit areas of refuge and alternative blood meals for the vector within the home, and potential shelter for the vector outside the home. As a result, domestic infestation was maintained at ≤ 3% and peridomestic infestation at ≤ 2% for 5 years beyond the last insecticide spraying, in sharp contrast to the rapid reinfestation experienced in earlier insecticide only interventions. PMID:23382173

A new method for the prediction of chatter stability lobes based on dynamic cutting force simulation model and support vector machine

NASA Astrophysics Data System (ADS)

Peng, Chong; Wang, Lun; Liao, T. Warren

2015-10-01

Currently, chatter has become the critical factor in hindering machining quality and productivity in machining processes. To avoid cutting chatter, a new method based on dynamic cutting force simulation model and support vector machine (SVM) is presented for the prediction of chatter stability lobes. The cutting force is selected as the monitoring signal, and the wavelet energy entropy theory is used to extract the feature vectors. A support vector machine is constructed using the MATLAB LIBSVM toolbox for pattern classification based on the feature vectors derived from the experimental cutting data. Then combining with the dynamic cutting force simulation model, the stability lobes diagram (SLD) can be estimated. Finally, the predicted results are compared with existing methods such as zero-order analytical (ZOA) and semi-discretization (SD) method as well as actual cutting experimental results to confirm the validity of this new method.

Construction of broad-host-range cosmid cloning vectors: identification of genes necessary for growth of Methylobacterium organophilum on methanol

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

Allen, L.N.; Hanson, R.S.

Four new cloning vectors have been constructed from the broad-host-range cloning vector pRK290. These vectors, pLA2901, pLA2905, pLA2910, and pLA2917, confer resistance to kanamycin and tetracycline. The latter two are cosmid derivatives of pLA2901. The new vectors can be mobilized into, and are stably maintained in, a variety of gram-negative bacteria. A Sau3A genomic bank of Methylobacterium organophilum strain xx DNA has been constructed in pLA2917, and complementation analysis, with a variety of mutants unable to grow on methanol, revealed at least five separate regions necessary for growth on methanol. Complementation analysis and Tn5 mutagenesis data suggest that at leastmore » three genes are responsible for expression of active methanol dehydrogenase.« less

Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination.

PubMed

Stivala, Alex; Robins, Garry; Kashima, Yoshihisa; Kirley, Michael

2014-05-02

The Axelrod model of cultural diffusion is an apparently simple model that is capable of complex behaviour. A recent work used a real-world dataset of opinions as initial conditions, demonstrating the effects of the ultrametric distribution of empirical opinion vectors in promoting cultural diversity in the model. Here we quantify the degree of ultrametricity of the initial culture vectors and investigate the effect of varying degrees of ultrametricity on the absorbing state of both a simple and extended model. Unlike the simple model, ultrametricity alone is not sufficient to sustain long-term diversity in the extended Axelrod model; rather, the initial conditions must also have sufficiently large variance in intervector distances. Further, we find that a scheme for evolving synthetic opinion vectors from cultural "prototypes" shows the same behaviour as real opinion data in maintaining cultural diversity in the extended model; whereas neutral evolution of cultural vectors does not.

Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination

NASA Astrophysics Data System (ADS)

Stivala, Alex; Robins, Garry; Kashima, Yoshihisa; Kirley, Michael

2014-05-01

The Axelrod model of cultural diffusion is an apparently simple model that is capable of complex behaviour. A recent work used a real-world dataset of opinions as initial conditions, demonstrating the effects of the ultrametric distribution of empirical opinion vectors in promoting cultural diversity in the model. Here we quantify the degree of ultrametricity of the initial culture vectors and investigate the effect of varying degrees of ultrametricity on the absorbing state of both a simple and extended model. Unlike the simple model, ultrametricity alone is not sufficient to sustain long-term diversity in the extended Axelrod model; rather, the initial conditions must also have sufficiently large variance in intervector distances. Further, we find that a scheme for evolving synthetic opinion vectors from cultural ``prototypes'' shows the same behaviour as real opinion data in maintaining cultural diversity in the extended model; whereas neutral evolution of cultural vectors does not.

Curing Genetic Disease with Gene Therapy

PubMed Central

Williams, David A.

2014-01-01

Development of viral vectors that allow high efficiency gene transfer into mammalian cells in the early 1980s foresaw the treatment of severe monogenic diseases in humans. The application of gene transfer using viral vectors has been successful in diseases of the blood and immune systems, albeit with several curative studies also showing serious adverse events (SAEs). In children with X-linked severe combined immunodeficiency (SCID-X1), chronic granulomatous disease, and Wiskott-Aldrich syndrome, these SAEs were caused by inappropriate activation of oncogenes. Subsequent studies have defined the vector sequences responsible for these transforming events. Members of the Transatlantic Gene Therapy Consortium [TAGTC] have collaboratively developed new vectors that have proven safer in preclinical studies and used these vectors in new clinical trials in SCID-X1. These trials have shown evidence of early efficacy and preliminary integration analysis data from the SCID-X1 trial suggest an improved safety profile. PMID:25125725

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.

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

Model-based VQ for image data archival, retrieval and distribution

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1995-01-01

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Experimental Results of Underwater Cooperative Source Localization Using a Single Acoustic Vector Sensor

PubMed Central

Felisberto, Paulo; Rodriguez, Orlando; Santos, Paulo; Ey, Emanuel; Jesus, Sérgio M.

2013-01-01

This paper aims at estimating the azimuth, range and depth of a cooperative broadband acoustic source with a single vector sensor in a multipath underwater environment, where the received signal is assumed to be a linear combination of echoes of the source emitted waveform. A vector sensor is a device that measures the scalar acoustic pressure field and the vectorial acoustic particle velocity field at a single location in space. The amplitudes of the echoes in the vector sensor components allow one to determine their azimuth and elevation. Assuming that the environmental conditions of the channel are known, source range and depth are obtained from the estimates of elevation and relative time delays of the different echoes using a ray-based backpropagation algorithm. The proposed method is tested using simulated data and is further applied to experimental data from the Makai'05 experiment, where 8–14 kHz chirp signals were acquired by a vector sensor array. It is shown that for short ranges, the position of the source is estimated in agreement with the geometry of the experiment. The method is low computational demanding, thus well-suited to be used in mobile and light platforms, where space and power requirements are limited. PMID:23857257

Selection of optimum median-filter-based ambiguity removal algorithm parameters for NSCAT. [NASA scatterometer

NASA Technical Reports Server (NTRS)

Shaffer, Scott; Dunbar, R. Scott; Hsiao, S. Vincent; Long, David G.

1989-01-01

The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.

Fuzzy Relational Compression Applied on Feature Vectors for Infant Cry Recognition

NASA Astrophysics Data System (ADS)

Reyes-Galaviz, Orion Fausto; Reyes-García, Carlos Alberto

Data compression is always advisable when it comes to handling and processing information quickly and efficiently. There are two main problems that need to be solved when it comes to handling data; store information in smaller spaces and processes it in the shortest possible time. When it comes to infant cry analysis (ICA), there is always the need to construct large sound repositories from crying babies. Samples that have to be analyzed and be used to train and test pattern recognition algorithms; making this a time consuming task when working with uncompressed feature vectors. In this work, we show a simple, but efficient, method that uses Fuzzy Relational Product (FRP) to compresses the information inside a feature vector, building with this a compressed matrix that will help us recognize two kinds of pathologies in infants; Asphyxia and Deafness. We describe the sound analysis, which consists on the extraction of Mel Frequency Cepstral Coefficients that generate vectors which will later be compressed by using FRP. There is also a description of the infant cry database used in this work, along with the training and testing of a Time Delay Neural Network with the compressed features, which shows a performance of 96.44% with our proposed feature vector compression.

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

Covalent decoration of adenovirus vector capsids with the carbohydrate epitope αGal does not improve vector immunogenicity, but allows to study the in vivo fate of adenovirus immunocomplexes.

