Group prioritisation with unknown expert weights in incomplete linguistic context

NASA Astrophysics Data System (ADS)

Cheng, Dong; Cheng, Faxin; Zhou, Zhili; Wang, Juan

2017-09-01

In this paper, we study a group prioritisation problem in situations when the expert weights are completely unknown and their judgement preferences are linguistic and incomplete. Starting from the theory of relative entropy (RE) and multiplicative consistency, an optimisation model is provided for deriving an individual priority vector without estimating the missing value(s) of an incomplete linguistic preference relation. In order to address the unknown expert weights in the group aggregating process, we define two new kinds of expert weight indicators based on RE: proximity entropy weight and similarity entropy weight. Furthermore, a dynamic-adjusting algorithm (DAA) is proposed to obtain an objective expert weight vector and capture the dynamic properties involved in it. Unlike the extant literature of group prioritisation, the proposed RE approach does not require pre-allocation of expert weights and can solve incomplete preference relations. An interesting finding is that once all the experts express their preference relations, the final expert weight vector derived from the DAA is fixed irrespective of the initial settings of expert weights. Finally, an application example is conducted to validate the effectiveness and robustness of the RE approach.

The parallel-antiparallel signal difference in double-wave-vector diffusion-weighted MR at short mixing times: A phase evolution perspective

NASA Astrophysics Data System (ADS)

Finsterbusch, Jürgen

2011-01-01

Experiments with two diffusion weightings applied in direct succession in a single acquisition, so-called double- or two-wave-vector diffusion-weighting (DWV) experiments at short mixing times, have been shown to be a promising tool to estimate cell or compartment sizes, e.g. in living tissue. The basic theory for such experiments predicts that the signal decays for parallel and antiparallel wave vector orientations differ by a factor of three for small wave vectors. This seems to be surprising because in standard, single-wave-vector experiments the polarity of the diffusion weighting has no influence on the signal attenuation. Thus, the question how this difference can be understood more pictorially is often raised. In this rather educational manuscript, the phase evolution during a DWV experiment for simple geometries, e.g. diffusion between parallel, impermeable planes oriented perpendicular to the wave vectors, is considered step-by-step and demonstrates how the signal difference develops. Considering the populations of the phase distributions obtained, the factor of three between the signal decays which is predicted by the theory can be reproduced. Furthermore, the intermediate signal decay for orthogonal wave vector orientations can be derived when investigating diffusion in a box. Thus, the presented “phase gymnastics” approach may help to understand the signal modulation observed in DWV experiments at short mixing times.

Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic

NASA Astrophysics Data System (ADS)

Sukono, Sidi, Pramono; Bon, Abdul Talib bin; Supian, Sudradjat

2017-03-01

The problems of investing in financial assets are to choose a combination of weighting a portfolio can be maximized return expectations and minimizing the risk. This paper discusses the modeling of Mean-VaR portfolio optimization by risk tolerance, when square-shaped utility functions. It is assumed that the asset return has a certain distribution, and the risk of the portfolio is measured using the Value-at-Risk (VaR). So, the process of optimization of the portfolio is done based on the model of Mean-VaR portfolio optimization model for the Mean-VaR done using matrix algebra approach, and the Lagrange multiplier method, as well as Khun-Tucker. The results of the modeling portfolio optimization is in the form of a weighting vector equations depends on the vector mean return vector assets, identities, and matrix covariance between return of assets, as well as a factor in risk tolerance. As an illustration of numeric, analyzed five shares traded on the stock market in Indonesia. Based on analysis of five stocks return data gained the vector of weight composition and graphics of efficient surface of portfolio. Vector composition weighting weights and efficient surface charts can be used as a guide for investors in decisions to invest.

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

Strain Variation along Cimandiri Fault, West Java Based on Continuous and Campaign GPS Observation From 2006-2016

NASA Astrophysics Data System (ADS)

Safitri, A. A.; Meilano, I.; Gunawan, E.; Abidin, H. Z.; Efendi, J.; Kriswati, E.

2018-03-01

The Cimandiri fault which is running in the direction from Pelabuhan Ratu to Padalarang is the longest fault in West Java with several previous shallow earthquakes in the last 20 years. By using continues and campaign GPS observation from 2006-2016, we obtain the deformation pattern along the fault through the variation of strain tensor. We use the velocity vector of GPS station which is fixed in stable International Terrestrial Reference Frame 2008 to calculate horizontal strain tensor. Least Square Collocation is applied to produce widely dense distributed velocity vector and optimum scale factor for the Least Square Weighting matrix. We find that the strain tensor tend to change from dominantly contraction in the west to dominantly extension to the east of fault. Both the maximum shear strain and dilatation show positive value along the fault and increasing from the west to the east. The findings of strain tensor variation along Cimandiri Fault indicate the post seismic effect of the 2006 Java Earthquake.

Application of Numerical Integration and Data Fusion in Unit Vector Method

NASA Astrophysics Data System (ADS)

Zhang, J.

2012-01-01

The Unit Vector Method (UVM) is a series of orbit determination methods which are designed by Purple Mountain Observatory (PMO) and have been applied extensively. It gets the conditional equations for different kinds of data by projecting the basic equation to different unit vectors, and it suits for weighted process for different kinds of data. The high-precision data can play a major role in orbit determination, and accuracy of orbit determination is improved obviously. The improved UVM (PUVM2) promoted the UVM from initial orbit determination to orbit improvement, and unified the initial orbit determination and orbit improvement dynamically. The precision and efficiency are improved further. In this thesis, further research work has been done based on the UVM: Firstly, for the improvement of methods and techniques for observation, the types and decision of the observational data are improved substantially, it is also asked to improve the decision of orbit determination. The analytical perturbation can not meet the requirement. So, the numerical integration for calculating the perturbation has been introduced into the UVM. The accuracy of dynamical model suits for the accuracy of the real data, and the condition equations of UVM are modified accordingly. The accuracy of orbit determination is improved further. Secondly, data fusion method has been introduced into the UVM. The convergence mechanism and the defect of weighted strategy have been made clear in original UVM. The problem has been solved in this method, the calculation of approximate state transition matrix is simplified and the weighted strategy has been improved for the data with different dimension and different precision. Results of orbit determination of simulation and real data show that the work of this thesis is effective: (1) After the numerical integration has been introduced into the UVM, the accuracy of orbit determination is improved obviously, and it suits for the high-accuracy data of available observation apparatus. Compare with the classical differential improvement with the numerical integration, its calculation speed is also improved obviously. (2) After data fusion method has been introduced into the UVM, weighted distribution accords rationally with the accuracy of different kinds of data, all data are fully used and the new method is also good at numerical stability and rational weighted distribution.

Telomerase-mediated life-span extension of human primary fibroblasts by human artificial chromosome (HAC) vector

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

Shitara, Shingo; Kakeda, Minoru; Nagata, Keiko

2008-05-09

Telomerase-mediated life-span extension enables the expansion of normal cells without malignant transformation, and thus has been thought to be useful in cell therapies. Currently, integrating vectors including the retrovirus are used for human telomerase reverse transcriptase (hTERT)-mediated expansion of normal cells; however, the use of these vectors potentially causes unexpected insertional mutagenesis and/or activation of oncogenes. Here, we established normal human fibroblast (hPF) clones retaining non-integrating human artificial chromosome (HAC) vectors harboring the hTERT expression cassette. In hTERT-HAC/hPF clones, we observed the telomerase activity and the suppression of senescent-associated SA-{beta}-galactosidase activity. Furthermore, the hTERT-HAC/hPF clones continued growing beyond 120 daysmore » after cloning, whereas the hPF clones retaining the silent hTERT-HAC senesced within 70 days. Thus, hTERT-HAC-mediated episomal expression of hTERT allows the extension of the life-span of human primary cells, implying that gene delivery by non-integrating HAC vectors can be used to control cellular proliferative capacity of primary cultured cells.« less

SSE-based Thomas algorithm for quasi-block-tridiagonal linear equation systems, optimized for small dense blocks

NASA Astrophysics Data System (ADS)

Barnaś, Dawid; Bieniasz, Lesław K.

2017-07-01

We have recently developed a vectorized Thomas solver for quasi-block tridiagonal linear algebraic equation systems using Streaming SIMD Extensions (SSE) and Advanced Vector Extensions (AVX) in operations on dense blocks [D. Barnaś and L. K. Bieniasz, Int. J. Comput. Meth., accepted]. The acceleration caused by vectorization was observed for large block sizes, but was less satisfactory for small blocks. In this communication we report on another version of the solver, optimized for small blocks of size up to four rows and/or columns.

Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO

PubMed Central

Zhu, Zhichuan; Zhao, Qingdong; Liu, Liwei; Zhang, Lijuan

2018-01-01

Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved good results therein. Based on grid search, however, the MKL-SVM algorithm needs long optimization time in course of parameter optimization; also its identification accuracy depends on the fineness of grid. In the paper, swarm intelligence is introduced and the Particle Swarm Optimization (PSO) is combined with MKL-SVM algorithm to be MKL-SVM-PSO algorithm so as to realize global optimization of parameters rapidly. In order to obtain the global optimal solution, different inertia weights such as constant inertia weight, linear inertia weight, and nonlinear inertia weight are applied to pulmonary nodules recognition. The experimental results show that the model training time of the proposed MKL-SVM-PSO algorithm is only 1/7 of the training time of the MKL-SVM grid search algorithm, achieving better recognition effect. Moreover, Euclidean norm of normalized error vector is proposed to measure the proximity between the average fitness curve and the optimal fitness curve after convergence. Through statistical analysis of the average of 20 times operation results with different inertial weights, it can be seen that the dynamic inertial weight is superior to the constant inertia weight in the MKL-SVM-PSO algorithm. In the dynamic inertial weight algorithm, the parameter optimization time of nonlinear inertia weight is shorter; the average fitness value after convergence is much closer to the optimal fitness value, which is better than the linear inertial weight. Besides, a better nonlinear inertial weight is verified. PMID:29853983

Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO.

PubMed

Li, Yang; Zhu, Zhichuan; Hou, Alin; Zhao, Qingdong; Liu, Liwei; Zhang, Lijuan

2018-01-01

Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved good results therein. Based on grid search, however, the MKL-SVM algorithm needs long optimization time in course of parameter optimization; also its identification accuracy depends on the fineness of grid. In the paper, swarm intelligence is introduced and the Particle Swarm Optimization (PSO) is combined with MKL-SVM algorithm to be MKL-SVM-PSO algorithm so as to realize global optimization of parameters rapidly. In order to obtain the global optimal solution, different inertia weights such as constant inertia weight, linear inertia weight, and nonlinear inertia weight are applied to pulmonary nodules recognition. The experimental results show that the model training time of the proposed MKL-SVM-PSO algorithm is only 1/7 of the training time of the MKL-SVM grid search algorithm, achieving better recognition effect. Moreover, Euclidean norm of normalized error vector is proposed to measure the proximity between the average fitness curve and the optimal fitness curve after convergence. Through statistical analysis of the average of 20 times operation results with different inertial weights, it can be seen that the dynamic inertial weight is superior to the constant inertia weight in the MKL-SVM-PSO algorithm. In the dynamic inertial weight algorithm, the parameter optimization time of nonlinear inertia weight is shorter; the average fitness value after convergence is much closer to the optimal fitness value, which is better than the linear inertial weight. Besides, a better nonlinear inertial weight is verified.

Chinese Text Summarization Algorithm Based on Word2vec

NASA Astrophysics Data System (ADS)

Chengzhang, Xu; Dan, Liu

2018-02-01

In order to extract some sentences that can cover the topic of a Chinese article, a Chinese text summarization algorithm based on Word2vec is used in this paper. Words in an article are represented as vectors trained by Word2vec, the weight of each word, the sentence vector and the weight of each sentence are calculated by combining word-sentence relationship with graph-based ranking model. Finally the summary is generated on the basis of the final sentence vector and the final weight of the sentence. The experimental results on real datasets show that the proposed algorithm has a better summarization quality compared with TF-IDF and TextRank.

Vectorization of a classical trajectory code on a floating point systems, Inc. Model 164 attached processor.

PubMed

Kraus, Wayne A; Wagner, Albert F

1986-04-01

A triatomic classical trajectory code has been modified by extensive vectorization of the algorithms to achieve much improved performance on an FPS 164 attached processor. Extensive timings on both the FPS 164 and a VAX 11/780 with floating point accelerator are presented as a function of the number of trajectories simultaneously run. The timing tests involve a potential energy surface of the LEPS variety and trajectories with 1000 time steps. The results indicate that vectorization results in timing improvements on both the VAX and the FPS. For larger numbers of trajectories run simultaneously, up to a factor of 25 improvement in speed occurs between VAX and FPS vectorized code. Copyright © 1986 John Wiley & Sons, Inc.

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.

Breaking the polar-nonpolar division in solvation free energy prediction.

PubMed

Wang, Bao; Wang, Chengzhang; Wu, Kedi; Wei, Guo-Wei

2018-02-05

Implicit solvent models divide solvation free energies into polar and nonpolar additive contributions, whereas polar and nonpolar interactions are inseparable and nonadditive. We present a feature functional theory (FFT) framework to break this ad hoc division. The essential ideas of FFT are as follows: (i) representability assumption: there exists a microscopic feature vector that can uniquely characterize and distinguish one molecule from another; (ii) feature-function relationship assumption: the macroscopic features, including solvation free energy, of a molecule is a functional of microscopic feature vectors; and (iii) similarity assumption: molecules with similar microscopic features have similar macroscopic properties, such as solvation free energies. Based on these assumptions, solvation free energy prediction is carried out in the following protocol. First, we construct a molecular microscopic feature vector that is efficient in characterizing the solvation process using quantum mechanics and Poisson-Boltzmann theory. Microscopic feature vectors are combined with macroscopic features, that is, physical observable, to form extended feature vectors. Additionally, we partition a solvation dataset into queries according to molecular compositions. Moreover, for each target molecule, we adopt a machine learning algorithm for its nearest neighbor search, based on the selected microscopic feature vectors. Finally, from the extended feature vectors of obtained nearest neighbors, we construct a functional of solvation free energy, which is employed to predict the solvation free energy of the target molecule. The proposed FFT model has been extensively validated via a large dataset of 668 molecules. The leave-one-out test gives an optimal root-mean-square error (RMSE) of 1.05 kcal/mol. FFT predictions of SAMPL0, SAMPL1, SAMPL2, SAMPL3, and SAMPL4 challenge sets deliver the RMSEs of 0.61, 1.86, 1.64, 0.86, and 1.14 kcal/mol, respectively. Using a test set of 94 molecules and its associated training set, the present approach was carefully compared with a classic solvation model based on weighted solvent accessible surface area. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Novel strategies to construct complex synthetic vectors to produce DNA molecular weight standards.

PubMed

Chen, Zhe; Wu, Jianbing; Li, Xiaojuan; Ye, Chunjiang; Wenxing, He

2009-05-01

DNA molecular weight standards (DNA markers, nucleic acid ladders) are commonly used in molecular biology laboratories as references to estimate the size of various DNA samples in electrophoresis process. One method of DNA marker production is digestion of synthetic vectors harboring multiple DNA fragments of known sizes by restriction enzymes. In this article, we described three novel strategies-sequential DNA fragment ligation, screening of ligation products by polymerase chain reaction (PCR) with end primers, and "small fragment accumulation"-for constructing complex synthetic vectors and minimizing the mass differences between DNA fragments produced from restrictive digestion of synthetic vectors. The strategy could be applied to construct various complex synthetic vectors to produce any type of low-range DNA markers, usually available commercially. In addition, the strategy is useful for single-step ligation of multiple DNA fragments for construction of complex synthetic vectors and other applications in molecular biology field.

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.

Attitude Determination Using Two Vector Measurements

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1998-01-01

Many spacecraft attitude determination methods use exactly two vector measurements. The two vectors are typically the unit vector to the Sun and the Earth's magnetic field vector for coarse "sun-mag" attitude determination or unit vectors to two stars tracked by two star trackers for fine attitude determination. TRIAD, the earliest published algorithm for determining spacecraft attitude from two vector measurements, has been widely used in both ground-based and onboard attitude determination. Later attitude determination methods have been based on Wahba's optimality criterion for n arbitrarily weighted observations. The solution of Wahba's problem is somewhat difficult in the general case, but there is a simple closed-form solution in the two-observation case. This solution reduces to the TRIAD solution for certain choices of measurement weights. This paper presents and compares these algorithms as well as sub-optimal algorithms proposed by Bar-Itzhack, Harman, and Reynolds. Some new results will be presented, but the paper is primarily a review and tutorial.

Vector-Vector Scattering on the Lattice

NASA Astrophysics Data System (ADS)

Romero-López, Fernando; Urbach, Carsten; Rusetsky, Akaki

2018-03-01

In this work we present an extension of the LüScher formalism to include the interaction of particles with spin, focusing on the scattering of two vector particles. The derived formalism will be applied to Scalar QED in the Higgs Phase, where the U(1) gauge boson acquires mass.

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Rajnarayan, Dev (Inventor); Sturdza, Peter (Inventor)

2016-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For an instability mode in the plurality of instability modes, a covariance vector is determined. A predicted local instability growth rate at the point is determined using the covariance vector and the vector of regressor weights. Based on the predicted local instability growth rate, an n-factor envelope at the point is determined.

Minimum Variance Distortionless Response Beamformer with Enhanced Nulling Level Control via Dynamic Mutated Artificial Immune System

PubMed Central

Kiong, Tiong Sieh; Salem, S. Balasem; Paw, Johnny Koh Siaw; Sankar, K. Prajindra

2014-01-01

In smart antenna applications, the adaptive beamforming technique is used to cancel interfering signals (placing nulls) and produce or steer a strong beam toward the target signal according to the calculated weight vectors. Minimum variance distortionless response (MVDR) beamforming is capable of determining the weight vectors for beam steering; however, its nulling level on the interference sources remains unsatisfactory. Beamforming can be considered as an optimization problem, such that optimal weight vector should be obtained through computation. Hence, in this paper, a new dynamic mutated artificial immune system (DM-AIS) is proposed to enhance MVDR beamforming for controlling the null steering of interference and increase the signal to interference noise ratio (SINR) for wanted signals. PMID:25003136

Minimum variance distortionless response beamformer with enhanced nulling level control via dynamic mutated artificial immune system.

PubMed

Kiong, Tiong Sieh; Salem, S Balasem; Paw, Johnny Koh Siaw; Sankar, K Prajindra; Darzi, Soodabeh

2014-01-01

In smart antenna applications, the adaptive beamforming technique is used to cancel interfering signals (placing nulls) and produce or steer a strong beam toward the target signal according to the calculated weight vectors. Minimum variance distortionless response (MVDR) beamforming is capable of determining the weight vectors for beam steering; however, its nulling level on the interference sources remains unsatisfactory. Beamforming can be considered as an optimization problem, such that optimal weight vector should be obtained through computation. Hence, in this paper, a new dynamic mutated artificial immune system (DM-AIS) is proposed to enhance MVDR beamforming for controlling the null steering of interference and increase the signal to interference noise ratio (SINR) for wanted signals.

Nonlinear Deep Kernel Learning for Image Annotation.

PubMed

Jiu, Mingyuan; Sahbi, Hichem

2017-02-08

Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

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

NASA Technical Reports Server (NTRS)

Bates, Lisa B.; Young, David T.

2012-01-01

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

Extensions of the standard model

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

Ramond, P.

1983-01-01

In these lectures we focus on several issues that arise in theoretical extensions of the standard model. First we describe the kinds of fermions that can be added to the standard model without affecting known phenomenology. We focus in particular on three types: the vector-like completion of the existing fermions as would be predicted by a Kaluza-Klein type theory, which we find cannot be realistically achieved without some chiral symmetry; fermions which are vector-like by themselves, such as do appear in supersymmetric extensions, and finally anomaly-free chiral sets of fermions. We note that a chiral symmetry, such as the Peccei-Quinnmore » symmetry can be used to produce a vector-like theory which, at scales less than M/sub W/, appears to be chiral. Next, we turn to the analysis of the second hierarchy problem which arises in Grand Unified extensions of the standard model, and plays a crucial role in proton decay of supersymmetric extensions. We review the known mechanisms for avoiding this problem and present a new one which seems to lead to the (family) triplication of the gauge group. Finally, this being a summer school, we present a list of homework problems. 44 references.« less

Optimal cue integration in ants.

PubMed

Wystrach, Antoine; Mangan, Michael; Webb, Barbara

2015-10-07

In situations with redundant or competing sensory information, humans have been shown to perform cue integration, weighting different cues according to their certainty in a quantifiably optimal manner. Ants have been shown to merge the directional information available from their path integration (PI) and visual memory, but as yet it is not clear that they do so in a way that reflects the relative certainty of the cues. In this study, we manipulate the variance of the PI home vector by allowing ants (Cataglyphis velox) to run different distances and testing their directional choice when the PI vector direction is put in competition with visual memory. Ants show progressively stronger weighting of their PI direction as PI length increases. The weighting is quantitatively predicted by modelling the expected directional variance of home vectors of different lengths and assuming optimal cue integration. However, a subsequent experiment suggests ants may not actually compute an internal estimate of the PI certainty, but are using the PI home vector length as a proxy. © 2015 The Author(s).

Tomo3D 2.0--exploitation of advanced vector extensions (AVX) for 3D reconstruction.

PubMed

Agulleiro, Jose-Ignacio; Fernandez, Jose-Jesus

2015-02-01

Tomo3D is a program for fast tomographic reconstruction on multicore computers. Its high speed stems from code optimization, vectorization with Streaming SIMD Extensions (SSE), multithreading and optimization of disk access. Recently, Advanced Vector eXtensions (AVX) have been introduced in the x86 processor architecture. Compared to SSE, AVX double the number of simultaneous operations, thus pointing to a potential twofold gain in speed. However, in practice, achieving this potential is extremely difficult. Here, we provide a technical description and an assessment of the optimizations included in Tomo3D to take advantage of AVX instructions. Tomo3D 2.0 allows huge reconstructions to be calculated in standard computers in a matter of minutes. Thus, it will be a valuable tool for electron tomography studies with increasing resolution needs. Copyright © 2014 Elsevier Inc. All rights reserved.

Vectorization with SIMD extensions speeds up reconstruction in electron tomography.

PubMed

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

2010-06-01

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

Preliminary Observations on the Changing Roles of Malaria Vectors in Southern Belize

DTIC Science & Technology

1993-01-01

darlingi (Diptera: Cu- licidae) de la Ceiba, Atlantida, Honduras. Thesis. Maestria en Entomologia. Universidad de Panama, Panama City, Panama. 456...Brown and C. Cordon-Rosales. 1992. Potential malaria vectors in northern Guatemala (Vectores potenciales de ma- laria in la region norte de Guatemala...Serra de Aqua in June 1946 (Linthicum 1988). We initiated a malaria vector research pro- gram in Belize in 1990 and conducted extensive larval

FPGA Implementation of Generalized Hebbian Algorithm for Texture Classification

PubMed Central

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

2012-01-01

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

MANCOVA for one way classification with homogeneity of regression coefficient vectors

NASA Astrophysics Data System (ADS)

Mokesh Rayalu, G.; Ravisankar, J.; Mythili, G. Y.

2017-11-01

The MANOVA and MANCOVA are the extensions of the univariate ANOVA and ANCOVA techniques to multidimensional or vector valued observations. The assumption of a Gaussian distribution has been replaced with the Multivariate Gaussian distribution for the vectors data and residual term variables in the statistical models of these techniques. The objective of MANCOVA is to determine if there are statistically reliable mean differences that can be demonstrated between groups later modifying the newly created variable. When randomization assignment of samples or subjects to groups is not possible, multivariate analysis of covariance (MANCOVA) provides statistical matching of groups by adjusting dependent variables as if all subjects scored the same on the covariates. In this research article, an extension has been made to the MANCOVA technique with more number of covariates and homogeneity of regression coefficient vectors is also tested.

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

A New Model of Progressive Visceral Leishmaniasis in Hamsters by Natural Transmission via Bites of Vector Sand Flies

PubMed Central

Aslan, Hamide; Dey, Ranadhir; Meneses, Claudio; Castrovinci, Philip; Jeronimo, Selma Maria Bezerra; Oliva, Gætano; Fischer, Laurent; Duncan, Robert C.; Nakhasi, Hira L.; Valenzuela, Jesus G.; Kamhawi, Shaden

2013-01-01

Background. Visceral leishmaniasis (VL) is transmitted by sand flies. Protection of needle-challenged vaccinated mice was abrogated in vector-initiated cutaneous leishmaniasis, highlighting the importance of developing natural transmission models for VL. Methods. We used Lutzomyia longipalpis to transmit Leishmania infantum or Leishmania donovani to hamsters. Vector-initiated infections were monitored and compared with intracardiac infections. Body weights were recorded weekly. Organ parasite loads and parasite pick-up by flies were assessed in sick hamsters. Results. Vector-transmitted L. infantum and L. donovani caused ≥5-fold increase in spleen weight compared with uninfected organs and had geometric mean parasite loads (GMPL) comparable to intracardiac inoculation of 107–108 parasites, although vector-initiated disease progression was slower and weight loss was greater. Only vector-initiated L. infantum infections caused cutaneous lesions at transmission and distal sites. Importantly, 45.6%, 50.0%, and 33.3% of sand flies feeding on ear, mouth, and testicular lesions, respectively, were parasite-positive. Successful transmission was associated with a high mean percent of metacyclics (66%–82%) rather than total GMPL (2.0 × 104–8.0 × 104) per midgut. Conclusions. This model provides an improved platform to study initial immune events at the bite site, parasite tropism, and pathogenesis and to test drugs and vaccines against naturally acquired VL. PMID:23288926

Bunch of restless vector solitons in a fiber laser with SESAM.

PubMed

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

2009-05-11

We report on the experimental observation of a novel form of vector soliton interaction in a fiber laser mode-locked with SESAM. Several vector solitons bunch in the cavity and move as a unit with the cavity repetition rate. However, inside the bunch the vector solitons make repeatedly contractive and repulsive motions, resembling the contraction and extension of a spring. The number of vector solitons in the bunch is controllable by changing the pump power. In addition, polarization rotation locking and period doubling bifurcation of the vector soliton bunch are also experimentally observed.

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

Literature-based concept profiles for gene annotation: the issue of weighting.

PubMed

Jelier, Rob; Schuemie, Martijn J; Roes, Peter-Jan; van Mulligen, Erik M; Kors, Jan A

2008-05-01

Text-mining has been used to link biomedical concepts, such as genes or biological processes, to each other for annotation purposes or the generation of new hypotheses. To relate two concepts to each other several authors have used the vector space model, as vectors can be compared efficiently and transparently. Using this model, a concept is characterized by a list of associated concepts, together with weights that indicate the strength of the association. The associated concepts in the vectors and their weights are derived from a set of documents linked to the concept of interest. An important issue with this approach is the determination of the weights of the associated concepts. Various schemes have been proposed to determine these weights, but no comparative studies of the different approaches are available. Here we compare several weighting approaches in a large scale classification experiment. Three different techniques were evaluated: (1) weighting based on averaging, an empirical approach; (2) the log likelihood ratio, a test-based measure; (3) the uncertainty coefficient, an information-theory based measure. The weighting schemes were applied in a system that annotates genes with Gene Ontology codes. As the gold standard for our study we used the annotations provided by the Gene Ontology Annotation project. Classification performance was evaluated by means of the receiver operating characteristics (ROC) curve using the area under the curve (AUC) as the measure of performance. All methods performed well with median AUC scores greater than 0.84, and scored considerably higher than a binary approach without any weighting. Especially for the more specific Gene Ontology codes excellent performance was observed. The differences between the methods were small when considering the whole experiment. However, the number of documents that were linked to a concept proved to be an important variable. When larger amounts of texts were available for the generation of the concepts' vectors, the performance of the methods diverged considerably, with the uncertainty coefficient then outperforming the two other methods.

Method and system of filtering and recommending documents

DOEpatents

Patton, Robert M.; Potok, Thomas E.

2016-02-09

Disclosed is a method and system for discovering documents using a computer and providing a small set of the most relevant documents to the attention of a human observer. Using the method, the computer obtains a seed document from the user and generates a seed document vector using term frequency-inverse corpus frequency weighting. A keyword index for a plurality of source documents can be compared with the weighted terms of the seed document vector. The comparison is then filtered to reduce the number of documents, which define an initial subset of the source documents. Initial subset vectors are generated and compared to the seed document vector to obtain a similarity value for each comparison. Based on the similarity value, the method then recommends one or more of the source documents.

Elements of the quality management in the materials' industry

NASA Astrophysics Data System (ADS)

Ioana, Adrian; Semenescu, Augustin; Costoiu, Mihnea; Marcu, Dragoş

2017-12-01

The criteria function concept consists of transforming the criteria function (CF) in a quality-economical matrix math MQE. The levels of prescribing the criteria function was obtained by using a composition algorithm for three vectors: T¯ vector - technical parameters' vector (ti); Ē vector - economical parameters' vector (ej) and P¯ vector - weight vector (p1). For each product or service, the area of the circle represents the value of its sales. The BCG Matrix thus offers a very useful map of the organization's service strengths and weaknesses, at least in terms of current profitability, as well as the likely cash flows.

Numerical simulations of short-mixing-time double-wave-vector diffusion-weighting experiments with multiple concatenations on whole-body MR systems

NASA Astrophysics Data System (ADS)

Finsterbusch, Jürgen

2010-12-01

Double- or two-wave-vector diffusion-weighting experiments with short mixing times in which two diffusion-weighting periods are applied in direct succession, are a promising tool to estimate cell sizes in the living tissue. However, the underlying effect, a signal difference between parallel and antiparallel wave vector orientations, is considerably reduced for the long gradient pulses required on whole-body MR systems. Recently, it has been shown that multiple concatenations of the two wave vectors in a single acquisition can double the modulation amplitude if short gradient pulses are used. In this study, numerical simulations of such experiments were performed with parameters achievable with whole-body MR systems. It is shown that the theoretical model yields a good approximation of the signal behavior if an additional term describing free diffusion is included. More importantly, it is demonstrated that the shorter gradient pulses sufficient to achieve the desired diffusion weighting for multiple concatenations, increase the signal modulation considerably, e.g. by a factor of about five for five concatenations. Even at identical echo times, achieved by a shortened diffusion time, a moderate number of concatenations significantly improves the signal modulation. Thus, experiments on whole-body MR systems may benefit from multiple concatenations.

Locomotor Adaptation to an Asymmetric Force on the Human Pelvis Directed Along the Right Leg.

PubMed

Vashista, Vineet; Martelli, Dario; Agrawal, Sunil

2015-09-11

In this work, we study locomotor adaptation in healthy adults when an asymmetric force vector is applied to the pelvis directed along the right leg. A cable-driven Active Tethered Pelvic Assist Device (A-TPAD) is used to apply an external force on the pelvis, specific to a subject's gait pattern. The force vector is intended to provide external weight bearing during walking and modify the durations of limb supports. The motivation is to use this paradigm to improve weight bearing and stance phase symmetry in individuals with hemiparesis. An experiment with nine healthy subjects was conducted. The results show significant changes in the gait kinematics and kinetics while the healthy subjects developed temporal and spatial asymmetry in gait pattern in response to the applied force vector. This was followed by aftereffects once the applied force vector was removed. The adaptation to the applied force resulted in asymmetry in stance phase timing and lower limb muscle activity. We believe this paradigm, when extended to individuals with hemiparesis, can show improvements in weight bearing capability with positive effects on gait symmetry and walking speed.

A link between torse-forming vector fields and rotational hypersurfaces

NASA Astrophysics Data System (ADS)

Chen, Bang-Yen; Verstraelen, Leopold

Torse-forming vector fields introduced by Yano [On torse forming direction in a Riemannian space, Proc. Imp. Acad. Tokyo 20 (1944) 340-346] are natural extension of concurrent and concircular vector fields. Such vector fields have many nice applications to geometry and mathematical physics. In this paper, we establish a link between rotational hypersurfaces and torse-forming vector fields. More precisely, our main result states that, for a hypersurface M of 𝔼n+1 with n ≥ 3, the tangential component xT of the position vector field of M is a proper torse-forming vector field on M if and only if M is contained in a rotational hypersurface whose axis of rotation contains the origin.

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

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1996-01-01

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

Evaluation of the specificity and sensitivity of ferritin as an MRI reporter gene in the mouse brain using lentiviral and adeno-associated viral vectors.

PubMed

Vande Velde, G; Rangarajan, J R; Toelen, J; Dresselaers, T; Ibrahimi, A; Krylychkina, O; Vreys, R; Van der Linden, A; Maes, F; Debyser, Z; Himmelreich, U; Baekelandt, V

2011-06-01

The development of in vivo imaging protocols to reliably track transplanted cells or to report on gene expression is critical for treatment monitoring in (pre)clinical cell and gene therapy protocols. Therefore, we evaluated the potential of lentiviral vectors (LVs) and adeno-associated viral vectors (AAVs) to express the magnetic resonance imaging (MRI) reporter gene ferritin in the rodent brain. First, we compared the induction of background MRI contrast for both vector systems in immune-deficient and immune-competent mice. LV injection resulted in hypointense (that is, dark) changes of T(2)/T(2)(*) (spin-spin relaxation time)-weighted MRI contrast at the injection site, which can be partially explained by an inflammatory response against the vector injection. In contrast to LVs, AAV injection resulted in reduced background contrast. Moreover, AAV-mediated ferritin overexpression resulted in significantly enhanced contrast to background on T(2)(*)-weighted MRI. Although sensitivity associated with the ferritin reporter remains modest, AAVs seem to be the most promising vector system for in vivo MRI reporter gene imaging.

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification

DTIC Science & Technology

1999-05-17

Experimental Results In this section, we compare kNN -mut which uses the weight vector obtained using mutual information as the fi- nal weight vector and...WAKNN against kNN , C4.5 [Qui93], RIPPER [Coh95], PEBLS [CS93], Rainbow [McC96], VSM [Low95] on several synthetic and real data sets. VSM is another k...obtained without this option. 3 C4.5 RIPPER PEBLS Rainbow kNN WAKNN Syn-1 100.0 100.0 100.0 100.0 77.3 100.0 Syn-2 67.5 69.5 62.0 50.0 66.0 68.8 Syn

Higher-dimensional generalizations of the Watanabe–Strogatz transform for vector models of synchronization

NASA Astrophysics Data System (ADS)

Lohe, M. A.

2018-06-01

We generalize the Watanabe–Strogatz (WS) transform, which acts on the Kuramoto model in d  =  2 dimensions, to a higher-dimensional vector transform which operates on vector oscillator models of synchronization in any dimension , for the case of identical frequency matrices. These models have conserved quantities constructed from the cross ratios of inner products of the vector variables, which are invariant under the vector transform, and have trajectories which lie on the unit sphere S d‑1. Application of the vector transform leads to a partial integration of the equations of motion, leaving independent equations to be solved, for any number of nodes N. We discuss properties of complete synchronization and use the reduced equations to derive a stability condition for completely synchronized trajectories on S d‑1. We further generalize the vector transform to a mapping which acts in and in particular preserves the unit ball , and leaves invariant the cross ratios constructed from inner products of vectors in . This mapping can be used to partially integrate a system of vector oscillators with trajectories in , and for d  =  2 leads to an extension of the Kuramoto system to a system of oscillators with time-dependent amplitudes and trajectories in the unit disk. We find an inequivalent generalization of the Möbius map which also preserves but leaves invariant a different set of cross ratios, this time constructed from the vector norms. This leads to a different extension of the Kuramoto model with trajectories in the complex plane that can be partially integrated by means of fractional linear transformations.