PubMed

Kratzer, Ramona F; Espenlaub, Sigrid; Hoffmeister, Andrea; Kron, Matthias W; Kreppel, Florian

2017-01-01

Adenovirus-based vectors are promising tools for genetic vaccination. However, several obstacles have to be overcome prior to a routine clinical application of adenovirus-based vectors as efficacious vectored vaccines. The linear trisaccharide epitope αGal (alpha-Gal) with the carbohydrate sequence galactose-α-1,3-galactosyl-β-1,4-N-acetylglucosamine has been described as a potent adjuvant for recombinant or attenuated vaccines. Humans and α-1,3-galactosyltransferase knockout mice do not express this epitope. Upon exposure of α-1,3-galactosyltransferase-deficient organisms to αGal in the environment, large amounts of circulating anti-Gal antibodies are produced consistently. Immunocomplexes formed between recombinant αGal-decorated vaccines and anti-Gal antibodies exhibit superior immunogenicity. We studied the effects of the trisaccharide epitope on CD8 T cell responses that are directed specifically to vector-encoded transgenic antigens. For that, covalently αGal-decorated adenovirus vectors were delivered to anti-Gal α-1,3-galactosyltransferase knockout mice. We generated replication-defective, E1-deleted adenovirus type 5 vectors that were decorated with αGal at the hexon hypervariable regions 1 or 5, at fiber knob, or at penton base. Surprisingly, none of the adenovirus immunocomplexes being formed from αGal-decorated adenovirus vectors and anti-Gal immunoglobulins improved the frequencies of CD8 T cell responses against the transgenic antigen ovalbumin. Humoral immunity directed to the adenovirus vector was neither increased. However, our data indicated that decoration of Ad vectors with the αGal epitope is a powerful tool to analyze the fate of adenovirus immunocomplexes in vivo.

Seasonal Variation in Biting Rates of Simulium damnosum sensu lato, Vector of Onchocerca volvulus, in Two Sudanese Foci

PubMed Central

Zarroug, Isam M. A.; Hashim, Kamal; Elaagip, Arwa H.; Samy, Abdallah M.; Frah, Ehab A.; ElMubarak, Wigdan A.; Mohamed, Hanan A.; Deran, Tong Chor M.; Aziz, Nabil; Higazi, Tarig B.

2016-01-01

Background The abundance of onchocerciasis vectors affects the epidemiology of disease in Sudan, therefore, studies of vector dynamics are crucial for onchocerciasis control/elimination programs. This study aims to compare the relative abundance, monthly biting-rates (MBR) and hourly-based distribution of onchocerciasis vectors in Abu-Hamed and Galabat foci. These seasonally-based factors can be used to structure vector control efforts to reduce fly-biting rates as a component of onchocerciasis elimination programs. Methods A cross-sectional study was conducted in four endemic villages in Abu-Hamed and Galabat foci during two non-consecutive years (2007–2008 and 2009–2010). Both adults and aquatic stages of the potential onchocerciasis vector Simulium damnosum sensu lato were collected following standard procedures during wet and dry seasons. Adult flies were collected using human landing capture for 5 days/month. The data was recorded on handheld data collection sheets to calculate the relative abundance, MBR, and hourly-based distribution associated with climatic factors. The data analysis was carried out using ANOVA and Spearman rank correlation tests. Results Data on vector surveillance revealed higher relative abundance of S. damnosum s.l. in Abu- Hamed (39,934 flies) than Galabat (8,202 flies). In Abu-Hamed, vector populations increased in January-April then declined in June-July until they disappeared in August-October. Highest black fly density and MBR were found in March 2007 (N = 9,444, MBR = 58,552.8 bites/person/month), and March 2010 (N = 2,603, MBR = 16,138.6 bites/person/month) while none of flies were collected in August-October (MBR = 0 bites/person/month). In Galabat, vectors increased in September-December, then decreased in February-June. The highest vector density and MBR were recorded in September 2007 (N = 1,138, MBR = 6,828 bites/person/month) and September 2010 (N = 1,163, MBR = 6,978 bites/person/month), whereas, none appeared in collection from April to June. There was a significant difference in mean monthly density of S. damnosum s.l. across the two foci in 2007–2008 (df = 3, F = 3.91, P = 0.011). Minimum temperature showed significant correlation with adult flies counts in four areas sampled; the adult counts were increased in Nady village (rs = 0.799) and were decreased in Kalasecal (rs = - 0.676), Gumaiza (rs = - 0.585), and Hilat Khateir (rs = - 0.496). Maximum temperature showed positive correlation with black fly counts only in Galabat focus. Precipitation was significantly correlated with adult flies counts in Nady village, Abu-Hamed, but no significance was found in the rest of the sampled villages in both foci. Hourly-based distribution of black flies showed a unimodal pattern in Abu-Hamed with one peak (10:00–18:00), while a bimodal pattern with two peaks (07:00–10:00) and (14:00–18:00) was exhibited in Galabat. Conclusion Transmission of onchocerciasis in both foci showed marked differences in seasonality, which may be attributed to ecology, microclimate and proximity of breeding sites to collection sites. The seasonal shifts between the two foci might be related to variations in climate zones. This information on black fly vector seasonality, ecology, distribution and biting activity has obvious implications in monitoring transmission levels to guide the national and regional onchocerciasis elimination programs in Sudan. PMID:26943668

iVAR: a program for imputing missing data in multivariate time series using vector autoregressive models.

PubMed

Liu, Siwei; Molenaar, Peter C M

2014-12-01

This article introduces iVAR, an R program for imputing missing data in multivariate time series on the basis of vector autoregressive (VAR) models. We conducted a simulation study to compare iVAR with three methods for handling missing data: listwise deletion, imputation with sample means and variances, and multiple imputation ignoring time dependency. The results showed that iVAR produces better estimates for the cross-lagged coefficients than do the other three methods. We demonstrate the use of iVAR with an empirical example of time series electrodermal activity data and discuss the advantages and limitations of the program.

Research on Classification of Chinese Text Data Based on SVM

NASA Astrophysics Data System (ADS)

Lin, Yuan; Yu, Hongzhi; Wan, Fucheng; Xu, Tao

2017-09-01

Data Mining has important application value in today’s industry and academia. Text classification is a very important technology in data mining. At present, there are many mature algorithms for text classification. KNN, NB, AB, SVM, decision tree and other classification methods all show good classification performance. Support Vector Machine’ (SVM) classification method is a good classifier in machine learning research. This paper will study the classification effect based on the SVM method in the Chinese text data, and use the support vector machine method in the chinese text to achieve the classify chinese text, and to able to combination of academia and practical application.

Combining Relevance Vector Machines and exponential regression for bearing residual life estimation

NASA Astrophysics Data System (ADS)

Di Maio, Francesco; Tsui, Kwok Leung; Zio, Enrico

2012-08-01

In this paper we present a new procedure for estimating the bearing Residual Useful Life (RUL) by combining data-driven and model-based techniques. Respectively, we resort to (i) Relevance Vector Machines (RVMs) for selecting a low number of significant basis functions, called Relevant Vectors (RVs), and (ii) exponential regression to compute and continuously update residual life estimations. The combination of these techniques is developed with reference to partially degraded thrust ball bearings and tested on real world vibration-based degradation data. On the case study considered, the proposed procedure outperforms other model-based methods, with the added value of an adequate representation of the uncertainty associated to the estimates of the quantification of the credibility of the results by the Prognostic Horizon (PH) metric.

Verifying the equivalence of representations of the knee joint moment vector from a drop vertical jump task.

PubMed

Nichols, Julia K; O'Reilly, Oliver M

2017-03-01

Biomechanics software programs, such as Visual3D, Nexus, Cortex, and OpenSim, have the capability of generating several distinct component representations for joint moments and forces from motion capture data. These representations include those for orthonormal proximal and distal coordinate systems and a non-orthogonal joint coordinate system. In this article, a method is presented to address the challenging problem of evaluating and verifying the equivalence of these representations. The method accommodates the difficulty that there are two possible sets of non-orthogonal basis vectors that can be used to express a vector in the joint coordinate system and is illuminated using motion capture data from a drop vertical jump task. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of the Three-Dimensional Vector FAÇADE Model Created from Photogrammetric Data

NASA Astrophysics Data System (ADS)

Kamnev, I. S.; Seredovich, V. A.

2017-12-01

The results of the accuracy assessment analysis for creation of a three-dimensional vector model of building façade are described. In the framework of the analysis, analytical comparison of three-dimensional vector façade models created by photogrammetric and terrestrial laser scanning data has been done. The three-dimensional model built from TLS point clouds was taken as the reference one. In the course of the experiment, the three-dimensional model to be analyzed was superimposed on the reference one, the coordinates were measured and deviations between the same model points were determined. The accuracy estimation of the three-dimensional model obtained by using non-metric digital camera images was carried out. Identified façade surface areas with the maximum deviations were revealed.

An Auto-flag Method of Radio Visibility Data Based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Dai, Hui-mei; Mei, Ying; Wang, Wei; Deng, Hui; Wang, Feng

2017-01-01

The Mingantu Ultrawide Spectral Radioheliograph (MUSER) has entered a test observation stage. After the construction of the data acquisition and storage system, it is urgent to automatically flag and eliminate the abnormal visibility data so as to improve the imaging quality. In this paper, according to the observational records, we create a credible visibility set, and further obtain the corresponding flag model of visibility data by using the support vector machine (SVM) technique. The results show that the SVM is a robust approach to flag the MUSER visibility data, and can attain an accuracy of about 86%. Meanwhile, this method will not be affected by solar activities, such as flare eruptions.

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

NASA Technical Reports Server (NTRS)

Rutishauser, David

2006-01-01

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Community detection in complex networks using proximate support vector clustering

NASA Astrophysics Data System (ADS)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

Vector splines on the sphere with application to the estimation of vorticity and divergence from discrete, noisy data

NASA Technical Reports Server (NTRS)

Wahba, G.

1982-01-01

Vector smoothing splines on the sphere are defined. Theoretical properties are briefly alluded to. The appropriate Hilbert space norms used in a specific meteorological application are described and justified via a duality theorem. Numerical procedures for computing the splines as well as the cross validation estimate of two smoothing parameters are given. A Monte Carlo study is described which suggests the accuracy with which upper air vorticity and divergence can be estimated using measured wind vectors from the North American radiosonde network.

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Spin Resonances for Stored Deuteron Beams in COSY. Vector Polarization. Tracking with Spink

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

Luccio,A.; Lehrach, A.

2008-04-01

Results of measurements of vector and tensor polarization of a deuteron beam in the storage ring COSY have been published by the SPIN{at}COSY collaboration. In this experiment a RF Dipole was used that produced spin flip. The strength of the RFD-induced depolarizing resonance was calculated from the amount of spin flipping and the results shown in the figures of the cited paper. In this note we present the simulation of the experimental data (vector polarization) with the spin tracking code Spink.

Determination of the axial-vector weak coupling constant with ultracold neutrons.

PubMed

Liu, J; Mendenhall, M P; Holley, A T; Back, H O; Bowles, T J; Broussard, L J; Carr, R; Clayton, S; Currie, S; Filippone, B W; García, A; Geltenbort, P; Hickerson, K P; Hoagland, J; Hogan, G E; Hona, B; Ito, T M; Liu, C-Y; Makela, M; Mammei, R R; Martin, J W; Melconian, D; Morris, C L; Pattie, R W; Pérez Galván, A; Pitt, M L; Plaster, B; Ramsey, J C; Rios, R; Russell, R; Saunders, A; Seestrom, S J; Sondheim, W E; Tatar, E; Vogelaar, R B; VornDick, B; Wrede, C; Yan, H; Young, A R

2010-10-29

A precise measurement of the neutron decay β asymmetry A₀ has been carried out using polarized ultracold neutrons from the pulsed spallation ultracold neutron source at the Los Alamos Neutron Science Center. Combining data obtained in 2008 and 2009, we report A₀ = -0.119 66±0.000 89{-0.001 40}{+0.001 23}, from which we determine the ratio of the axial-vector to vector weak coupling of the nucleon g{A}/g{V}=-1.275 90{-0.004 45}{+0.004 09}.

Vector tomography for reconstructing electric fields with non-zero divergence in bounded domains

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

Koulouri, Alexandra, E-mail: koulouri@uni-muenster.de; Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, London SW7 2BT; Brookes, Mike

In vector tomography (VT), the aim is to reconstruct an unknown multi-dimensional vector field using line integral data. In the case of a 2-dimensional VT, two types of line integral data are usually required. These data correspond to integration of the parallel and perpendicular projection of the vector field along the integration lines and are called the longitudinal and transverse measurements, respectively. In most cases, however, the transverse measurements cannot be physically acquired. Therefore, the VT methods are typically used to reconstruct divergence-free (or source-free) velocity and flow fields that can be reconstructed solely from the longitudinal measurements. In thismore » paper, we show how vector fields with non-zero divergence in a bounded domain can also be reconstructed from the longitudinal measurements without the need of explicitly evaluating the transverse measurements. To the best of our knowledge, VT has not previously been used for this purpose. In particular, we study low-frequency, time-harmonic electric fields generated by dipole sources in convex bounded domains which arise, for example, in electroencephalography (EEG) source imaging. We explain in detail the theoretical background, the derivation of the electric field inverse problem and the numerical approximation of the line integrals. We show that fields with non-zero divergence can be reconstructed from the longitudinal measurements with the help of two sparsity constraints that are constructed from the transverse measurements and the vector Laplace operator. As a comparison to EEG source imaging, we note that VT does not require mathematical modeling of the sources. By numerical simulations, we show that the pattern of the electric field can be correctly estimated using VT and the location of the source activity can be determined accurately from the reconstructed magnitudes of the field. - Highlights: • Vector tomography is used to reconstruct electric fields generated by dipole sources. • Inverse solutions are based on longitudinal and transverse line integral measurements. • Transverse line integral measurements are used as a sparsity constraint. • Numerical procedure to approximate the line integrals is described in detail. • Patterns of the studied electric fields are correctly estimated.« less

Insecticide susceptibility and dengue vector status of wild Stegomyia albopicta in a strategically important area of Assam, India

PubMed Central

2014-01-01

Background Dengue vector control programmes are facing operational challenges due to resistance against commonly used insecticides throughout the endemic countries. Recently, there has been appreciable increase in the dengue cases in India, however, no recent data are available on susceptible status of dengue vectors. We have studied the susceptibility level of St. albopicta to commonly used insecticides in India. Adult mosquitoes were tested for the presence of dengue virus. Methods St. albopicta larval bioassays were carried out to determine the lethal concentrations (LC10, LC50 and LC99) and the resistance ratios (RR10, RR50 and RR99) for temephos. Susceptibility to 4% DDT, 0.05% deltamethrin and 5% malathion was assessed following standard procedure. Knock-down times (KDT10, KDT50 and KDT99) were estimated and knock-down resistance ratios (KRR10, KRR50 and KRR99) were calculated. VectorTest™ dengue antigen assay was used to detect the dengue virus in the field collected mosquitoes. Results In larval bioassays, the RR ranged from 1.4 (for RR99) to 1.7 (for RR50), which suggested that the tested St. albopicta were susceptible to temephos. There was no deviation among the lethal concentration data from linearity (r2 = 0.61). Adult St. albopicta mosquitoes were resistant to DDT, while fully susceptible to deltamethrin and malathion. The knock-down values (KDT10, KDT50 and KDT99) obtained for DDT displayed straight line in log-dose-probit analysis and follow linear regression model. The KRR99 for DDT was 4.9, which indicated a 4.9 folds increase in knock-down resistance to DDT. However, for malathion and deltamethrin, the KRR99 values were 1.6 and 1.5 respectively suggesting that mosquitoes were knock-down sensitive. None of the mosquito pool was dengue virus positive. Conclusion St. albopicta showed resistance to DDT and reduced sensitivity to deltamethrin and malathion. This data on insecticide resistance could help public health authorities in India to design more effective vector control measures. More dengue vector specimens need to be scanned to identify the potential dengue vector. PMID:24981885

Chagas Disease, Migration and Community Settlement Patterns in Arequipa, Peru

PubMed Central

Gilman, Robert H.; Cornejo del Carpio, Juan G.; Naquira, Cesar; Bern, Caryn; Levy, Michael Z.