Effects of phase vector and history extension on prediction power of adaptive-network based fuzzy inference system (ANFIS) model for a real scale anaerobic wastewater treatment plant operating under unsteady state.

PubMed

Perendeci, Altinay; Arslan, Sever; Tanyolaç, Abdurrahman; Celebi, Serdar S

2009-10-01

A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a sugar factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5-10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power. History of 7 days with two-valued phase vector in the matrix comprised of only on-line variables yielded fairly well estimations. The developed ANFIS model with phase vector and history extension has been able to adequately represent the behavior of the treatment system.

On vector-valued Poincaré series of weight 2

NASA Astrophysics Data System (ADS)

Meneses, Claudio

2017-10-01

Given a pair (Γ , ρ) of a Fuchsian group of the first kind, and a unitary representation ρ of Γ of arbitrary rank, the problem of construction of vector-valued Poincaré series of weight 2 is considered. Implications in the theory of parabolic bundles are discussed. When the genus of the group is zero, it is shown how an explicit basis for the space of these functions can be constructed.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2017-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Full Gradient Solution to Adaptive Hybrid Control

NASA Technical Reports Server (NTRS)

Bean, Jacob; Schiller, Noah H.; Fuller, Chris

2016-01-01

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered-reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.

Combinatorial vector fields and the valley structure of fitness landscapes.

PubMed

Stadler, Bärbel M R; Stadler, Peter F

2010-12-01

Adaptive (downhill) walks are a computationally convenient way of analyzing the geometric structure of fitness landscapes. Their inherently stochastic nature has limited their mathematical analysis, however. Here we develop a framework that interprets adaptive walks as deterministic trajectories in combinatorial vector fields and in return associate these combinatorial vector fields with weights that measure their steepness across the landscape. We show that the combinatorial vector fields and their weights have a product structure that is governed by the neutrality of the landscape. This product structure makes practical computations feasible. The framework presented here also provides an alternative, and mathematically more convenient, way of defining notions of valleys, saddle points, and barriers in landscape. As an application, we propose a refined approximation for transition rates between macrostates that are associated with the valleys of the landscape.

System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

DOEpatents

Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

2014-06-17

A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

RNA interference targeting the ACE gene reduced blood pressure and improved myocardial remodelling in SHRs.

PubMed

He, Junhua; Bian, Yunfei; Gao, Fen; Li, Maolian; Qiu, Ling; Wu, Weidong; Zhou, Hua; Liu, Gaizhen; Xiao, Chuanshi

2009-02-01

The purpose of the present study was to investigate the effects on blood pressure and myocardial hypertrophy in SHRs (spontaneously hypertensive rats) of RNAi (RNA interference) targeting ACE (angiotensin-converting enzyme). SHRs were treated with normal saline as vehicle controls, with Ad5-EGFP as vector controls, and with recombinant adenoviral vectors Ad5-EGFP-ACE-shRNA, carrying shRNA (small hairpin RNA) for ACE as ACE-RNAi. WKY (Wistar-Kyoto) rats were used as normotensive controls treated with normal saline. The systolic blood pressure of the caudal artery was recorded. Serum levels of ACE and AngII (angiotensin II) were determined using ELISA. ACE mRNA and protein levels were determined in aorta, myocardium, kidney and lung. On day 32 of the experiment, the heart was pathologically examined. The ratios of heart weight/body weight and left ventricular weight/body weight were calculated. The serum concentration of ACE was lower in ACE-RNAi rats (16.37+/-3.90 ng/ml) compared with vehicle controls and vector controls (48.26+/-1.50 ng/ml and 46.67+/-2.82 ng/ml respectively; both P<0.05), but comparable between ACE-RNAi rats and WKY rats (14.88+/-3.15 ng/ml; P>0.05). The serum concentration of AngII was also significantly lower in ACE-RNAi rats (18.24+/-3.69 pg/ml) compared with vehicle controls and vector controls (46.21+/-5.06 pg/ml and 44.93+/-4.12 pg/ml respectively; both P<0.05), but comparable between ACE-RNAi rats and WKY rats (16.06+/-3.11 pg/ml; P>0.05). The expression of ACE mRNA and ACE protein were significantly reduced in the myocardium, aorta, kidney and lung in ACE-RNAi rats compared with that in vehicle controls and in vector controls (all P<0.05). ACE-RNAi treatment resulted in a reduction in systolic blood pressure by 22+/-3 mmHg and the ACE-RNAi-induced reduction lasted for more than 14 days. In contrast, blood pressure was continuously increased in the vehicle controls as well as in the vector controls. The ratios of heart weight/body weight and left ventricular weight/body weight were significantly lower in ACE-RNAi rats (3.12+/-0.23 mg/g and 2.24+/-0.19 mg/g) compared with the vehicle controls (4.29+/-0.24 mg/g and 3.21+/-0.13 mg/g; P<0.05) and the vector controls (4.43+/-0.19 mg/g and 3.13+/-0.12 mg/g; P<0.05). The conclusion of the present study is that ACE-silencing had significant antihypertensive effects and reversed hypertensive-induced cardiac hypertrophy in SHRs, and therefore RNAi might be a new strategy in controlling hypertension.

A generalized graph-theoretical matrix of heterosystems and its application to the VMV procedure.

PubMed

Mozrzymas, Anna

2011-12-14

The extensions of generalized (molecular) graph-theoretical matrix and vector-matrix-vector procedure are considered. The elements of the generalized matrix are redefined in order to describe molecules containing heteroatoms and multiple bonds. The adjacency, distance, detour and reciprocal distance matrices of heterosystems, and corresponding vectors are derived from newly defined generalized graph matrix. The topological indices, which are most widely used in predicting physicochemical and biological properties/activities of various compounds, can be calculated from the new generalized vector-matrix-vector invariant. Copyright © 2011 Elsevier Ltd. All rights reserved.

Poly(ethylene glycol) analogs grafted with low molecular weight poly(ethylene imine) as non-viral gene vectors.

PubMed

Zhang, Zhenfang; Yang, Cuihong; Duan, Yajun; Wang, Yanming; Liu, Jianfeng; Wang, Lianyong; Kong, Deling

2010-07-01

A novel class of non-viral gene vectors consisting of low molecular weight poly(ethylene imine) (PEI) (molecular weight 800 Da) grafted onto degradable linear poly(ethylene glycol) (PEG) analogs was synthesized. First, a Michael addition reaction between poly(ethylene glycol) diacrylates (PEGDA) (molecular weight 258 Da) and d,l-dithiothreitol (DTT) was carried out to generate a linear polymer (PEG-DTT) having a terminal thiol, methacrylate and pendant hydroxyl functional groups. Five PEG-DTT analogs were synthesized by varying the molar ratio of diacrylates to thiols from 1.2:1 to 1:1.2. Then PEI (800 Da) was grafted onto the main chain of the PEG-DTTs using 1,1'-carbonyldiimidazole as the linker. The above reaction gave rise to a new class of non-viral gene vectors, (PEG-DTT)-g-PEI copolymers, which can effectively complex DNA to form nanoparticles. The molecular weights and structures of the copolymers were characterized by gel permeation chromatography, (1)H nuclear magnetic resonance and Fourier transform infrared spectroscopy. The size of the nanoparticles was<200 nm and the surface charge of the nanoparticles, expressed as the zeta potential, was between+20 and+40 mV. Cytotoxicity assays showed that the copolymers exhibited much lower cytotoxicities than high molecular weight PEI (25 kDa). Transfection was performed in cultured HeLa, HepG2, MCF-7 and COS-7 cells. The copolymers showed higher transfection efficiencies than PEI (25 kDa) tested in four cell lines. The presence of serum (up to 30%) had no inhibitory effect on the transfection efficiency. These results indicate that this new class of non-viral gene vectors may be a promising gene carrier that is worth further investigation. Copyright 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

PubMed Central

Qian, Jiuchao; Pei, Ling; Ma, Jiabin; Ying, Rendong; Liu, Peilin

2015-01-01

The paper presents a hybrid indoor positioning solution based on a pedestrian dead reckoning (PDR) approach using built-in sensors on a smartphone. To address the challenges of flexible and complex contexts of carrying a phone while walking, a robust step detection algorithm based on motion-awareness has been proposed. Given the fact that step length is influenced by different motion states, an adaptive step length estimation algorithm based on motion recognition is developed. Heading estimation is carried out by an attitude acquisition algorithm, which contains a two-phase filter to mitigate the distortion of magnetic anomalies. In order to estimate the heading for an unconstrained smartphone, principal component analysis (PCA) of acceleration is applied to determine the offset between the orientation of smartphone and the actual heading of a pedestrian. Moreover, a particle filter with vector graph assisted particle weighting is introduced to correct the deviation in step length and heading estimation. Extensive field tests, including four contexts of carrying a phone, have been conducted in an office building to verify the performance of the proposed algorithm. Test results show that the proposed algorithm can achieve sub-meter mean error in all contexts. PMID:25738763

9 CFR 124.20 - Patent term extension calculation.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Patent term extension calculation. 124... OF AGRICULTURE VIRUSES, SERUMS, TOXINS, AND ANALOGOUS PRODUCTS; ORGANISMS AND VECTORS PATENT TERM RESTORATION Regulatory Review Period § 124.20 Patent term extension calculation. (a) As provided in 37 CFR 1...

9 CFR 124.20 - Patent term extension calculation.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Patent term extension calculation. 124... OF AGRICULTURE VIRUSES, SERUMS, TOXINS, AND ANALOGOUS PRODUCTS; ORGANISMS AND VECTORS PATENT TERM RESTORATION Regulatory Review Period § 124.20 Patent term extension calculation. (a) As provided in 37 CFR 1...

9 CFR 124.20 - Patent term extension calculation.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Patent term extension calculation. 124... OF AGRICULTURE VIRUSES, SERUMS, TOXINS, AND ANALOGOUS PRODUCTS; ORGANISMS AND VECTORS PATENT TERM RESTORATION Regulatory Review Period § 124.20 Patent term extension calculation. (a) As provided in 37 CFR 1...

9 CFR 124.20 - Patent term extension calculation.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Patent term extension calculation. 124... OF AGRICULTURE VIRUSES, SERUMS, TOXINS, AND ANALOGOUS PRODUCTS; ORGANISMS AND VECTORS PATENT TERM RESTORATION Regulatory Review Period § 124.20 Patent term extension calculation. (a) As provided in 37 CFR 1...

9 CFR 124.20 - Patent term extension calculation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Patent term extension calculation. 124... OF AGRICULTURE VIRUSES, SERUMS, TOXINS, AND ANALOGOUS PRODUCTS; ORGANISMS AND VECTORS PATENT TERM RESTORATION Regulatory Review Period § 124.20 Patent term extension calculation. (a) As provided in 37 CFR 1...

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

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

PubMed

Li, H; Landa-Silva, D

2011-01-01

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

Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes.

PubMed

Wang, Yuanjia; Chen, Tianle; Zeng, Donglin

2016-01-01

Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse probability weighting or rank-based regression, which may be inefficient. In this paper, we develop a new support vector hazards machine (SVHM) approach to predict censored outcomes. Our method is based on predicting the counting process associated with the time-to-event outcomes among subjects at risk via a series of support vector machines. Introducing counting processes to represent time-to-event data leads to a connection between support vector machines in supervised learning and hazards regression in standard survival analysis. To account for different at risk populations at observed event times, a time-varying offset is used in estimating risk scores. The resulting optimization is a convex quadratic programming problem that can easily incorporate non-linearity using kernel trick. We demonstrate an interesting link from the profiled empirical risk function of SVHM to the Cox partial likelihood. We then formally show that SVHM is optimal in discriminating covariate-specific hazard function from population average hazard function, and establish the consistency and learning rate of the predicted risk using the estimated risk scores. Simulation studies show improved prediction accuracy of the event times using SVHM compared to existing machine learning methods and standard conventional approaches. Finally, we analyze two real world biomedical study data where we use clinical markers and neuroimaging biomarkers to predict age-at-onset of a disease, and demonstrate superiority of SVHM in distinguishing high risk versus low risk subjects.

Facilitating protein solubility by use of peptide extensions

DOEpatents

Freimuth, Paul I; Zhang, Yian-Biao; Howitt, Jason

2013-09-17

Expression vectors for expression of a protein or polypeptide of interest as a fusion product composed of the protein or polypeptide of interest fused at one terminus to a solubility enhancing peptide extension are provided. Sequences encoding the peptide extensions are provided. The invention further comprises antibodies which bind specifically to one or more of the solubility enhancing peptide extensions.

Low molecular weight polyethylenimine cross-linked by 2-hydroxypropyl-gamma-cyclodextrin coupled to peptide targeting HER2 as a gene delivery vector.

PubMed

Huang, Hongliang; Yu, Hai; Tang, Guping; Wang, Qingqing; Li, Jun

2010-03-01

Gene delivery is one of the critical steps for gene therapy. Non-viral vectors have many advantages but suffered from low gene transfection efficiency. Here, in order to develop new polymeric gene vectors with low cytotoxicity and high gene transfection efficiency, we synthesized a cationic polymer composed of low molecular weight polyethylenimine (PEI) of molecular weight of 600 Da cross-linked by 2-hydroxypropyl-gamma-cyclodextrin (HP gamma-CD) and then coupled to MC-10 oligopeptide containing a sequence of Met-Ala-Arg-Ala-Lys-Glu. The oligopeptide can target to HER2, the human epidermal growth factor receptor 2, which is often over expressed in many breast and ovary cancers. The new gene vector was expected to be able to target delivery of genes to HER2 positive cancer cells for gene therapy. The new gene vector was composed of chemically bonded HP gamma-CD, PEI (600 Da), and MC-10 peptide at a molar ratio of 1:3.3:1.2. The gene vector could condense plasmid DNA at an N/P ratio of 6 or above. The particle size of HP gamma-CD-PEI-P/DNA complexes at N/P ratios 40 was around 170-200 nm, with zeta potential of about 20 mV. The gene vector showed very low cytotoxicity, strong targeting specificity to HER2 receptor, and high efficiency of delivering DNA to target cells in vitro and in vivo with the reporter genes. The delivery of therapeutic IFN-alpha gene mediated by the new gene vector and the therapeutic efficiency were also studied in mice animal model. The animal study results showed that the new gene vector HP gamma-CD-PEI-P significantly enhanced the anti-tumor effect on tumor-bearing nude mice as compared to PEI (25 kDa), HP gamma-CD-PEI, and other controls, indicating that this new polymeric gene vector is a potential candidate for cancer gene therapy. (c) 2009 Elsevier Ltd. All rights reserved.

Feasibility study for a numerical aerodynamic simulation facility. Volume 3: FMP language specification/user manual

NASA Technical Reports Server (NTRS)

Kenner, B. G.; Lincoln, N. R.

1979-01-01

The manual is intended to show the revisions and additions to the current STAR FORTRAN. The changes are made to incorporate an FMP (Flow Model Processor) for use in the Numerical Aerodynamic Simulation Facility (NASF) for the purpose of simulating fluid flow over three-dimensional bodies in wind tunnel environments and in free space. The FORTRAN programming language for the STAR-100 computer contains both CDC and unique STAR extensions to the standard FORTRAN. Several of the STAR FORTRAN extensions to standard FOR-TRAN allow the FORTRAN user to exploit the vector processing capabilities of the STAR computer. In STAR FORTRAN, vectors can be expressed with an explicit notation, functions are provided that return vector results, and special call statements enable access to any machine instruction.

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Sturdza, Peter (Inventor); Rajnarayan, Dev (Inventor)

2013-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of boundary-layer properties at the point are obtained from a steady-state solution of a fluid flow in a region adjacent to the point. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For each instability mode in the plurality of instability modes, a covariance vector is determined, which is the covariance of a predicted local growth rate with the known instability growth rates. Each covariance vector is used with the vector of regressor weights to determine a predicted local growth rate at the point. Based on the predicted local growth rates, an n-factor envelope at the point is determined.

Medical and Transmission Vector Vocabulary Alignment with Schema.org

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

Smith, William P.; Chappell, Alan R.; Corley, Courtney D.

Available biomedical ontologies and knowledge bases currently lack formal and standards-based interconnections between disease, disease vector, and drug treatment vocabularies. The PNNL Medical Linked Dataset (PNNL-MLD) addresses this gap. This paper describes the PNNL-MLD, which provides a unified vocabulary and dataset of drug, disease, side effect, and vector transmission background information. Currently, the PNNL-MLD combines and curates data from the following research projects: DrugBank, DailyMed, Diseasome, DisGeNet, Wikipedia Infobox, Sider, and PharmGKB. The main outcomes of this effort are a dataset aligned to Schema.org, including a parsing framework, and extensible hooks ready for integration with selected medical ontologies. The PNNL-MLDmore » enables researchers more quickly and easily to query distinct datasets. Future extensions to the PNNL-MLD will include Traditional Chinese Medicine, broader interlinks across genetic structures, a larger thesaurus of synonyms and hypernyms, explicit coding of diseases and drugs across research systems, and incorporating vector-borne transmission vocabularies.« less

Influence of molecular weight upon mannosylated bio-synthetic hybrids for targeted antigen presenting cell gene delivery

PubMed Central

Jones, Charles H.; Gollakota, Akhila; Chen, Mingfu; Chung, Tai-Chun; Ravikrishnan, Anitha; Zhang, Guojian; Pfeifer, Blaine A.

2015-01-01

Given the rise of antibiotic resistant microbes, genetic vaccination is a promising prophylactic strategy that enables rapid design and manufacture. Facilitating this process is the choice of vector, which is often situationally-specific and limited in engineering capacity. Furthermore, these shortcomings are usually tied to an incomplete understanding of the structure-function relationships driving vector-mediated gene delivery. Building upon our initial report of a hybrid bacterial-biomaterial gene delivery vector, a comprehensive structure-function assessment was completed using a class of mannosylated poly(beta-amino esters). Through a top-down screening methodology, an ideal polymer was selected on the basis of gene delivery efficacy and then used for the synthesis of a stratified molecular weight polymer library. By eliminating contributions of polymer chemical background, we were able to complete an in-depth assessment of gene delivery as a function of (1) polymer molecular weight, (2) relative mannose content, (3) polymer-membrane biophysical properties, (4) APC uptake specificity, and (5) serum inhibition. In summary, the flexibility and potential of the hybrid design featured in this work highlights the ability to systematically probe vector-associated properties for the development of translational gene delivery candidates. PMID:25941787

The Multi-Attribute Group Decision-Making Method Based on Interval Grey Trapezoid Fuzzy Linguistic Variables.

PubMed

Yin, Kedong; Wang, Pengyu; Li, Xuemei

2017-12-13

With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV.

Singular vectors for the WN algebras

NASA Astrophysics Data System (ADS)

Ridout, David; Siu, Steve; Wood, Simon

2018-03-01

In this paper, we use free field realisations of the A-type principal, or Casimir, WN algebras to derive explicit formulae for singular vectors in Fock modules. These singular vectors are constructed by applying screening operators to Fock module highest weight vectors. The action of the screening operators is then explicitly evaluated in terms of Jack symmetric functions and their skew analogues. The resulting formulae depend on sequences of pairs of integers that completely determine the Fock module as well as the Jack symmetric functions.

Single-Sided Noinvasive Inspection of Multielement Sample Using Fan-Beam Multiplexed Compton Scatter Tomography

DTIC Science & Technology

2000-05-01

a vector , ρ "# represents the set of voxel densities sorted into a vector , and ( )A ρ $# "# represents a 8 mapping of the voxel densities to...density vector in equation (4) suggests that solving for ρ "# by direct inversion is not possible, calling for an iterative technique beginning with...the vector of measured spectra, and D is the diagonal matrix of the inverse of the variances. The diagonal matrix provides weighting terms, which

Adenoviral Vector Immunity: Its Implications and circumvention strategies

PubMed Central

Ahi, Yadvinder S.; Bangari, Dinesh S.; Mittal, Suresh K.

2014-01-01

Adenoviral (Ad) vectors have emerged as a promising gene delivery platform for a variety of therapeutic and vaccine purposes during last two decades. However, the presence of preexisting Ad immunity and the rapid development of Ad vector immunity still pose significant challenges to the clinical use of these vectors. Innate inflammatory response following Ad vector administration may lead to systemic toxicity, drastically limit vector transduction efficiency and significantly abbreviate the duration of transgene expression. Currently, a number of approaches are being extensively pursued to overcome these drawbacks by strategies that target either the host or the Ad vector. In addition, significant progress has been made in the development of novel Ad vectors based on less prevalent human Ad serotypes and nonhuman Ad. This review provides an update on our current understanding of immune responses to Ad vectors and delineates various approaches for eluding Ad vector immunity. Approaches targeting the host and those targeting the vector are discussed in light of their promises and limitations. PMID:21453277

Statistical Mechanical Analysis of Online Learning with Weight Normalization in Single Layer Perceptron

NASA Astrophysics Data System (ADS)

Yoshida, Yuki; Karakida, Ryo; Okada, Masato; Amari, Shun-ichi

2017-04-01

Weight normalization, a newly proposed optimization method for neural networks by Salimans and Kingma (2016), decomposes the weight vector of a neural network into a radial length and a direction vector, and the decomposed parameters follow their steepest descent update. They reported that learning with the weight normalization achieves better converging speed in several tasks including image recognition and reinforcement learning than learning with the conventional parameterization. However, it remains theoretically uncovered how the weight normalization improves the converging speed. In this study, we applied a statistical mechanical technique to analyze on-line learning in single layer linear and nonlinear perceptrons with weight normalization. By deriving order parameters of the learning dynamics, we confirmed quantitatively that weight normalization realizes fast converging speed by automatically tuning the effective learning rate, regardless of the nonlinearity of the neural network. This property is realized when the initial value of the radial length is near the global minimum; therefore, our theory suggests that it is important to choose the initial value of the radial length appropriately when using weight normalization.

Automatic recognition of vector and parallel operations in a higher level language

NASA Technical Reports Server (NTRS)

Schneck, P. B.

1971-01-01

A compiler for recognizing statements of a FORTRAN program which are suited for fast execution on a parallel or pipeline machine such as Illiac-4, Star or ASC is described. The technique employs interval analysis to provide flow information to the vector/parallel recognizer. Where profitable the compiler changes scalar variables to subscripted variables. The output of the compiler is an extension to FORTRAN which shows parallel and vector operations explicitly.

Research on intrusion detection based on Kohonen network and support vector machine

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Generalized sidelobe canceller beamforming method for ultrasound imaging.

PubMed

Wang, Ping; Li, Na; Luo, Han-Wu; Zhu, Yong-Kun; Cui, Shi-Gang

2017-03-01

A modified generalized sidelobe canceller (IGSC) algorithm is proposed to enhance the resolution and robustness against the noise of the traditional generalized sidelobe canceller (GSC) and coherence factor combined method (GSC-CF). In the GSC algorithm, weighting vector is divided into adaptive and non-adaptive parts, while the non-adaptive part does not block all the desired signal. A modified steer vector of the IGSC algorithm is generated by the projection of the non-adaptive vector on the signal space constructed by the covariance matrix of received data. The blocking matrix is generated based on the orthogonal complementary space of the modified steer vector and the weighting vector is updated subsequently. The performance of IGSC was investigated by simulations and experiments. Through simulations, IGSC outperformed GSC-CF in terms of spatial resolution by 0.1 mm regardless there is noise or not, as well as the contrast ratio respect. The proposed IGSC can be further improved by combining with CF. The experimental results also validated the effectiveness of the proposed algorithm with dataset provided by the University of Michigan.

Extension Home Economists as Therapists in a Behavior Modification Weight Loss Program.

ERIC Educational Resources Information Center

Beneke, William M.; Paulsen, Barbara K.

A total of 150 overweight female subjects entered a behavior modification weight loss program with extension home economists as therapists to determine the feasibility of state extension services as a vehicle for widespread dissemination of behavioral weight loss programs. The treatment, emphasizing stimulus control and nutrition education,…

Fast Quaternion Attitude Estimation from Two Vector Measurements

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Bauer, Frank H. (Technical Monitor)

2001-01-01

Many spacecraft attitude determination methods use exactly two vector measurements. The two vectors are typically the unit vector to the Sun and the Earth's magnetic field vector for coarse "sun-mag" attitude determination or unit vectors to two stars tracked by two star trackers for fine attitude determination. Existing closed-form attitude estimates based on Wahba's optimality criterion for two arbitrarily weighted observations are somewhat slow to evaluate. This paper presents two new fast quaternion attitude estimation algorithms using two vector observations, one optimal and one suboptimal. The suboptimal method gives the same estimate as the TRIAD algorithm, at reduced computational cost. Simulations show that the TRIAD estimate is almost as accurate as the optimal estimate in representative test scenarios.

Design and cloning strategies for constructing shRNA expression vectors

PubMed Central

McIntyre, Glen J; Fanning, Gregory C

2006-01-01

Background Short hairpin RNA (shRNA) encoded within an expression vector has proven an effective means of harnessing the RNA interference (RNAi) pathway in mammalian cells. A survey of the literature revealed that shRNA vector construction can be hindered by high mutation rates and the ensuing sequencing is often problematic. Current options for constructing shRNA vectors include the use of annealed complementary oligonucleotides (74 % of surveyed studies), a PCR approach using hairpin containing primers (22 %) and primer extension of hairpin templates (4 %). Results We considered primer extension the most attractive method in terms of cost. However, in initial experiments we encountered a mutation frequency of 50 % compared to a reported 20 – 40 % for other strategies. By modifying the technique to be an isothermal reaction using the DNA polymerase Phi29, we reduced the error rate to 10 %, making primer extension the most efficient and cost-effective approach tested. We also found that inclusion of a restriction site in the loop could be exploited for confirming construct integrity by automated sequencing, while maintaining intended gene suppression. Conclusion In this study we detail simple improvements for constructing and sequencing shRNA that overcome current limitations. We also compare the advantages of our solutions against proposed alternatives. Our technical modifications will be of tangible benefit to researchers looking for a more efficient and reliable shRNA construction process. PMID:16396676

Improved Autoassociative Neural Networks

NASA Technical Reports Server (NTRS)

Hand, Charles

2003-01-01

Improved autoassociative neural networks, denoted nexi, have been proposed for use in controlling autonomous robots, including mobile exploratory robots of the biomorphic type. In comparison with conventional autoassociative neural networks, nexi would be more complex but more capable in that they could be trained to do more complex tasks. A nexus would use bit weights and simple arithmetic in a manner that would enable training and operation without a central processing unit, programs, weight registers, or large amounts of memory. Only a relatively small amount of memory (to hold the bit weights) and a simple logic application- specific integrated circuit would be needed. A description of autoassociative neural networks is prerequisite to a meaningful description of a nexus. An autoassociative network is a set of neurons that are completely connected in the sense that each neuron receives input from, and sends output to, all the other neurons. (In some instantiations, a neuron could also send output back to its own input terminal.) The state of a neuron is completely determined by the inner product of its inputs with weights associated with its input channel. Setting the weights sets the behavior of the network. The neurons of an autoassociative network are usually regarded as comprising a row or vector. Time is a quantized phenomenon for most autoassociative networks in the sense that time proceeds in discrete steps. At each time step, the row of neurons forms a pattern: some neurons are firing, some are not. Hence, the current state of an autoassociative network can be described with a single binary vector. As time goes by, the network changes the vector. Autoassociative networks move vectors over hyperspace landscapes of possibilities.

Feature weight estimation for gene selection: a local hyperlinear learning approach

PubMed Central

2014-01-01

Background Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers. Results We propose an innovative feature weighting algorithm, called LHR, to select informative genes from highly noisy data. LHR is based on RELIEF for feature weighting using classical margin maximization. The key idea of LHR is to estimate the feature weights through local approximation rather than global measurement, which is typically used in existing methods. The weights obtained by our method are very robust in terms of degradation of noisy features, even those with vast dimensions. To demonstrate the performance of our method, extensive experiments involving classification tests have been carried out on both synthetic and real microarray benchmark datasets by combining the proposed technique with standard classifiers, including the support vector machine (SVM), k-nearest neighbor (KNN), hyperplane k-nearest neighbor (HKNN), linear discriminant analysis (LDA) and naive Bayes (NB). Conclusion Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: 1) high classification accuracy, 2) excellent robustness to noise and 3) good stability using to various classification algorithms. PMID:24625071

Molecular weight dependency of polyrotaxane-cross-linked polymer gel extensibility.

PubMed

Ohmori, Kana; Abu Bin, Imran; Seki, Takahiro; Liu, Chang; Mayumi, Koichi; Ito, Kohzo; Takeoka, Yukikazu

2016-12-11

This work investigates the influence of the molecular weight of polyrotaxane (PR) cross-linkers on the extensibility of polymer gels. The polymer gels, which were prepared using PR cross-linkers of three different molecular weights but the same number of cross-linking points per unit volume of gel, have almost the same Young's modulus. By contrast, the extensibility and rupture strength of the polymer gels are substantially increased with increasing molecular weight of the PR cross-linker.

General Quantum Meet-in-the-Middle Search Algorithm Based on Target Solution of Fixed Weight

NASA Astrophysics Data System (ADS)

Fu, Xiang-Qun; Bao, Wan-Su; Wang, Xiang; Shi, Jian-Hong

2016-10-01

Similar to the classical meet-in-the-middle algorithm, the storage and computation complexity are the key factors that decide the efficiency of the quantum meet-in-the-middle algorithm. Aiming at the target vector of fixed weight, based on the quantum meet-in-the-middle algorithm, the algorithm for searching all n-product vectors with the same weight is presented, whose complexity is better than the exhaustive search algorithm. And the algorithm can reduce the storage complexity of the quantum meet-in-the-middle search algorithm. Then based on the algorithm and the knapsack vector of the Chor-Rivest public-key crypto of fixed weight d, we present a general quantum meet-in-the-middle search algorithm based on the target solution of fixed weight, whose computational complexity is \\sumj = 0d {(O(\\sqrt {Cn - k + 1d - j }) + O(C_kj log C_k^j))} with Σd i =0 Ck i memory cost. And the optimal value of k is given. Compared to the quantum meet-in-the-middle search algorithm for knapsack problem and the quantum algorithm for searching a target solution of fixed weight, the computational complexity of the algorithm is lower. And its storage complexity is smaller than the quantum meet-in-the-middle-algorithm. Supported by the National Basic Research Program of China under Grant No. 2013CB338002 and the National Natural Science Foundation of China under Grant No. 61502526

Influence of molecular weight upon mannosylated bio-synthetic hybrids for targeted antigen presenting cell gene delivery.

PubMed

Jones, Charles H; Gollakota, Akhila; Chen, Mingfu; Chung, Tai-Chun; Ravikrishnan, Anitha; Zhang, Guojian; Pfeifer, Blaine A

2015-07-01

Given the rise of antibiotic resistant microbes, genetic vaccination is a promising prophylactic strategy that enables rapid design and manufacture. Facilitating this process is the choice of vector, which is often situationally-specific and limited in engineering capacity. Furthermore, these shortcomings are usually tied to an incomplete understanding of the structure-function relationships driving vector-mediated gene delivery. Building upon our initial report of a hybrid bacterial-biomaterial gene delivery vector, a comprehensive structure-function assessment was completed using a class of mannosylated poly(beta-amino esters). Through a top-down screening methodology, an ideal polymer was selected on the basis of gene delivery efficacy and then used for the synthesis of a stratified molecular weight polymer library. By eliminating contributions of polymer chemical background, we were able to complete an in-depth assessment of gene delivery as a function of (1) polymer molecular weight, (2) relative mannose content, (3) polymer-membrane biophysical properties, (4) APC uptake specificity, and (5) serum inhibition. In summary, the flexibility and potential of the hybrid design featured in this work highlights the ability to systematically probe vector-associated properties for the development of translational gene delivery candidates. Copyright © 2015 Elsevier Ltd. All rights reserved.

Advanced Techniques for Scene Analysis

DTIC Science & Technology

2010-06-01

robustness prefers a bigger intergration window to handle larger motions. The advantage of pyramidal implementation is that, while each motion vector dL...labeled SAR images. Now the previous algorithm leads to a more dedicated classifier for the particular target; however, our algorithm trades generality for...accuracy is traded for generality. 7.3.2 I-RELIEF Feature weighting transforms the original feature vector x into a new feature vector x′ by assigning each

Associative memory - An optimum binary neuron representation

NASA Technical Reports Server (NTRS)

Awwal, A. A.; Karim, M. A.; Liu, H. K.

1989-01-01

Convergence mechanism of vectors in the Hopfield's neural network is studied in terms of both weights (i.e., inner products) and Hamming distance. It is shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, weights (which in turn depend on the neuron representation) are found to play a more dominant role in the convergence mechanism. Consequently, a new binary neuron representation for associative memory is proposed. With the new neuron representation, the associative memory responds unambiguously to the partial input in retrieving the stored information.

AGT, N-Burge partitions and {{W}}_N minimal models

NASA Astrophysics Data System (ADS)

Belavin, Vladimir; Foda, Omar; Santachiara, Raoul

2015-10-01

Let {B}_{N,n}^{p,p', H} be a conformal block, with n consecutive channels χ ι , ι = 1, ⋯ n, in the conformal field theory {M}_N^{p,p'× {M}^{H} , where {M}_N^{p,p' } is a {W}_N minimal model, generated by chiral spin-2, ⋯ spin- N currents, and labeled by two co-prime integers p and p', 1 < p < p', while {M}^{H} is a free boson conformal field theory. {B}_{N,n}^{p,p', H} is the expectation value of vertex operators between an initial and a final state. Each vertex operator is labelled by a charge vector that lives in the weight lattice of the Lie algebra A N - 1, spanned by weight vectors {overrightarrow{ω}}_1,\\cdots, {overrightarrow{ω}}_{N-1} . We restrict our attention to conformal blocks with vertex operators whose charge vectors point along {overrightarrow{ω}}_1 . The charge vectors that label the initial and final states can point in any direction.

NUDTSNA at TREC 2015 Microblog Track: A Live Retrieval System Framework for Social Network based on Semantic Expansion and Quality Model

DTIC Science & Technology

2015-11-20

between tweets and profiles as follow, • TFIDF Score, which calculates the cosine similarity between a tweet and a profile in vector space model with...TFIDF weight of terms. Vector space model is a model which represents a document as a vector. Tweets and profiles can be expressed as vectors, ~ T = (t...gain(Tr i ) (13) where Tr is the returned tweet sets, gain() is the score func- tion for a tweet. Not interesting, spam/ junk tweets receive a gain of 0

Rapid construction of capsid-modified adenoviral vectors through bacteriophage lambda Red recombination.