2009-01-01

Background Chagas disease is one of the most important neglected tropical diseases in the Americas. Vectorborne transmission of Chagas disease has been historically rare in urban settings. However, in marginal communities near the city of Arequipa, Peru, urban transmission cycles have become established. We examined the history of migration and settlement patterns in these communities, and their connections to Chagas disease transmission. Methodology/Principal Findings This was a qualitative study that employed focus group discussions and in-depth interviews. Five focus groups and 50 in-depth interviews were carried out with 94 community members from three shantytowns and two traditional towns near Arequipa, Peru. Focus groups utilized participatory methodologies to explore the community's mobility patterns and the historical and current presence of triatomine vectors. In-depth interviews based on event history calendars explored participants' migration patterns and experience with Chagas disease and vectors. Focus group data were analyzed using participatory analysis methodologies, and interview data were coded and analyzed using a grounded theory approach. Entomologic data were provided by an ongoing vector control campaign. We found that migrants to shantytowns in Arequipa were unlikely to have brought triatomines to the city upon arrival. Frequent seasonal moves, however, took shantytown residents to valleys surrounding Arequipa where vectors are prevalent. In addition, the pattern of settlement of shantytowns and the practice of raising domestic animals by residents creates a favorable environment for vector proliferation and dispersal. Finally, we uncovered a phenomenon of population loss and replacement by low-income migrants in one traditional town, which created the human settlement pattern of a new shantytown within this traditional community. Conclusions/Significance The pattern of human migration is therefore an important underlying determinant of Chagas disease risk in and around Arequipa. Frequent seasonal migration by residents of peri-urban shantytowns provides a path of entry of vectors into these communities. Changing demographic dynamics of traditional towns are also leading to favorable conditions for Chagas disease transmission. Control programs must include surveillance for infestation in communities assumed to be free of vectors. PMID:20016830

OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

NASA Astrophysics Data System (ADS)

Erickson, T. A.; Koziol, B. W.; Rood, R. B.

2011-12-01

The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

Are Bred Vectors The Same As Lyapunov Vectors?

NASA Astrophysics Data System (ADS)

Kalnay, E.; Corazza, M.; Cai, M.

Regional loss of predictability is an indication of the instability of the underlying flow, where small errors in the initial conditions (or imperfections in the model) grow to large amplitudes in finite times. The stability properties of evolving flows have been studied using Lyapunov vectors (e.g., Alligood et al, 1996, Ott, 1993, Kalnay, 2002), singular vectors (e.g., Lorenz, 1965, Farrell, 1988, Molteni and Palmer, 1993), and, more recently, with bred vectors (e.g., Szunyogh et al, 1997, Cai et al, 2001). Bred vectors (BVs) are, by construction, closely related to Lyapunov vectors (LVs). In fact, after an infinitely long breeding time, and with the use of infinitesimal ampli- tudes, bred vectors are identical to leading Lyapunov vectors. In practical applications, however, bred vectors are different from Lyapunov vectors in two important ways: a) bred vectors are never globally orthogonalized and are intrinsically local in space and time, and b) they are finite-amplitude, finite-time vectors. These two differences are very significant in a dynamical system whose size is very large. For example, the at- mosphere is large enough to have "room" for several synoptic scale instabilities (e.g., storms) to develop independently in different regions (say, North America and Aus- tralia), and it is complex enough to have several different possible types of instabilities (such as barotropic, baroclinic, convective, and even Brownian motion). Bred vectors share some of their properties with leading LVs (Corazza et al, 2001a, 2001b, Toth and Kalnay, 1993, 1997, Cai et al, 2001). For example, 1) Bred vectors are independent of the norm used to define the size of the perturba- tion. Corazza et al. (2001) showed that bred vectors obtained using a potential enstro- phy norm were indistinguishable from bred vectors obtained using a streamfunction squared norm, in contrast with singular vectors. 2) Bred vectors are independent of the length of the rescaling period as long as the perturbations remain approximately linear (for example, for atmospheric models the interval for rescaling could be varied between a single time step and 1 day without affecting qualitatively the characteristics of the bred vectors. However, the finite-amplitude, finite-time, and lack of orthogonalization of the BVs introduces important differences with LVs: 1) In regions that undergo strong instabilities, the bred vectors tend to be locally domi- 1 nated by simple, low-dimensional structures. Patil et al (2001) showed that the BV-dim (appendix) gives a good estimate of the number of dominant directions (shapes) of the local k bred vectors. For example, if half of them are aligned in one direction, and half in a different direction, the BV-dim is about two. If the majority of the bred vectors are aligned predominantly in one direction and only a few are aligned in a second direction, then the BV-dim is between 1 and 2. Patil et al., (2001) showed that the regions with low dimensionality cover about 20% of the atmosphere. They also found that these low-dimensionality regions have a very well defined vertical structure, and a typical lifetime of 3-7 days. The low dimensionality identifies regions where the in- stability of the basic flow has manifested itself in a low number of preferred directions of perturbation growth. 2) Using a Quasi-Geostrophic simulation system of data assimilation developed by Morss (1999), Corazza et al (2001a, b) found that bred vectors have structures that closely resemble the background (short forecasts used as first guess) errors, which in turn dominate the local analysis errors. This is especially true in regions of low dimensionality, which is not surprising if these are unstable regions where errors grow in preferred shapes. 3) The number of bred vectors needed to represent the unstable subspace in the QG system is small (about 6-10). This was shown by computing the local BV-dim as a function of the number of independent bred vectors. Convergence in the local dimen- sion starts to occur at about 6 BVs, and is essentially complete when the number of vectors is about 10-15 (Corazza et al, 2001a). This should be contrasted with the re- sults of Snyder and Joly (1998) and Palmer et al (1998) who showed that hundreds of Lyapunov vectors with positive Lyapunov exponents are needed to represent the attractor of the system in quasi-geostrophic models. 4) Since only a few bred vectors are needed, and background errors project strongly in the subspace of bred vectors, Corazza et al (2001b) were able to develop cost-efficient methods to improve the 3D-Var data assimilation by adding to the background error covariance terms proportional to the outer product of the bred vectors, thus represent- ing the "errors of the day". This approach led to a reduction of analysis error variance of about 40% at very low cost. 5) The fact that BVs have finite amplitude provides a natural way to filter out instabil- ities present in the system that have fast growth, but saturate nonlinearly at such small amplitudes that they are irrelevant for ensemble perturbations. As shown by Lorenz (1996) Lyapunov vectors (and singular vectors) of models including these physical phenomena would be dominated by the fast but small amplitude instabilities, unless they are explicitly excluded from the linearized models. Bred vectors, on the other 2 hand, through the choice of an appropriate size for the perturbation, provide a natural filter based on nonlinear saturation of fast but irrelevant instabilities. 6) Every bred vector is qualitatively similar to the *leading* LV. LVs beyond the leading LV are obtained by orthogonalization after each time step with respect to the previous LVs subspace. The orthogonalization requires the introduction of a norm. With an enstrophy norm, the successive LVs have larger and larger horizontal scales, and a choice of a stream function norm would lead to successively smaller scales in the LVs. Beyond the first few LVs, there is little qualitative similarity between the background errors and the LVs. In summary, in a system like the atmosphere with enough physical space for several independent local instabilities, BVs and LVs share some properties but they also have significant differences. BV are finite-amplitude, finite-time, and because they are not globally orthogonalized, they have local properties in space. Bred vectors are akin to the leading LV, but bred vectors derived from different arbitrary initial perturba- tions remain distinct from each other, instead of collapsing into a single leading vec- tor, presumably because the nonlinear terms and physical parameterizations introduce sufficient stochastic forcing to avoid such convergence. As a result, there is no need for global orthogonalization, and the number of bred vectors required to describe the natural instabilities in an atmospheric system (from a local point of view) is much smaller than the number of Lyapunov vectors with positive Lyapunov exponents. The BVs are independent of the norm, whereas the LVs beyond the first one do depend on the choice of norm: for example, they become larger in scale with a vorticity norm, and smaller with a stream function norm. These properties of BVs result in significant advantages for data assimilation and en- semble forecasting for the atmosphere. Errors in the analysis have structures very similar to bred vectors, and it is found that they project very strongly on the subspace of a few bred vectors. This is not true for either Lyapunov vectors beyond the lead- ing LVs, or for singular vectors unless they are constructed with a norm based on the analysis error covariance matrix (or a bred vector covariance). The similarity between bred vectors and analysis errors leads to the ability to include "errors of the day" in the background error covariance and a significant improvement of the analysis beyond 3D-Var at a very low cost (Corazza, 2001b). References Alligood K. T., T. D. Sauer and J. A. Yorke, 1996: Chaos: an introduction to dynamical systems. Springer-Verlag, New York. Buizza R., J. Tribbia, F. Molteni and T. Palmer, 1993: Computation of optimal unstable 3 structures for numerical weather prediction models. Tellus, 45A, 388-407. Cai, M., E. Kalnay and Z. Toth, 2001: Potential impact of bred vectors on ensemble forecasting and data assimilation in the Zebiak-Cane model. Submitted to J of Climate. Corazza, M., E. Kalnay, D. J. Patil, R. Morss, M. Cai, I. Szunyogh, B. R. Hunt, E. Ott and J. Yorke, 2001: Use of the breeding technique to determine the structure of the "errors of the day". Submitted to Nonlinear Processes in Geophysics. Corazza, M., E. Kalnay, DJ Patil, E. Ott, J. Yorke, I Szunyogh and M. Cai, 2001: Use of the breeding technique in the estimation of the background error covariance matrix for a quasigeostrophic model. AMS Symposium on Observations, Data Assimilation and Predictability, Preprints volume, Orlando, FA, 14-17 January 2002. Farrell, B., 1988: Small error dynamics and the predictability of atmospheric flow, J. Atmos. Sciences, 45, 163-172. Kalnay, E 2002: Atmospheric modeling, data assimilation and predictability. Chapter 6. Cambridge University Press, UK. In press. Kalnay E and Z Toth 1994: Removing growing errors in the analysis. Preprints, Tenth Conference on Numerical Weather Prediction, pp 212-215. Amer. Meteor. Soc., July 18-22, 1994. Lorenz, E.N., 1965: A study of the predictability of a 28-variable atmospheric model. Tellus, 21, 289-307. Lorenz, E.N., 1996: Predictability- A problem partly solved. Proceedings of the ECMWF Seminar on Predictability, Reading, England, Vol. 1 1-18. Molteni F. and TN Palmer, 1993: Predictability and finite-time instability of the north- ern winter circulation. Q. J. Roy. Meteorol. Soc. 119, 269-298. Morss, R.E.: 1999: Adaptive observations: Idealized sampling strategies for improving numerical weather prediction. Ph.D. Thesis, Massachussetts Institute of Technology, 225pp. Ott, E., 1993: Chaos in Dynamical Systems. Cambridge University Press. New York. Palmer, TN, R. Gelaro, J. Barkmeijer and R. Buizza, 1998: Singular vectors, metrics and adaptive observations. J. Atmos Sciences, 55, 633-653. Patil, DJ, BR Hunt, E Kalnay, J. Yorke, and E. Ott, 2001: Local low dimensionality of atmospheric dynamics. Phys. Rev. Lett., 86, 5878. Patil, DJ, I. Szunyogh, BR Hunt, E Kalnay, E Ott, and J. Yorke, 2001: Using large 4 member ensembles to isolate local low dimensionality of atmospheric dynamics. AMS Symposium on Observations, Data Assimilation and Predictability, Preprints volume, Orlando, FA, 14-17 January 2002. Snyder, C. and A. Joly, 1998: Development of perturbations within growing baroclinic waves. Q. J. Roy. Meteor. Soc., 124, pp 1961. Szunyogh, I, E. Kalnay and Z. Toth, 1997: A comparison of Lyapunov and Singular vectors in a low resolution GCM. Tellus, 49A, 200-227. Toth, Z and E Kalnay 1993: Ensemble forecasting at NMC - the generation of pertur- bations. Bull. Amer. Meteorol. Soc., 74, 2317-2330. Toth, Z and E Kalnay 1997: Ensemble forecasting at NCEP and the breeding method. Mon Wea Rev, 125, 3297-3319. * Corresponding author address: Eugenia Kalnay, Meteorology Depart- ment, University of Maryland, College Park, MD 20742-2425, USA; email: ekalnay@atmos.umd.edu Appendix: BV-dimension Patil et al., (2001) defined local bred vectors around a point in the 3-dimensional grid of the model by taking the 24 closest horizontal neighbors. If there are k bred vectors available, and N model variables for each grid point, the k local bred vectors form the columns of a 25Nxk matrix B. The kxk covariance matrix is C=B^T B. Its eigen- values are positive, and its eigenvectors v(i) are the singular vectors of the local bred vector subspace. The Bred Vector dimension (BV-dim) measures the local effective dimension: BV-dim[s,s,...,s(k)]={SUM[s(i)]}^2/SUM[s(i)]^2 where s(i) are the square roots of the eigenvalues of the covariance matrix. 5

Data on Support Vector Machines (SVM) model to forecast photovoltaic power.

PubMed

Malvoni, M; De Giorgi, M G; Congedo, P M

2016-12-01

The data concern the photovoltaic (PV) power, forecasted by a hybrid model that considers weather variations and applies a technique to reduce the input data size, as presented in the paper entitled "Photovoltaic forecast based on hybrid pca-lssvm using dimensionality reducted data" (M. Malvoni, M.G. De Giorgi, P.M. Congedo, 2015) [1]. The quadratic Renyi entropy criteria together with the principal component analysis (PCA) are applied to the Least Squares Support Vector Machines (LS-SVM) to predict the PV power in the day-ahead time frame. The data here shared represent the proposed approach results. Hourly PV power predictions for 1,3,6,12, 24 ahead hours and for different data reduction sizes are provided in Supplementary material.

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.

A group matrix representation relevant to scales of measurement of clinical disease states via stratified vectors.

PubMed

Sawamura, Jitsuki; Morishita, Shigeru; Ishigooka, Jun

2016-02-09

Previously, we applied basic group theory and related concepts to scales of measurement of clinical disease states and clinical findings (including laboratory data). To gain a more concrete comprehension, we here apply the concept of matrix representation, which was not explicitly exploited in our previous work. Starting with a set of orthonormal vectors, called the basis, an operator Rj (an N-tuple patient disease state at the j-th session) was expressed as a set of stratified vectors representing plural operations on individual components, so as to satisfy the group matrix representation. The stratified vectors containing individual unit operations were combined into one-dimensional square matrices [Rj]s. The [Rj]s meet the matrix representation of a group (ring) as a K-algebra. Using the same-sized matrix of stratified vectors, we can also express changes in the plural set of [Rj]s. The method is demonstrated on simple examples. Despite the incompleteness of our model, the group matrix representation of stratified vectors offers a formal mathematical approach to clinical medicine, aligning it with other branches of natural science.

Rotational polarities of sudden impulses in the magnetotail lobe

NASA Technical Reports Server (NTRS)

Kawano, H.; Yamamoto, T.; Kokubun, S.; Lepping, R. P.

1992-01-01

A sudden impulse (SI) is a sudden change in the magnetic field strength which is caused by a change in the solar wind pressure and is observed throughout the magnetosphere. In this report we have examined the rotations of the magnetic field vectors at times of SIs in the magnetotail lobe, by using IMP 6, 7, and 8 magnetometer data. The following properties have been found: (1) at the time of SI the arrowhead of the magnetic vector tends to rotate in one plane; (2) the plane of rotation tends to include the unperturbed magnetic field vector; (3) the plane of rotation tends to be aligned with the radial direction from the magnetotail axis; and (4) the magnetic vectors have a particular rotational polarity: when the plane of rotation is viewed so that the Sun is to the right of the viewed plane and the magnetotail axis is to the bottom, the arrowhead of the vector tends to rotate counterclockwise in this plane. These magnetic vector properties are consistent with those expected when part of an increase in solar wind lateral pressure squeezes the magnetotail axisymmetrically while moving tailward.