PubMed

Campos, Samuel K; Barry, Michael A

2004-11-01

There are extensive efforts to develop cell-targeting adenoviral vectors for gene therapy wherein endogenous cell-binding ligands are ablated and exogenous ligands are introduced by genetic means. Although current approaches can genetically manipulate the capsid genes of adenoviral vectors, these approaches can be time-consuming and require multiple steps to produce a modified viral genome. We present here the use of the bacteriophage lambda Red recombination system as a valuable tool for the easy and rapid construction of capsid-modified adenoviral genomes.

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.

Vaxvec: The first web-based recombinant vaccine vector database and its data analysis

PubMed Central

Deng, Shunzhou; Martin, Carly; Patil, Rasika; Zhu, Felix; Zhao, Bin; Xiang, Zuoshuang; He, Yongqun

2015-01-01

A recombinant vector vaccine uses an attenuated virus, bacterium, or parasite as the carrier to express a heterologous antigen(s). Many recombinant vaccine vectors and related vaccines have been developed and extensively investigated. To compare and better understand recombinant vectors and vaccines, we have generated Vaxvec (http://www.violinet.org/vaxvec), the first web-based database that stores various recombinant vaccine vectors and those experimentally verified vaccines that use these vectors. Vaxvec has now included 59 vaccine vectors that have been used in 196 recombinant vector vaccines against 66 pathogens and cancers. These vectors are classified to 41 viral vectors, 15 bacterial vectors, 1 parasitic vector, and 1 fungal vector. The most commonly used viral vaccine vectors are double-stranded DNA viruses, including herpesviruses, adenoviruses, and poxviruses. For example, Vaxvec includes 63 poxvirus-based recombinant vaccines for over 20 pathogens and cancers. Vaxvec collects 30 recombinant vector influenza vaccines that use 17 recombinant vectors and were experimentally tested in 7 animal models. In addition, over 60 protective antigens used in recombinant vector vaccines are annotated and analyzed. User-friendly web-interfaces are available for querying various data in Vaxvec. To support data exchange, the information of vaccine vectors, vaccines, and related information is stored in the Vaccine Ontology (VO). Vaxvec is a timely and vital source of vaccine vector database and facilitates efficient vaccine vector research and development. PMID:26403370

Investigation of propagation dynamics of truncated vector vortex beams.

PubMed

Srinivas, P; Perumangatt, C; Lal, Nijil; Singh, R P; Srinivasan, B

2018-06-01

In this Letter, we experimentally investigate the propagation dynamics of truncated vector vortex beams generated using a Sagnac interferometer. Upon focusing, the truncated vector vortex beam is found to regain its original intensity structure within the Rayleigh range. In order to explain such behavior, the propagation dynamics of a truncated vector vortex beam is simulated by decomposing it into the sum of integral charge beams with associated complex weights. We also show that the polarization of the truncated composite vector vortex beam is preserved all along the propagation axis. The experimental observations are consistent with theoretical predictions based on previous literature and are in good agreement with our simulation results. The results hold importance as vector vortex modes are eigenmodes of the optical fiber.

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

Extended vector-tensor theories

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

Kimura, Rampei; Naruko, Atsushi; Yoshida, Daisuke, E-mail: rampei@th.phys.titech.ac.jp, E-mail: naruko@th.phys.titech.ac.jp, E-mail: yoshida@th.phys.titech.ac.jp

Recently, several extensions of massive vector theory in curved space-time have been proposed in many literatures. In this paper, we consider the most general vector-tensor theories that contain up to two derivatives with respect to metric and vector field. By imposing a degeneracy condition of the Lagrangian in the context of ADM decomposition of space-time to eliminate an unwanted mode, we construct a new class of massive vector theories where five degrees of freedom can propagate, corresponding to three for massive vector modes and two for massless tensor modes. We find that the generalized Proca and the beyond generalized Procamore » theories up to the quartic Lagrangian, which should be included in this formulation, are degenerate theories even in curved space-time. Finally, introducing new metric and vector field transformations, we investigate the properties of thus obtained theories under such transformations.« less

Self-entanglement of long linear DNA vectors using transient non-B-DNA attachment points: a new concept for improvement of non-viral therapeutic gene delivery.

PubMed

Tolmachov, Oleg E

2012-05-01

The cell-specific and long-term expression of therapeutic transgenes often requires a full array of native gene control elements including distal enhancers, regulatory introns and chromatin organisation sequences. The delivery of such extended gene expression modules to human cells can be accomplished with non-viral high-molecular-weight DNA vectors, in particular with several classes of linear DNA vectors. All high-molecular-weight DNA vectors are susceptible to damage by shear stress, and while for some of the vectors the harmful impact of shear stress can be minimised through the transformation of the vectors to compact topological configurations by supercoiling and/or knotting, linear DNA vectors with terminal loops or covalently attached terminal proteins cannot be self-compacted in this way. In this case, the only available self-compacting option is self-entangling, which can be defined as the folding of single DNA molecules into a configuration with mutual restriction of molecular motion by the individual segments of bent DNA. A negatively charged phosphate backbone makes DNA self-repulsive, so it is reasonable to assume that a certain number of 'sticky points' dispersed within DNA could facilitate the entangling by bringing DNA segments into proximity and by interfering with the DNA slipping away from the entanglement. I propose that the spontaneous entanglement of vector DNA can be enhanced by the interlacing of the DNA with sites capable of mutual transient attachment through the formation of non-B-DNA forms, such as interacting cruciform structures, inter-segment triplexes, slipped-strand DNA, left-handed duplexes (Z-forms) or G-quadruplexes. It is expected that the non-B-DNA based entanglement of the linear DNA vectors would consist of the initial transient and co-operative non-B-DNA mediated binding events followed by tight self-ensnarement of the vector DNA. Once in the nucleoplasm of the target human cells, the DNA can be disentangled by type II topoisomerases. The technology for such self-entanglement can be an avenue for the improvement of gene delivery with high-molecular-weight naked DNA using therapeutically important methods associated with considerable shear stress. Priority applications include in vivo muscle electroporation and sonoporation for Duchenne muscular dystrophy patients, aerosol inhalation to reach the target lung cells of cystic fibrosis patients and bio-ballistic delivery to skin melanomas with the vector DNA adsorbed on gold or tungsten projectiles. Copyright © 2012 Elsevier Ltd. All rights reserved.

A network-based meta-population approach to model Rift Valley fever epidemics.

PubMed

Xue, Ling; Scott, H Morgan; Cohnstaedt, Lee W; Scoglio, Caterina

2012-08-07

Rift Valley fever virus (RVFV) has been expanding its geographical distribution with important implications for both human and animal health. The emergence of Rift Valley fever (RVF) in the Middle East, and its continuing presence in many areas of Africa, has negatively impacted both medical and veterinary infrastructures and human morbidity, mortality, and economic endpoints. Furthermore, worldwide attention should be directed towards the broader infection dynamics of RVFV, because suitable host, vector and environmental conditions for additional epidemics likely exist on other continents; including Asia, Europe and the Americas. We propose a new compartmentalized model of RVF and the related ordinary differential equations to assess disease spread in both time and space; with the latter driven as a function of contact networks. Humans and livestock hosts and two species of vector mosquitoes are included in the model. The model is based on weighted contact networks, where nodes of the networks represent geographical regions and the weights represent the level of contact between regional pairings for each set of species. The inclusion of human, animal, and vector movements among regions is new to RVF modeling. The movement of the infected individuals is not only treated as a possibility, but also an actuality that can be incorporated into the model. We have tested, calibrated, and evaluated the model using data from the recent 2010 RVF outbreak in South Africa as a case study; mapping the epidemic spread within and among three South African provinces. An extensive set of simulation results shows the potential of the proposed approach for accurately modeling the RVF spreading process in additional regions of the world. The benefits of the proposed model are twofold: not only can the model differentiate the maximum number of infected individuals among different provinces, but also it can reproduce the different starting times of the outbreak in multiple locations. Finally, the exact value of the reproduction number is numerically computed and upper and lower bounds for the reproduction number are analytically derived in the case of homogeneous populations. Copyright © 2012 Elsevier Ltd. All rights reserved.

A novel three-stage distance-based consensus ranking method

NASA Astrophysics Data System (ADS)

Aghayi, Nazila; Tavana, Madjid

2018-05-01

In this study, we propose a three-stage weighted sum method for identifying the group ranks of alternatives. In the first stage, a rank matrix, similar to the cross-efficiency matrix, is obtained by computing the individual rank position of each alternative based on importance weights. In the second stage, a secondary goal is defined to limit the vector of weights since the vector of weights obtained in the first stage is not unique. Finally, in the third stage, the group rank position of alternatives is obtained based on a distance of individual rank positions. The third stage determines a consensus solution for the group so that the ranks obtained have a minimum distance from the ranks acquired by each alternative in the previous stage. A numerical example is presented to demonstrate the applicability and exhibit the efficacy of the proposed method and algorithms.

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

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

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

2013-12-15

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.« less

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

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

Lee, Taewoo, E-mail: taewoo.lee@utoronto.ca; Hammad, Muhannad; Chan, Timothy C. Y.

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. Amore » regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.« less

Preliminary efficacy investigations of oral fipronil against Anopheles arabiensis when administered to Zebu cattle (Bos indicus) under field conditions.

PubMed

Poché, Richard M; Githaka, Naftaly; van Gool, Frans; Kading, Rebekah C; Hartman, Daniel; Polyakova, Larisa; Abworo, Edward Okoth; Nene, Vishvanath; Lozano-Fuentes, Saul

2017-12-01

Globally, malaria remains one of the most important vector-borne diseases despite the extensive use of vector control, including indoor residual spraying (IRS) and insecticide-treated nets (ITNs). These control methods target endophagic vectors, whereas some malaria vectors, such as Anopheles arabiensis, preferentially feed outdoors on cattle, making it a complicated vector to control using conventional strategies. Our study evaluated whether treating cattle with a capsule containing the active ingredient (AI) fipronil could reduce vector density and sporozoite rates, and alter blood feeding behavior, when applied in a small-scale field study. A pilot field study was carried out in the Samia District, Western Kenya, from May to July 2015. Four plots, each comprised of 50 huts used for sleeping, were randomly designated to serve as control or treatment. A week before cattle treatment, baseline mosquito collections were performed inside the houses using mechanical aspirators. Animals in the treatment (and buffer) were administered a single oral application of fipronil at ∼0.5mg/kg of body weight. Indoor mosquito collections were performed once a week for four weeks following treatment. Female mosquitoes were first identified morphologically to species complex, followed by PCR-based methods to obtain species identity, sporozoite presence, and the host source of the blood meal. All three species of anophelines found in the study area (An. gambiae s.s., An. arabiensis, An. funestus s.s.) were actively transmitting Plasmodium falciparum during the study period. The indoor resting density of An. arabiensis was significantly reduced in treatment plot one at three weeks post-treatment (T1) (efficacy=89%; T1 density=0.08, 95% credibility intervals [0.05, 0.10]; control plot density=0.78 [0.22, 0.29]) and at four weeks post-treatment (efficacy=64%; T1 density=0.16 [0.08, 0.14]; control plot density=0.48 [0.17, 0.22]). The reduction of An. arabiensis mosquitoes captured in the treatment plot two was higher: zero females were collected after treatment. The indoor resting density of An. gambiae s.s. was not significantly different between the treatment (T1, T2) and their corresponding control plots (C1, C2). An. funestus s.s. showed an increase in density over time. The results of this preliminary study suggest that treating cattle orally with fipronil, to target exophagic and zoophagic malaria vectors, could be a valuable control strategy to supplement existing vector control interventions which target endophilic anthropophilic species. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Nilpotent representations of classical quantum groups at roots of unity

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

Abe, Yuuki; Nakashima, Toshiki

2005-11-01

Properly specializing the parameters in 'Schnizer modules', for types A,B,C, and D, we get its unique primitive vector. Then we show that the module generated by the primitive vector is an irreducible highest weight module of finite dimensional classical quantum groups at roots of unity.

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

Multi-centre diagnostic classification of individual structural neuroimaging scans from patients with major depressive disorder.

PubMed

Mwangi, Benson; Ebmeier, Klaus P; Matthews, Keith; Steele, J Douglas

2012-05-01

Quantitative abnormalities of brain structure in patients with major depressive disorder have been reported at a group level for decades. However, these structural differences appear subtle in comparison with conventional radiologically defined abnormalities, with considerable inter-subject variability. Consequently, it has not been possible to readily identify scans from patients with major depressive disorder at an individual level. Recently, machine learning techniques such as relevance vector machines and support vector machines have been applied to predictive classification of individual scans with variable success. Here we describe a novel hybrid method, which combines machine learning with feature selection and characterization, with the latter aimed at maximizing the accuracy of machine learning prediction. The method was tested using a multi-centre dataset of T(1)-weighted 'structural' scans. A total of 62 patients with major depressive disorder and matched controls were recruited from referred secondary care clinical populations in Aberdeen and Edinburgh, UK. The generalization ability and predictive accuracy of the classifiers was tested using data left out of the training process. High prediction accuracy was achieved (~90%). While feature selection was important for maximizing high predictive accuracy with machine learning, feature characterization contributed only a modest improvement to relevance vector machine-based prediction (~5%). Notably, while the only information provided for training the classifiers was T(1)-weighted scans plus a categorical label (major depressive disorder versus controls), both relevance vector machine and support vector machine 'weighting factors' (used for making predictions) correlated strongly with subjective ratings of illness severity. These results indicate that machine learning techniques have the potential to inform clinical practice and research, as they can make accurate predictions about brain scan data from individual subjects. Furthermore, machine learning weighting factors may reflect an objective biomarker of major depressive disorder illness severity, based on abnormalities of brain structure.

On Multifunctional Collaborative Methods in Engineering Science

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.

2001-01-01

Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized.

Self-assembled magnetic theranostic nanoparticles for highly sensitive MRI of minicircle DNA delivery.

PubMed

Wan, Qian; Xie, Lisi; Gao, Lin; Wang, Zhiyong; Nan, Xiang; Lei, Hulong; Long, Xiaojing; Chen, Zhi-Ying; He, Cheng-Yi; Liu, Gang; Liu, Xin; Qiu, Bensheng

2013-01-21

As a versatile gene vector, minicircle DNA (mcDNA) has a great potential for gene therapy. However, some serious challenges remain, such as to effectively deliver mcDNA into targeted cells/tissues and to non-invasively monitor the delivery of the mcDNA. Superparamagnetic iron oxide (SPIO) nanoparticles have been extensively used for both drug/gene delivery and diagnosis. In this study, an MRI visible gene delivery system was developed with a core of SPIO nanocrystals and a shell of biodegradable stearic acid-modified low molecular weight polyethyleneimine (Stearic-LWPEI) via self-assembly. The Stearic-LWPEI-SPIO nanoparticles possess a controlled clustering structure, narrow size distribution and ultrasensitive imaging capacity. Furthermore, the nanoparticle can effectively bind with mcDNA and protect it from enzymatic degradation. In conclusion, the nanoparticle shows synergistic advantages in the effective transfection of mcDNA and non-invasive MRI of gene delivery.

Finger vein recognition with personalized feature selection.

PubMed

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-08-22

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.

Finger Vein Recognition with Personalized Feature Selection

PubMed Central

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing

2013-01-01

Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG. PMID:23974154

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

Sharma, Vishal C.; Gopalakrishnan, Ganesh; Krishnamoorthy, Sriram

The systems resilience research community has developed methods to manually insert additional source-program level assertions to trap errors, and also devised tools to conduct fault injection studies for scalar program codes. In this work, we contribute the first vector oriented LLVM-level fault injector VULFI to help study the effects of faults in vector architectures that are of growing importance, especially for vectorizing loops. Using VULFI, we conduct a resiliency study of nine real-world vector benchmarks using Intel’s AVX and SSE extensions as the target vector instruction sets, and offer the first reported understanding of how faults affect vector instruction sets.more » We take this work further toward automating the insertion of resilience assertions during compilation. This is based on our observation that during intermediate (e.g., LLVM-level) code generation to handle full and partial vectorization, modern compilers exploit (and explicate in their code-documentation) critical invariants. These invariants are turned into error-checking code. We confirm the efficacy of these automatically inserted low-overhead error detectors for vectorized for-loops.« less

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Music Signal Processing Using Vector Product Neural Networks

NASA Astrophysics Data System (ADS)

Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

Behavior Change Strategies for Successful Long-Term Weight Loss: Focusing on Dietary and Physical Activity Adherence, Not Weight Loss

ERIC Educational Resources Information Center

Hongu, Nobuko; Kataura, Martha P.; Block, Linda M.

2011-01-01

This article helps Extension professionals guide individuals in a successful long-term weight loss program. A program should focus on behavioral changes (improving eating habits and physical activity), not just weight loss. In order to do this, Extension professionals should implement behavior change strategies that motivate individuals to…

Walsh-Hadamard transform kernel-based feature vector for shot boundary detection.

PubMed

Lakshmi, Priya G G; Domnic, S

2014-12-01

Video shot boundary detection (SBD) is the first step of video analysis, summarization, indexing, and retrieval. In SBD process, videos are segmented into basic units called shots. In this paper, a new SBD method is proposed using color, edge, texture, and motion strength as vector of features (feature vector). Features are extracted by projecting the frames on selected basis vectors of Walsh-Hadamard transform (WHT) kernel and WHT matrix. After extracting the features, based on the significance of the features, weights are calculated. The weighted features are combined to form a single continuity signal, used as input for Procedure Based shot transition Identification process (PBI). Using the procedure, shot transitions are classified into abrupt and gradual transitions. Experimental results are examined using large-scale test sets provided by the TRECVID 2007, which has evaluated hard cut and gradual transition detection. To evaluate the robustness of the proposed method, the system evaluation is performed. The proposed method yields F1-Score of 97.4% for cut, 78% for gradual, and 96.1% for overall transitions. We have also evaluated the proposed feature vector with support vector machine classifier. The results show that WHT-based features can perform well than the other existing methods. In addition to this, few more video sequences are taken from the Openvideo project and the performance of the proposed method is compared with the recent existing SBD method.

Real weights, bound states and duality orbits

NASA Astrophysics Data System (ADS)

Marrani, Alessio; Riccioni, Fabio; Romano, Luca

2016-01-01

We show that the duality orbits of extremal black holes in supergravity theories with symmetric scalar manifolds can be derived by studying the stabilizing subalgebras of suitable representatives, realized as bound states of specific weight vectors of the corresponding representation of the duality symmetry group. The weight vectors always correspond to weights that are real, where the reality properties are derived from the Tits-Satake diagram that identifies the real form of the Lie algebra of the duality symmetry group. Both 𝒩 = 2 magic Maxwell-Einstein supergravities and the semisimple infinite sequences of 𝒩 = 2 and 𝒩 = 4 theories in D = 4 and 5 are considered, and various results, obtained over the years in the literature using different methods, are retrieved. In particular, we show that the stratification of the orbits of these theories occurs because of very specific properties of the representations: in the case of the theory based on the real numbers, whose symmetry group is maximally noncompact and therefore all the weights are real, the stratification is due to the presence of weights of different lengths, while in the other cases it is due to the presence of complex weights.

Summary of Fluidic Thrust Vectoring Research Conducted at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Deere, Karen A.

2003-01-01

Interest in low-observable aircraft and in lowering an aircraft's exhaust system weight sparked decades of research for fixed geometry exhaust nozzles. The desire for such integrated exhaust nozzles was the catalyst for new fluidic control techniques; including throat area control, expansion control, and thrust-vector angle control. This paper summarizes a variety of fluidic thrust vectoring concepts that have been tested both experimentally and computationally at NASA Langley Research Center. The nozzle concepts are divided into three categories according to the method used for fluidic thrust vectoring: the shock vector control method, the throat shifting method, and the counterflow method. This paper explains the thrust vectoring mechanism for each fluidic method, provides examples of configurations tested for each method, and discusses the advantages and disadvantages of each method.

Vaxvec: The first web-based recombinant vaccine vector database and its data analysis.

PubMed

Deng, Shunzhou; Martin, Carly; Patil, Rasika; Zhu, Felix; Zhao, Bin; Xiang, Zuoshuang; He, Yongqun

2015-11-27

A recombinant vector vaccine uses an attenuated virus, bacterium, or parasite as the carrier to express a heterologous antigen(s). Many recombinant vaccine vectors and related vaccines have been developed and extensively investigated. To compare and better understand recombinant vectors and vaccines, we have generated Vaxvec (http://www.violinet.org/vaxvec), the first web-based database that stores various recombinant vaccine vectors and those experimentally verified vaccines that use these vectors. Vaxvec has now included 59 vaccine vectors that have been used in 196 recombinant vector vaccines against 66 pathogens and cancers. These vectors are classified to 41 viral vectors, 15 bacterial vectors, 1 parasitic vector, and 1 fungal vector. The most commonly used viral vaccine vectors are double-stranded DNA viruses, including herpesviruses, adenoviruses, and poxviruses. For example, Vaxvec includes 63 poxvirus-based recombinant vaccines for over 20 pathogens and cancers. Vaxvec collects 30 recombinant vector influenza vaccines that use 17 recombinant vectors and were experimentally tested in 7 animal models. In addition, over 60 protective antigens used in recombinant vector vaccines are annotated and analyzed. User-friendly web-interfaces are available for querying various data in Vaxvec. To support data exchange, the information of vaccine vectors, vaccines, and related information is stored in the Vaccine Ontology (VO). Vaxvec is a timely and vital source of vaccine vector database and facilitates efficient vaccine vector research and development. Copyright © 2015 Elsevier Ltd. All rights reserved.

Long-Term Safety and Efficacy of Factor IX Gene Therapy in Hemophilia B

PubMed Central

Nathwani, A.C.; Reiss, U.M.; Tuddenham, E.G.D.; Rosales, C.; Chowdary, P.; McIntosh, J.; Della Peruta, M.; Lheriteau, E.; Patel, N.; Raj, D.; Riddell, A.; Pie, J.; Rangarajan, S.; Bevan, D.; Recht, M.; Shen, Y.-M.; Halka, K.G.; Basner-Tschakarjan, E.; Mingozzi, F.; High, K.A.; Allay, J.; Kay, M.A.; Ng, C.Y.C.; Zhou, J.; Cancio, M.; Morton, C.L.; Gray, J.T.; Srivastava, D.; Nienhuis, A.W.; Davidoff, A.M.

2014-01-01

BACKGROUND In patients with severe hemophilia B, gene therapy that is mediated by a novel self-complementary adeno-associated virus serotype 8 (AAV8) vector has been shown to raise factor IX levels for periods of up to 16 months. We wanted to determine the durability of transgene expression, the vector dose–response relationship, and the level of persistent or late toxicity. METHODS We evaluated the stability of transgene expression and long-term safety in 10 patients with severe hemophilia B: 6 patients who had been enrolled in an initial phase 1 dose-escalation trial, with 2 patients each receiving a low, intermediate, or high dose, and 4 additional patients who received the high dose (2×1012 vector genomes per kilogram of body weight). The patients subsequently underwent extensive clinical and laboratory monitoring. RESULTS A single intravenous infusion of vector in all 10 patients with severe hemophilia B resulted in a dose-dependent increase in circulating factor IX to a level that was 1 to 6% of the normal value over a median period of 3.2 years, with observation ongoing. In the high-dose group, a consistent increase in the factor IX level to a mean (±SD) of 5.1±1.7% was observed in all 6 patients, which resulted in a reduction of more than 90% in both bleeding episodes and the use of prophylactic factor IX concentrate. A transient increase in the mean alanine aminotransferase level to 86 IU per liter (range, 36 to 202) occurred between week 7 and week 10 in 4 of the 6 patients in the high-dose group but resolved over a median of 5 days (range, 2 to 35) after prednisolone treatment. CONCLUSIONS In 10 patients with severe hemophilia B, the infusion of a single dose of AAV8 vector resulted in long-term therapeutic factor IX expression associated with clinical improvement. With a follow-up period of up to 3 years, no late toxic effects from the therapy were reported. (Funded by the National Heart, Lung, and Blood Institute and others; ClinicalTrials.gov number, NCT00979238.) PMID:25409372

GPU Accelerated Vector Median Filter

NASA Technical Reports Server (NTRS)

Aras, Rifat; Shen, Yuzhong

2011-01-01

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

Disease Vector Ecology Profile: Ecuador

DTIC Science & Technology

1998-12-01

fleas, has not been reported since 1985; however, extensive outbreaks in neighboring Peru occurred in 1992-94. Avoid rodent -infested areas and use PPM...throughout the year ( Peru ). Heavy shade in permanent bodies of water with abundant floatage. Commonly bites humans but apparently prefers rodents ...Vectors of Arboviruses other than Dengue or Yellow Fever in the Amazon Basin and Associated Northwestern Regions of South America

Engineering adeno-associated viruses for clinical gene therapy.

PubMed

Kotterman, Melissa A; Schaffer, David V

2014-07-01

Clinical gene therapy has been increasingly successful owing both to an enhanced molecular understanding of human disease and to progressively improving gene delivery technologies. Among these technologies, delivery vectors based on adeno-associated viruses (AAVs) have emerged as safe and effective and, in one recent case, have led to regulatory approval. Although shortcomings in viral vector properties will render extension of such successes to many other human diseases challenging, new approaches to engineer and improve AAV vectors and their genetic cargo are increasingly helping to overcome these barriers.

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.

Engineering adeno-associated viruses for clinical gene therapy

PubMed Central

Kotterman, Melissa A.; Schaffer, David V.

2015-01-01

Clinical gene therapy has been increasingly successful, due both to an enhanced molecular understanding of human disease and to progressively improving gene delivery technologies. Among the latter, delivery vectors based on adeno-associated virus (AAV) have emerged as safe and effective – in one recent case leading to regulatory approval. Although shortcomings in viral vector properties will render extension of such successes to many other human diseases challenging, new approaches to engineer and improve AAV vectors and their genetic cargo are increasingly helping to overcome these barriers. PMID:24840552

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.

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.

The Weighted Burgers Vector: a new quantity for constraining dislocation densities and types using electron backscatter diffraction on 2D sections through crystalline materials.

PubMed

Wheeler, J; Mariani, E; Piazolo, S; Prior, D J; Trimby, P; Drury, M R

2009-03-01

The Weighted Burgers Vector (WBV) is defined here as the sum, over all types of dislocations, of [(density of intersections of dislocation lines with a map) x (Burgers vector)]. Here we show that it can be calculated, for any crystal system, solely from orientation gradients in a map view, unlike the full dislocation density tensor, which requires gradients in the third dimension. No assumption is made about gradients in the third dimension and they may be non-zero. The only assumption involved is that elastic strains are small so the lattice distortion is entirely due to dislocations. Orientation gradients can be estimated from gridded orientation measurements obtained by EBSD mapping, so the WBV can be calculated as a vector field on an EBSD map. The magnitude of the WBV gives a lower bound on the magnitude of the dislocation density tensor when that magnitude is defined in a coordinate invariant way. The direction of the WBV can constrain the types of Burgers vectors of geometrically necessary dislocations present in the microstructure, most clearly when it is broken down in terms of lattice vectors. The WBV has three advantages over other measures of local lattice distortion: it is a vector and hence carries more information than a scalar quantity, it has an explicit mathematical link to the individual Burgers vectors of dislocations and, since it is derived via tensor calculus, it is not dependent on the map coordinate system. If a sub-grain wall is included in the WBV calculation, the magnitude of the WBV becomes dependent on the step size but its direction still carries information on the Burgers vectors in the wall. The net Burgers vector content of dislocations intersecting an area of a map can be simply calculated by an integration round the edge of that area, a method which is fast and complements point-by-point WBV calculations.

Stable solutions of inflation driven by vector fields

NASA Astrophysics Data System (ADS)

Emami, Razieh; Mukohyama, Shinji; Namba, Ryo; Zhang, Ying-li

2017-03-01

Many models of inflation driven by vector fields alone have been known to be plagued by pathological behaviors, namely ghost and/or gradient instabilities. In this work, we seek a new class of vector-driven inflationary models that evade all of the mentioned instabilities. We build our analysis on the Generalized Proca Theory with an extension to three vector fields to realize isotropic expansion. We obtain the conditions required for quasi de-Sitter solutions to be an attractor analogous to the standard slow-roll one and those for their stability at the level of linearized perturbations. Identifying the remedy to the existing unstable models, we provide a simple example and explicitly show its stability. This significantly broadens our knowledge on vector inflationary scenarios, reviving potential phenomenological interests for this class of models.

Conceptual analyses of extensible booms to support a solar sail

NASA Technical Reports Server (NTRS)

Crawford, R. F.; Benton, M. D.

1977-01-01

Extensible booms which could function as the diagonal spars and central mast of an 800 meter square, non-rotating Solar Sailing Vehicle were conceptually designed and analyzed. The boom design concept that was investigated is an extensible lattice boom which is stowed and deployed by elastically coiling and uncoiling its continuous longerons. The seven different free-span lengths in each spar which would minimize the total weights of the spars and mast were determined. Boom weights were calculated by using a semi-empirical formulation which related the overall weight of a boom to the weight of its longerons.

Internal performance characteristics of vectored axisymmetric ejector nozzles

NASA Technical Reports Server (NTRS)

Lamb, Milton

1993-01-01

A series of vectoring axisymmetric ejector nozzles were designed and experimentally tested for internal performance and pumping characteristics at NASA-Langley Research Center. These ejector nozzles used convergent-divergent nozzles as the primary nozzles. The model geometric variables investigated were primary nozzle throat area, primary nozzle expansion ratio, effective ejector expansion ratio (ratio of shroud exit area to primary nozzle throat area), ratio of minimum ejector area to primary nozzle throat area, ratio of ejector upper slot height to lower slot height (measured on the vertical centerline), and thrust vector angle. The primary nozzle pressure ratio was varied from 2.0 to 10.0 depending upon primary nozzle throat area. The corrected ejector-to-primary nozzle weight-flow ratio was varied from 0 (no secondary flow) to approximately 0.21 (21 percent of primary weight-flow rate) depending on ejector nozzle configuration. In addition to the internal performance and pumping characteristics, static pressures were obtained on the shroud walls.

Thrust vector control using electric actuation

NASA Astrophysics Data System (ADS)

Bechtel, Robert T.; Hall, David K.

1995-01-01

Presently, gimbaling of launch vehicle engines for thrust vector control is generally accomplished using a hydraulic system. In the case of the space shuttle solid rocket boosters and main engines, these systems are powered by hydrazine auxiliary power units. Use of electromechanical actuators would provide significant advantages in cost and maintenance. However, present energy source technologies such as batteries are heavy to the point of causing significant weight penalties. Utilizing capacitor technology developed by the Auburn University Space Power Institute in collaboration with the Auburn CCDS, Marshall Space Flight Center (MSFC) and Auburn are developing EMA system components with emphasis on high discharge rate energy sources compatible with space shuttle type thrust vector control requirements. Testing has been done at MSFC as part of EMA system tests with loads up to 66000 newtons for pulse times of several seconds. Results show such an approach to be feasible providing a potential for reduced weight and operations costs for new launch vehicles.

Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

NASA Astrophysics Data System (ADS)

Yu, Fei; Hui, Mei; Zhao, Yue-jin

2009-08-01

The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

Poxvirus-vectored vaccines for rabies--a review.

PubMed

Weyer, Jacqueline; Rupprecht, Charles E; Nel, Louis H

2009-11-27

Oral rabies vaccination of target reservoir species has proved to be one of the pillars of successful rabies elimination programs. The use of live attenuated rabies virus vaccines has been extensive but several limitations hamper its future use. A recombinant vaccinia-rabies vaccine has also been successfully used for the oral vaccination of several species. Nevertheless, its lack of efficacy in certain important rabies reservoirs and concerns on the use of this potent live virus as vaccine carrier (vector) impair the expansion of its use for new target species and new areas. Several attenuated and host-restricted poxvirus alternatives, which supposedly offer enhanced safety, have been investigated. Once again, efficacy in certain target species and innocuity through the oral route remain major limitations of these vaccines. Alternative recombinant vaccines using adenovirus as an antigen delivery vector have been extensively investigated and may provide an important addition to the currently available oral rabies vaccine repertoire, but are not the primary subject of this review.

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.

HIV-1 vaccine strategies utilizing viral vectors including antigen- displayed inoviral vectors.

PubMed

Hassapis, Kyriakos A; Kostrikis, Leondios G

2013-12-01

Antigen-presenting viral vectors have been extensively used as vehicles for the presentation of antigens to the immune system in numerous vaccine strategies. Particularly in HIV vaccine development efforts, two main viral vectors have been used as antigen carriers: (a) live attenuated vectors and (b) virus-like particles (VLPs); the former, although highly effective in animal studies, cannot be clinically tested in humans due to safety concerns and the latter have failed to induce broadly neutralizing anti-HIV antibodies. For more than two decades, Inoviruses (non-lytic bacterial phages) have also been utilized as antigen carriers in several vaccine studies. Inoviral vectors are important antigen-carriers in vaccine development due to their ability to present an antigen on their outer architecture in many copies and to their natural high immunogenicity. Numerous fundamental studies have been conducted, which have established the unique properties of antigen-displayed inoviral vectors in HIV vaccine efforts. The recent isolation of new, potent anti-HIV broadly neutralizing monoclonal antibodies provides a new momentum in this emerging technology.

Weighted optimization of irradiance for photodynamic therapy of port wine stains

NASA Astrophysics Data System (ADS)

He, Linhuan; Zhou, Ya; Hu, Xiaoming

2016-10-01

Planning of irradiance distribution (PID) is one of the foremost factors for on-demand treatment of port wine stains (PWS) with photodynamic therapy (PDT). A weighted optimization method for PID was proposed according to the grading of PWS with a three dimensional digital illumination instrument. Firstly, the point clouds of lesions were filtered to remove the error or redundant points, the triangulation was carried out and the lesion was divided into small triangular patches. Secondly, the parameters such as area, normal vector and orthocenter for optimization of each triangular patch were calculated, and the weighted coefficients were determined by the erythema indexes and areas of patches. Then, the optimization initial point was calculated based on the normal vectors and orthocenters to optimize the light direction. In the end, the irradiation can be optimized according to cosine values of irradiance angles and weighted coefficients. Comparing the irradiance distribution before and after optimization, the proposed weighted optimization method can make the irradiance distribution match better with the characteristics of lesions, and has the potential to improve the therapeutic efficacy.

PubMed-supported clinical term weighting approach for improving inter-patient similarity measure in diagnosis prediction.