Search for heavy vector-like quarks coupling to light quarks in proton–proton collisions at s = 7   TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2012-05-01

This Letter presents a search for singly produced vector-like quarks, Q, coupling to light quarks, q. The search is sensitive to both charged current (CC) and neutral current (NC) processes, pp→Qq→Wqq' and pp→Qq→Zqq' with a leptonic decay of the vector gauge boson. In 1.04fb -1 of data taken in 2011 by the ATLAS experiment at a center-of-mass energy √s=7TeV, no evidence of such heavy vector-like quarks is observed above the expected Standard Model background. Limits on the heavy vector-like quark production cross section times branching ratio as a function of mass m Q are obtained. For a coupling κ qQ=v/mmore » Q, where v is the Higgs vacuum expectation value, 95% C.L. lower limits on the mass of a vector-like quark are set at 900 GeV and 760 GeV from CC and NC processes, respectively.« less

Structural Analysis of Biodiversity

PubMed Central

Sirovich, Lawrence; Stoeckle, Mark Y.; Zhang, Yu

2010-01-01

Large, recently-available genomic databases cover a wide range of life forms, suggesting opportunity for insights into genetic structure of biodiversity. In this study we refine our recently-described technique using indicator vectors to analyze and visualize nucleotide sequences. The indicator vector approach generates correlation matrices, dubbed Klee diagrams, which represent a novel way of assembling and viewing large genomic datasets. To explore its potential utility, here we apply the improved algorithm to a collection of almost 17000 DNA barcode sequences covering 12 widely-separated animal taxa, demonstrating that indicator vectors for classification gave correct assignment in all 11000 test cases. Indicator vector analysis revealed discontinuities corresponding to species- and higher-level taxonomic divisions, suggesting an efficient approach to classification of organisms from poorly-studied groups. As compared to standard distance metrics, indicator vectors preserve diagnostic character probabilities, enable automated classification of test sequences, and generate high-information density single-page displays. These results support application of indicator vectors for comparative analysis of large nucleotide data sets and raise prospect of gaining insight into broad-scale patterns in the genetic structure of biodiversity. PMID:20195371

Magnetic and gravity anomalies in the Americas

NASA Technical Reports Server (NTRS)

Braile, L. W.; Hinze, W. J.; Vonfrese, R. R. B. (Principal Investigator)

1981-01-01

The cleaning and magnetic tape storage of spherical Earth processing programs are reported. These programs include: NVERTSM which inverts total or vector magnetic anomaly data on a distribution of point dipoles in spherical coordinates; SMFLD which utilizes output from NVERTSM to compute total or vector magnetic anomaly fields for a distribution of point dipoles in spherical coordinates; NVERTG; and GFLD. Abstracts are presented for papers dealing with the mapping and modeling of magnetic and gravity anomalies, and with the verification of crustal components in satellite data.

Space Object Classification Using Fused Features of Time Series Data

NASA Astrophysics Data System (ADS)

Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.

In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.

Pulse Code Modulation (PCM) encoder handbook for Aydin Vector MMP-900 series system

NASA Technical Reports Server (NTRS)

Raphael, David

1995-01-01

This handbook explicates the hardware and software properties of a time division multiplex system. This system is used to sample analog and digital data. The data is then merged with frame synchronization information to produce a serial pulse coded modulation (PCM) bit stream. Information in this handbook is required by users to design congruous interface and attest effective utilization of this encoder system. Aydin Vector provides all of the components for these systems to Goddard Space Flight Center/Wallops Flight Facility.

Genomic Approaches for Detection and Treatment of Breast Cancer

DTIC Science & Technology

2006-07-01

display vectors to allow for both lytic and filamentous versions of the library. For lytic phage display, we chose the T7 -based vector T7Select®10-3b... phage , which do not display a FLAG epitope (data not shown). These data suggest that peptides can be displayed on the surface of T7 using this system...Auto-Antibodies as Breast Cancer Biomarkers To identify auto-antibodies that could be used as breast cancer biomarkers, we are generating a phage

Smisc - A collection of miscellaneous functions

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

Landon Sego, PNNL

2015-08-31

A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAsmore » d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an ".Rdata" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).« less

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates

USDA-ARS?s Scientific Manuscript database

Methods based on sequence data analysis facilitate the tracking of disease outbreaks, allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are used postfactum after an outbreak has happened. Here, we show that support vector machine a...

Vectorized multigrid Poisson solver for the CDC CYBER 205

NASA Technical Reports Server (NTRS)

Barkai, D.; Brandt, M. A.

1984-01-01

The full multigrid (FMG) method is applied to the two dimensional Poisson equation with Dirichlet boundary conditions. This has been chosen as a relatively simple test case for examining the efficiency of fully vectorizing of the multigrid method. Data structure and programming considerations and techniques are discussed, accompanied by performance details.

Model independent new physics analysis in Λ _b→ Λ μ ^+μ ^- decay

NASA Astrophysics Data System (ADS)

Das, Diganta

2018-03-01

We study the rare Λ _b→ Λ μ ^+μ ^- decay in the Standard Model and beyond. Beyond the Standard Model we include new vector and axial-vector operators, scalar and pseudo-scalar operators, and tensor operators in the effective Hamiltonian. Working in the helicity basis and using appropriate parametrization of the Λ _b → Λ hadronic matrix elements, we give expressions of hadronic and leptonic helicity amplitudes and derive expression of double differential branching ratio with respect to dilepton invariant mass squared and cosine of lepton angle. Appropriately integrating the differential branching ratio over the lepton angle, we obtain the longitudinal polarization fraction and the leptonic forward-backward asymmetry and sequentially study the observables in the presence of the new couplings. To analyze the implications of the new vector and axial-vector couplings, we follow the current global fits to b→ sμ ^+μ ^- data. While the impacts of scalar couplings can be significant, exclusive \\bar{B}→ X_sμ ^+μ ^- data imply stringent constraints on the tensor couplings and hence the effects on Λ _b→ Λ μ ^+μ ^- are negligible.

Polar decomposition for attitude determination from vector observations

NASA Technical Reports Server (NTRS)

Bar-Itzhack, Itzhack Y.

1993-01-01

This work treats the problem of weighted least squares fitting of a 3D Euclidean-coordinate transformation matrix to a set of unit vectors measured in the reference and transformed coordinates. A closed-form analytic solution to the problem is re-derived. The fact that the solution is the closest orthogonal matrix to some matrix defined on the measured vectors and their weights is clearly demonstrated. Several known algorithms for computing the analytic closed form solution are considered. An algorithm is discussed which is based on the polar decomposition of matrices into the closest unitary matrix to the decomposed matrix and a Hermitian matrix. A somewhat longer improved algorithm is suggested too. A comparison of several algorithms is carried out using simulated data as well as real data from the Upper Atmosphere Research Satellite. The comparison is based on accuracy and time consumption. It is concluded that the algorithms based on polar decomposition yield a simple although somewhat less accurate solution. The precision of the latter algorithms increase with the number of the measured vectors and with the accuracy of their measurement.

Genetic modification of human trabecular meshwork with lentiviral vectors.

PubMed

Loewen, N; Fautsch, M P; Peretz, M; Bahler, C K; Cameron, J D; Johnson, D H; Poeschla, E M

2001-11-20

Glaucoma, a group of optic neuropathies, is the leading cause of irreversible blindness. Neuronal apoptosis in glaucoma is primarily associated with high intraocular pressure caused by chronically impaired outflow of aqueous humor through the trabecular meshwork, a reticulum of mitotically inactive endothelial-like cells located in the angle of the anterior chamber. Anatomic, genetic, and expression profiling data suggest the possibility of using gene transfer to treat glaucomatous intraocular pressure dysregulation, but this approach will require stable genetic modification of the differentiated aqueous outflow tract. We injected transducing unit-normalized preparations of either of two lentiviral vectors or an oncoretroviral vector as a single bolus into the aqueous circulation of cultured human donor eyes, under perfusion conditions that mimicked natural anterior chamber flow and maintained viability ex vivo. Reporter gene expression was assessed in trabecular meshwork from 3 to 16 days after infusion of 1.0 x 10(8) transducing units of each vector. The oncoretroviral vector failed to transduce the trabecular meshwork. In contrast, feline immunodeficiency virus and human immunodeficiency virus vectors produced efficient, localized transduction of the trabecular meshwork in situ. The results demonstrate that lentiviral vectors permit efficient genetic modification of the human trabecular meshwork when delivered via the afferent aqueous circulation, a clinically accessible route. In addition, controlled comparisons in this study establish that feline and human immunodeficiency virus vectors are equivalently efficacious in delivering genes to this terminally differentiated human tissue.