PubMed

Chan, Lawrence Wc; Liu, Ying; Chan, Tao; Law, Helen Kw; Wong, S C Cesar; Yeung, Andy Ph; Lo, K F; Yeung, S W; Kwok, K Y; Chan, William Yl; Lau, Thomas Yh; Shyu, Chi-Ren

2015-06-02

Similarity-based retrieval of Electronic Health Records (EHRs) from large clinical information systems provides physicians the evidence support in making diagnoses or referring examinations for the suspected cases. Clinical Terms in EHRs represent high-level conceptual information and the similarity measure established based on these terms reflects the chance of inter-patient disease co-occurrence. The assumption that clinical terms are equally relevant to a disease is unrealistic, reducing the prediction accuracy. Here we propose a term weighting approach supported by PubMed search engine to address this issue. We collected and studied 112 abdominal computed tomography imaging examination reports from four hospitals in Hong Kong. Clinical terms, which are the image findings related to hepatocellular carcinoma (HCC), were extracted from the reports. Through two systematic PubMed search methods, the generic and specific term weightings were established by estimating the conditional probabilities of clinical terms given HCC. Each report was characterized by an ontological feature vector and there were totally 6216 vector pairs. We optimized the modified direction cosine (mDC) with respect to a regularization constant embedded into the feature vector. Equal, generic and specific term weighting approaches were applied to measure the similarity of each pair and their performances for predicting inter-patient co-occurrence of HCC diagnoses were compared by using Receiver Operating Characteristics (ROC) analysis. The Areas under the curves (AUROCs) of similarity scores based on equal, generic and specific term weighting approaches were 0.735, 0.728 and 0.743 respectively (p < 0.01). In comparison with equal term weighting, the performance was significantly improved by specific term weighting (p < 0.01) but not by generic term weighting. The clinical terms "Dysplastic nodule", "nodule of liver" and "equal density (isodense) lesion" were found the top three image findings associated with HCC in PubMed. Our findings suggest that the optimized similarity measure with specific term weighting to EHRs can improve significantly the accuracy for predicting the inter-patient co-occurrence of diagnosis when compared with equal and generic term weighting approaches.

A feedforward artificial neural network based on quantum effect vector-matrix multipliers.

PubMed

Levy, H J; McGill, T C

1993-01-01

The vector-matrix multiplier is the engine of many artificial neural network implementations because it can simulate the way in which neurons collect weighted input signals from a dendritic arbor. A new technology for building analog weighting elements that is theoretically capable of densities and speeds far beyond anything that conventional VLSI in silicon could ever offer is presented. To illustrate the feasibility of such a technology, a small three-layer feedforward prototype network with five binary neurons and six tri-state synapses was built and used to perform all of the fundamental logic functions: XOR, AND, OR, and NOT.

Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.

PubMed

Deylami, Ali Mohades; Asl, Babak Mohammadzadeh

2018-06-04

Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L 3 ) to O(L 2 ). Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Balanced Centrality of Networks.

PubMed

Debono, Mark; Lauri, Josef; Sciriha, Irene

2014-01-01

There is an age-old question in all branches of network analysis. What makes an actor in a network important, courted, or sought? Both Crossley and Bonacich contend that rather than its intrinsic wealth or value, an actor's status lies in the structures of its interactions with other actors. Since pairwise relation data in a network can be stored in a two-dimensional array or matrix, graph theory and linear algebra lend themselves as great tools to gauge the centrality (interpreted as importance, power, or popularity, depending on the purpose of the network) of each actor. We express known and new centralities in terms of only two matrices associated with the network. We show that derivations of these expressions can be handled exclusively through the main eigenvectors (not orthogonal to the all-one vector) associated with the adjacency matrix. We also propose a centrality vector (SWIPD) which is a linear combination of the square, walk, power, and degree centrality vectors with weightings of the various centralities depending on the purpose of the network. By comparing actors' scores for various weightings, a clear understanding of which actors are most central is obtained. Moreover, for threshold networks, the (SWIPD) measure turns out to be independent of the weightings.

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…

The multidisciplinary design optimization of a distributed propulsion blended-wing-body aircraft

NASA Astrophysics Data System (ADS)

Ko, Yan-Yee Andy

The purpose of this study is to examine the multidisciplinary design optimization (MDO) of a distributed propulsion blended-wing-body (BWB) aircraft. The BWB is a hybrid shape resembling a flying wing, placing the payload in the inboard sections of the wing. The distributed propulsion concept involves replacing a small number of large engines with many smaller engines. The distributed propulsion concept considered here ducts part of the engine exhaust to exit out along the trailing edge of the wing. The distributed propulsion concept affects almost every aspect of the BWB design. Methods to model these effects and integrate them into an MDO framework were developed. The most important effect modeled is the impact on the propulsive efficiency. There has been conjecture that there will be an increase in propulsive efficiency when there is blowing out of the trailing edge of a wing. A mathematical formulation was derived to explain this. The formulation showed that the jet 'fills in' the wake behind the body, improving the overall aerodynamic/propulsion system, resulting in an increased propulsive efficiency. The distributed propulsion concept also replaces the conventional elevons with a vectored thrust system for longitudinal control. An extension of Spence's Jet Flap theory was developed to estimate the effects of this vectored thrust system on the aircraft longitudinal control. It was found to provide a reasonable estimate of the control capability of the aircraft. An MDO framework was developed, integrating all the distributed propulsion effects modeled. Using a gradient based optimization algorithm, the distributed propulsion BWB aircraft was optimized and compared with a similarly optimized conventional BWB design. Both designs are for an 800 passenger, 0.85 cruise Mach number and 7000 nmi mission. The MDO results found that the distributed propulsion BWB aircraft has a 4% takeoff gross weight and a 2% fuel weight. Both designs have similar planform shapes, although the planform area of the distributed propulsion BWB design is 10% smaller. Through parametric studies, it was also found that the aircraft was most sensitive to the amount of savings in propulsive efficiency and the weight of the ducts used to divert the engine exhaust.

Boosting specificity of MEG artifact removal by weighted support vector machine.

PubMed

Duan, Fang; Phothisonothai, Montri; Kikuchi, Mitsuru; Yoshimura, Yuko; Minabe, Yoshio; Watanabe, Kastumi; Aihara, Kazuyuki

2013-01-01

An automatic artifact removal method of magnetoencephalogram (MEG) was presented in this paper. The method proposed is based on independent components analysis (ICA) and support vector machine (SVM). However, different from the previous studies, in this paper we consider two factors which would influence the performance. First, the imbalance factor of independent components (ICs) of MEG is handled by weighted SVM. Second, instead of simply setting a fixed weight to each class, a re-weighting scheme is used for the preservation of useful MEG ICs. Experimental results on manually marked MEG dataset showed that the method proposed could correctly distinguish the artifacts from the MEG ICs. Meanwhile, 99.72% ± 0.67 of MEG ICs were preserved. The classification accuracy was 97.91% ± 1.39. In addition, it was found that this method was not sensitive to individual differences. The cross validation (leave-one-subject-out) results showed an averaged accuracy of 97.41% ± 2.14.

Nodal distances for rooted phylogenetic trees.

PubMed

Cardona, Gabriel; Llabrés, Mercè; Rosselló, Francesc; Valiente, Gabriel

2010-08-01

Dissimilarity measures for (possibly weighted) phylogenetic trees based on the comparison of their vectors of path lengths between pairs of taxa, have been present in the systematics literature since the early seventies. For rooted phylogenetic trees, however, these vectors can only separate non-weighted binary trees, and therefore these dissimilarity measures are metrics only on this class of rooted phylogenetic trees. In this paper we overcome this problem, by splitting in a suitable way each path length between two taxa into two lengths. We prove that the resulting splitted path lengths matrices single out arbitrary rooted phylogenetic trees with nested taxa and arcs weighted in the set of positive real numbers. This allows the definition of metrics on this general class of rooted phylogenetic trees by comparing these matrices through metrics in spaces M(n)(R) of real-valued n x n matrices. We conclude this paper by establishing some basic facts about the metrics for non-weighted phylogenetic trees defined in this way using L(p) metrics on M(n)(R), with p [epsilon] R(>0).

Viruses vector control proposal: genus Aedes emphasis.

PubMed

Reis, Nelson Nogueira; Silva, Alcino Lázaro da; Reis, Elma Pereira Guedes; Silva, Flávia Chaves E; Reis, Igor Guedes Nogueira

The dengue fever is a major public health problem in the world. In Brazil, in 2015, there were 1,534,932 cases, being 20,320 cases of severe form, and 811 deaths related to this disease. The distribution of Aedes aegypti, the vector, is extensive. Recently, Zika and Chikungunya viruses had arisen, sharing the same vector as dengue and became a huge public health issue. Without specific treatment, it is urgently required as an effective vector control. This article is focused on reviewing vector control strategies, their effectiveness, viability and economical impact. Among all, the Sterile Insect Technique is highlighted as the best option to be adopted in Brazil, once it is largely effectively used in the USA and Mexico for plagues related to agribusiness. Copyright © 2017 Sociedade Brasileira de Infectologia. Published by Elsevier Editora Ltda. All rights reserved.

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.

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.

The Coordinate Orthogonality Check (corthog)

NASA Astrophysics Data System (ADS)

Avitabile, P.; Pechinsky, F.

1998-05-01

A new technique referred to as the coordinate orthogonality check (CORTHOG) helps to identify how each physical degree of freedom contributes to the overall orthogonality relationship between analytical and experimental modal vectors on a mass-weighted basis. Using the CORTHOG technique together with the pseudo-orthogonality check (POC) clarifies where potential discrepancies exist between the analytical and experimental modal vectors. CORTHOG improves the understanding of the correlation (or lack of correlation) that exists between modal vectors. The CORTHOG theory is presented along with the evaluation of several cases to show the use of the technique.

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.

Interpreting support vector machine models for multivariate group wise analysis in neuroimaging

PubMed Central

Gaonkar, Bilwaj; Shinohara, Russell T; Davatzikos, Christos

2015-01-01

Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that contribute significantly to classifier decisions remains an open problem. This is an issue of critical importance in imaging studies seeking to determine which anatomical or physiological imaging features contribute to the classifier’s decision, thereby allowing users to critically evaluate the findings of such machine learning methods and to understand disease mechanisms. The majority of published work addresses the question of statistical inference for support vector classification using permutation tests based on SVM weight vectors. Such permutation testing ignores the SVM margin, which is critical in SVM theory. In this work we emphasize the use of a statistic that explicitly accounts for the SVM margin and show that the null distributions associated with this statistic are asymptotically normal. Further, our experiments show that this statistic is a lot less conservative as compared to weight based permutation tests and yet specific enough to tease out multivariate patterns in the data. Thus, we can better understand the multivariate patterns that the SVM uses for neuroimaging based classification. PMID:26210913

Link-Based Similarity Measures Using Reachability Vectors

PubMed Central

Yoon, Seok-Ho; Kim, Ji-Soo; Ryu, Minsoo; Choi, Ho-Jin

2014-01-01

We present a novel approach for computing link-based similarities among objects accurately by utilizing the link information pertaining to the objects involved. We discuss the problems with previous link-based similarity measures and propose a novel approach for computing link based similarities that does not suffer from these problems. In the proposed approach each target object is represented by a vector. Each element of the vector corresponds to all the objects in the given data, and the value of each element denotes the weight for the corresponding object. As for this weight value, we propose to utilize the probability of reaching from the target object to the specific object, computed using the “Random Walk with Restart” strategy. Then, we define the similarity between two objects as the cosine similarity of the two vectors. In this paper, we provide examples to show that our approach does not suffer from the aforementioned problems. We also evaluate the performance of the proposed methods in comparison with existing link-based measures, qualitatively and quantitatively, with respect to two kinds of data sets, scientific papers and Web documents. Our experimental results indicate that the proposed methods significantly outperform the existing measures. PMID:24701188

Multiclass Reduced-Set Support Vector Machines

NASA Technical Reports Server (NTRS)

Tang, Benyang; Mazzoni, Dominic

2006-01-01

There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduced-set methods can be applied to multiclass SVMs made up of several binary SVMs, with significantly better results than reducing each binary SVM independently. Our approach is based on Burges' approach that constructs each reduced-set vector as the pre-image of a vector in kernel space, but we extend this by recomputing the SVM weights and bias optimally using the original SVM objective function. This leads to greater accuracy for a binary reduced-set SVM, and also allows vectors to be 'shared' between multiple binary SVMs for greater multiclass accuracy with fewer reduced-set vectors. We also propose computing pre-images using differential evolution, which we have found to be more robust than gradient descent alone. We show experimental results on a variety of problems and find that this new approach is consistently better than previous multiclass reduced-set methods, sometimes with a dramatic difference.

A novel dynamical community detection algorithm based on weighting scheme

NASA Astrophysics Data System (ADS)

Li, Ju; Yu, Kai; Hu, Ke

2015-12-01

Network dynamics plays an important role in analyzing the correlation between the function properties and the topological structure. In this paper, we propose a novel dynamical iteration (DI) algorithm, which incorporates the iterative process of membership vector with weighting scheme, i.e. weighting W and tightness T. These new elements can be used to adjust the link strength and the node compactness for improving the speed and accuracy of community structure detection. To estimate the optimal stop time of iteration, we utilize a new stability measure which is defined as the Markov random walk auto-covariance. We do not need to specify the number of communities in advance. It naturally supports the overlapping communities by associating each node with a membership vector describing the node's involvement in each community. Theoretical analysis and experiments show that the algorithm can uncover communities effectively and efficiently.

The Effects of Walking Speed on Tibiofemoral Loading Estimated Via Musculoskeletal Modeling

PubMed Central

Lerner, Zachary F.; Haight, Derek J.; DeMers, Matthew S.; Board, Wayne J.; Browning, Raymond C.

2015-01-01

Net muscle moments (NMMs) have been used as proxy measures of joint loading, but musculoskeletal models can estimate contact forces within joints. The purpose of this study was to use a musculoskeletal model to estimate tibiofemoral forces and to examine the relationship between NMMs and tibiofemoral forces across walking speeds. We collected kinematic, kinetic, and electromyographic data as ten adult participants walked on a dual-belt force-measuring treadmill at 0.75, 1.25, and 1.50 m/s. We scaled a musculoskeletal model to each participant and used OpenSim to calculate the NMMs and muscle forces through inverse dynamics and weighted static optimization, respectively. We determined tibiofemoral forces from the vector sum of intersegmental and muscle forces crossing the knee. Estimated tibiofemoral forces increased with walking speed. Peak early-stance compressive tibiofemoral forces increased 52% as walking speed increased from 0.75 to 1.50 m/s, whereas peak knee extension NMMs increased by 168%. During late stance, peak compressive tibiofemoral forces increased by 18% as speed increased. Although compressive loads at the knee did not increase in direct proportion to NMMs, faster walking resulted in greater compressive forces during weight acceptance and increased compressive and anterior/posterior tibiofemoral loading rates in addition to a greater abduction NMM. PMID:23878264

The Forest Method as a New Parallel Tree Method with the Sectional Voronoi Tessellation

NASA Astrophysics Data System (ADS)

Yahagi, Hideki; Mori, Masao; Yoshii, Yuzuru

1999-09-01

We have developed a new parallel tree method which will be called the forest method hereafter. This new method uses the sectional Voronoi tessellation (SVT) for the domain decomposition. The SVT decomposes a whole space into polyhedra and allows their flat borders to move by assigning different weights. The forest method determines these weights based on the load balancing among processors by means of the overload diffusion (OLD). Moreover, since all the borders are flat, before receiving the data from other processors, each processor can collect enough data to calculate the gravity force with precision. Both the SVT and the OLD are coded in a highly vectorizable manner to accommodate on vector parallel processors. The parallel code based on the forest method with the Message Passing Interface is run on various platforms so that a wide portability is guaranteed. Extensive calculations with 15 processors of Fujitsu VPP300/16R indicate that the code can calculate the gravity force exerted on 105 particles in each second for some ideal dark halo. This code is found to enable an N-body simulation with 107 or more particles for a wide dynamic range and is therefore a very powerful tool for the study of galaxy formation and large-scale structure in the universe.

Initialization of Formation Flying Using Primer Vector Theory

NASA Technical Reports Server (NTRS)

Mailhe, Laurie; Schiff, Conrad; Folta, David

2002-01-01

In this paper, we extend primer vector analysis to formation flying. Optimization of the classical rendezvous or free-time transfer problem between two orbits using primer vector theory has been extensively studied for one spacecraft. However, an increasing number of missions are now considering flying a set of spacecraft in close formation. Missions such as the Magnetospheric MultiScale (MMS) and Leonardo-BRDF (Bidirectional Reflectance Distribution Function) need to determine strategies to transfer each spacecraft from the common launch orbit to their respective operational orbit. In addition, all the spacecraft must synchronize their states so that they achieve the same desired formation geometry over each orbit. This periodicity requirement imposes constraints on the boundary conditions that can be used for the primer vector algorithm. In this work we explore the impact of the periodicity requirement in optimizing each spacecraft transfer trajectory using primer vector theory. We first present our adaptation of primer vector theory to formation flying. Using this method, we then compute the AV budget for each spacecraft subject to different formation endpoint constraints.

Applications of lentiviral vectors in molecular imaging.

PubMed

Chatterjee, Sushmita; De, Abhijit

2014-06-01

Molecular imaging provides the ability of simultaneous visual and quantitative estimation of long term gene expression directly from living organisms. To reveal the kinetics of gene expression by imaging method, often sustained expression of the transgene is required. Lentiviral vectors have been extensively used over last fifteen years for delivery of a transgene in a wide variety of cell types. Lentiviral vectors have the well known advantages such as sustained transgene delivery through stable integration into the host genome, the capability of infecting non-dividing and dividing cells, broad tissue tropism, a reasonably large carrying capacity for delivering therapeutic and reporter gene combinations. Additionally, they do not express viral proteins during transduction, have a potentially safe integration site profile, and a relatively easy system for vector manipulation and infective viral particle production. As a result, lentiviral vector mediated therapeutic and imaging reporter gene delivery to various target organs holds promise for the future treatment. In this review, we have conducted a brief survey of important lentiviral vector developments in diverse biomedical fields including reproductive biology.

Android malware detection based on evolutionary super-network

NASA Astrophysics Data System (ADS)

Yan, Haisheng; Peng, Lingling

2018-04-01

In the paper, an android malware detection method based on evolutionary super-network is proposed in order to improve the precision of android malware detection. Chi square statistics method is used for selecting characteristics on the basis of analyzing android authority. Boolean weighting is utilized for calculating characteristic weight. Processed characteristic vector is regarded as the system training set and test set; hyper edge alternative strategy is used for training super-network classification model, thereby classifying test set characteristic vectors, and it is compared with traditional classification algorithm. The results show that the detection method proposed in the paper is close to or better than traditional classification algorithm. The proposed method belongs to an effective Android malware detection means.

Applications and challenges of multivalent recombinant vaccines

PubMed Central

Naim, Hussein Y.

2013-01-01

The exceptional discoveries of antigen/gene delivery systems have allowed the development of novel prophylactic and therapeutic vaccine candidates. The vaccine candidates employ various antigen-delivery systems, particularly recombinant viral vectors. Recombinant viral vectors are experimental vaccines similar to DNA vaccines, but they use attenuated viruses or bacterium as a carrier “vector” to introduce microbial DNA to cells of the body. They closely mimic a natural infection and therefore can efficiently stimulate the immune system. Although such recombinant vectors may face extensive preclinical testing and will possibly have to meet stringent regulatory requirements, some of these vectors (e.g. measles virus vectors) may benefit from the profound industrial and clinical experience of the parent vaccine. Most notably, novel vaccines based on live attenuated viruses combine the induction of broad, strong and persistent immune responses with acceptable safety profiles. We assess certain technologies in light of their use against human immunodeficiency virus (HIV). PMID:23249651

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.

Photoalignment and resulting holographic vector grating formation in composites of low molecular weight liquid crystals and photoreactive liquid crystalline polymers

NASA Astrophysics Data System (ADS)

Sasaki, Tomoyuki; Shoho, Takashi; Goto, Kohei; Noda, Kohei; Kawatsuki, Nobuhiro; Ono, Hiroshi

2015-08-01

Polarization holographic gratings were formed in liquid crystal (LC) cells fabricated from a mixture of low molecular weight nematic LC and a photoreactive liquid crystalline polymer (PLCP) with 4-(4-methoxycinnamoyloxy)biphenyl side groups. The diffraction properties of the gratings were analyzed using theoretical models which were determined based on the polarization patterns of the polarization holography. The results demonstrated that vector gratings comprised of periodic orientation distributions of the LC molecule were induced in the cells based on the axis-selective photoreaction of the PLCP. The vector gratings were erased by applying a sufficiently high voltage to the cells and then were reformed with no hysteresis after the voltage was removed. This phenomenon suggested that the PLCP molecules were stabilized based on the axis-selective photocrosslink reaction and that the LC molecules were aligned by the photocrosslinked PLCP. This LC composite with axis-selective photoreactivity is useful for various optical applications, because of their stability, transparency, and response to applied voltage.

An artificial neural network model for periodic trajectory generation

NASA Astrophysics Data System (ADS)

Shankar, S.; Gander, R. E.; Wood, H. C.

A neural network model based on biological systems was developed for potential robotic application. The model consists of three interconnected layers of artificial neurons or units: an input layer subdivided into state and plan units, an output layer, and a hidden layer between the two outer layers which serves to implement nonlinear mappings between the input and output activation vectors. Weighted connections are created between the three layers, and learning is effected by modifying these weights. Feedback connections between the output and the input state serve to make the network operate as a finite state machine. The activation vector of the plan units of the input layer emulates the supraspinal commands in biological central pattern generators in that different plan activation vectors correspond to different sequences or trajectories being recalled, even with different frequencies. Three trajectories were chosen for implementation, and learning was accomplished in 10,000 trials. The fault tolerant behavior, adaptiveness, and phase maintenance of the implemented network are discussed.

A person trade-off study to estimate age-related weights for health gains in economic evaluation.

PubMed

Petrou, Stavros; Kandala, Ngianga-Bakwin; Robinson, Angela; Baker, Rachel

2013-10-01

An increasing body of literature is exploring whether the age of the recipient of health care should be a criterion in how health care resources are allocated. The existing literature is constrained both by the relatively small number of age comparison groups within preference-elicitation studies, and by a paucity of methodological robustness tests for order and framing effects and the reliability and transitivity of preferences that would strengthen confidence in the results. This paper reports the results of a study aimed at estimating granulated age-related weights for health gains across the age spectrum that can potentially inform health care decision-making. A sample of 2,500 participants recruited from the health care consumer panels of a social research company completed a person trade-off (or 'matching') study designed to estimate age-related weights for 5- and 10-year life extensions. The results are presented in terms of matrices for alternative age comparisons across the age spectrum. The results revealed a general, although not invariable, tendency to give more weight to health gains, expressed in terms of life extensions, in younger age groups. In over 85% of age comparisons, the person trade-off exercises revealed a preference for life extensions by the younger of the two age groups that were compared. This pattern held regardless of the method of aggregating responses across study participants. Moreover, the relative weight placed on life extensions by the younger of the two age groups was generally, although not invariably, found to increase as the age difference between the comparator age groups increased. Further analyses revealed that the highest mean relative weight placed on life extensions was estimated for 30-year-olds when the ratio of means method was used to aggregate person trade-off responses across study participants. The highest mean relative weight placed on life extensions was estimated for 10-year-olds for 5-year life extensions and for 30-year-olds for 10-year life extensions, when the median of individual ratios method was used to aggregate person trade-off responses across study participants. Methodological tests framed around alternative referents in the person trade-off questions and the stability of preferences had no discernible effects on the study results. This study has produced new evidence on age-related weights for health gains that can potentially inform health care decision-making.

Point-based warping with optimized weighting factors of displacement vectors

NASA Astrophysics Data System (ADS)

Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

2000-06-01

The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

Low molecular weight chitosan conjugated with folate for siRNA delivery in vitro: optimization studies

PubMed Central

Fernandes, Julio C; Qiu, Xingping; Winnik, Francoise M; Benderdour, Mohamed; Zhang, Xiaoling; Dai, Kerong; Shi, Qin

2012-01-01

The low transfection efficiency of chitosan is one of its drawbacks as a gene delivery carrier. Low molecular weight chitosan may help to form small-sized polymer-DNA or small interfering RNA (siRNA) complexes. Folate conjugation may improve gene transfection efficiency because of the promoted uptake of folate receptor-bearing cells. In the present study, chitosan was conjugated with folate and investigated for its efficacy as a delivery vector for siRNA in vitro. We demonstrate that the molecular weight of chitosan has a major influence on its biological and physicochemical properties, and very low molecular weight chitosan (below 10 kDa) has difficulty in forming stable complexes with siRNA. In this study, chitosan 25 kDa and 50 kDa completely absorbed siRNA and formed nanoparticles (≤220 nm) at a chitosan to siRNA weight ratio of 50:1. The introduction of a folate ligand onto chitosan decreased nanoparticle toxicity. Compared with chitosan-siRNA, folate-chitosan-siRNA nanoparticles improved gene silencing transfection efficiency. Therefore, folate-chitosan shows potential as a viable candidate vector for safe and efficient siRNA delivery. PMID:23209368

Molecular analysis of vector genome structures after liver transduction by conventional and self-complementary adeno-associated viral serotype vectors in murine and nonhuman primate models.

PubMed

Sun, Xun; Lu, You; Bish, Lawrence T; Calcedo, Roberto; Wilson, James M; Gao, Guangping

2010-06-01

Vectors based on several new adeno-associated viral (AAV) serotypes demonstrated strong hepatocyte tropism and transduction efficiency in both small- and large-animal models for liver-directed gene transfer. Efficiency of liver transduction by AAV vectors can be further improved in both murine and nonhuman primate (NHP) animals when the vector genomes are packaged in a self-complementary (sc) format. In an attempt to understand potential molecular mechanism(s) responsible for enhanced transduction efficiency of the sc vector in liver, we performed extensive molecular studies of genome structures of conventional single-stranded (ss) and sc AAV vectors from liver after AAV gene transfer in both mice and NHPs. These included treatment with exonucleases with specific substrate preferences, single-cutter restriction enzyme digestion and polarity-specific hybridization-based vector genome mapping, and bacteriophage phi29 DNA polymerase-mediated and double-stranded circular template-specific rescue of persisted circular genomes. In mouse liver, vector genomes of both genome formats seemed to persist primarily as episomal circular forms, but sc vectors converted into circular forms more rapidly and efficiently. However, the overall differences in vector genome abundance and structure in the liver between ss and sc vectors could not account for the remarkable differences in transduction. Molecular structures of persistent genomes of both ss and sc vectors were significantly more heterogeneous in macaque liver, with noticeable structural rearrangements that warrant further characterizations.

Molecular Analysis of Vector Genome Structures After Liver Transduction by Conventional and Self-Complementary Adeno-Associated Viral Serotype Vectors in Murine and Nonhuman Primate Models

PubMed Central

Sun, Xun; Lu, You; Bish, Lawrence T.; Calcedo, Roberto; Wilson, James M.

2010-01-01

Abstract Vectors based on several new adeno-associated viral (AAV) serotypes demonstrated strong hepatocyte tropism and transduction efficiency in both small- and large-animal models for liver-directed gene transfer. Efficiency of liver transduction by AAV vectors can be further improved in both murine and nonhuman primate (NHP) animals when the vector genomes are packaged in a self-complementary (sc) format. In an attempt to understand potential molecular mechanism(s) responsible for enhanced transduction efficiency of the sc vector in liver, we performed extensive molecular studies of genome structures of conventional single-stranded (ss) and sc AAV vectors from liver after AAV gene transfer in both mice and NHPs. These included treatment with exonucleases with specific substrate preferences, single-cutter restriction enzyme digestion and polarity-specific hybridization-based vector genome mapping, and bacteriophage ϕ29 DNA polymerase-mediated and double-stranded circular template-specific rescue of persisted circular genomes. In mouse liver, vector genomes of both genome formats seemed to persist primarily as episomal circular forms, but sc vectors converted into circular forms more rapidly and efficiently. However, the overall differences in vector genome abundance and structure in the liver between ss and sc vectors could not account for the remarkable differences in transduction. Molecular structures of persistent genomes of both ss and sc vectors were significantly more heterogeneous in macaque liver, with noticeable structural rearrangements that warrant further characterizations. PMID:20113166

Bioelectrical impedance vector distribution in the first year of life.

PubMed

Savino, Francesco; Grasso, Giulia; Cresi, Francesco; Oggero, Roberto; Silvestro, Leandra

2003-06-01

We assessed the bioelectrical impedance vector distribution in a sample of healthy infants in the first year of life, which is not available in literature. The study was conducted as a cross-sectional study in 153 healthy Caucasian infants (90 male and 63 female) younger than 1 y, born at full term, adequate for gestational age, free from chronic diseases or growth problems, and not feverish. Z scores for weight, length, cranial circumference, and body mass index for the study population were within the range of +/-1.5 standard deviations according to the Euro-Growth Study references. Concurrent anthropometrics (weight, length, and cranial circumference), body mass index, and bioelectrical impedance (resistance and reactance) measurements were made by the same operator. Whole-body (hand to foot) tetrapolar measurements were performed with a single-frequency (50 kHz), phase-sensitive impedance analyzer. The study population was subdivided into three classes of age for statistical analysis: 0 to 3.99 mo, 4 to 7.99 mo, and 8 to 11.99 mo. Using the bivariate normal distribution of resistance and reactance components standardized by the infant's length, the bivariate 95% confidence limits for the mean impedance vector separated by sex and age groups were calculated and plotted. Further, the bivariate 95%, 75%, and 50% tolerance intervals for individual vector measurements in the first year of life were plotted. Resistance and reactance values often fluctuated during the first year of life, particularly as raw measurements (without normalization by subject's length). However, 95% confidence ellipses of mean vectors from the three age groups overlapped each other, as did confidence ellipses by sex for each age class, indicating no significant vector migration during the first year of life. We obtained an estimate of mean impedance vector in a sample of healthy infants in the first year of life and calculated the bivariate values for an individual vector (95%, 75%, and 50% tolerance ellipses).

Density functional theory for the description of spherical non-associating monomers in confined media using the SAFT-VR equation of state and weighted density approximations.

PubMed

Malheiro, Carine; Mendiboure, Bruno; Plantier, Frédéric; Blas, Felipe J; Miqueu, Christelle

2014-04-07

As a first step of an ongoing study of thermodynamic properties and adsorption of complex fluids in confined media, we present a new theoretical description for spherical monomers using the Statistical Associating Fluid Theory for potential of Variable Range (SAFT-VR) and a Non-Local Density Functional Theory (NLDFT) with Weighted Density Approximations (WDA). The well-known Modified Fundamental Measure Theory is used to describe the inhomogeneous hard-sphere contribution as a reference for the monomer and two WDA approaches are developed for the dispersive terms from the high-temperature Barker and Henderson perturbation expansion. The first approach extends the dispersive contributions using the scalar and vector weighted densities introduced in the Fundamental Measure Theory (FMT) and the second one uses a coarse-grained (CG) approach with a unique weighted density. To test the accuracy of this new NLDFT/SAFT-VR coupling, the two versions of the theoretical model are compared with Grand Canonical Monte Carlo (GCMC) molecular simulations using the same molecular model. Only the version with the "CG" approach for the dispersive terms provides results in excellent agreement with GCMC calculations in a wide range of conditions while the "FMT" extension version gives a good representation solely at low pressures. Hence, the "CG" version of the theoretical model is used to reproduce methane adsorption isotherms in a Carbon Molecular Sieve and compared with experimental data after a characterization of the material. The whole results show an excellent agreement between modeling and experiments. Thus, through a complete and consistent comparison both with molecular simulations and with experimental data, the NLDFT/SAFT-VR theory has been validated for the description of monomers.

voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data.

PubMed

Zararsiz, Gokmen; Goksuluk, Dincer; Klaus, Bernd; Korkmaz, Selcuk; Eldem, Vahap; Karabulut, Erdem; Ozturk, Ahmet

2017-01-01

RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom) extensions of the nearest shrunken centroids (NSC) and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom's precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

Plant X-tender: An extension of the AssemblX system for the assembly and expression of multigene constructs in plants.

PubMed

Lukan, Tjaša; Machens, Fabian; Coll, Anna; Baebler, Špela; Messerschmidt, Katrin; Gruden, Kristina

2018-01-01

Cloning multiple DNA fragments for delivery of several genes of interest into the plant genome is one of the main technological challenges in plant synthetic biology. Despite several modular assembly methods developed in recent years, the plant biotechnology community has not widely adopted them yet, probably due to the lack of appropriate vectors and software tools. Here we present Plant X-tender, an extension of the highly efficient, scar-free and sequence-independent multigene assembly strategy AssemblX, based on overlap-depended cloning methods and rare-cutting restriction enzymes. Plant X-tender consists of a set of plant expression vectors and the protocols for most efficient cloning into the novel vector set needed for plant expression and thus introduces advantages of AssemblX into plant synthetic biology. The novel vector set covers different backbones and selection markers to allow full design flexibility. We have included ccdB counterselection, thereby allowing the transfer of multigene constructs into the novel vector set in a straightforward and highly efficient way. Vectors are available as empty backbones and are fully flexible regarding the orientation of expression cassettes and addition of linkers between them, if required. We optimised the assembly and subcloning protocol by testing different scar-less assembly approaches: the noncommercial SLiCE and TAR methods and the commercial Gibson assembly and NEBuilder HiFi DNA assembly kits. Plant X-tender was applicable even in combination with low efficient homemade chemically competent or electrocompetent Escherichia coli. We have further validated the developed procedure for plant protein expression by cloning two cassettes into the newly developed vectors and subsequently transferred them to Nicotiana benthamiana in a transient expression setup. Thereby we show that multigene constructs can be delivered into plant cells in a streamlined and highly efficient way. Our results will support faster introduction of synthetic biology into plant science.

Plant X-tender: An extension of the AssemblX system for the assembly and expression of multigene constructs in plants

PubMed Central

Machens, Fabian; Coll, Anna; Baebler, Špela; Messerschmidt, Katrin; Gruden, Kristina

2018-01-01

Cloning multiple DNA fragments for delivery of several genes of interest into the plant genome is one of the main technological challenges in plant synthetic biology. Despite several modular assembly methods developed in recent years, the plant biotechnology community has not widely adopted them yet, probably due to the lack of appropriate vectors and software tools. Here we present Plant X-tender, an extension of the highly efficient, scar-free and sequence-independent multigene assembly strategy AssemblX, based on overlap-depended cloning methods and rare-cutting restriction enzymes. Plant X-tender consists of a set of plant expression vectors and the protocols for most efficient cloning into the novel vector set needed for plant expression and thus introduces advantages of AssemblX into plant synthetic biology. The novel vector set covers different backbones and selection markers to allow full design flexibility. We have included ccdB counterselection, thereby allowing the transfer of multigene constructs into the novel vector set in a straightforward and highly efficient way. Vectors are available as empty backbones and are fully flexible regarding the orientation of expression cassettes and addition of linkers between them, if required. We optimised the assembly and subcloning protocol by testing different scar-less assembly approaches: the noncommercial SLiCE and TAR methods and the commercial Gibson assembly and NEBuilder HiFi DNA assembly kits. Plant X-tender was applicable even in combination with low efficient homemade chemically competent or electrocompetent Escherichia coli. We have further validated the developed procedure for plant protein expression by cloning two cassettes into the newly developed vectors and subsequently transferred them to Nicotiana benthamiana in a transient expression setup. Thereby we show that multigene constructs can be delivered into plant cells in a streamlined and highly efficient way. Our results will support faster introduction of synthetic biology into plant science. PMID:29300787

Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2010-01-01

Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

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

Emami, Razieh; Mukohyama, Shinji; Namba, Ryo

Many models of inflation driven by vector fields alone have been known to be plagued by pathological behaviors, namely ghost and/or gradient instabilities. In this work, we seek a new class of vector-driven inflationary models that evade all of the mentioned instabilities. We build our analysis on the Generalized Proca Theory with an extension to three vector fields to realize isotropic expansion. We obtain the conditions required for quasi de-Sitter solutions to be an attractor analogous to the standard slow-roll one and those for their stability at the level of linearized perturbations. Identifying the remedy to the existing unstable models,more » we provide a simple example and explicitly show its stability. This significantly broadens our knowledge on vector inflationary scenarios, reviving potential phenomenological interests for this class of models.« less

In Vivo Stable Transduction of Humanized Liver Tissue in Chimeric Mice via High-Capacity Adenovirus–Lentivirus Hybrid Vector

PubMed Central

Kataoka, Miho; Tateno, Chise; Yoshizato, Katsutoshi; Kawasaki, Yoshiko; Kimura, Takahiro; Faure-Kumar, Emmanuelle; Palmer, Donna J.; Ng, Philip; Okamura, Haruki; Kasahara, Noriyuki

2010-01-01

Abstract We developed hybrid vectors employing high-capacity adenovirus as a first-stage carrier encoding all the components required for in situ production of a second-stage lentivirus, thereby achieving stable transgene expression in secondary target cells. Such vectors have never previously been tested in normal tissues, because of the scarcity of suitable in vivo systems permissive for second-stage lentivirus assembly. Here we employed a novel murine model in which endogenous liver tissue is extensively reconstituted with engrafted human hepatocytes, and successfully achieved stable transduction by the second-stage lentivirus produced in situ from first-stage adenovirus. This represents the first demonstration of the functionality of adenoviral-lentiviral hybrid vectors in a normal parenchymal organ in vivo. PMID:19725756

76 FR 472 - Harmonization of Airworthiness Standards for Transport Category Airplanes-Landing Gear Retracting...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-05

... design takeoff weight), occurring during retraction and extension at any airspeed up to 1.5 V SR1 with...) currently uses a peripheral speed equal to 1.3 V S during retraction and extension at any airspeed up to 1.6... design takeoff weight), occurring during retraction and extension at any airspeed up to 1.5 V SR1 (with...

Vector Meson Production at Hera

NASA Astrophysics Data System (ADS)

Szuba, Dorota

The diffractive production of vector mesons ep→eVMY, with VM=ρ0, ω, ϕ, J/ψ, ψ‧ or ϒ and with Y being either the scattered proton or a low mass hadronic system, has been extensively investigated at HERA. HERA offers a unique opportunity to study the dependences of diffractive processes on different scales: the mass of the vector meson, mVM, the centre-of-mass energy of the γp system, W, the photon virtuality, Q2 and the four-momentum transfer squared at the proton vertex, |t|. Strong interactions can be investigated in the transition from the hard to the soft regime, where the confinement of quarks and gluons occurs.

CURRENT CONDITIONS AND RESIDENCE PREFERENCES OR CITIZENS' PERCEPTIONS ON NONCONVENTIONAL WATER RESOURCES

NASA Astrophysics Data System (ADS)

Tsuzuki, Yoshiaki; Aramaki, Toshiya

Preferences or perceptions of ordinary citizens on three kinds of nonconventional water resources including rainwater, permissible groundwater exuding to underground railway stations and tunnels and reclaimed wastewater were investigated by use of the Internet survey method. The survey results were analysed with analytical hierar chal process (AHP) and willingness to pay (WTP). Weight vectors of natural environment and people's lives were found larger than other three first order evaluation conditions, society, economics and technology. The order of the weight vector values for the three water resources were rainwater, reclaimed wastewater and permissible groundwater. That for the five water usages were agricultural and horticulture water, water storage in preparation for disaster, toilet flushing water, environment water and sprinkler water for washing road and cooling atmosphere temperature. The difference between toilet flushing water and environment water was not significant by 5% significance. The analyzed data showed that differences between the weight vector values of the alternatives (water resources and their usages) became small by increasing the number of the evaluation conditions, which would be a topic to be resolved for AHP application to actual public projects. For water resources, WTP with public budgets was Japanese Yen (JY) 53,100-55,100 person-1 year-1, and WTP with private finances was JY 19,100-20,800 person-1 year-1. For water usages, public WTP was JY 20,400-47,200 person-1 year-1 and private WTP was JY 8,400-16,000 person-1 year-1. The orders of WTP values were similar to the orders of the weight vector values for both water resources and their usages obtained by the AHP analysis. Effective dissemination subjects and objects of the nonconventional water resources and their usages were extracted by the analysis for attributes including sex, age, living area, occupation and education.

Prediction of subcellular localization of eukaryotic proteins using position-specific profiles and neural network with weighted inputs.

PubMed

Zou, Lingyun; Wang, Zhengzhi; Huang, Jiaomin

2007-12-01

Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles (PSP) have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific Iterative-Basic Local Alignment Search Tool (PSI-BLAST) has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and 1st-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network (PSP-WNN). The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.

The method for froth floatation condition recognition based on adaptive feature weighted

NASA Astrophysics Data System (ADS)

Wang, Jieran; Zhang, Jun; Tian, Jinwen; Zhang, Daimeng; Liu, Xiaomao

2018-03-01

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.

Automatic EEG artifact removal: a weighted support vector machine approach with error correction.

PubMed

Shao, Shi-Yun; Shen, Kai-Quan; Ong, Chong Jin; Wilder-Smith, Einar P V; Li, Xiao-Ping

2009-02-01

An automatic electroencephalogram (EEG) artifact removal method is presented in this paper. Compared to past methods, it has two unique features: 1) a weighted version of support vector machine formulation that handles the inherent unbalanced nature of component classification and 2) the ability to accommodate structural information typically found in component classification. The advantages of the proposed method are demonstrated on real-life EEG recordings with comparisons made to several benchmark methods. Results show that the proposed method is preferable to the other methods in the context of artifact removal by achieving a better tradeoff between removing artifacts and preserving inherent brain activities. Qualitative evaluation of the reconstructed EEG epochs also demonstrates that after artifact removal inherent brain activities are largely preserved.

Noise generated by a flight weight, air flow control valve in a vertical takeoff and landing aircraft thrust vectoring system

NASA Technical Reports Server (NTRS)

Huff, Ronald G.

1989-01-01

Tests were conducted in the NASA Lewis Research Center's Powered Lift Facility to experimentally evaluate the noise generated by a flight weight, 12 in. butterfly valve installed in a proposed vertical takeoff and landing thrust vectoring system. Fluctuating pressure measurements were made in the circular duct upstream and downstream of the valve. This data report presents the results of these tests. The maximum overall sound pressure level is generated in the duct downstream of the valve and reached a value of 180 dB at a valve pressure ratio of 2.8. At the higher valve pressure ratios the spectra downstream of the valve is broad banded with its maximum at 1000 Hz.

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.

Determination of key parameters of vector multifractal vector fields

NASA Astrophysics Data System (ADS)

Schertzer, D. J. M.; Tchiguirinskaia, I.

2017-12-01

For too long time, multifractal analyses and simulations have been restricted to scalar-valued fields (Schertzer and Tchiguirinskaia, 2017a,b). For instance, the wind velocity multifractality has been mostly analysed in terms of scalar structure functions and with the scalar energy flux. This restriction has had the unfortunate consequences that multifractals were applicable to their full extent in geophysics, whereas it has inspired them. Indeed a key question in geophysics is the complexity of the interactions between various fields or they components. Nevertheless, sophisticated methods have been developed to determine the key parameters of scalar valued fields. In this communication, we first present the vector extensions of the universal multifractal analysis techniques to multifractals whose generator belong to a Levy-Clifford algebra (Schertzer and Tchiguirinskaia, 2015). We point out further extensions noting the increased complexity. For instance, the (scalar) index of multifractality becomes a matrice. Schertzer, D. and Tchiguirinskaia, I. (2015) `Multifractal vector fields and stochastic Clifford algebra', Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(12), p. 123127. doi: 10.1063/1.4937364. Schertzer, D. and Tchiguirinskaia, I. (2017) `An Introduction to Multifractals and Scale Symmetry Groups', in Ghanbarian, B. and Hunt, A. (eds) Fractals: Concepts and Applications in Geosciences. CRC Press, p. (in press). Schertzer, D. and Tchiguirinskaia, I. (2017b) `Pandora Box of Multifractals: Barely Open ?', in Tsonis, A. A. (ed.) 30 Years of Nonlinear Dynamics in Geophysics. Berlin: Springer, p. (in press).

Application of optimal control theory to the design of the NASA/JPL 70-meter antenna servos

NASA Technical Reports Server (NTRS)

Alvarez, L. S.; Nickerson, J.

1989-01-01

The application of Linear Quadratic Gaussian (LQG) techniques to the design of the 70-m axis servos is described. Linear quadratic optimal control and Kalman filter theory are reviewed, and model development and verification are discussed. Families of optimal controller and Kalman filter gain vectors were generated by varying weight parameters. Performance specifications were used to select final gain vectors.

Leather quality of beefalo-Nellore cattle in different production systems.

PubMed

Ítavo, Luís Carlos Vinhas; Mateus, Rodrigo Gonçalves; Ítavo, Camila Celeste Brandão Ferreira; Dias, Alexandre Menezes; Gomes, Fabio Candal; da Silva, Fabiano Ferreira; Schio, Alex Resende; Nogueira, Eriklis; Petit, Hélène Véronique

2017-05-01

The aim was to compare the effects of two production systems on performance, carcass traits and physical-mechanical characteristics of leather from Beefalo-Nellore steers and heifers and to determine if the response to the production system was similar for both genders. A total of 40 Beefalo-Nellore cattle, 20 steers and 20 heifers, were evaluated. Animals were divided into two production systems: slaughtered at 15 (intensive system) or 26 (extensive system) months of age. In the intensive system, all animals received a ration containing 600 g/kg corn silage and 400 g/kg concentrate. In the extensive system, animals were kept on a pasture predominantly based on Brachiaria sp. and supplemented with 2 kg/day concentrate. In the intensive system, there was no difference in slaughter weight (470 kg body weight) between steers and heifers but steers in the extensive system had greater slaughter weight than heifers (463 and 428 kg body weight, respectively). Leather weight was higher for animals in the intensive than extensive system but there was no difference in leather weight once excess fat was removed. Leather quality from Beefalo-Nellore cattle slaughtered at 15 or 26 months of age is similar although carcass yield is higher for cattle slaughtered at a younger age. © 2016 Japanese Society of Animal Science.

Low-rate image coding using vector quantization

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

Makur, A.

1990-01-01

This thesis deals with the development and analysis of a computationally simple vector quantization image compression system for coding monochrome images at low bit rate. Vector quantization has been known to be an effective compression scheme when a low bit rate is desirable, but the intensive computation required in a vector quantization encoder has been a handicap in using it for low rate image coding. The present work shows that, without substantially increasing the coder complexity, it is indeed possible to achieve acceptable picture quality while attaining a high compression ratio. Several modifications to the conventional vector quantization coder aremore » proposed in the thesis. These modifications are shown to offer better subjective quality when compared to the basic coder. Distributed blocks are used instead of spatial blocks to construct the input vectors. A class of input-dependent weighted distortion functions is used to incorporate psychovisual characteristics in the distortion measure. Computationally simple filtering techniques are applied to further improve the decoded image quality. Finally, unique designs of the vector quantization coder using electronic neural networks are described, so that the coding delay is reduced considerably.« less

Mineral Replacement Reactions as a Precursor to Strain Localisation: an (HR-)EBSD approach

NASA Astrophysics Data System (ADS)

Gardner, J.; Wheeler, J.; Wallis, D.; Hansen, L. N.; Mariani, E.

2017-12-01

Much remains to be learned about the links between metamorphism and deformation. Our work investigates the behaviour of fluid-mediated mineral replacement reaction products when exposed to subsequent shear stresses. We focus on albite from a metagabbro that has experienced metamorphism and subsequent deformation at greenschist facies, resulting in a reduction in grain size and associated strain localisation. EBSD maps show that prior to grain size reduction, product grains are highly distorted, yet they formed, and subsequently deformed, at temperatures at which extensive dislocation creep is unlikely. The Weighted Burgers Vector can be used to quantitatively describe the types of Burgers vectors present in geometrically necessary dislocation (GND) populations derived from 2-D EBSD map data. Application of this technique to the distorted product grains reveals the prominence of, among others, dislocations with apparent [010] Burgers vectors. This supports (with some caveats) the idea that dislocation creep is not responsible for the observed lattice distortion, as there are no known slip systems in plagioclase with a [010] Burgers vector. Distortion in a replacement microstructure has also been attributed to the presence of nanoscale product grains, which share very similar, but not identical, orientations due to topotactic nucleation from adjacent sites on the same substrate. As a precipitate, the product grains should be expected to be largely free of elastic strain. However, high angular resolution EBSD results demonstrate that product grains contain both elastic strains (> 10-3) and residual stresses (several hundred MPa), as well as GND densities on the order of 1014-1015 m-2. Thus we suggest the observed distortion (elastic strain plus rotations) in the lattice is produced during the mineral replacement reaction by a lattice mismatch and volume change between parent and product. Stored strain energy then provides a driving force for recovery and recrystallization. Recrystallization produces smaller grains with high angle boundaries, reducing the strength of, and allowing deformation to localise in, the albite phase. Grain size reduction in turn facilitates shear deformation to high strains by a grain size sensitive mechanism (fluid-assisted diffusion creep).

Weighted polygamy inequalities of multiparty entanglement in arbitrary-dimensional quantum systems

NASA Astrophysics Data System (ADS)

Kim, Jeong San

2018-04-01

We provide a generalization for the polygamy constraint of multiparty entanglement in arbitrary-dimensional quantum systems. By using the β th power of entanglement of assistance for 0 ≤β ≤1 and the Hamming weight of the binary vector related with the distribution of subsystems, we establish a class of weighted polygamy inequalities of multiparty entanglement in arbitrary-dimensional quantum systems. We further show that our class of weighted polygamy inequalities can even be improved to be tighter inequalities with some conditions on the assisted entanglement of bipartite subsystems.

Unification with vector-like fermions and signals at LHC

NASA Astrophysics Data System (ADS)

Bhattacherjee, Biplob; Byakti, Pritibhajan; Kushwaha, Ashwani; Vempati, Sudhir K.

2018-05-01

We look for minimal extensions of Standard Model with vector like fermions leading to precision unification of gauge couplings. Constraints from proton decay, Higgs stability and perturbativity are considered. The simplest models contain several copies of vector fermions in two different (incomplete) representations. Some of these models encompass Type III seesaw mechanism for neutrino masses whereas some others have a dark matter candidate. In all the models, at least one of the candidates has non-trivial representation under SU(3)color. In the limit of vanishing Yukawa couplings, new QCD bound states are formed, which can be probed at LHC. The present limits based on results from 13 TeV already probe these particles for masses around a TeV. Similar models can be constructed with three or four vector representations, examples of which are presented.

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

Lightweight, Miniature Inertial Measurement System

NASA Technical Reports Server (NTRS)

Tang, Liang; Crassidis, Agamemnon

2012-01-01

A miniature, lighter-weight, and highly accurate inertial navigation system (INS) is coupled with GPS receivers to provide stable and highly accurate positioning, attitude, and inertial measurements while being subjected to highly dynamic maneuvers. In contrast to conventional methods that use extensive, groundbased, real-time tracking and control units that are expensive, large, and require excessive amounts of power to operate, this method focuses on the development of an estimator that makes use of a low-cost, miniature accelerometer array fused with traditional measurement systems and GPS. Through the use of a position tracking estimation algorithm, onboard accelerometers are numerically integrated and transformed using attitude information to obtain an estimate of position in the inertial frame. Position and velocity estimates are subject to drift due to accelerometer sensor bias and high vibration over time, and so require the integration with GPS information using a Kalman filter to provide highly accurate and reliable inertial tracking estimations. The method implemented here uses the local gravitational field vector. Upon determining the location of the local gravitational field vector relative to two consecutive sensors, the orientation of the device may then be estimated, and the attitude determined. Improved attitude estimates further enhance the inertial position estimates. The device can be powered either by batteries, or by the power source onboard its target platforms. A DB9 port provides the I/O to external systems, and the device is designed to be mounted in a waterproof case for all-weather conditions.

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.

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.

A Partial E3 Deletion in Replication-Defective Adenoviral Vectors Allows for Stable Expression of Potentially Toxic Transgene Products.

PubMed

Haut, Larissa H; Gill, Amanda L; Kurupati, Raj K; Bian, Ang; Li, Yan; Giles-Davis, Wynetta; Xiang, Zhiquan; Zhou, Xiang Yang; Ertl, Hildegund C J

2016-10-01

Adenovirus (Ad) is used extensively for construction of viral vectors, most commonly with deletion in its E1 and/or E3 genomic regions. Previously, our attempts to insert envelope proteins (Env) of HIV-1 into such vectors based on chimpanzee-derived Ad (AdC) viruses were thwarted. Here, we describe that genetic instability of an E1- and E3-deleted AdC vector of serotype C6 expressing Env of HIV-1 can be overcome by reinsertion of E3 sequences with anti-apoptotic activities. This partial E3 deletion presumably delays premature death of HEK-293 packaging cell lines due to Env-induced cell apoptosis. The same partial E3 deletion also allows for the generation of stable glycoprotein 140 (gp140)- and gp160-expressing Ad vectors based on AdC7, a distinct AdC serotype. Env-expressing AdC vectors containing the partial E3 deletion are genetically stable upon serial cell culture passaging, produce yields comparable to those of other AdC vectors, and induce transgene product-specific antibody responses in mice. A partial E3 deletion thereby allows expansion of the repertoire of transgenes that can be expressed by Ad vectors.

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

PubMed

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

2017-09-01

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

Search for charged lepton flavor violation of vector mesons in the BLMSSM model

NASA Astrophysics Data System (ADS)

Dong, Xing-Xing; Zhao, Shu-Min; Feng, Jing-Jing; Ning, Guo-Zhu; Chen, Jian-Bin; Zhang, Hai-Bin; Feng, Tai-Fu

2018-03-01

We analyze the charged lepton flavor violating (CLFV) decays of vector mesons V →li±lj∓ with V ∈{ϕ ,J /Ψ ,ϒ ,ρ0,ω } in the BLMSSM model. This new model is introduced as a supersymmetric extension of the Standard Model (SM), where local gauged baryon number B and lepton number L are considered. The numerical results indicate the BLMSSM model can produce significant contributions to such two-body CLFV decays, and the branching ratios to these CLFV processes can easily reach the present experimental upper bounds. Therefore, searching for CLFV processes of vector mesons may be an effective channel to study new physics.

Energy allocation during the maturation of adults in a long-lived insect: implications for dispersal and reproduction.

PubMed

David, G; Giffard, B; van Halder, I; Piou, D; Jactel, H

2015-10-01

Energy allocation strategies have been widely documented in insects and were formalized in the context of the reproduction process by the terms 'capital breeder' and 'income breeder'. We propose here the extension of this framework to dispersal ability, with the concepts of 'capital disperser' and 'income disperser', and explore the trade-off in resource allocation between dispersal and reproduction. We hypothesized that flight capacity was sex-dependent, due to a trade-off in energy allocation between dispersal and egg production in females. We used Monochamus galloprovincialis as model organism, a long-lived beetle which is the European vector of the pine wood nematode. We estimated the flight capacity with a flight mill and used the number of mature eggs as a proxy for the investment in reproduction. We used the ratio between dry weights of the thorax and the abdomen to investigate the trade-off. The probability of flying increased with the adult weight at emergence, but was not dependent on insect age or sex. Flight distance increased with age in individuals but did not differ between sexes. It was also positively associated with energy allocation to thorax reserves, which increased with age. In females, the abdomen weight and the number of eggs also increase with age with no negative effect on flight capacity, indicating a lack of trade-off. This long-lived beetle has a complex strategy of energy allocation, being a 'capital disperser' in terms of flight ability, an 'income disperser' in terms of flight performance and an 'income breeder' in terms of egg production.

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

New vector-like fermions and flavor physics

DOE PAGES

Ishiwata, Koji; Ligeti, Zoltan; Wise, Mark B.

2015-10-06

We study renormalizable extensions of the standard model that contain vector-like fermions in a (single) complex representation of the standard model gauge group. There are 11 models where the vector-like fermions Yukawa couple to the standard model fermions via the Higgs field. These models do not introduce additional fine-tunings. They can lead to, and are constrained by, a number of different flavor-changing processes involving leptons and quarks, as well as direct searches. An interesting feature of the models with strongly interacting vector-like fermions is that constraints from neutral meson mixings (apart from CP violation inmore » $$ {K}^0-{\\overline{K}}^0 $$ mixing) are not sensitive to higher scales than other flavor-changing neutral-current processes. We identify order 1/(4πM) 2 (where M is the vector-like fermion mass) one-loop contributions to the coefficients of the four-quark operators for meson mixing, that are not suppressed by standard model quark masses and/or mixing angles.« less

Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine.

PubMed

Lao, Zhiqiang; Shen, Dinggang; Liu, Dengfeng; Jawad, Abbas F; Melhem, Elias R; Launer, Lenore J; Bryan, R Nick; Davatzikos, Christos

2008-03-01

Brain lesions, especially white matter lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging. Quantitative analysis of WML in large clinical trials is becoming more and more important. In this article, we present a computer-assisted WML segmentation method, based on local features extracted from multiparametric magnetic resonance imaging (MRI) sequences (ie, T1-weighted, T2-weighted, proton density-weighted, and fluid attenuation inversion recovery MRI scans). A support vector machine classifier is first trained on expert-defined WMLs, and is then used to classify new scans. Postprocessing analysis further reduces false positives by using anatomic knowledge and measures of distance from the training set. Cross-validation on a population of 35 patients from three different imaging sites with WMLs of varying sizes, shapes, and locations tests the robustness and accuracy of the proposed segmentation method, compared with the manual segmentation results from two experienced neuroradiologists.

Semi-automatic feedback using concurrence between mixture vectors for general databases

NASA Astrophysics Data System (ADS)

Larabi, Mohamed-Chaker; Richard, Noel; Colot, Olivier; Fernandez-Maloigne, Christine

2001-12-01

This paper describes how a query system can exploit the basic knowledge by employing semi-automatic relevance feedback to refine queries and runtimes. For general databases, it is often useless to call complex attributes, because we have not sufficient information about images in the database. Moreover, these images can be topologically very different from one to each other and an attribute that is powerful for a database category may be very powerless for the other categories. The idea is to use very simple features, such as color histogram, correlograms, Color Coherence Vectors (CCV), to fill out the signature vector. Then, a number of mixture vectors is prepared depending on the number of very distinctive categories in the database. Knowing that a mixture vector is a vector containing the weight of each attribute that will be used to compute a similarity distance. We post a query in the database using successively all the mixture vectors defined previously. We retain then the N first images for each vector in order to make a mapping using the following information: Is image I present in several mixture vectors results? What is its rank in the results? These informations allow us to switch the system on an unsupervised relevance feedback or user's feedback (supervised feedback).

Spatial distribution of an infectious disease in a small mammal community

NASA Astrophysics Data System (ADS)

Correa, Juana P.; Bacigalupo, Antonella; Fontúrbel, Francisco E.; Oda, Esteban; Cattan, Pedro E.; Solari, Aldo; Botto-Mahan, Carezza

2015-10-01

Chagas disease is a zoonosis caused by the parasite Trypanosoma cruzi and transmitted by insect vectors to several mammals, but little is known about its spatial epidemiology. We assessed the spatial distribution of T. cruzi infection in vectors and small mammals to test if mammal infection status is related to the proximity to vector colonies. During four consecutive years we captured and georeferenced the locations of mammal species and colonies of Mepraia spinolai, a restricted-movement vector. Infection status on mammals and vectors was evaluated by molecular techniques. To examine the effect of vector colonies on mammal infection status, we constructed an infection distance index using the distance between the location of each captured mammal to each vector colony and the average T. cruzi prevalence of each vector colony, weighted by the number of colonies assessed. We collected and evaluated T. cruzi infection in 944 mammals and 1976 M. spinolai. We found a significant effect of the infection distance index in explaining their infection status, when considering all mammal species together. By examining the most abundant species separately, we found this effect only for the diurnal and gregarious rodent Octodon degus. Spatially explicit models involving the prevalence and location of infected vectors and hosts had not been reported previously for a wild disease.

Intruder Polarization.

DTIC Science & Technology

1985-12-01

mentioned project whose objective was to produce 0DIST~i8LT1,vAAILABILITr OF ABSTRACT 21 ABSTRACT SEC R.ITY CLASSiF CATION ~ .~ C.,NCLASSIFIEDI’.,NLMITED M ...wave propagation vector m . Thl-; -’esns that, f we wnnt to perform the tv-o-lirensional inverse 7’,urier ’ransformar i7! (to transform from i-space...nropaqition vector ~,which was used extensively in the -’-i-al npnro)arh, is still retained in the new approach. It is used in nodellin" m . if

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

PubMed

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

2017-03-30

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

Assembly and Functional Analysis of an S/MAR Based Episome with the Cystic Fibrosis Transmembrane Conductance Regulator Gene.

PubMed

De Rocco, Davide; Pompili, Barbara; Castellani, Stefano; Morini, Elena; Cavinato, Luca; Cimino, Giuseppe; Mariggiò, Maria A; Guarnieri, Simone; Conese, Massimo; Del Porto, Paola; Ascenzioni, Fiorentina

2018-04-17

Improving the efficacy of gene therapy vectors is still an important goal toward the development of safe and efficient gene therapy treatments. S/MAR (scaffold/matrix attached region)-based vectors are maintained extra-chromosomally in numerous cell types, which is similar to viral-based vectors. Additionally, when established as an episome, they show a very high mitotic stability. In the present study we tested the idea that addition of an S/MAR element to a CFTR (cystic fibrosis transmembrane conductance regulator) expression vector, may allow the establishment of a CFTR episome in bronchial epithelial cells. Starting from the observation that the S/MAR vector pEPI-EGFP (enhanced green fluorescence protein) is maintained as an episome in human bronchial epithelial cells, we assembled the CFTR vector pBQ-S/MAR. This vector, transfected in bronchial epithelial cells with mutated CFTR , supported long term wt CFTR expression and activity, which in turn positively impacted on the assembly of tight junctions in polarized epithelial cells. Additionally, the recovery of intact pBQ-S/MAR, but not the parental vector lacking the S/MAR element, from transfected cells after extensive proliferation, strongly suggested that pBQ-S/MAR was established as an episome. These results add a new element, the S/MAR, that can be considered to improve the persistence and safety of gene therapy vectors for cystic fibrosis pulmonary disease.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

PubMed

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Sierpinski Triangle Plane

NASA Astrophysics Data System (ADS)

Ettestad, David; Carbonara, Joaquin

The Sierpinski Triangle (ST) is a fractal which has Haussdorf dimension log23 ≈ 1.585 that has been studied extensively. In this paper, we introduce the Sierpinski Triangle Plane (STP), an infinite extension of the ST that spans the entire real plane but is not a vector subspace or a tiling of the plane with a finite set of STs. STP is shown to be a radial fractal with many interesting and surprising properties.

The network organisation of consumer complaints

NASA Astrophysics Data System (ADS)

Rocha, L. E. C.; Holme, P.

2010-07-01

Interaction between consumers and companies can create conflict. When a consensus is unreachable there are legal authorities to resolve the case. This letter is a study of data from the Brazilian Department of Justice from which we build a bipartite network of categories of complaints linked to the companies receiving those complaints. We find the complaint categories organised in an hierarchical way where companies only get complaints of lower degree if they already got complaints of higher degree. The fraction of resolved complaints for a company appears to be nearly independent of the equity of the company but is positively correlated with the total number of complaints received. We construct feature vectors based on the edge-weight —the weight of an edge represents the times complaints of a category have been filed against that company— and use these vectors to study the similarity between the categories of complaints. From this analysis, we obtain trees mapping the hierarchical organisation of the complaints. We also apply principal component analysis to the set of feature vectors concluding that a reduction of the dimensionality of these from 8827 to 27 gives an optimal hierarchical representation.

Different types of degradable vectors from low-molecular-weight polycation-functionalized poly(aspartic acid) for efficient gene delivery.

PubMed

Dou, X B; Hu, Y; Zhao, N N; Xu, F J

2014-03-01

Poly(aspartic acid) (PAsp) has been employed as the potential backbone for the preparation of efficient gene carriers, due to its low cytotoxicity, good biodegradability and excellent biocompatibility. In this work, the degradable linear or star-shaped PBLA was first prepared via ring-opining polymerization of β-benzyl-L-aspartate N-carboxy anhydride (BLA-NCA) initiated by ethylenediamine (ED) or ED-functionalized cyclodextrin cores. Then, PBLA was functionalized via aminolysis reaction with low-molecular-weight poly(2-(dimethylamino)ethyl methacrylate) with one terminal primary amine group (PDMAEMA-NH2), followed by addition of excess ED or ethanolamine (EA) to complete the aminolysis process. The obtained different types of cationic PAsp-based vectors including linear or star PAsp-PDM-NH2 and PAsp-PDM-OH exhibited good condensation capability and degradability, benefiting gene delivery process. In comparison with gold standard polyethylenimine (PEI, ∼ 25 kDa), the cationic PAsp-based vectors, particularly star-shaped ones, exhibited much better transfection performances. Copyright © 2013 Elsevier Ltd. All rights reserved.

Distance learning in discriminative vector quantization.

PubMed

Schneider, Petra; Biehl, Michael; Hammer, Barbara

2009-10-01

Discriminative vector quantization schemes such as learning vector quantization (LVQ) and extensions thereof offer efficient and intuitive classifiers based on the representation of classes by prototypes. The original methods, however, rely on the Euclidean distance corresponding to the assumption that the data can be represented by isotropic clusters. For this reason, extensions of the methods to more general metric structures have been proposed, such as relevance adaptation in generalized LVQ (GLVQ) and matrix learning in GLVQ. In these approaches, metric parameters are learned based on the given classification task such that a data-driven distance measure is found. In this letter, we consider full matrix adaptation in advanced LVQ schemes. In particular, we introduce matrix learning to a recent statistical formalization of LVQ, robust soft LVQ, and we compare the results on several artificial and real-life data sets to matrix learning in GLVQ, a derivation of LVQ-like learning based on a (heuristic) cost function. In all cases, matrix adaptation allows a significant improvement of the classification accuracy. Interestingly, however, the principled behavior of the models with respect to prototype locations and extracted matrix dimensions shows several characteristic differences depending on the data sets.

Concerning an application of the method of least squares with a variable weight matrix

NASA Technical Reports Server (NTRS)

Sukhanov, A. A.

1979-01-01

An estimate of a state vector for a physical system when the weight matrix in the method of least squares is a function of this vector is considered. An iterative procedure is proposed for calculating the desired estimate. Conditions for the existence and uniqueness of the limit of this procedure are obtained, and a domain is found which contains the limit estimate. A second method for calculating the desired estimate which reduces to the solution of a system of algebraic equations is proposed. The question of applying Newton's method of tangents to solving the given system of algebraic equations is considered and conditions for the convergence of the modified Newton's method are obtained. Certain properties of the estimate obtained are presented together with an example.

Remote sensing and environment in the study of the malaria vector Anopheles gambiae in Mali

NASA Astrophysics Data System (ADS)

Rian, Sigrid Katrine Eivindsdatter

The malaria mosquito Anopheles gambiae is the most important vector for the most devastating form of human malaria, the parasite Plasmodium falciparum. In-depth knowledge of the vector's history and environmental preferences is essential in the pursuit of new malaria mitigation strategies. Research was conducted in Mali across a range of habitats occupied by the vector, focusing on three identified chromosomal forms in the mosquito complex. The development of a 500-m landcover classification map was carried out using MODIS satellite imagery and extensive ground survey. The resulting product has the highest resolution and is the most up-to-date and most extensively ground-surveyed among land-cover maps for the study region. The new landcover classification product is a useful tool in the mapping of the varying ecological preferences of the different An. gambiae chromosomal forms. Climate and vegetation characteristics and their relationship to chromosomal forms were investigated further along a Southwest-Northeast moisture gradient in Mali. This research demonstrates particular ecological preferences of each chromosomal form, and gives a detailed examination of particular vegetation structural and climatological patterns across the study region. A key issue in current research into the population structure of An. gambiae is speciation and evolution in the complex, as an understanding of the mechanisms of change can help in the development of new mitigation strategies. A historical review of the paleoecology, archaeology, and other historical sources intended to shed light on the evolutionary history of the vector is presented. The generally held assumption that the current breed of An. gambiae emerged in the rainforest is called into question and discussed within the framework of paleoenvironment and human expansions in sub-Saharan West Africa.

A Precise Drunk Driving Detection Using Weighted Kernel Based on Electrocardiogram.

PubMed

Wu, Chung Kit; Tsang, Kim Fung; Chi, Hao Ran; Hung, Faan Hei

2016-05-09

Globally, 1.2 million people die and 50 million people are injured annually due to traffic accidents. These traffic accidents cost $500 billion dollars. Drunk drivers are found in 40% of the traffic crashes. Existing drunk driving detection (DDD) systems do not provide accurate detection and pre-warning concurrently. Electrocardiogram (ECG) is a proven biosignal that accurately and simultaneously reflects human's biological status. In this letter, a classifier for DDD based on ECG is investigated in an attempt to reduce traffic accidents caused by drunk drivers. At this point, it appears that there is no known research or literature found on ECG classifier for DDD. To identify drunk syndromes, the ECG signals from drunk drivers are studied and analyzed. As such, a precise ECG-based DDD (ECG-DDD) using a weighted kernel is developed. From the measurements, 10 key features of ECG signals were identified. To incorporate the important features, the feature vectors are weighted in the customization of kernel functions. Four commonly adopted kernel functions are studied. Results reveal that weighted feature vectors improve the accuracy by 11% compared to the computation using the prime kernel. Evaluation shows that ECG-DDD improved the accuracy by 8% to 18% compared to prevailing methods.

Feasibility study of new energy projects on three-level indicator system

NASA Astrophysics Data System (ADS)

Zhan, Zhigang

2018-06-01

With the rapid development of new energy industry, many new energy development projects are being carried out all over the world. To analyze the feasibility of the project. we build feasibility of new energy projects assessment model, based on the gathered abundant data about progress in new energy projects.12 indicators are selected by principal component analysis(PCA). Then we construct a new three-level indicator system, where the first level has 1 indicator, the second level has 5 indicators and the third level has 12 indicators to evaluate. Moreover, we use the entropy weight method (EWM) to get weight vector of the indicators in the third level and the multivariate statistical analysis(MVA)to get the weight vector of indicators in the second-class. We use this evaluation model to evaluate the feasibility of the new energy project and make a reference for the subsequent new energy investment. This could be a contribution to the world's low-carbon and green development by investing in sustainable new energy projects. We will introduce new variables and improve the weight model in the future. We also conduct a sensitivity analysis of the model and illustrate the strengths and weaknesses.

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.

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

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.