Intramammary expression and therapeutic effect of a human lysozyme-expressing vector for treating bovine mastitis*

PubMed Central

Sun, Huai-Chang; Xue, Fang-Ming; Qian, Ke; Fang, Hao-Xia; Qiu, Hua-Lei; Zhang, Xin-Yu; Yin, Zhao-Hua

2006-01-01

To develop a gene therapy strategy for treating bovine mastitis, a new mammary-specific vector containing human lysozyme (hLYZ) cDNA and kanamycin resistance gene was constructed for intramammary expression and clinical studies. After one time acupuncture or intracisternal infusion of healthy cows with 400 μg of the p215C3LYZ vector, over 2.0 μg/ml of rhLYZ could be detected by enzymatic assay for about 3 weeks in the milk samples. Western blotting showed that rhLYZ secreted into milk samples from the vector-injected cows had molecular weight similar to that of the natural hLYZ in human colostrums. Twenty days after the primary injection, the quarters were re-injected with the same vector by quarter acupuncture and even higher concentrations of rhLYZ could be detected. Indirect competitive ELISA of milk samples showed that the vector injection did not induce detectable humoral immune response against hLYZ. Clinical studies showed that twice acupuncture of quarters with the p215C3LYZ vector had overt therapeutic effect on clinical and subclinical mastitis previously treated with antibiotics, including disappearance of clinical symptoms and relatively high microbiological cure rates. These data provide a solid rationale for using the vector to develop gene therapy for treating bovine mastitis. PMID:16532537

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

Mathematical modelling of vector-borne diseases and insecticide resistance evolution.

PubMed

Gabriel Kuniyoshi, Maria Laura; Pio Dos Santos, Fernando Luiz

2017-01-01

Vector-borne diseases are important public health issues and, consequently, in silico models that simulate them can be useful. The susceptible-infected-recovered (SIR) model simulates the population dynamics of an epidemic and can be easily adapted to vector-borne diseases, whereas the Hardy-Weinberg model simulates allele frequencies and can be used to study insecticide resistance evolution. The aim of the present study is to develop a coupled system that unifies both models, therefore enabling the analysis of the effects of vector population genetics on the population dynamics of an epidemic. Our model consists of an ordinary differential equation system. We considered the populations of susceptible, infected and recovered humans, as well as susceptible and infected vectors. Concerning these vectors, we considered a pair of alleles, with complete dominance interaction that determined the rate of mortality induced by insecticides. Thus, we were able to separate the vectors according to the genotype. We performed three numerical simulations of the model. In simulation one, both alleles conferred the same mortality rate values, therefore there was no resistant strain. In simulations two and three, the recessive and dominant alleles, respectively, conferred a lower mortality. Our numerical results show that the genetic composition of the vector population affects the dynamics of human diseases. We found that the absolute number of vectors and the proportion of infected vectors are smaller when there is no resistant strain, whilst the ratio of infected people is larger in the presence of insecticide-resistant vectors. The dynamics observed for infected humans in all simulations has a very similar shape to real epidemiological data. The population genetics of vectors can affect epidemiological dynamics, and the presence of insecticide-resistant strains can increase the number of infected people. Based on the present results, the model is a basis for development of other models and for investigating population dynamics.

Preliminary calibration plan for the Advanced Particles and Field Observatory (APAFO) magnetometer experiment

NASA Technical Reports Server (NTRS)

Voorhies, C. V.; Langel, R. A.; Slavin, J.; Lancaster, E. R.; Jones, S.

1991-01-01

Prelaunch and postlaunch calibration plans for the APAFO magnetometer experiment are presented. A study of tradeoffs between boom length and spacecraft field is described; the results are summarized. The prelaunch plan includes: calibration of the Vector Fluxgate Magnetometer (VFM), Star Sensors, and Scalar Helium Magnetometer (SHM); optical bench integration; and acquisition of basic spacecraft field data. Postlaunch calibration has two phases. In phase one, SHM data are used to calibrate the VFM, total vector magnetic field data are used to calibrate a physical model of the spacecraft field, and both calibrations are refined by iteration. In phase two, corrected vector data are transformed into geocentric coordinates, previously undetected spacecraft fields are isolated, and initial geomagnetic field models are computed. Provided the SHM is accurate to the required 1.0 nT and can be used to calibrate the VFM to the required 3.0- nT accuracy, the tradeoff study indicates that a 12 m boom and a spacecraft field model uncertainty of 5 percent together allow the 1.0 nT spacecraft field error requirement to be met.

Color and Vector Flow Imaging in Parallel Ultrasound With Sub-Nyquist Sampling.

PubMed

Madiena, Craig; Faurie, Julia; Poree, Jonathan; Garcia, Damien; Garcia, Damien; Madiena, Craig; Faurie, Julia; Poree, Jonathan

2018-05-01

RF acquisition with a high-performance multichannel ultrasound system generates massive data sets in short periods of time, especially in "ultrafast" ultrasound when digital receive beamforming is required. Sampling at a rate four times the carrier frequency is the standard procedure since this rule complies with the Nyquist-Shannon sampling theorem and simplifies quadrature sampling. Bandpass sampling (or undersampling) outputs a bandpass signal at a rate lower than the maximal frequency without harmful aliasing. Advantages over Nyquist sampling are reduced storage volumes and data workflow, and simplified digital signal processing tasks. We used RF undersampling in color flow imaging (CFI) and vector flow imaging (VFI) to decrease data volume significantly (factor of 3 to 13 in our configurations). CFI and VFI with Nyquist and sub-Nyquist samplings were compared in vitro and in vivo. The estimate errors due to undersampling were small or marginal, which illustrates that Doppler and vector Doppler images can be correctly computed with a drastically reduced amount of RF samples. Undersampling can be a method of choice in CFI and VFI to avoid information overload and reduce data transfer and storage.

Recurrent evolution of host and vector association in bacteria of the Borrelia burgdorferi sensu lato species complex.

PubMed

Becker, Noémie S; Margos, Gabriele; Blum, Helmut; Krebs, Stefan; Graf, Alexander; Lane, Robert S; Castillo-Ramírez, Santiago; Sing, Andreas; Fingerle, Volker

2016-09-15

The Borrelia burgdorferi sensu lato (s.l.) species complex consists of tick-transmitted bacteria and currently comprises approximately 20 named and proposed genospecies some of which are known to cause Lyme Borreliosis. Species have been defined via genetic distances and ecological niches they occupy. Understanding the evolutionary relationship of species of the complex is fundamental to explaining patterns of speciation. This in turn forms a crucial basis to frame testable hypotheses concerning the underlying processes including host and vector adaptations. Illumina Technology was used to obtain genome-wide sequence data for 93 strains of 14 named genospecies of the B. burgdorferi species complex and genomic data already published for 18 additional strain (including one new species) was added. Phylogenetic reconstruction based on 114 orthologous single copy genes shows that the genospecies represent clearly distinguishable taxa with recent and still ongoing speciation events apparent in Europe and Asia. The position of Borrelia species in the phylogeny is consistent with host associations constituting a major driver for speciation. Interestingly, the data also demonstrate that vector associations are an additional driver for diversification in this tick-borne species complex. This is particularly obvious in B. bavariensis, a rodent adapted species that has diverged from the bird-associated B. garinii most likely in Asia. It now consists of two populations one of which most probably invaded Europe following adaptation to a new vector (Ixodes ricinus) and currently expands its distribution range. The results imply that genotypes/species with novel properties regarding host or vector associations have evolved recurrently during the history of the species complex and may emerge at any time. We suggest that the finding of vector associations as a driver for diversification may be a general pattern for tick-borne pathogens. The core genome analysis presented here provides an important source for investigations of the underlying mechanisms of speciation in tick-borne pathogens.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: SHARPs - Space-Weather HMI Active Region Patches

NASA Astrophysics Data System (ADS)

Bobra, M. G.; Sun, X.; Hoeksema, J. T.; Turmon, M.; Liu, Y.; Hayashi, K.; Barnes, G.; Leka, K. D.

2014-09-01

A new data product from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) called Space-weather HMI Active Region Patches ( SHARPs) is now available. SDO/HMI is the first space-based instrument to map the full-disk photospheric vector magnetic field with high cadence and continuity. The SHARP data series provide maps in patches that encompass automatically tracked magnetic concentrations for their entire lifetime; map quantities include the photospheric vector magnetic field and its uncertainty, along with Doppler velocity, continuum intensity, and line-of-sight magnetic field. Furthermore, keywords in the SHARP data series provide several parameters that concisely characterize the magnetic-field distribution and its deviation from a potential-field configuration. These indices may be useful for active-region event forecasting and for identifying regions of interest. The indices are calculated per patch and are available on a twelve-minute cadence. Quick-look data are available within approximately three hours of observation; definitive science products are produced approximately five weeks later. SHARP data are available at jsoc.stanford.edu and maps are available in either of two different coordinate systems. This article describes the SHARP data products and presents examples of SHARP data and parameters.