Dark matter phenomenology of SM and enlarged Higgs sectors extended with vector-like leptons

NASA Astrophysics Data System (ADS)

Angelescu, Andrei; Arcadi, Giorgio

2017-07-01

We will investigate the scenario in which the Standard Model (SM) Higgs sector and its two-doublet extension (called the Two Higgs Doublet Model or 2HDM) are the "portal" for the interactions between the Standard Model and a fermionic Dark Matter (DM) candidate. The latter is the lightest stable neutral particle of a family of vector-like leptons (VLLs). We will provide an extensive overview of this scenario combining the constraints coming purely from DM phenomenology with more general constraints like Electroweak Precision Test (EWPT) as well as with collider searches. In the case that the new fermionic sector interacts with the SM Higgs sector, constraints from DM phenomenology force the new states to lie above the TeV scale. This requirement is relaxed in the case of 2HDM. Nevertheless, strong constraints coming from EWPTs and the Renormalization Group Equations (RGEs) limit the impact of VLFs on collider phenomenology.

Dark matter phenomenology of SM and enlarged Higgs sectors extended with vector-like leptons.

PubMed

Angelescu, Andrei; Arcadi, Giorgio

2017-01-01

We will investigate the scenario in which the Standard Model (SM) Higgs sector and its two-doublet extension (called the Two Higgs Doublet Model or 2HDM) are the "portal" for the interactions between the Standard Model and a fermionic Dark Matter (DM) candidate. The latter is the lightest stable neutral particle of a family of vector-like leptons (VLLs). We will provide an extensive overview of this scenario combining the constraints coming purely from DM phenomenology with more general constraints like Electroweak Precision Test (EWPT) as well as with collider searches. In the case that the new fermionic sector interacts with the SM Higgs sector, constraints from DM phenomenology force the new states to lie above the TeV scale. This requirement is relaxed in the case of 2HDM. Nevertheless, strong constraints coming from EWPTs and the Renormalization Group Equations (RGEs) limit the impact of VLFs on collider phenomenology.

New syndrome decoder for (n, 1) convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

The letter presents a new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck. The new technique uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). A recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector E(D). An example is given for the binary nonsystematic (2, 1) CC.

Automatic assessment of mitral regurgitation severity based on extensive textural features on 2D echocardiography videos.

PubMed

Moghaddasi, Hanie; Nourian, Saeed

2016-06-01

Heart disease is the major cause of death as well as a leading cause of disability in the developed countries. Mitral Regurgitation (MR) is a common heart disease which does not cause symptoms until its end stage. Therefore, early diagnosis of the disease is of crucial importance in the treatment process. Echocardiography is a common method of diagnosis in the severity of MR. Hence, a method which is based on echocardiography videos, image processing techniques and artificial intelligence could be helpful for clinicians, especially in borderline cases. In this paper, we introduce novel features to detect micro-patterns of echocardiography images in order to determine the severity of MR. Extensive Local Binary Pattern (ELBP) and Extensive Volume Local Binary Pattern (EVLBP) are presented as image descriptors which include details from different viewpoints of the heart in feature vectors. Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Template Matching techniques are used as classifiers to determine the severity of MR based on textural descriptors. The SVM classifier with Extensive Uniform Local Binary Pattern (ELBPU) and Extensive Volume Local Binary Pattern (EVLBP) have the best accuracy with 99.52%, 99.38%, 99.31% and 99.59%, respectively, for the detection of Normal, Mild MR, Moderate MR and Severe MR subjects among echocardiography videos. The proposed method achieves 99.38% sensitivity and 99.63% specificity for the detection of the severity of MR and normal subjects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Communications and control for electric power systems: Power flow classification for static security assessment

NASA Technical Reports Server (NTRS)

Niebur, D.; Germond, A.

1993-01-01

This report investigates the classification of power system states using an artificial neural network model, Kohonen's self-organizing feature map. The ultimate goal of this classification is to assess power system static security in real-time. Kohonen's self-organizing feature map is an unsupervised neural network which maps N-dimensional input vectors to an array of M neurons. After learning, the synaptic weight vectors exhibit a topological organization which represents the relationship between the vectors of the training set. This learning is unsupervised, which means that the number and size of the classes are not specified beforehand. In the application developed in this report, the input vectors used as the training set are generated by off-line load-flow simulations. The learning algorithm and the results of the organization are discussed.

Advances in the development of bacterial vector technology.

PubMed

Kochi, Sims K; Killeen, Kevin P; Ryan, Una S

2003-02-01

The demand for new and improved vaccines against human diseases has continued unabated over the past century. While the need continues for traditional vaccines in areas such as infectious diseases, there is an increasing demand for new therapies in nontraditional areas, such as cancer treatment, bioterrorism and food safety. Prompted by these changes, there has been a renewed interest in the application and development of live, attenuated bacteria expressing foreign antigens as vaccines. The application of bacterial vector vaccines to human maladies has been studied most extensively in attenuted strains of Salmonella. Live, attenuated strains of Shigella, Listeria monocytogenes, Mycobacterium bovis-BCG and Vibrio cholerae provide unique alternatives in terms of antigen delivery and immune presentation, however and also show promise as potentially useful bacterial vectors.

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

Immune Recognition of Gene Transfer Vectors: Focus on Adenovirus as a Paradigm

PubMed Central

Aldhamen, Yasser Ali; Seregin, Sergey S.; Amalfitano, Andrea

2011-01-01

Recombinant Adenovirus (Ad) based vectors have been utilized extensively as a gene transfer platform in multiple pre-clinical and clinical applications. These applications are numerous, and inclusive of both gene therapy and vaccine based approaches to human or animal diseases. The widespread utilization of these vectors in both animal models, as well as numerous human clinical trials (Ad-based vectors surpass all other gene transfer vectors relative to numbers of patients treated, as well as number of clinical trials overall), has shed light on how this virus vector interacts with both the innate and adaptive immune systems. The ability to generate and administer large amounts of this vector likely contributes not only to their ability to allow for highly efficient gene transfer, but also their elicitation of host immune responses to the vector and/or the transgene the vector expresses in vivo. These facts, coupled with utilization of several models that allow for full detection of these responses has predicted several observations made in human trials, an important point as lack of similar capabilities by other vector systems may prevent detection of such responses until only after human trials are initiated. Finally, induction of innate or adaptive immune responses by Ad vectors may be detrimental in one setting (i.e., gene therapy) and be entirely beneficial in another (i.e., prophylactic or therapeutic vaccine based applications). Herein, we review the current understanding of innate and adaptive immune responses to Ad vectors, as well some recent advances that attempt to capitalize on this understanding so as to further broaden the safe and efficient use of Ad-based gene transfer therapies in general. PMID:22566830

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

Effects of upright weight bearing and the knee flexion angle on patellofemoral indices using magnetic resonance imaging in patients with patellofemoral instability.

PubMed

Becher, Christoph; Fleischer, Benjamin; Rase, Marten; Schumacher, Thees; Ettinger, Max; Ostermeier, Sven; Smith, Tomas

2017-08-01

This study analysed the effects of upright weight bearing and the knee flexion angle on patellofemoral indices, determined using magnetic resonance imaging (MRI), in patients with patellofemoral instability (PI). Healthy volunteers (control group, n = 9) and PI patients (PI group, n = 16) were scanned in an open-configuration MRI scanner during upright weight bearing and supine non-weight bearing positions at full extension (0° flexion) and at 15°, 30°, and 45° flexion. Patellofemoral indices included the Insall-Salvati Index, Caton-Deschamp Index, and Patellotrochlear Index (PTI) to determine patellar height and the patellar tilt angle (PTA), bisect offset (BO), and the tibial tubercle-trochlear groove (TT-TG) distance to assess patellar rotation and translation with respect to the femur and alignment of the extensor mechanism. A significant interaction effect of weight bearing by flexion angle was observed for the PTI, PTA, and BO for subjects with PI. At full extension, post hoc pairwise comparisons revealed a significant effect of weight bearing on the indices, with increased patellar height and increased PTA and BO in the PI group. Except for the BO, no such changes were seen in the control group. Independent of weight bearing, flexing the knee caused the PTA, BO, and TT-TG distance to be significantly reduced. Upright weight bearing and the knee flexion angle affected patellofemoral MRI indices in PI patients, with significantly increased values at full extension. The observations of this study provide a caution to be considered by professionals when treating PI patients. These patients should be evaluated clinically and radiographically at full extension and various flexion angles in context with quadriceps engagement. Explorative case-control study, Level III.

Water deficit enhances the transmission of plant viruses by insect vectors

PubMed Central

Yvon, Michel; Vile, Denis; Dader, Beatriz; Fereres, Alberto

2017-01-01

Drought is a major threat to crop production worldwide and is accentuated by global warming. Plant responses to this abiotic stress involve physiological changes overlapping, at least partially, the defense pathways elicited both by viruses and their herbivore vectors. Recently, a number of theoretical and empirical studies anticipated the influence of climate changes on vector-borne viruses of plants and animals, mainly addressing the effects on the virus itself or on the vector population dynamics, and inferring possible consequences on virus transmission. Here, we directly assess the effect of a severe water deficit on the efficiency of aphid-transmission of the Cauliflower mosaic virus (CaMV) or the Turnip mosaic virus (TuMV). For both viruses, our results demonstrate that the rate of vector-transmission is significantly increased from water-deprived source plants: CaMV transmission reproducibly increased by 34% and that of TuMV by 100%. In both cases, the enhanced transmission rate could not be explained by a higher virus accumulation, suggesting a more complex drought-induced process that remains to be elucidated. The evidence that infected plants subjected to drought are much better virus sources for insect vectors may have extensive consequences for viral epidemiology, and should be investigated in a wide range of plant-virus-vector systems. PMID:28467423

Water deficit enhances the transmission of plant viruses by insect vectors.

PubMed

van Munster, Manuella; Yvon, Michel; Vile, Denis; Dader, Beatriz; Fereres, Alberto; Blanc, Stéphane

2017-01-01

Drought is a major threat to crop production worldwide and is accentuated by global warming. Plant responses to this abiotic stress involve physiological changes overlapping, at least partially, the defense pathways elicited both by viruses and their herbivore vectors. Recently, a number of theoretical and empirical studies anticipated the influence of climate changes on vector-borne viruses of plants and animals, mainly addressing the effects on the virus itself or on the vector population dynamics, and inferring possible consequences on virus transmission. Here, we directly assess the effect of a severe water deficit on the efficiency of aphid-transmission of the Cauliflower mosaic virus (CaMV) or the Turnip mosaic virus (TuMV). For both viruses, our results demonstrate that the rate of vector-transmission is significantly increased from water-deprived source plants: CaMV transmission reproducibly increased by 34% and that of TuMV by 100%. In both cases, the enhanced transmission rate could not be explained by a higher virus accumulation, suggesting a more complex drought-induced process that remains to be elucidated. The evidence that infected plants subjected to drought are much better virus sources for insect vectors may have extensive consequences for viral epidemiology, and should be investigated in a wide range of plant-virus-vector systems.

Evidence for instantaneous e-vector detection in the honeybee using an associative learning paradigm

PubMed Central

Sakura, Midori; Okada, Ryuichi; Aonuma, Hitoshi

2012-01-01

Many insects use the polarization pattern of the sky for obtaining compass information during orientation or navigation. E-vector information is collected by a specialized area in the dorsal-most part of the compound eye, the dorsal rim area (DRA). We tested honeybees' capability of learning certain e-vector orientations by using a classical conditioning paradigm with the proboscis extension reflex. When one e-vector orientation (CS+) was associated with sugar water, while another orientation (CS−) was not rewarded, the honeybees could discriminate CS+ from CS−. Bees whose DRA was inactivated by painting did not learn CS+. When ultraviolet (UV) polarized light (350 nm) was used for CS, the bees discriminated CS+ from CS−, but no discrimination was observed in blue (442 nm) or green light (546 nm). Our data indicate that honeybees can learn and discriminate between different e-vector orientations, sensed by the UV receptors of the DRA, suggesting that bees can determine their flight direction from polarized UV skylight during foraging. Fixing the bees' heads during the experiments did not prevent learning, indicating that they use an ‘instantaneous’ algorithm of e-vector detection; that is, the bees do not need to actively scan the sky with their DRAs (‘sequential’ method) to determine e-vector orientation. PMID:21733901

Shuttle of lentiviral vectors via transplanted cells in vivo.

PubMed

Blömer, U; Gruh, I; Witschel, H; Haverich, A; Martin, U

2005-01-01

Lentiviral vectors have turned out to be an efficient method for stable gene transfer in vitro and in vivo. Not only do fields of application include cell marking and tracing following transplantation in vivo, but also the stable delivery of biological active proteins for gene therapy. A variety of cells, however, need immediate transplantation after preparation, for example, to prevent cell death, differentiation or de-differentiation. Although these cells are usually washed several times following lentiviral transduction, there may be the risk of viral vector shuttle via transplanted cells resulting in undesired in vivo transduction of recipient cells. We investigated whether infectious lentiviral particles are transmitted via ex vivo lentivirally transduced cells. To this end, we explored potential viral shuttle via ex vivo lentivirally transduced cardiomyocytes in vitro and following transplantation into the brain and peripheral muscle. We demonstrate that, even after extensive washing, infectious viral vector particles can be detected in cell suspensions. Those lentiviral vector particles were able to transduce target cells in transwell experiments. Moreover, transmitted vector particles stably transduced resident cells of the recipient central nervous system and muscle in vivo. Our results of lentiviral vector shuttle via transduced cardiomyocytes are significant for both ex vivo gene therapy and for lentiviral cell tracing, in particular for investigation of stem cell differentiation in transplantation models and co-cultivation systems.

Getting genetic access to natural adenovirus genomes to explore vector diversity.

PubMed

Zhang, Wenli; Ehrhardt, Anja

2017-10-01

Recombinant vectors based on the human adenovirus type 5 (HAdV5) have been developed and extensively used in preclinical and clinical studies for over 30 years. However, certain restrictions of HAdV5-based vectors have limited their clinical applications because they are rather inefficient in specifically transducing cells of therapeutic interest that lack the coxsackievirus and adenovirus receptor (CAR). Moreover, enhanced vector-associated toxicity and widespread preexisting immunity have been shown to significantly hamper the effectiveness of HAdV-5-mediated gene transfer. However, evolution of adenoviruses in the natural host is driving the generation of novel types with altered virulence, enhanced transmission, and altered tissue tropism. As a consequence, an increasing number of alternative adenovirus types were identified, which may represent a valuable resource for the development of novel vector types. Thus, researchers are focusing on the other naturally occurring adenovirus types, which are structurally similar but functionally different from HAdV5. To this end, several strategies have been devised for getting genetic access to adenovirus genomes, resulting in a new panel of adenoviral vectors. Importantly, these vectors were shown to have a host range different from HAdV5 and to escape the anti-HAdV5 immune response, thus underlining the great potential of this approach. In summary, this review provides a state-of-the-art overview of one essential step in adenoviral vector development.

Multiple sensor fault diagnosis for dynamic processes.

PubMed

Li, Cheng-Chih; Jeng, Jyh-Cheng

2010-10-01

Modern industrial plants are usually large scaled and contain a great amount of sensors. Sensor fault diagnosis is crucial and necessary to process safety and optimal operation. This paper proposes a systematic approach to detect, isolate and identify multiple sensor faults for multivariate dynamic systems. The current work first defines deviation vectors for sensor observations, and further defines and derives the basic sensor fault matrix (BSFM), consisting of the normalized basic fault vectors, by several different methods. By projecting a process deviation vector to the space spanned by BSFM, this research uses a vector with the resulted weights on each direction for multiple sensor fault diagnosis. This study also proposes a novel monitoring index and derives corresponding sensor fault detectability. The study also utilizes that vector to isolate and identify multiple sensor faults, and discusses the isolatability and identifiability. Simulation examples and comparison with two conventional PCA-based contribution plots are presented to demonstrate the effectiveness of the proposed methodology. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Robust Lentiviral Gene Delivery But Limited Transduction Capacity of Commonly Used Adeno-Associated Viral Serotypes in Xenotransplanted Human Skin.

PubMed

Jakobsen, Maria; Askou, Anne Louise; Stenderup, Karin; Rosada, Cecilia; Dagnæs-Hansen, Frederik; Jensen, Thomas G; Corydon, Thomas J; Mikkelsen, Jacob Giehm; Aagaard, Lars

2015-08-01

Skin is an easily accessible organ, and therapeutic gene transfer to skin remains an attractive alternative for the treatment of skin diseases. Although we have previously documented potent lentiviral gene delivery to human skin, vectors based on adeno-associated virus (AAV) rank among the most promising gene delivery tools for in vivo purposes. Thus, we compared the potential usefulness of various serotypes of recombinant AAV vectors and lentiviral vectors for gene transfer to human skin in a xenotransplanted mouse model. Vector constructs encoding firefly luciferase were packaged in AAV capsids of serotype 1, 2, 5, 6, 8, and 9 and separately administered by intradermal injection in human skin transplants. For all serotypes, live bioimaging demonstrated low levels of transgene expression in the human skin graft, and firefly luciferase expression was observed primarily in neighboring tissue outside of the graft. In contrast, gene delivery by intradermally injected lentiviral vectors was efficient and led to extensive and persistent firefly luciferase expression within the human skin graft only. The study demonstrates the limited capacity of single-stranded AAV vectors of six commonly used serotypes for gene delivery to human skin in vivo.

Robust Lentiviral Gene Delivery But Limited Transduction Capacity of Commonly Used Adeno-Associated Viral Serotypes in Xenotransplanted Human Skin

PubMed Central

Jakobsen, Maria; Askou, Anne Louise; Stenderup, Karin; Rosada, Cecilia; Dagnæs-Hansen, Frederik; Jensen, Thomas G.; Corydon, Thomas J.; Mikkelsen, Jacob Giehm; Aagaard, Lars

2015-01-01

Skin is an easily accessible organ, and therapeutic gene transfer to skin remains an attractive alternative for the treatment of skin diseases. Although we have previously documented potent lentiviral gene delivery to human skin, vectors based on adeno-associated virus (AAV) rank among the most promising gene delivery tools for in vivo purposes. Thus, we compared the potential usefulness of various serotypes of recombinant AAV vectors and lentiviral vectors for gene transfer to human skin in a xenotransplanted mouse model. Vector constructs encoding firefly luciferase were packaged in AAV capsids of serotype 1, 2, 5, 6, 8, and 9 and separately administered by intradermal injection in human skin transplants. For all serotypes, live bioimaging demonstrated low levels of transgene expression in the human skin graft, and firefly luciferase expression was observed primarily in neighboring tissue outside of the graft. In contrast, gene delivery by intradermally injected lentiviral vectors was efficient and led to extensive and persistent firefly luciferase expression within the human skin graft only. The study demonstrates the limited capacity of single-stranded AAV vectors of six commonly used serotypes for gene delivery to human skin in vivo. PMID:26204415

Light-weight extension tubes for compressed-air garden sprayers

Treesearch

Thomas W. McConkey; Charles E. Swett

1967-01-01

To hand-spray taller trees safely and efficiently, 8-, 12-, and 16-foot extension tubes for compressed-air garden sprayers were designed and built. These light-weight tubes have been used successfully for spraying white pine leaders for weevil control on the Massabesic Experimental Forest in Maine. Bill of materials and assembly instructions are included.

An Adaptive Spectrally Weighted Structure Tensor Applied to Tensor Anisotropic Nonlinear Diffusion for Hyperspectral Images

ERIC Educational Resources Information Center

Marin Quintero, Maider J.

2013-01-01

The structure tensor for vector valued images is most often defined as the average of the scalar structure tensors in each band. The problem with this definition is the assumption that all bands provide the same amount of edge information giving them the same weights. As a result non-edge pixels can be reinforced and edges can be weakened…

sw-SVM: sensor weighting support vector machines for EEG-based brain-computer interfaces.

PubMed

Jrad, N; Congedo, M; Phlypo, R; Rousseau, S; Flamary, R; Yger, F; Rakotomamonjy, A

2011-10-01

In many machine learning applications, like brain-computer interfaces (BCI), high-dimensional sensor array data are available. Sensor measurements are often highly correlated and signal-to-noise ratio is not homogeneously spread across sensors. Thus, collected data are highly variable and discrimination tasks are challenging. In this work, we focus on sensor weighting as an efficient tool to improve the classification procedure. We present an approach integrating sensor weighting in the classification framework. Sensor weights are considered as hyper-parameters to be learned by a support vector machine (SVM). The resulting sensor weighting SVM (sw-SVM) is designed to satisfy a margin criterion, that is, the generalization error. Experimental studies on two data sets are presented, a P300 data set and an error-related potential (ErrP) data set. For the P300 data set (BCI competition III), for which a large number of trials is available, the sw-SVM proves to perform equivalently with respect to the ensemble SVM strategy that won the competition. For the ErrP data set, for which a small number of trials are available, the sw-SVM shows superior performances as compared to three state-of-the art approaches. Results suggest that the sw-SVM promises to be useful in event-related potentials classification, even with a small number of training trials.

Effect of thumb anaesthesia on weight perception, muscle activity and the stretch reflex in man.

PubMed Central

Marsden, C D; Rothwell, J C; Traub, M M

1979-01-01

1. We have confirmed the results of Gandevia & McCloskey (1977) on the effect of thumb anaesthesia on perception of weights lifted by the thumb. Weights lifted by flexion feel heavier and weights lifted by extension feel lighter. 2. The change in size of the long-latency stretch reflex in flexor pollicis longus or extensor pollicis longus after thumb anaesthesia cannot explain the effect on weight perception by removal or augmentation of the background servo assistance to muscular contraction. 3. During smooth thumb flexion, thumb anaesthesia increases e.m.g. activity in flexor pollicis longus and extensor pollicis longus for any given opposing torque. 4. During smooth thumb extension the opposite occurs: e.m.g. activity in both extensor and flexor pollicis longus decreases. 5. Clamping the thumb at the proximal phalanx to limit movement solely to the interphalangeal joint reduces or abolishes the effect of anaesthesia on both weight perception and e.m.g. activity during both flexion or extension tasks. 6. Gandevia & McCloskey's findings on the distorting effects of thumb anaesthesia on weight perception cannot be used to support the hypothesis of an efferent monitoring system of the sense of effort. Our results emphasize the close functional relationship between cutaneous and joint afferent information and motor control. PMID:512948

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.

Vector-algebra approach to extract Denavit-Hartenberg parameters of assembled robot arms

NASA Technical Reports Server (NTRS)

Barker, L. K.

1983-01-01

The Denavit-Hartenberg parameters characterize the joint axis systems in a robot arm and, naturally, appear in the transformation matrices from one joint axis system to another. These parameters are needed in the control of robot arms and in the passage of sensor information along the arm. This paper presents a vector algebra method to determine these parameters for any assembled robot arm. The idea is to measure the location of the robot hand (or extension) for different joint angles and then use these measurements to calculate the parameters.

Extended phase matching of second-harmonic generation in periodically poled KTiOPO4 with zero group-velocity mismatch

NASA Astrophysics Data System (ADS)

König, Friedrich; Wong, Franco N. C.

2004-03-01

Under extended phase-matching conditions, the first frequency derivative of the wave-vector mismatch is zero and the phase-matching bandwidth is greatly increased. We present extensive three-wave mixing measurements of the wave-vector mismatch and obtain improved Sellmeier equations for KTiOPO4. We observed a type-II extended phase-matching bandwidth of 100 nm for second-harmonic generation in periodically poled KTiOPO4, centered at the fundamental wavelength of 1584 nm. Applications in quantum entanglement and frequency metrology are discussed.

Credit Risk Evaluation Using a C-Variable Least Squares Support Vector Classification Model

NASA Astrophysics Data System (ADS)

Yu, Lean; Wang, Shouyang; Lai, K. K.

Credit risk evaluation is one of the most important issues in financial risk management. In this paper, a C-variable least squares support vector classification (C-VLSSVC) model is proposed for credit risk analysis. The main idea of this model is based on the prior knowledge that different classes may have different importance for modeling and more weights should be given to those classes with more importance. The C-VLSSVC model can be constructed by a simple modification of the regularization parameter in LSSVC, whereby more weights are given to the lease squares classification errors with important classes than the lease squares classification errors with unimportant classes while keeping the regularized terms in its original form. For illustration purpose, a real-world credit dataset is used to test the effectiveness of the C-VLSSVC model.

Silk-Elastinlike Copolymers for Breast Cancer Gene Therapy

DTIC Science & Technology

2005-05-01

linearized expression vector were mixed hydrolysis of the sample in 6 N HCI at 110 ’C for 20 h. at a high monomer-to-vector molar ratio in the presence of...measurements were taken for each sample GAGTA(GA(GTGC(GGTGTA(GAGTTCCTGCGATrT’GC( for calculation of q. TAcCAC(;AGTA(;(;CGTACCGCGAGG’AGGAGTGCC(;,GGTC The...P (Pro), proline ; Q (Gln), steps are to examine the influence of polymer molecular glutamine; Q, weight equilibrium swelling ratios of hydrogels

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

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

Robotic application of a dynamic resultant force vector using real-time load-control: simulation of an ideal follower load on Cadaveric L4-L5 segments.

PubMed

Bennett, Charles R; Kelly, Brian P

2013-08-09

Standard in-vitro spine testing methods have focused on application of isolated and/or constant load components while the in-vivo spine is subject to multiple components that can be resolved into resultant dynamic load vectors. To advance towards more in-vivo like simulations the objective of the current study was to develop a methodology to apply robotically-controlled, non-zero, real-time dynamic resultant forces during flexion-extension on human lumbar motion segment units (MSU) with initial application towards simulation of an ideal follower load (FL) force vector. A proportional-integral-derivative (PID) controller with custom algorithms coordinated the motion of a Cartesian serial manipulator comprised of six axes each capable of position- or load-control. Six lumbar MSUs (L4-L5) were tested with continuously increasing sagittal plane bending to 8 Nm while force components were dynamically programmed to deliver a resultant 400 N FL that remained normal to the moving midline of the intervertebral disc. Mean absolute load-control tracking errors between commanded and experimental loads were computed. Global spinal ranges of motion and sagittal plane inter-body translations were compared to previously published values for non-robotic applications. Mean TEs for zero-commanded force and moment axes were 0.7 ± 0.4N and 0.03 ± 0.02 Nm, respectively. For non-zero force axes mean TEs were 0.8 ± 0.8 N, 1.3 ± 1.6 Nm, and 1.3 ± 1.6N for Fx, Fz, and the resolved ideal follower load vector FL(R), respectively. Mean extension and flexion ranges of motion were 2.6° ± 1.2° and 5.0° ± 1.7°, respectively. Relative vertebral body translations and rotations were very comparable to data collected with non-robotic systems in the literature. The robotically coordinated Cartesian load controlled testing system demonstrated robust real-time load-control that permitted application of a real-time dynamic non-zero load vector during flexion-extension. For single MSU investigations the methodology has potential to overcome conventional follower load limitations, most notably via application outside the sagittal plane. This methodology holds promise for future work aimed at reducing the gap between current in-vitro testing and in-vivo circumstances. Copyright © 2013 Elsevier Ltd. All rights reserved.

Selected advanced aerodynamics and active controls technology concepts development on a derivative B-747 aircraft

NASA Technical Reports Server (NTRS)

1983-01-01

Analytical design and wind tunnel test evaluations covering the feasibility of applying wing tip extensions, winglets, and active control wing had alleviation to the model B747 are described. Aerodynamic improvement offered by wing tip extension and winglet individually, and the combined aerodynamic and weight improvements when wing load alleviation is combined with the tip extension or the winglet are evaluated. Results are presented in the form of incremental effects on weight mission range, fuel usage, cost, and airline operating economics.

FNV: light-weight flash-based network and pathway viewer.

PubMed

Dannenfelser, Ruth; Lachmann, Alexander; Szenk, Mariola; Ma'ayan, Avi

2011-04-15

Network diagrams are commonly used to visualize biochemical pathways by displaying the relationships between genes, proteins, mRNAs, microRNAs, metabolites, regulatory DNA elements, diseases, viruses and drugs. While there are several currently available web-based pathway viewers, there is still room for improvement. To this end, we have developed a flash-based network viewer (FNV) for the visualization of small to moderately sized biological networks and pathways. Written in Adobe ActionScript 3.0, the viewer accepts simple Extensible Markup Language (XML) formatted input files to display pathways in vector graphics on any web-page providing flexible layout options, interactivity with the user through tool tips, hyperlinks and the ability to rearrange nodes on the screen. FNV was utilized as a component in several web-based systems, namely Genes2Networks, Lists2Networks, KEA, ChEA and PathwayGenerator. In addition, FVN can be used to embed pathways inside pdf files for the communication of pathways in soft publication materials. FNV is available for use and download along with the supporting documentation and sample networks at http://www.maayanlab.net/FNV. avi.maayan@mssm.edu.

Capillary wave Hamiltonian for the Landau-Ginzburg-Wilson density functional

NASA Astrophysics Data System (ADS)

Chacón, Enrique; Tarazona, Pedro

2016-06-01

We study the link between the density functional (DF) formalism and the capillary wave theory (CWT) for liquid surfaces, focused on the Landau-Ginzburg-Wilson (LGW) model, or square gradient DF expansion, with a symmetric double parabola free energy, which has been extensively used in theoretical studies of this problem. We show the equivalence between the non-local DF results of Parry and coworkers and the direct evaluation of the mean square fluctuations of the intrinsic surface, as is done in the intrinsic sampling method for computer simulations. The definition of effective wave-vector dependent surface tensions is reviewed and we obtain new proposals for the LGW model. The surface weight proposed by Blokhuis and the surface mode analysis proposed by Stecki provide consistent and optimal effective definitions for the extended CWT Hamiltonian associated to the DF model. A non-local, or coarse-grained, definition of the intrinsic surface provides the missing element to get the mesoscopic surface Hamiltonian from the molecular DF description, as had been proposed a long time ago by Dietrich and coworkers.

Capillary wave Hamiltonian for the Landau-Ginzburg-Wilson density functional.

PubMed

Chacón, Enrique; Tarazona, Pedro

2016-06-22

We study the link between the density functional (DF) formalism and the capillary wave theory (CWT) for liquid surfaces, focused on the Landau-Ginzburg-Wilson (LGW) model, or square gradient DF expansion, with a symmetric double parabola free energy, which has been extensively used in theoretical studies of this problem. We show the equivalence between the non-local DF results of Parry and coworkers and the direct evaluation of the mean square fluctuations of the intrinsic surface, as is done in the intrinsic sampling method for computer simulations. The definition of effective wave-vector dependent surface tensions is reviewed and we obtain new proposals for the LGW model. The surface weight proposed by Blokhuis and the surface mode analysis proposed by Stecki provide consistent and optimal effective definitions for the extended CWT Hamiltonian associated to the DF model. A non-local, or coarse-grained, definition of the intrinsic surface provides the missing element to get the mesoscopic surface Hamiltonian from the molecular DF description, as had been proposed a long time ago by Dietrich and coworkers.

Dendrimers in drug delivery and targeting: Drug-dendrimer interactions and toxicity issues

PubMed Central

Madaan, Kanika; Kumar, Sandeep; Poonia, Neelam; Lather, Viney; Pandita, Deepti

2014-01-01

Dendrimers are the emerging polymeric architectures that are known for their defined structures, versatility in drug delivery and high functionality whose properties resemble with biomolecules. These nanostructured macromolecules have shown their potential abilities in entrapping and/or conjugating the high molecular weight hydrophilic/hydrophobic entities by host-guest interactions and covalent bonding (prodrug approach) respectively. Moreover, high ratio of surface groups to molecular volume has made them a promising synthetic vector for gene delivery. Owing to these properties dendrimers have fascinated the researchers in the development of new drug carriers and they have been implicated in many therapeutic and biomedical applications. Despite of their extensive applications, their use in biological systems is limited due to toxicity issues associated with them. Considering this, the present review has focused on the different strategies of their synthesis, drug delivery and targeting, gene delivery and other biomedical applications, interactions involved in formation of drug-dendrimer complex along with characterization techniques employed for their evaluation, toxicity problems and associated approaches to alleviate their inherent toxicity. PMID:25035633

[Cloning and gene expression in lactic acid bacteria].

PubMed

Bondarenko, V M; Beliavskaia, V A

2000-01-01

The possibility of using the genera Lactobacillus and Lactococcus as vector representatives is widely discussed at present. The prospects of the construction of recombinant bacteria are closely connected with the solution of a number of problems: the level of the transcription of cloned genes, the effectiveness of the translation of heterologous mRNA, the stability of protein with respect to bacterial intracellular proteases, the method by protein molecules leave the cell (by secretion or as the result of lysis). To prevent segregation instability, the construction of vector molecules on the basis of stable cryptic plasmids found in wild strains of lactic acid bacteria was proposed. High copying plasmids with low molecular weight were detected in L. plantarum and L. pentosus strains. Several plasmids with molecular weights of 1.7, 1.8 and 2.3 kb were isolated from bacterial cells to be used as the basis for the construction of vector molecules. Genes of chloramphenicol- and erythromycin-resistance from Staphylococcus aureus plasmids were used as marker genes ensuring cell transformation. The vector plasmids thus constructed exhibited high transformation activity in the electroporation of different strains, including L. casei, L. plantarum, L. acidophilus, L. fermentum and L. brevis which could be classified with the replicons of a wide circle of hosts. But the use of these plasmids was limited due to the risk of the uncontrolled dissemination of recombinant plasmids. L. acidophilus were also found to have strictly specific plasmids with good prospects of being used as the basis for the creation of vectors, incapable of dissemination. In addition to the search of strain-specific plasmids, incapable of uncontrolled gene transmission, the use of chromosome-integrated heterologous genes is recommended in cloning to ensure the maximum safety.

Adaptive vector validation in image velocimetry to minimise the influence of outlier clusters

NASA Astrophysics Data System (ADS)

Masullo, Alessandro; Theunissen, Raf

2016-03-01

The universal outlier detection scheme (Westerweel and Scarano in Exp Fluids 39:1096-1100, 2005) and the distance-weighted universal outlier detection scheme for unstructured data (Duncan et al. in Meas Sci Technol 21:057002, 2010) are the most common PIV data validation routines. However, such techniques rely on a spatial comparison of each vector with those in a fixed-size neighbourhood and their performance subsequently suffers in the presence of clusters of outliers. This paper proposes an advancement to render outlier detection more robust while reducing the probability of mistakenly invalidating correct vectors. Velocity fields undergo a preliminary evaluation in terms of local coherency, which parametrises the extent of the neighbourhood with which each vector will be compared subsequently. Such adaptivity is shown to reduce the number of undetected outliers, even when implemented in the afore validation schemes. In addition, the authors present an alternative residual definition considering vector magnitude and angle adopting a modified Gaussian-weighted distance-based averaging median. This procedure is able to adapt the degree of acceptable background fluctuations in velocity to the local displacement magnitude. The traditional, extended and recommended validation methods are numerically assessed on the basis of flow fields from an isolated vortex, a turbulent channel flow and a DNS simulation of forced isotropic turbulence. The resulting validation method is adaptive, requires no user-defined parameters and is demonstrated to yield the best performances in terms of outlier under- and over-detection. Finally, the novel validation routine is applied to the PIV analysis of experimental studies focused on the near wake behind a porous disc and on a supersonic jet, illustrating the potential gains in spatial resolution and accuracy.

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.

Boosting with Averaged Weight Vectors

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Clancy, Daniel (Technical Monitor)

2002-01-01

AdaBoost is a well-known ensemble learning algorithm that constructs its constituent or base models in sequence. A key step in AdaBoost is constructing a distribution over the training examples to create each base model. This distribution, represented as a vector, is constructed to be orthogonal to the vector of mistakes made by the previous base model in the sequence. The idea is to make the next base model's errors uncorrelated with those of the previous model. Some researchers have pointed out the intuition that it is probably better to construct a distribution that is orthogonal to the mistake vectors of all the previous base models, but that this is not always possible. We present an algorithm that attempts to come as close as possible to this goal in an efficient manner. We present experimental results demonstrating significant improvement over AdaBoost and the Totally Corrective boosting algorithm, which also attempts to satisfy this goal.

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.

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

Malheiro, Carine; Mendiboure, Bruno; Plantier, Frédéric

As a first step of an ongoing study of thermodynamic properties and adsorption of complex fluids in confined media, we present a new theoretical description for spherical monomers using the Statistical Associating Fluid Theory for potential of Variable Range (SAFT-VR) and a Non-Local Density Functional Theory (NLDFT) with Weighted Density Approximations (WDA). The well-known Modified Fundamental Measure Theory is used to describe the inhomogeneous hard-sphere contribution as a reference for the monomer and two WDA approaches are developed for the dispersive terms from the high-temperature Barker and Henderson perturbation expansion. The first approach extends the dispersive contributions using the scalarmore » and vector weighted densities introduced in the Fundamental Measure Theory (FMT) and the second one uses a coarse-grained (CG) approach with a unique weighted density. To test the accuracy of this new NLDFT/SAFT-VR coupling, the two versions of the theoretical model are compared with Grand Canonical Monte Carlo (GCMC) molecular simulations using the same molecular model. Only the version with the “CG” approach for the dispersive terms provides results in excellent agreement with GCMC calculations in a wide range of conditions while the “FMT” extension version gives a good representation solely at low pressures. Hence, the “CG” version of the theoretical model is used to reproduce methane adsorption isotherms in a Carbon Molecular Sieve and compared with experimental data after a characterization of the material. The whole results show an excellent agreement between modeling and experiments. Thus, through a complete and consistent comparison both with molecular simulations and with experimental data, the NLDFT/SAFT-VR theory has been validated for the description of monomers.« less

Fall Detection System for the Elderly Based on the Classification of Shimmer Sensor Prototype Data

PubMed Central

Ahmed, Moiz; Mehmood, Nadeem; Mehmood, Amir; Rizwan, Kashif

2017-01-01

Objectives Falling in the elderly is considered a major cause of death. In recent years, ambient and wireless sensor platforms have been extensively used in developed countries for the detection of falls in the elderly. However, we believe extra efforts are required to address this issue in developing countries, such as Pakistan, where most deaths due to falls are not even reported. Considering this, in this paper, we propose a fall detection system prototype that s based on the classification on real time shimmer sensor data. Methods We first developed a data set, ‘SMotion’ of certain postures that could lead to falls in the elderly by using a body area network of Shimmer sensors and categorized the items in this data set into age and weight groups. We developed a feature selection and classification system using three classifiers, namely, support vector machine (SVM), K-nearest neighbor (KNN), and neural network (NN). Finally, a prototype was fabricated to generate alerts to caregivers, health experts, or emergency services in case of fall. Results To evaluate the proposed system, SVM, KNN, and NN were used. The results of this study identified KNN as the most accurate classifier with maximum accuracy of 96% for age groups and 93% for weight groups. Conclusions In this paper, a classification-based fall detection system is proposed. For this purpose, the SMotion data set was developed and categorized into two groups (age and weight groups). The proposed fall detection system for the elderly is implemented through a body area sensor network using third-generation sensors. The evaluation results demonstrate the reasonable performance of the proposed fall detection prototype system in the tested scenarios. PMID:28875049

Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER.

PubMed

Ferreira, Miguel; Roma, Nuno; Russo, Luis M S

2014-05-30

HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrar's striped processing pattern with Intel SSE2 instruction set extension. A new SIMD vectorization of the Viterbi decoding algorithm is proposed, based on an SSE2 inter-task parallelization approach similar to the DNA alignment algorithm proposed by Rognes. Besides this alternative vectorization scheme, the proposed implementation also introduces a new partitioning of the Markov model that allows a significantly more efficient exploitation of the cache locality. Such optimization, together with an improved loading of the emission scores, allows the achievement of a constant processing throughput, regardless of the innermost-cache size and of the dimension of the considered model. The proposed optimized vectorization of the Viterbi decoding algorithm was extensively evaluated and compared with the HMMER3 decoder to process DNA and protein datasets, proving to be a rather competitive alternative implementation. Being always faster than the already highly optimized ViterbiFilter implementation of HMMER3, the proposed Cache-Oblivious Parallel SIMD Viterbi (COPS) implementation provides a constant throughput and offers a processing speedup as high as two times faster, depending on the model's size.

On Kedlaya-type inequalities for weighted means.

PubMed

Páles, Zsolt; Pasteczka, Paweł

2018-01-01

In 2016 we proved that for every symmetric, repetition invariant and Jensen concave mean [Formula: see text] the Kedlaya-type inequality [Formula: see text] holds for an arbitrary [Formula: see text] ([Formula: see text] stands for the arithmetic mean). We are going to prove the weighted counterpart of this inequality. More precisely, if [Formula: see text] is a vector with corresponding (non-normalized) weights [Formula: see text] and [Formula: see text] denotes the weighted mean then, under analogous conditions on [Formula: see text], the inequality [Formula: see text] holds for every [Formula: see text] and [Formula: see text] such that the sequence [Formula: see text] is decreasing.

Investigating the Performance of Alternate Regression Weights by Studying All Possible Criteria in Regression Models with a Fixed Set of Predictors

ERIC Educational Resources Information Center

Waller, Niels; Jones, Jeff

2011-01-01

We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

Adaptive Neural Network-Based Event-Triggered Control of Single-Input Single-Output Nonlinear Discrete-Time Systems.

PubMed

Sahoo, Avimanyu; Xu, Hao; Jagannathan, Sarangapani

2016-01-01

This paper presents a novel adaptive neural network (NN) control of single-input and single-output uncertain nonlinear discrete-time systems under event sampled NN inputs. In this control scheme, the feedback signals are transmitted, and the NN weights are tuned in an aperiodic manner at the event sampled instants. After reviewing the NN approximation property with event sampled inputs, an adaptive state estimator (SE), consisting of linearly parameterized NNs, is utilized to approximate the unknown system dynamics in an event sampled context. The SE is viewed as a model and its approximated dynamics and the state vector, during any two events, are utilized for the event-triggered controller design. An adaptive event-trigger condition is derived by using both the estimated NN weights and a dead-zone operator to determine the event sampling instants. This condition both facilitates the NN approximation and reduces the transmission of feedback signals. The ultimate boundedness of both the NN weight estimation error and the system state vector is demonstrated through the Lyapunov approach. As expected, during an initial online learning phase, events are observed more frequently. Over time with the convergence of the NN weights, the inter-event times increase, thereby lowering the number of triggered events. These claims are illustrated through the simulation results.

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

PubMed

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

2016-09-01

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

Current status of non-viral gene therapy for CNS disorders

PubMed Central

Jayant, Rahul Dev; Sosa, Daniela; Kaushik, Ajeet; Atluri, Venkata; Vashist, Arti; Tomitaka, Asahi; Nair, Madhavan

2017-01-01

Introduction Viral and non-viral vectors have been used as methods of delivery in gene therapy for many CNS diseases. Currently, viral vectors such as adeno-associated viruses (AAV), retroviruses, lentiviruses, adenoviruses and herpes simplex viruses (HHV) are being used as successful vectors in gene therapy at clinical trial levels. However, many disadvantages have risen from their usage. Non-viral vectors like cationic polymers, cationic lipids, engineered polymers, nanoparticles, and naked DNA offer a much safer option and can therefore be explored for therapeutic purposes. Areas covered This review discusses different types of viral and non-viral vectors for gene therapy and explores clinical trials for CNS diseases that have used these types of vectors for gene delivery. Highlights include non-viral gene delivery and its challenges, possible strategies to improve transfection, regulatory issues concerning vector usage, and future prospects for clinical applications. Expert opinion Transfection efficiency of cationic lipids and polymers can be improved through manipulation of molecules used. Efficacy of cationic lipids is dependent on cationic charge, saturation levels, and stability of linkers. Factors determining efficacy of cationic polymers are total charge density, molecular weights, and complexity of molecule. All of the above mentioned parameters must be taken care for efficient gene delivery. PMID:27249310

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

Hand digit control in children: motor overflow in multi-finger pressing force vector space during maximum voluntary force production.

PubMed

Shim, Jae Kun; Karol, Sohit; Hsu, Jeffrey; de Oliveira, Marcio Alves

2008-04-01

The aim of this study was to investigate the contralateral motor overflow in children during single-finger and multi-finger maximum force production tasks. Forty-five right handed children, 5-11 years of age produced maximum isometric pressing force in flexion or extension with single fingers or all four fingers of their right hand. The forces produced by individual fingers of the right and left hands were recorded and analyzed in four-dimensional finger force vector space. The results showed that increases in task (right) hand finger forces were linearly associated with non-task (left) hand finger forces. The ratio of the non-task hand finger force magnitude to the corresponding task hand finger force magnitude, termed motor overflow magnitude (MOM), was greater in extension than flexion. The index finger flexion task showed the smallest MOM values. The similarity between the directions of task hand and non-task hand finger force vectors in four-dimensional finger force vector space, termed motor overflow direction (MOD), was the greatest for index and smallest for little finger tasks. MOM of a four-finger task was greater than the sum of MOMs of single-finger tasks, and this phenomenon was termed motor overflow surplus. Contrary to previous studies, no single-finger or four-finger tasks showed significant changes of MOM or MOD with the age of children. We conclude that the contralateral motor overflow in children during finger maximum force production tasks is dependent upon the task fingers and the magnitude and direction of task finger forces.

Safety mechanism assisted by the repressor of tetracycline (SMART) vaccinia virus vectors for vaccines and therapeutics.

PubMed

Grigg, Patricia; Titong, Allison; Jones, Leslie A; Yilma, Tilahun D; Verardi, Paulo H

2013-09-17

Replication-competent viruses, such as Vaccinia virus (VACV), are powerful tools for the development of oncolytic viral therapies and elicit superior immune responses when used as vaccine and immunotherapeutic vectors. However, severe complications from uncontrolled viral replication can occur, particularly in immunocompromised individuals or in those with other predisposing conditions. VACVs constitutively expressing interferon-γ (IFN-γ) replicate in cell culture indistinguishably from control viruses; however, they replicate in vivo to low or undetectable levels, and are rapidly cleared even in immunodeficient animals. In an effort to develop safe and highly effective replication-competent VACV vectors, we established a system to inducibly express IFN-γ. Our SMART (safety mechanism assisted by the repressor of tetracycline) vectors are designed to express the tetracycline repressor under a constitutive VACV promoter and IFN-γ under engineered tetracycline-inducible promoters. Immunodeficient SCID mice inoculated with VACVs not expressing IFN-γ demonstrated severe weight loss, whereas those given VACVs expressing IFN-γ under constitutive VACV promoters showed no signs of infection. Most importantly, mice inoculated with a VACV expressing the IFN-γ gene under an inducible promoter remained healthy in the presence of doxycycline, but exhibited severe weight loss in the absence of doxycycline. In this study, we developed a safety mechanism for VACV based on the conditional expression of IFN-γ under a tightly controlled tetracycline-inducible VACV promoter for use in vaccines and oncolytic cancer therapies.

Weighted Feature Gaussian Kernel SVM for Emotion Recognition

PubMed Central

Jia, Qingxuan

2016-01-01

Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods. PMID:27807443

An elementary proof of a criterion for linear disjointness

NASA Astrophysics Data System (ADS)

Dobbs, David E.

2013-06-01

An elementary proof using matrix theory is given for the following criterion: if F/K and L/K are field extensions, with F and L both contained in a common extension field, then F and L are linearly disjoint over K if (and only if) some K-vector space basis of F is linearly independent over L. The material in this note could serve as enrichment material for the unit on fields in a first course on abstract algebra.

Patch-based image reconstruction for PET using prior-image derived dictionaries

NASA Astrophysics Data System (ADS)

Tahaei, Marzieh S.; Reader, Andrew J.

2016-09-01

In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images. Patch-based image processing techniques have recently been successfully used for regularization in medical image reconstruction through a penalized likelihood framework. Re-parameterization within reconstruction is another powerful regularization technique in which the object in the scanner is re-parameterized using coefficients for spatially-extensive basis vectors. In this work, a method for extracting patch-based basis vectors from the subject’s MR image is proposed. The coefficients for these basis vectors are then estimated using the conventional MLEM algorithm. Furthermore, using the alternating direction method of multipliers, an algorithm for optimizing the Poisson log-likelihood while imposing sparsity on the parameters is also proposed. This novel method is then utilized to find sparse coefficients for the patch-based basis vectors extracted from the MR image. The results indicate the superiority of the proposed methods to patch-based regularization using the penalized likelihood framework.

Optimization of composite tiltrotor wings with extensions and winglets

NASA Astrophysics Data System (ADS)

Kambampati, Sandilya

Tiltrotors suffer from an aeroelastic instability during forward flight called whirl flutter. Whirl flutter is caused by the whirling motion of the rotor, characterized by highly coupled wing-rotor-pylon modes of vibration. Whirl flutter is a major obstacle for tiltrotors in achieving high-speed flight. The conventional approach to assure adequate whirl flutter stability margins for tiltrotors is to design the wings with high torsional stiffness, typically using 23% thickness-to-chord ratio wings. However, the large aerodynamic drag associated with these high thickness-to-chord ratio wings decreases aerodynamic efficiency and increases fuel consumption. Wingtip devices such as wing extensions and winglets have the potential to increase the whirl flutter characteristics and the aerodynamic efficiency of a tiltrotor. However, wing-tip devices can add more weight to the aircraft. In this study, multi-objective parametric and optimization methodologies for tiltrotor aircraft with wing extensions and winglets are investigated. The objectives are to maximize aircraft aerodynamic efficiency while minimizing weight penalty due to extensions and winglets, subject to whirl flutter constraints. An aeroelastic model that predicts the whirl flutter speed and a wing structural model that computes strength and weight of a composite wing are developed. An existing aerodynamic model (that predicts the aerodynamic efficiency) is merged with the developed structural and aeroelastic models for the purpose of conducting parametric and optimization studies. The variables of interest are the wing thickness and structural properties, and extension and winglet planform variables. The Bell XV-15 tiltrotor aircraft the chosen as the parent aircraft for this study. Parametric studies reveal that a wing extension of span 25% of the inboard wing increases the whirl flutter speed by 10% and also increases the aircraft aerodynamic efficiency by 8%. Structurally tapering the wing of a tiltrotor equipped with an extension and a winglet can increase the whirl flutter speed by 15% while reducing the wing weight by 7.5%. The baseline design for the optimization is the optimized wing with no extension or winglet. The optimization studies reveal that the optimum design for a cruise speed of 250 knots has an increased aerodynamic efficiency of 7% over the baseline design for only a weight penalty of 3% - thus a better transport range of 5.5% more than the baseline. The optimal design for a cruise speed of 300 knots has an increased aerodynamic efficiency of 5%, a weight penalty of 2.5%, and a better transport range of 3.5% more than the baseline.

How should spin-weighted spherical functions be defined?

NASA Astrophysics Data System (ADS)

Boyle, Michael

2016-09-01

Spin-weighted spherical functions provide a useful tool for analyzing tensor-valued functions on the sphere. A tensor field can be decomposed into complex-valued functions by taking contractions with tangent vectors on the sphere and the normal to the sphere. These component functions are usually presented as functions on the sphere itself, but this requires an implicit choice of distinguished tangent vectors with which to contract. Thus, we may more accurately say that spin-weighted spherical functions are functions of both a point on the sphere and a choice of frame in the tangent space at that point. The distinction becomes extremely important when transforming the coordinates in which these functions are expressed, because the implicit choice of frame will also transform. Here, it is proposed that spin-weighted spherical functions should be treated as functions on the spin or rotation groups, which simultaneously tracks the point on the sphere and the choice of tangent frame by rotating elements of an orthonormal basis. In practice, the functions simply take a quaternion argument and produce a complex value. This approach more cleanly reflects the geometry involved, and allows for a more elegant description of the behavior of spin-weighted functions. In this form, the spin-weighted spherical harmonics have simple expressions as elements of the Wigner 𝔇 representations, and transformations under rotation are simple. Two variants of the angular-momentum operator are defined directly in terms of the spin group; one is the standard angular-momentum operator L, while the other is shown to be related to the spin-raising operator ð.

Soft computing techniques toward modeling the water supplies of Cyprus.

PubMed

Iliadis, L; Maris, F; Tachos, S

2011-10-01

This research effort aims in the application of soft computing techniques toward water resources management. More specifically, the target is the development of reliable soft computing models capable of estimating the water supply for the case of "Germasogeia" mountainous watersheds in Cyprus. Initially, ε-Regression Support Vector Machines (ε-RSVM) and fuzzy weighted ε-RSVMR models have been developed that accept five input parameters. At the same time, reliable artificial neural networks have been developed to perform the same job. The 5-fold cross validation approach has been employed in order to eliminate bad local behaviors and to produce a more representative training data set. Thus, the fuzzy weighted Support Vector Regression (SVR) combined with the fuzzy partition has been employed in an effort to enhance the quality of the results. Several rational and reliable models have been produced that can enhance the efficiency of water policy designers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Design of magnetic polyplexes taken up efficiently by dendritic cell for enhanced DNA vaccine delivery.

PubMed

Nawwab Al-Deen, F M; Selomulya, C; Kong, Y Y; Xiang, S D; Ma, C; Coppel, R L; Plebanski, M

2014-02-01

Dendritic cells (DC) targeting vaccines require high efficiency for uptake, followed by DC activation and maturation. We used magnetic vectors comprising polyethylenimine (PEI)-coated superparamagnetic iron oxide nanoparticles, with hyaluronic acid (HA) of different molecular weights (<10 and 900 kDa) to reduce cytotoxicity and to facilitate endocytosis of particles into DCs via specific surface receptors. DNA encoding Plasmodium yoelii merozoite surface protein 1-19 and a plasmid encoding yellow fluorescent gene were added to the magnetic complexes with various % charge ratios of HA: PEI. The presence of magnetic fields significantly enhanced DC transfection and maturation. Vectors containing a high-molecular-weight HA with 100% charge ratio of HA: PEI yielded a better transfection efficiency than others. This phenomenon was attributed to their longer molecular chains and higher mucoadhesive properties aiding DNA condensation and stability. Insights gained should improve the design of more effective DNA vaccine delivery systems.

Feature weighting using particle swarm optimization for learning vector quantization classifier

NASA Astrophysics Data System (ADS)

Dongoran, A.; Rahmadani, S.; Zarlis, M.; Zakarias

2018-03-01

This paper discusses and proposes a method of feature weighting in classification assignments on competitive learning artificial neural network LVQ. The weighting feature method is the search for the weight of an attribute using the PSO so as to give effect to the resulting output. This method is then applied to the LVQ-Classifier and tested on the 3 datasets obtained from the UCI Machine Learning repository. Then an accuracy analysis will be generated by two approaches. The first approach using LVQ1, referred to as LVQ-Classifier and the second approach referred to as PSOFW-LVQ, is a proposed model. The result shows that the PSO algorithm is capable of finding attribute weights that increase LVQ-classifier accuracy.

Visualization of Morse connection graphs for topologically rich 2D vector fields.

PubMed

Szymczak, Andrzej; Sipeki, Levente

2013-12-01

Recent advances in vector field topologymake it possible to compute its multi-scale graph representations for autonomous 2D vector fields in a robust and efficient manner. One of these representations is a Morse Connection Graph (MCG), a directed graph whose nodes correspond to Morse sets, generalizing stationary points and periodic trajectories, and arcs - to trajectories connecting them. While being useful for simple vector fields, the MCG can be hard to comprehend for topologically rich vector fields, containing a large number of features. This paper describes a visual representation of the MCG, inspired by previous work on graph visualization. Our approach aims to preserve the spatial relationships between the MCG arcs and nodes and highlight the coherent behavior of connecting trajectories. Using simulations of ocean flow, we show that it can provide useful information on the flow structure. This paper focuses specifically on MCGs computed for piecewise constant (PC) vector fields. In particular, we describe extensions of the PC framework that make it more flexible and better suited for analysis of data on complex shaped domains with a boundary. We also describe a topology simplification scheme that makes our MCG visualizations less ambiguous. Despite the focus on the PC framework, our approach could also be applied to graph representations or topological skeletons computed using different methods.

"RCL-Pooling Assay": A Simplified Method for the Detection of Replication-Competent Lentiviruses in Vector Batches Using Sequential Pooling.

PubMed

Corre, Guillaume; Dessainte, Michel; Marteau, Jean-Brice; Dalle, Bruno; Fenard, David; Galy, Anne

2016-02-01

Nonreplicative recombinant HIV-1-derived lentiviral vectors (LV) are increasingly used in gene therapy of various genetic diseases, infectious diseases, and cancer. Before they are used in humans, preparations of LV must undergo extensive quality control testing. In particular, testing of LV must demonstrate the absence of replication-competent lentiviruses (RCL) with suitable methods, on representative fractions of vector batches. Current methods based on cell culture are challenging because high titers of vector batches translate into high volumes of cell culture to be tested in RCL assays. As vector batch size and titers are continuously increasing because of the improvement of production and purification methods, it became necessary for us to modify the current RCL assay based on the detection of p24 in cultures of indicator cells. Here, we propose a practical optimization of this method using a pairwise pooling strategy enabling easier testing of higher vector inoculum volumes. These modifications significantly decrease material handling and operator time, leading to a cost-effective method, while maintaining optimal sensibility of the RCL testing. This optimized "RCL-pooling assay" ameliorates the feasibility of the quality control of large-scale batches of clinical-grade LV while maintaining the same sensitivity.

A Fast Reduced Kernel Extreme Learning Machine.

PubMed

Deng, Wan-Yu; Ong, Yew-Soon; Zheng, Qing-Hua

2016-04-01

In this paper, we present a fast and accurate kernel-based supervised algorithm referred to as the Reduced Kernel Extreme Learning Machine (RKELM). In contrast to the work on Support Vector Machine (SVM) or Least Square SVM (LS-SVM), which identifies the support vectors or weight vectors iteratively, the proposed RKELM randomly selects a subset of the available data samples as support vectors (or mapping samples). By avoiding the iterative steps of SVM, significant cost savings in the training process can be readily attained, especially on Big datasets. RKELM is established based on the rigorous proof of universal learning involving reduced kernel-based SLFN. In particular, we prove that RKELM can approximate any nonlinear functions accurately under the condition of support vectors sufficiency. Experimental results on a wide variety of real world small instance size and large instance size applications in the context of binary classification, multi-class problem and regression are then reported to show that RKELM can perform at competitive level of generalized performance as the SVM/LS-SVM at only a fraction of the computational effort incurred. Copyright © 2015 Elsevier Ltd. All rights reserved.

Lefschetz thimbles in fermionic effective models with repulsive vector-field

NASA Astrophysics Data System (ADS)

Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira

2018-06-01

We discuss two problems in complexified auxiliary fields in fermionic effective models, the auxiliary sign problem associated with the repulsive vector-field and the choice of the cut for the scalar field appearing from the logarithmic function. In the fermionic effective models with attractive scalar and repulsive vector-type interaction, the auxiliary scalar and vector fields appear in the path integral after the bosonization of fermion bilinears. When we make the path integral well-defined by the Wick rotation of the vector field, the oscillating Boltzmann weight appears in the partition function. This "auxiliary" sign problem can be solved by using the Lefschetz-thimble path-integral method, where the integration path is constructed in the complex plane. Another serious obstacle in the numerical construction of Lefschetz thimbles is caused by singular points and cuts induced by multivalued functions of the complexified scalar field in the momentum integration. We propose a new prescription which fixes gradient flow trajectories on the same Riemann sheet in the flow evolution by performing the momentum integration in the complex domain.

Infinite flag varieties and conjugacy theorems

PubMed Central

Peterson, Dale H.; Kac, Victor G.

1983-01-01

We study the orbit of a highest-weight vector in an integrable highest-weight module of the group G associated to a Kac-Moody algebra [unk](A). We obtain applications to the geometric structure of the associated flag varieties and to the algebraic structure of [unk](A). In particular, we prove conjugacy theorems for Cartan and Borel subalgebras of [unk](A), so that the Cartan matrix A is an invariant of [unk](A). PMID:16593298

User's and test case manual for FEMATS

NASA Technical Reports Server (NTRS)

Chatterjee, Arindam; Volakis, John; Nurnberger, Mike; Natzke, John

1995-01-01

The FEMATS program incorporates first-order edge-based finite elements and vector absorbing boundary conditions into the scattered field formulation for computation of the scattering from three-dimensional geometries. The code has been validated extensively for a large class of geometries containing inhomogeneities and satisfying transition conditions. For geometries that are too large for the workstation environment, the FEMATS code has been optimized to run on various supercomputers. Currently, FEMATS has been configured to run on the HP 9000 workstation, vectorized for the Cray Y-MP, and parallelized to run on the Kendall Square Research (KSR) architecture and the Intel Paragon.

Short cavity DFB fiber laser based vector hydrophone for low frequency signal detection

NASA Astrophysics Data System (ADS)

Zhang, Xiaolei; Zhang, Faxiang; Jiang, Shaodong; Min, Li; Li, Ming; Peng, Gangding; Ni, Jiasheng; Wang, Chang

2017-12-01

A short cavity distributed feedback (DFB) fiber laser is used for low frequency acoustic signal detection. Three DFB fiber lasers with different central wavelengths are chained together to make three-element vector hydrophone with proper sensitivity enhancement design, which has extensive and significant applications to underwater acoustic monitoring for the national defense, oil, gas exploration, and so on. By wavelength-phase demodulation, the lasing wavelength changes under different frequency signals can be interpreted, and the sensitivity is tested about 33 dB re pm/g. The frequency response range is rather flat from 5 Hz to 300 Hz.

Characterization of the Asian citrus psyllid transcriptome

USDA-ARS?s Scientific Manuscript database

The Asian citrus psyllid (Diaphorina citri Kuwayama) and other psyllids are important agricultural pests that cause extensive economic damage by feeding and as vectors of plant pathogens. No psyllid genomes have been characterized, and little is known about the composition of psyllid genomes or the ...

CHANGING APPROACHES TO CONTROLLING PATHOGENS IN BIOSOLIDS AND THEIR VECTOR ATTRACTIVENESS

EPA Science Inventory

This paper reviews the commonly employed Class A and B processes for controlling pathogens; notes how extensively they are used; and discusses issues and concerns with some of them. Processes presently being researched are also noted together with EPA's methodology for determinin...

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

NASA Astrophysics Data System (ADS)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

Classification of small lesions on dynamic breast MRI: Integrating dimension reduction and out-of-sample extension into CADx methodology

PubMed Central

Nagarajan, Mahesh B.; Huber, Markus B.; Schlossbauer, Thomas; Leinsinger, Gerda; Krol, Andrzej; Wismüller, Axel

2014-01-01

Objective While dimension reduction has been previously explored in computer aided diagnosis (CADx) as an alternative to feature selection, previous implementations of its integration into CADx do not ensure strict separation between training and test data required for the machine learning task. This compromises the integrity of the independent test set, which serves as the basis for evaluating classifier performance. Methods and Materials We propose, implement and evaluate an improved CADx methodology where strict separation is maintained. This is achieved by subjecting the training data alone to dimension reduction; the test data is subsequently processed with out-of-sample extension methods. Our approach is demonstrated in the research context of classifying small diagnostically challenging lesions annotated on dynamic breast magnetic resonance imaging (MRI) studies. The lesions were dynamically characterized through topological feature vectors derived from Minkowski functionals. These feature vectors were then subject to dimension reduction with different linear and non-linear algorithms applied in conjunction with out-of-sample extension techniques. This was followed by classification through supervised learning with support vector regression. Area under the receiver-operating characteristic curve (AUC) was evaluated as the metric of classifier performance. Results Of the feature vectors investigated, the best performance was observed with Minkowski functional ’perimeter’ while comparable performance was observed with ’area’. Of the dimension reduction algorithms tested with ’perimeter’, the best performance was observed with Sammon’s mapping (0.84 ± 0.10) while comparable performance was achieved with exploratory observation machine (0.82 ± 0.09) and principal component analysis (0.80 ± 0.10). Conclusions The results reported in this study with the proposed CADx methodology present a significant improvement over previous results reported with such small lesions on dynamic breast MRI. In particular, non-linear algorithms for dimension reduction exhibited better classification performance than linear approaches, when integrated into our CADx methodology. We also note that while dimension reduction techniques may not necessarily provide an improvement in classification performance over feature selection, they do allow for a higher degree of feature compaction. PMID:24355697

A path model for Whittaker vectors

NASA Astrophysics Data System (ADS)

Di Francesco, Philippe; Kedem, Rinat; Turmunkh, Bolor

2017-06-01

In this paper we construct weighted path models to compute Whittaker vectors in the completion of Verma modules, as well as Whittaker functions of fundamental type, for all finite-dimensional simple Lie algebras, affine Lie algebras, and the quantum algebra U_q(slr+1) . This leads to series expressions for the Whittaker functions. We show how this construction leads directly to the quantum Toda equations satisfied by these functions, and to the q-difference equations in the quantum case. We investigate the critical limit of affine Whittaker functions computed in this way.

Highest-weight representations of Brocherd`s algebras

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

Slansky, R.

1997-01-01

General features of highest-weight representations of Borcherd`s algebras are described. to show their typical features, several representations of Borcherd`s extensions of finite-dimensional algebras are analyzed. Then the example of the extension of affine- su(2) to a Borcherd`s algebra is examined. These algebras provide a natural way to extend a Kac-Moody algebra to include the hamiltonian and number-changing operators in a generalized symmetry structure.

Neighboring block based disparity vector derivation for multiview compatible 3D-AVC

NASA Astrophysics Data System (ADS)

Kang, Jewon; Chen, Ying; Zhang, Li; Zhao, Xin; Karczewicz, Marta

2013-09-01

3D-AVC being developed under Joint Collaborative Team on 3D Video Coding (JCT-3V) significantly outperforms the Multiview Video Coding plus Depth (MVC+D) which simultaneously encodes texture views and depth views with the multiview extension of H.264/AVC (MVC). However, when the 3D-AVC is configured to support multiview compatibility in which texture views are decoded without depth information, the coding performance becomes significantly degraded. The reason is that advanced coding tools incorporated into the 3D-AVC do not perform well due to the lack of a disparity vector converted from the depth information. In this paper, we propose a disparity vector derivation method utilizing only the information of texture views. Motion information of neighboring blocks is used to determine a disparity vector for a macroblock, so that the derived disparity vector is efficiently used for the coding tools in 3D-AVC. The proposed method significantly improves a coding gain of the 3D-AVC in the multiview compatible mode about 20% BD-rate saving in the coded views and 26% BD-rate saving in the synthesized views on average.

750 GeV diphoton excess at CERN LHC from a dark sector assisted scalar decay

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

Bhattacharya, Subhaditya; Patra, Sudhanwa; Sahoo, Nirakar

2016-06-06

We present a simple extension of the Standard Model (SM) to explain the recent diphoton excess, reported by CMS and ATLAS at CERN LHC. The SM is extended by a dark sector including a vector-like lepton doublet and a singlet of zero electromagnetic charge, which are odd under a Z{sub 2} symmetry. The charged particle of the vector-like lepton doublet assist the additional scalar, different from SM Higgs, to decay to di-photons of invariant mass around 750 GeV and thus explaining the excess observed at LHC. The admixture of neutral component of the vector-like lepton doublet and singlet constitute themore » dark matter of the Universe. We show the relevant parameter space for correct relic density and direct detection of dark matter.« less

An analysis of random projection for changeable and privacy-preserving biometric verification.

PubMed

Wang, Yongjin; Plataniotis, Konstantinos N

2010-10-01

Changeability and privacy protection are important factors for widespread deployment of biometrics-based verification systems. This paper presents a systematic analysis of a random-projection (RP)-based method for addressing these problems. The employed method transforms biometric data using a random matrix with each entry an independent and identically distributed Gaussian random variable. The similarity- and privacy-preserving properties, as well as the changeability of the biometric information in the transformed domain, are analyzed in detail. Specifically, RP on both high-dimensional image vectors and dimensionality-reduced feature vectors is discussed and compared. A vector translation method is proposed to improve the changeability of the generated templates. The feasibility of the introduced solution is well supported by detailed theoretical analyses. Extensive experimentation on a face-based biometric verification problem shows the effectiveness of the proposed method.

Watson, Swellengrebel and species sanitation: environmental and ecological aspects.

PubMed

Bradley, D J

1994-08-01

Following the discovery of mosquito transmission of malaria, the theory and practice of malaria control by general and selective removal of specific vector populations resulted particularly from Malcolm Watson's empirical work in peninsular Malaysia, first in the urban and peri-urban areas of Klang and Port Swettenham and subsequently in the rural rubber plantations, and from the work of N.H. Swellengrebel in nearby Indonesia on the taxonomy, ecology and control of anophelines. They developed the concept of species sanitation: the selective modification of the environment to render a particular anopheline of no importance as a vector in a particular situation. The lack of progress along these lines in India at that time is contrasted with that in south-east Asia. The extension of species sanitation and related concepts to other geographical areas and to other vector-borne disease situations is outlined.

Weighted fusion of depth and inertial data to improve view invariance for real-time human action recognition

NASA Astrophysics Data System (ADS)

Chen, Chen; Hao, Huiyan; Jafari, Roozbeh; Kehtarnavaz, Nasser

2017-05-01

This paper presents an extension to our previously developed fusion framework [10] involving a depth camera and an inertial sensor in order to improve its view invariance aspect for real-time human action recognition applications. A computationally efficient view estimation based on skeleton joints is considered in order to select the most relevant depth training data when recognizing test samples. Two collaborative representation classifiers, one for depth features and one for inertial features, are appropriately weighted to generate a decision making probability. The experimental results applied to a multi-view human action dataset show that this weighted extension improves the recognition performance by about 5% over equally weighted fusion deployed in our previous fusion framework.

Generalized Analysis Tools for Multi-Spacecraft Missions

NASA Astrophysics Data System (ADS)

Chanteur, G. M.