Real-time individualized training vectors for experiential learning.

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

Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie

2011-01-01

Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD)more » project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.« less

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

DOEpatents

Tobin, Kenneth W; Karnowski, Thomas P; Chaum, Edward

2013-08-06

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Spaceflight Ka-Band High-Rate Radiation-Hard Modulator

NASA Technical Reports Server (NTRS)

Jaso, Jeffery M.

2011-01-01

A document discusses the creation of a Ka-band modulator developed specifically for the NASA/GSFC Solar Dynamics Observatory (SDO). This flight design consists of a high-bandwidth, Quadriphase Shift Keying (QPSK) vector modulator with radiation-hardened, high-rate driver circuitry that receives I and Q channel data. The radiationhard design enables SDO fs Ka-band communications downlink system to transmit 130 Mbps (300 Msps after data encoding) of science instrument data to the ground system continuously throughout the mission fs minimum life of five years. The low error vector magnitude (EVM) of the modulator lowers the implementation loss of the transmitter in which it is used, thereby increasing the overall communication system link margin. The modulator comprises a component within the SDO transmitter, and meets the following specifications over a 0 to 40 C operational temperature range: QPSK/OQPSK modulator, 300-Msps symbol rate, 26.5-GHz center frequency, error vector magnitude less than or equal to 10 percent rms, and compliance with the NTIA (National Telecommunications and Information Administration) spectral mask.

Modelling Rift Valley fever (RVF) disease vector habitats using active and passive remote sensing systems

NASA Technical Reports Server (NTRS)

Ambrosia, Vincent G.; Linthicum, K. G.; Bailey, C. L.; Sebesta, P.

1989-01-01

The NASA Ames Ecosystem Science and Technology Branch and the U.S. Army Medical Research Institute of Infectious Diseases are conducting research to detect Rift Valley fever (RVF) vector habitats in eastern Africa using active and passive remote-sensing. The normalized difference vegetation index (NDVI) calculated from Landsat TM and SPOT data is used to characterize the vegetation common to the Aedes mosquito. Relationships have been found between the highest NDVI and the 'dambo' habitat areas near Riuru, Kenya on both wet and dry data. High NDVI values, when combined with the vegetation classifications, are clearly related to the areas of vector habitats. SAR data have been proposed for use during the rainy season when optical systems are of minimal use and the short frequency and duration of the optimum RVF mosquito habitat conditions necessitate rapid evaluation of the vegetation/moisture conditions; only then can disease potential be stemmed and eradication efforts initiated.

Vector intensity reconstruction using the data completion method.

PubMed

Langrenne, Christophe; Garcia, Alexandre

2013-04-01

This paper presents an application of the data completion method (DCM) for vector intensity reconstructions. A mobile array of 36 pressure-pressure probes (72 microphones) is used to perform measurements near a planar surface. Nevertheless, since the proposed method is based on integral formulations, DCM can be applied with any kind of geometry. This method requires the knowledge of Cauchy data (pressure and velocity) on a part of the boundary of an empty domain in order to evaluate pressure and velocity on the remaining part of the boundary. Intensity vectors are calculated in the interior domain surrounded by the measurement array. This inverse acoustic problem requires the use of a regularization method to obtain a realistic solution. An experiment in a closed wooden car trunk mock-up excited by a shaker and two loudspeakers is presented. In this case, where the volume of the mock-up is small (0.61 m(3)), standing-waves and fluid structure interactions appear and show that DCM is a powerful tool to identify sources in a confined space.

Using Support Vector Machines to Automatically Extract Open Water Signatures from POLDER Multi-Angle Data Over Boreal Regions

NASA Technical Reports Server (NTRS)

Pierce, J.; Diaz-Barrios, M.; Pinzon, J.; Ustin, S. L.; Shih, P.; Tournois, S.; Zarco-Tejada, P. J.; Vanderbilt, V. C.; Perry, G. L.; Brass, James A. (Technical Monitor)

2002-01-01

This study used Support Vector Machines to classify multiangle POLDER data. Boreal wetland ecosystems cover an estimated 90 x 10(exp 6) ha, about 36% of global wetlands, and are a major source of trace gases emissions to the atmosphere. Four to 20 percent of the global emission of methane to the atmosphere comes from wetlands north of 4 degrees N latitude. Large uncertainties in emissions exist because of large spatial and temporal variation in the production and consumption of methane. Accurate knowledge of the areal extent of open water and inundated vegetation is critical to estimating magnitudes of trace gas emissions. Improvements in land cover mapping have been sought using physical-modeling approaches, neural networks, and active microwave, examples that demonstrate the difficulties of separating open water, inundated vegetation and dry upland vegetation. Here we examine the feasibility of using a support vector machine to classify POLDER data representing open water, inundated vegetation and dry upland vegetation.

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

Tuning the cache memory usage in tomographic reconstruction on standard computers with Advanced Vector eXtensions (AVX)

PubMed Central

Agulleiro, Jose-Ignacio; Fernandez, Jose-Jesus

2015-01-01

Cache blocking is a technique widely used in scientific computing to minimize the exchange of information with main memory by reusing the data kept in cache memory. In tomographic reconstruction on standard computers using vector instructions, cache blocking turns out to be central to optimize performance. To this end, sinograms of the tilt-series and slices of the volumes to be reconstructed have to be divided into small blocks that fit into the different levels of cache memory. The code is then reorganized so as to operate with a block as much as possible before proceeding with another one. This data article is related to the research article titled Tomo3D 2.0 – Exploitation of Advanced Vector eXtensions (AVX) for 3D reconstruction (Agulleiro and Fernandez, 2015) [1]. Here we present data of a thorough study of the performance of tomographic reconstruction by varying cache block sizes, which allows derivation of expressions for their automatic quasi-optimal tuning. PMID:26217710

Tuning the cache memory usage in tomographic reconstruction on standard computers with Advanced Vector eXtensions (AVX).

PubMed

Agulleiro, Jose-Ignacio; Fernandez, Jose-Jesus

2015-06-01

Cache blocking is a technique widely used in scientific computing to minimize the exchange of information with main memory by reusing the data kept in cache memory. In tomographic reconstruction on standard computers using vector instructions, cache blocking turns out to be central to optimize performance. To this end, sinograms of the tilt-series and slices of the volumes to be reconstructed have to be divided into small blocks that fit into the different levels of cache memory. The code is then reorganized so as to operate with a block as much as possible before proceeding with another one. This data article is related to the research article titled Tomo3D 2.0 - Exploitation of Advanced Vector eXtensions (AVX) for 3D reconstruction (Agulleiro and Fernandez, 2015) [1]. Here we present data of a thorough study of the performance of tomographic reconstruction by varying cache block sizes, which allows derivation of expressions for their automatic quasi-optimal tuning.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

Behaviour of mathematics and physics students in solving problem of Vector-Physics context

NASA Astrophysics Data System (ADS)

Sardi; Rizal, M.; Mansyur, J.

2018-04-01

This research aimed to describe behaviors of mathematics and physics students in solving problem of the vector concept in physics context. The subjects of the research were students who enrolled in Mathematics Education Study Program and Physics Education Study Program of FKIP Universitas Tadulako. The selected participants were students who received the highest score in vector fundamental concept test in each study program. The data were collected through thinking-aloud activity followed by an interview. The steps of data analysis included data reduction, display, and conclusion drawing. The credibility of the data was tested using a triangulation method. Based on the data analysis, it can be concluded that the two groups of students did not show fundamental differences in problem-solving behavior, especially in the steps of understanding the problem (identifying, collecting and analyzing facts and information), planning (looking for alternative strategies) and conducting the alternative strategy. The two groups were differ only in the evaluation aspect. In contrast to Physics students who evaluated their answer, mathematics students did not conducted an evaluation activity on their work. However, the difference was not caused by the differences in background knowledge.