2011-12-01

Analysis tools for multi-spacecraft missions like CLUSTER or MMS have been designed since the end of the 90's to estimate gradients of fields or to characterize discontinuities crossed by a cluster of spacecraft. Different approaches have been presented and discussed in the book "Analysis Methods for Multi-Spacecraft Data" published as Scientific Report 001 of the International Space Science Institute in Bern, Switzerland (G. Paschmann and P. Daly Eds., 1998). On one hand the approach using methods of least squares has the advantage to apply to any number of spacecraft [1] but is not convenient to perform analytical computation especially when considering the error analysis. On the other hand the barycentric approach is powerful as it provides simple analytical formulas involving the reciprocal vectors of the tetrahedron [2] but appears limited to clusters of four spacecraft. Moreover the barycentric approach allows to derive theoretical formulas for errors affecting the estimators built from the reciprocal vectors [2,3,4]. Following a first generalization of reciprocal vectors proposed by Vogt et al [4] and despite the present lack of projects with more than four spacecraft we present generalized reciprocal vectors for a cluster made of any number of spacecraft : each spacecraft is given a positive or nul weight. The non-coplanarity of at least four spacecraft with strictly positive weights is a necessary and sufficient condition for this analysis to be enabled. Weights given to spacecraft allow to minimize the influence of some spacecraft if its location or the quality of its data are not appropriate, or simply to extract subsets of spacecraft from the cluster. Estimators presented in [2] are generalized within this new frame except for the error analysis which is still under investigation. References [1] Harvey, C. C.: Spatial Gradients and the Volumetric Tensor, in: Analysis Methods for Multi-Spacecraft Data, G. Paschmann and P. Daly (eds.), pp. 307-322, ISSI SR-001, 1998. [2] Chanteur, G.: Spatial Interpolation for Four Spacecraft: Theory, in: Analysis Methods for Multi-Spacecraft Data, G. Paschmann and P. Daly (eds.), pp. 371-393, ISSI SR-001, 1998. [3] Chanteur, G.: Accuracy of field gradient estimations by Cluster: Explanation of its dependency upon elongation and planarity of the tetrahedron, pp. 265-268, ESA SP-449, 2000. [4] Vogt, J., Paschmann, G., and Chanteur, G.: Reciprocal Vectors, pp. 33-46, ISSI SR-008, 2008.

Evaluation of candidate geomagnetic field models for IGRF-11

NASA Astrophysics Data System (ADS)

Finlay, C. C.; Maus, S.; Beggan, C. D.; Hamoudi, M.; Lowes, F. J.; Olsen, N.; Thébault, E.

2010-10-01

The eleventh generation of the International Geomagnetic Reference Field (IGRF) was agreed in December 2009 by a task force appointed by the International Association of Geomagnetism and Aeronomy (IAGA) Division V Working Group V-MOD. New spherical harmonic main field models for epochs 2005.0 (DGRF-2005) and 2010.0 (IGRF-2010), and predictive linear secular variation for the interval 2010.0-2015.0 (SV-2010-2015) were derived from weighted averages of candidate models submitted by teams led by DTU Space, Denmark (team A); NOAA/NGDC, U.S.A. (team B); BGS, U.K. (team C); IZMIRAN, Russia (team D); EOST, France (team E); IPGP, France (team F); GFZ, Germany (team G) and NASA-GSFC, U.S.A. (team H). Here, we report the evaluations of candidate models carried out by the IGRF-11 task force during October/November 2009 and describe the weightings used to derive the new IGRF-11 model. The evaluations include calculations of root mean square vector field differences between the candidates, comparisons of the power spectra, and degree correlations between the candidates and a mean model. Coefficient by coefficient analysis including determination of weighting factors used in a robust estimation of mean coefficients is also reported. Maps of differences in the vertical field intensity at Earth's surface between the candidates and weighted mean models are presented. Candidates with anomalous aspects are identified and efforts made to pinpoint both troublesome coefficients and geographical regions where large variations between candidates originate. A retrospective analysis of IGRF-10 main field candidates for epoch 2005.0 and predictive secular variation candidates for 2005.0-2010.0 using the new IGRF-11 models as a reference is also reported. The high quality and consistency of main field models derived using vector satellite data is demonstrated; based on internal consistency DGRF-2005 has a formal root mean square vector field error over Earth's surface of 1.0 nT. Difficulties nevertheless remain in accurately forecasting field evolution only five years into the future.

Intersection of Three Planes Revisited--An Algebraic Approach

ERIC Educational Resources Information Center

Trenkler, Götz; Trenkler, Dietrich

2017-01-01

Given three planes in space, a complete characterization of their intersection is provided. Special attention is paid to the case when the intersection set does not exist of one point only. Besides the vector cross product, the tool of generalized inverse of a matrix is used extensively.

Target weight achievement and ultrafiltration rate thresholds: potential patient implications.

PubMed

Flythe, Jennifer E; Assimon, Magdalene M; Overman, Robert A

2017-06-02

Higher ultrafiltration (UF) rates and extracellular hypo- and hypervolemia are associated with adverse outcomes among maintenance hemodialysis patients. The Centers for Medicare and Medicaid Services recently considered UF rate and target weight achievement measures for ESRD Quality Incentive Program inclusion. The dual measures were intended to promote balance between too aggressive and too conservative fluid removal. The National Quality Forum endorsed the UF rate measure but not the target weight measure. We examined the proposed target weight measure and quantified weight gains if UF rate thresholds were applied without treatment time (TT) extension or interdialytic weight gain (IDWG) reduction. Data were taken from the 2012 database of a large dialysis organization. Analyses considered 152,196 United States hemodialysis patients. We described monthly patient and dialysis facility target weight achievement patterns and examined differences in patient characteristics across target weight achievement status and differences in facilities across target weight measure scores. We computed the cumulative, theoretical 1-month fluid-related weight gain that would occur if UF rates were capped at 13 mL/h/kg without concurrent TT extension or IDWG reduction. Target weight achievement patterns were stable over the year. Patients who did not achieve target weight (post-dialysis weight ≥ 1 kg above or below target weight) tended to be younger, black and dialyze via catheter, and had shorter dialysis vintage, greater body weight, higher UF rate and more missed treatments compared with patients who achieved target weight. Facilities had, on average, 27.1 ± 9.7% of patients with average post-dialysis weight ≥ 1 kg above or below the prescribed target weight. In adjusted analyses, facilities located in the midwest and south and facilities with higher proportions of black and Hispanic patients and higher proportions of patients with shorter TTs were more likely to have unfavorable facility target weight measure scores. Without TT extension or IDWG reduction, UF rate threshold (13 mL/h/kg) implementation led to an average theoretical 1-month, fluid-related weight gain of 1.4 ± 3.0 kg. Target weight achievement patterns vary across clinical subgroups. Implementation of a maximum UF rate threshold without adequate attention to extracellular volume status may lead to fluid-related weight gain.

Carcass and meat quality of Gokceada Goat kids reared under extensive and semi-intensive production systems.

PubMed

Ozcan, Mustafa; Yalcintan, Hulya; Tölü, Cemil; Ekiz, Bulent; Yilmaz, Alper; Savaş, Türker

2014-01-01

The aim was to compare the carcass and meat quality characteristics of male and female Gokceada Goat kids produced in extensive (n=20) and semi-intensive (n=20) systems. In extensive and semi-intensive produced kids pre-slaughter weights were 17.44 and 12.51 kg; cold carcass weights were 8.66 and 5.35 kg and cold dressing percentages were 54.9 and 49.28%, respectively. The effect of kid sex was not significant on hot and cold dressing percentages, back fat thickness, M. longissimus dorsi section area, carcass fatness and conformation scores, and carcass measurements, while female kids had higher omental and mesenteric fat and kidney knob and channel fat percentages than male kids. Extensive produced kids had lower meat lightness. Panellists evaluated extensive system kids with higher scores of kid odour intensity, flavour intensity and overall acceptability. It was concluded that it would be more appropriate to use an extensive system in Gokceada Goat breeding for kid meat production. © 2013.

Modification and identification of a vector for making a large phage antibody library.

PubMed

Zhang, Guo-min; Chen, Yü-ping; Guan, Yuan-zhi; Wang, Yan; An, Yun-qing

2007-11-20

The large phage antibody library is used to obtain high-affinity human antibody, and the Loxp/cre site-specific recombination system is a potential method for constructing a large phage antibody library. In the present study, a phage antibody library vector pDF was reconstructed to construct diabody more quickly and conveniently without injury to homologous recombination and the expression function of the vector and thus to integrate construction of the large phage antibody library with the preparation of diabodies. scFv was obtained by overlap polymerase chain reaction (PCR) amplification with the newly designed VL and VH extension primers. loxp511 was flanked by VL and VH and the endonuclease ACC III encoding sequences were introduced on both sides of loxp511. scFv was cloned into the vector pDF to obtain the vector pDscFv. The vector expression function was identified and the feasibility of diabody preparation was evaluated. A large phage antibody library was constructed in pDscFv. Several antigens were used to screen the antibody library and the quality of the antibody library was evaluated. The phage antibody library expression vector pDscFv was successfully constructed and confirmed to express functional scFv. The large phage antibody library constructed using this vector was of high diversity. Screening of the library on 6 antigens confirmed the generation of specific antibodies to these antigens. Two antibodies were subjected to enzymatic digestion and were prepared into diabody with functional expression. The reconstructed vector pDscFv retains its recombination capability and expression function and can be used to construct large phage antibody libraries. It can be used as a convenient and quick method for preparing diabodies after simple enzymatic digestion, which facilitates clinical trials and application of antibody therapy.

Clozapine-associated weight loss.

PubMed

Hanwella, R; de Silva, V; Wijeratne, C; Ketharanathan, T; de Silva, J

2010-07-01

Clozapine is associated with weight gain. We report three patients with substantial weight loss following treatment with clozapine. The weight loss observed in the three patients was 33, 18 and 14.4 kg with percentage loss of body weight of 49, 18 and 21 respectively. Two patients had diabetes mellitus. History, physical examination and extensive investigations in the three patients did not reveal any cause that could account for the weight loss.

[MicroRNA Target Prediction Based on Support Vector Machine Ensemble Classification Algorithm of Under-sampling Technique].

PubMed

Chen, Zhiru; Hong, Wenxue

2016-02-01

Considering the low accuracy of prediction in the positive samples and poor overall classification effects caused by unbalanced sample data of MicroRNA (miRNA) target, we proposes a support vector machine (SVM)-integration of under-sampling and weight (IUSM) algorithm in this paper, an under-sampling based on the ensemble learning algorithm. The algorithm adopts SVM as learning algorithm and AdaBoost as integration framework, and embeds clustering-based under-sampling into the iterative process, aiming at reducing the degree of unbalanced distribution of positive and negative samples. Meanwhile, in the process of adaptive weight adjustment of the samples, the SVM-IUSM algorithm eliminates the abnormal ones in negative samples with robust sample weights smoothing mechanism so as to avoid over-learning. Finally, the prediction of miRNA target integrated classifier is achieved with the combination of multiple weak classifiers through the voting mechanism. The experiment revealed that the SVM-IUSW, compared with other algorithms on unbalanced dataset collection, could not only improve the accuracy of positive targets and the overall effect of classification, but also enhance the generalization ability of miRNA target classifier.

An automatic iterative decision-making method for intuitionistic fuzzy linguistic preference relations

NASA Astrophysics Data System (ADS)

Pei, Lidan; Jin, Feifei; Ni, Zhiwei; Chen, Huayou; Tao, Zhifu

2017-10-01

As a new preference structure, the intuitionistic fuzzy linguistic preference relation (IFLPR) was recently introduced to efficiently deal with situations in which the membership and non-membership are represented as linguistic terms. In this paper, we study the issues of additive consistency and the derivation of the intuitionistic fuzzy weight vector of an IFLPR. First, the new concepts of order consistency, additive consistency and weak transitivity for IFLPRs are introduced, and followed by a discussion of the characterisation about additive consistent IFLPRs. Then, a parameterised transformation approach is investigated to convert the normalised intuitionistic fuzzy weight vector into additive consistent IFLPRs. After that, a linear optimisation model is established to derive the normalised intuitionistic fuzzy weights for IFLPRs, and a consistency index is defined to measure the deviation degree between an IFLPR and its additive consistent IFLPR. Furthermore, we develop an automatic iterative decision-making method to improve the IFLPRs with unacceptable additive consistency until the adjusted IFLPRs are acceptable additive consistent, and it helps the decision-maker to obtain the reasonable and reliable decision-making results. Finally, an illustrative example is provided to demonstrate the validity and applicability of the proposed method.

Robust Weighted Sum Harvested Energy Maximization for SWIPT Cognitive Radio Networks Based on Particle Swarm Optimization.

PubMed

Tuan, Pham Viet; Koo, Insoo

2017-10-06

In this paper, we consider multiuser simultaneous wireless information and power transfer (SWIPT) for cognitive radio systems where a secondary transmitter (ST) with an antenna array provides information and energy to multiple single-antenna secondary receivers (SRs) equipped with a power splitting (PS) receiving scheme when multiple primary users (PUs) exist. The main objective of the paper is to maximize weighted sum harvested energy for SRs while satisfying their minimum required signal-to-interference-plus-noise ratio (SINR), the limited transmission power at the ST, and the interference threshold of each PU. For the perfect channel state information (CSI), the optimal beamforming vectors and PS ratios are achieved by the proposed PSO-SDR in which semidefinite relaxation (SDR) and particle swarm optimization (PSO) methods are jointly combined. We prove that SDR always has a rank-1 solution, and is indeed tight. For the imperfect CSI with bounded channel vector errors, the upper bound of weighted sum harvested energy (WSHE) is also obtained through the S-Procedure. Finally, simulation results demonstrate that the proposed PSO-SDR has fast convergence and better performance as compared to the other baseline schemes.

Passive acoustic mapping of cavitation using eigenspace-based robust Capon beamformer in ultrasound therapy.

PubMed

Lu, Shukuan; Hu, Hong; Yu, Xianbo; Long, Jiangying; Jing, Bowen; Zong, Yujin; Wan, Mingxi

2018-03-01

Pulse-echo imaging technique can only play a role when high intensity focused ultrasound (HIFU) is turned off due to the interference between the primary HIFU signal and the transmission pulse. Passive acoustic mapping (PAM) has been proposed as a tool for true real-time monitoring of HIFU therapy. However, the most-used PAM algorithm based on time exposure acoustic (TEA) limits the quality of cavitation image. Recently, robust Capon beamformer (RCB) has been used in PAM to provide improved resolution and reduced artifacts over TEA-based PAM, but the presented results have not been satisfactory. In the present study, we applied an eigenspace-based RCB (EISRCB) method to further improve the PAM image quality. The optimal weighting vector of the proposed method was found by projecting the RCB weighting vector onto the desired vector subspace constructed from the eigenstructure of the covariance matrix. The performance of the proposed PAM was validated by both simulations and in vitro histotripsy experiments. The results suggested that the proposed PAM significantly outperformed the conventionally used TEA and RCB-based PAM. The comparison results between pulse-echo images of the residual bubbles and cavitation images showed the potential of our proposed PAM in accurate localization of cavitation activity during HIFU therapy. Copyright © 2017 Elsevier B.V. All rights reserved.

Immune clearance of highly pathogenic SIV infection

PubMed Central

Hansen, Scott G.; Piatak, Michael; Ventura, Abigail B.; Hughes, Colette M.; Gilbride, Roxanne M.; Ford, Julia C.; Oswald, Kelli; Shoemaker, Rebecca; Li, Yuan; Lewis, Matthew S.; Gilliam, Awbrey N.; Xu, Guangwu; Whizin, Nathan; Burwitz, Benjamin J.; Planer, Shannon L.; Turner, John M.; Legasse, Alfred W.; Axthelm, Michael K.; Nelson, Jay A.; Früh, Klaus; Sacha, Jonah B.; Estes, Jacob D.; Keele, Brandon F.; Edlefsen, Paul T.; Lifson, Jeffrey D.; Picker, Louis J.

2013-01-01

Established infections with the human and simian immunodeficiency viruses (HIV, SIV) are thought to be permanent with even the most effective immune responses and anti-retroviral therapies (ART) only able to control, but not clear, these infections1–4. Whether the residual virus that maintains these infections is vulnerable to clearance is a question of central importance to the future management of millions of HIV-infected individuals. We recently reported that ~50% of rhesus macaques (RM) vaccinated with SIV protein-expressing Rhesus Cytomegalovirus (RhCMV/SIV) vectors manifest durable, aviremic control of infection with highly pathogenic SIVmac2395. Here, we demonstrate that regardless of route of challenge, RhCMV/SIV vector-elicited immune responses control SIVmac239 after demonstrable lymphatic and hematogenous viral dissemination, and that replication-competent SIV persists in multiple sites for weeks to months. However, over time, protected RM lost signs of SIV infection, showing a consistent lack of measurable plasma or tissue-associated virus using ultrasensitive assays, and loss of T cell reactivity to SIV determinants not in the vaccine. Extensive ultrasensitive RT-PCR and PCR analysis of tissues from RhCMV/SIV vector-protected RM necropsied 69–172 weeks after challenge did not detect SIV RNA or DNA over background, and replication-competent SIV was not detected in these RM by extensive co-culture analysis of tissues or by adoptive transfer of 60 million hematolymphoid cells to naïve RM. These data provide compelling evidence for progressive clearance of a pathogenic lentiviral infection, and suggest that some lentiviral reservoirs may be susceptible to the continuous effector memory T cell-mediated immune surveillance elicited and maintained by CMV vectors. PMID:24025770

Immune clearance of highly pathogenic SIV infection.

PubMed

Hansen, Scott G; Piatak, Michael; Ventura, Abigail B; Hughes, Colette M; Gilbride, Roxanne M; Ford, Julia C; Oswald, Kelli; Shoemaker, Rebecca; Li, Yuan; Lewis, Matthew S; Gilliam, Awbrey N; Xu, Guangwu; Whizin, Nathan; Burwitz, Benjamin J; Planer, Shannon L; Turner, John M; Legasse, Alfred W; Axthelm, Michael K; Nelson, Jay A; Früh, Klaus; Sacha, Jonah B; Estes, Jacob D; Keele, Brandon F; Edlefsen, Paul T; Lifson, Jeffrey D; Picker, Louis J

2013-10-03

Established infections with the human and simian immunodeficiency viruses (HIV and SIV, respectively) are thought to be permanent with even the most effective immune responses and antiretroviral therapies only able to control, but not clear, these infections. Whether the residual virus that maintains these infections is vulnerable to clearance is a question of central importance to the future management of millions of HIV-infected individuals. We recently reported that approximately 50% of rhesus macaques (RM; Macaca mulatta) vaccinated with SIV protein-expressing rhesus cytomegalovirus (RhCMV/SIV) vectors manifest durable, aviraemic control of infection with the highly pathogenic strain SIVmac239 (ref. 5). Here we show that regardless of the route of challenge, RhCMV/SIV vector-elicited immune responses control SIVmac239 after demonstrable lymphatic and haematogenous viral dissemination, and that replication-competent SIV persists in several sites for weeks to months. Over time, however, protected RM lost signs of SIV infection, showing a consistent lack of measurable plasma- or tissue-associated virus using ultrasensitive assays, and a loss of T-cell reactivity to SIV determinants not in the vaccine. Extensive ultrasensitive quantitative PCR and quantitative PCR with reverse transcription analyses of tissues from RhCMV/SIV vector-protected RM necropsied 69-172 weeks after challenge did not detect SIV RNA or DNA sequences above background levels, and replication-competent SIV was not detected in these RM by extensive co-culture analysis of tissues or by adoptive transfer of 60 million haematolymphoid cells to naive RM. These data provide compelling evidence for progressive clearance of a pathogenic lentiviral infection, and suggest that some lentiviral reservoirs may be susceptible to the continuous effector memory T-cell-mediated immune surveillance elicited and maintained by cytomegalovirus vectors.

Simple Method for Markerless Gene Deletion in Multidrug-Resistant Acinetobacter baumannii

PubMed Central

Oh, Man Hwan; Lee, Je Chul; Kim, Jungmin

2015-01-01

The traditional markerless gene deletion technique based on overlap extension PCR has been used for generating gene deletions in multidrug-resistant Acinetobacter baumannii. However, the method is time-consuming because it requires restriction digestion of the PCR products in DNA cloning and the construction of new vectors containing a suitable antibiotic resistance cassette for the selection of A. baumannii merodiploids. Moreover, the availability of restriction sites and the selection of recombinant bacteria harboring the desired chimeric plasmid are limited, making the construction of a chimeric plasmid more difficult. We describe a rapid and easy cloning method for markerless gene deletion in A. baumannii, which has no limitation in the availability of restriction sites and allows for easy selection of the clones carrying the desired chimeric plasmid. Notably, it is not necessary to construct new vectors in our method. This method utilizes direct cloning of blunt-end DNA fragments, in which upstream and downstream regions of the target gene are fused with an antibiotic resistance cassette via overlap extension PCR and are inserted into a blunt-end suicide vector developed for blunt-end cloning. Importantly, the antibiotic resistance cassette is placed outside the downstream region in order to enable easy selection of the recombinants carrying the desired plasmid, to eliminate the antibiotic resistance cassette via homologous recombination, and to avoid the necessity of constructing new vectors. This strategy was successfully applied to functional analysis of the genes associated with iron acquisition by A. baumannii ATCC 19606 and to ompA gene deletion in other A. baumannii strains. Consequently, the proposed method is invaluable for markerless gene deletion in multidrug-resistant A. baumannii. PMID:25746991

Cosmology in beyond-generalized Proca theories

NASA Astrophysics Data System (ADS)

Nakamura, Shintaro; Kase, Ryotaro; Tsujikawa, Shinji

2017-05-01

The beyond-generalized Proca theories are the extension of second-order massive vector-tensor theories (dubbed generalized Proca theories) with two transverse vector modes and one longitudinal scalar besides two tensor polarizations. Even with this extension, the propagating degrees of freedom remain unchanged on the isotropic cosmological background without an Ostrogradski instability. We study the cosmology in beyond-generalized Proca theories by paying particular attention to the dynamics of late-time cosmic acceleration and resulting observational consequences. We derive conditions for avoiding ghosts and instabilities of tensor, vector, and scalar perturbations and discuss viable parameter spaces in concrete models allowing the dark energy equation of state smaller than -1 . The propagation speeds of those perturbations are subject to modifications beyond the domain of generalized Proca theories. There is a mixing between scalar and matter sound speeds, but such a mixing is suppressed during most of the cosmic expansion history without causing a new instability. On the other hand, we find that derivative interactions arising in beyond-generalized Proca theories give rise to important modifications to the cosmic growth history. The growth rate of matter perturbations can be compatible with the redshift-space distortion data due to the realization of gravitational interaction weaker than that in generalized Proca theories. Thus, it is possible to distinguish the dark energy model in beyond-generalized Proca theories from the counterpart in generalized Proca theories as well as from the Λ CDM model.

Factors That Influence the Transmission of West Nile Virus in Florida.

PubMed

Day, Jonathan F; Tabachnick, Walter J; Smartt, Chelsea T

2015-09-01

West Nile virus (WNV) was first detected in North America in New York City during the late summer of 1999 and was first detected in Florida in 2001. Although WNV has been responsible for widespread and extensive epidemics in human populations and epizootics in domestic animals and wildlife throughout North America, comparable epidemics have never materialized in Florida. Here, we review some of the reasons why WNV has yet to cause an extensive outbreak in Florida. The primary vector of mosquito-borne encephalitis virus in Florida is Culex nigripalpus Theobald. Rainfall, drought, and temperature are the primary factors that regulate annual populations of this species. Cx. nigripalpus is a competent vector of WNV, St. Louis encephalitis virus, and eastern equine encephalitis virus in Florida, and populations of this species can support focal amplification and transmission of these arboviruses. We propose that a combination of environmental factors influencing Cx. nigripalpus oviposition, blood-feeding behavior, and vector competence have limited WNV transmission in Florida to relatively small focal outbreaks and kept the state free of a major epidemic. Florida must remain vigilant to the danger from WNV, because a change in these environmental factors could easily result in a substantial WNV epidemic rivaling those seen elsewhere in the United States. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cache-Oblivious parallel SIMD Viterbi decoding for sequence search in HMMER

PubMed Central

2014-01-01

Background HMMER is a commonly used bioinformatics tool based on Hidden Markov Models (HMMs) to analyze and process biological sequences. One of its main homology engines is based on the Viterbi decoding algorithm, which was already highly parallelized and optimized using Farrar’s striped processing pattern with Intel SSE2 instruction set extension. Results A new SIMD vectorization of the Viterbi decoding algorithm is proposed, based on an SSE2 inter-task parallelization approach similar to the DNA alignment algorithm proposed by Rognes. Besides this alternative vectorization scheme, the proposed implementation also introduces a new partitioning of the Markov model that allows a significantly more efficient exploitation of the cache locality. Such optimization, together with an improved loading of the emission scores, allows the achievement of a constant processing throughput, regardless of the innermost-cache size and of the dimension of the considered model. Conclusions The proposed optimized vectorization of the Viterbi decoding algorithm was extensively evaluated and compared with the HMMER3 decoder to process DNA and protein datasets, proving to be a rather competitive alternative implementation. Being always faster than the already highly optimized ViterbiFilter implementation of HMMER3, the proposed Cache-Oblivious Parallel SIMD Viterbi (COPS) implementation provides a constant throughput and offers a processing speedup as high as two times faster, depending on the model’s size. PMID:24884826

N-body simulation for self-gravitating collisional systems with a new SIMD instruction set extension to the x86 architecture, Advanced Vector eXtensions

NASA Astrophysics Data System (ADS)

Tanikawa, Ataru; Yoshikawa, Kohji; Okamoto, Takashi; Nitadori, Keigo

2012-02-01

We present a high-performance N-body code for self-gravitating collisional systems accelerated with the aid of a new SIMD instruction set extension of the x86 architecture: Advanced Vector eXtensions (AVX), an enhanced version of the Streaming SIMD Extensions (SSE). With one processor core of Intel Core i7-2600 processor (8 MB cache and 3.40 GHz) based on Sandy Bridge micro-architecture, we implemented a fourth-order Hermite scheme with individual timestep scheme ( Makino and Aarseth, 1992), and achieved the performance of ˜20 giga floating point number operations per second (GFLOPS) for double-precision accuracy, which is two times and five times higher than that of the previously developed code implemented with the SSE instructions ( Nitadori et al., 2006b), and that of a code implemented without any explicit use of SIMD instructions with the same processor core, respectively. We have parallelized the code by using so-called NINJA scheme ( Nitadori et al., 2006a), and achieved ˜90 GFLOPS for a system containing more than N = 8192 particles with 8 MPI processes on four cores. We expect to achieve about 10 tera FLOPS (TFLOPS) for a self-gravitating collisional system with N ˜ 10 5 on massively parallel systems with at most 800 cores with Sandy Bridge micro-architecture. This performance will be comparable to that of Graphic Processing Unit (GPU) cluster systems, such as the one with about 200 Tesla C1070 GPUs ( Spurzem et al., 2010). This paper offers an alternative to collisional N-body simulations with GRAPEs and GPUs.

Ideas.

ERIC Educational Resources Information Center

Cook, Marcy

1989-01-01

Provided are four activities focusing on the application of mathematics to real-world situations: (1) Baby Weight; (2) High Temperature; (3) Skin Weight; and (4) Whale Weight. Each activity contains the objective, directions, extensions, and answers with worksheet. The activities required include the skills of making charts and graphs. (YP)

A Force-Velocity Relationship and Coordination Patterns in Overarm Throwing

PubMed Central

van den Tillaar, Roland; Ettema, Gertjan

2004-01-01

A force-velocity relationship in overarm throwing was determined using ball weights varying from 0.2 to 0.8 kg. Seven experienced handball players were filmed at 240 frames per second. Velocity of joints of the upper extremity and ball together with the force on the ball were derived from the data. A statistically significant negative relationship between force and maximal ball velocity, as well as between ball weight and maximal ball velocity was observed. Also, with increase of ball weight the total throwing movement time increased. No significant change in relative timing of the different joints was demonstrated, suggesting that the subjects did not change their “global ”coordination pattern (kinematics) within the tested range of ball weights. A simple model revealed that 67% of ball velocity at ball release was explained by the summation of effects from the velocity of elbow extension and internal rotation of the shoulder. With regard to the upper extremity the internal rotation of the shoulder and elbow extension are two important contributors to the total ball velocity at release. Key Points An inverse relationship between load and velocity and a linear force-velocity exists in overarm throwing with ball weights varying from 0.2 to 0.8 kg. Qualitatively, no changes in coordination pattern (relative timing) occur with increasing ball weight within the tested range of ball weights. The absolute throwing movement time increased with ball weight. Quantitatively, with regard to the upper extremity, the internal rotation of the shoulder and elbow extension are two important contributors to the total ball velocity at release. PMID:24624005

Extensions and improvements on XTRAN3S

NASA Technical Reports Server (NTRS)

Borland, C. J.

1989-01-01

Improvements to the XTRAN3S computer program are summarized. Work on this code, for steady and unsteady aerodynamic and aeroelastic analysis in the transonic flow regime has concentrated on the following areas: (1) Maintenance of the XTRAN3S code, including correction of errors, enhancement of operational capability, and installation on the Cray X-MP system; (2) Extension of the vectorization concepts in XTRAN3S to include additional areas of the code for improved execution speed; (3) Modification of the XTRAN3S algorithm for improved numerical stability for swept, tapered wing cases and improved computational efficiency; and (4) Extension of the wing-only version of XTRAN3S to include pylon and nacelle or external store capability.

Decoding the Ubiquitin-Mediated Pathway of Arthropod Disease Vectors

PubMed Central

Choy, Anthony; Severo, Maiara S.; Sun, Ruobai; Girke, Thomas; Gillespie, Joseph J.; Pedra, Joao H. F.

2013-01-01

Protein regulation by ubiquitin has been extensively described in model organisms. However, characterization of the ubiquitin machinery in disease vectors remains mostly unknown. This fundamental gap in knowledge presents a concern because new therapeutics are needed to control vector-borne diseases, and targeting the ubiquitin machinery as a means for disease intervention has been already adopted in the clinic. In this study, we employed a bioinformatics approach to uncover the ubiquitin-mediated pathway in the genomes of Anopheles gambiae, Aedes aegypti, Culex quinquefasciatus, Ixodes scapularis, Pediculus humanus and Rhodnius prolixus. We observed that (1) disease vectors encode a lower percentage of ubiquitin-related genes when compared to Drosophila melanogaster, Mus musculus and Homo sapiens but not Saccharomyces cerevisiae; (2) overall, there are more proteins categorized as E3 ubiquitin ligases when compared to E2-conjugating or E1-activating enzymes; (3) the ubiquitin machinery within the three mosquito genomes is highly similar; (4) ubiquitin genes are more than doubled in the Chagas disease vector (R. prolixus) when compared to other arthropod vectors; (5) the deer tick I. scapularis and the body louse (P. humanus) genomes carry low numbers of E1-activating enzymes and HECT-type E3 ubiquitin ligases; (6) R. prolixus have low numbers of RING-type E3 ubiquitin ligases; and (7) C. quinquefasciatus present elevated numbers of predicted F-box E3 ubiquitin ligases, JAB and UCH deubiquitinases. Taken together, these findings provide novel opportunities to study the interaction between a pathogen and an arthropod vector. PMID:24205097

Identification of Host Proteins Associated with Retroviral Vector Particles by Proteomic Analysis of Highly Purified Vector Preparations▿

PubMed Central

Segura, María Mercedes; Garnier, Alain; Di Falco, Marcos Rafael; Whissell, Gavin; Meneses-Acosta, Angélica; Arcand, Normand; Kamen, Amine

2008-01-01

The Moloney murine leukemia virus (MMLV) belongs to the Retroviridae family of enveloped viruses, which is known to acquire minute amounts of host cellular proteins both on the surface and inside the virion. Despite the extensive use of retroviral vectors in experimental and clinical applications, the repertoire of host proteins incorporated into MMLV vector particles remains unexplored. We report here the identification of host proteins from highly purified retroviral vector preparations obtained by rate-zonal ultracentrifugation. Viral proteins were fractionated by one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis, in-gel tryptic digested, and subjected to liquid chromatography/tandem mass spectrometry analysis. Immunogold electron microscopy studies confirmed the presence of several host membrane proteins exposed at the vector surface. These studies led to the identification of 27 host proteins on MMLV vector particles derived from 293 HEK cells, including 5 proteins previously described as part of wild-type MMLV. Nineteen host proteins identified corresponded to intracellular proteins. A total of eight host membrane proteins were identified, including cell adhesion proteins integrin β1 (fibronectin receptor subunit beta) and HMFG-E8, tetraspanins CD81 and CD9, and late endosomal markers CD63 and Lamp-2. Identification of membrane proteins on the retroviral surface is particularly attractive, since they can serve as anchoring sites for the insertion of tags for targeting or purification purposes. The implications of our findings for retrovirus-mediated gene therapy are discussed. PMID:18032515

A country bug in the city: urban infestation by the Chagas disease vector Triatoma infestans in Arequipa, Peru

PubMed Central

2013-01-01

Background Interruption of vector-borne transmission of Trypanosoma cruzi remains an unrealized objective in many Latin American countries. The task of vector control is complicated by the emergence of vector insects in urban areas. Methods Utilizing data from a large-scale vector control program in Arequipa, Peru, we explored the spatial patterns of infestation by Triatoma infestans in an urban and peri-urban landscape. Multilevel logistic regression was utilized to assess the associations between household infestation and household- and locality-level socio-environmental measures. Results Of 37,229 households inspected for infestation, 6,982 (18.8%; 95% CI: 18.4 – 19.2%) were infested by T. infestans. Eighty clusters of infestation were identified, ranging in area from 0.1 to 68.7 hectares and containing as few as one and as many as 1,139 infested households. Spatial dependence between infested households was significant at distances up to 2,000 meters. Household T. infestans infestation was associated with household- and locality-level factors, including housing density, elevation, land surface temperature, and locality type. Conclusions High levels of T. infestans infestation, characterized by spatial heterogeneity, were found across extensive urban and peri-urban areas prior to vector control. Several environmental and social factors, which may directly or indirectly influence the biology and behavior of T. infestans, were associated with infestation. Spatial clustering of infestation in the urban context may both challenge and inform surveillance and control of vector reemergence after insecticide intervention. PMID:24171704

Modeling Vehicle Collision Angle in Traffic Crashes Based on Three-Dimensional Laser Scanning Data

PubMed Central

Lyu, Nengchao; Huang, Gang; Wu, Chaozhong; Duan, Zhicheng; Li, Pingfan

2017-01-01

In road traffic accidents, the analysis of a vehicle’s collision angle plays a key role in identifying a traffic accident’s form and cause. However, because accurate estimation of vehicle collision angle involves many factors, it is difficult to accurately determine it in cases in which less physical evidence is available and there is a lack of monitoring. This paper establishes the mathematical relation model between collision angle, deformation, and normal vector in the collision region according to the equations of particle deformation and force in Hooke’s law of classical mechanics. At the same time, the surface reconstruction method suitable for a normal vector solution is studied. Finally, the estimation model of vehicle collision angle is presented. In order to verify the correctness of the model, verification of multi-angle collision experiments and sensitivity analysis of laser scanning precision for the angle have been carried out using three-dimensional (3D) data obtained by a 3D laser scanner in the collision deformation zone. Under the conditions with which the model has been defined, validation results show that the collision angle is a result of the weighted synthesis of the normal vector of the collision point and the weight value is the deformation of the collision point corresponding to normal vectors. These conclusions prove the applicability of the model. The collision angle model proposed in this paper can be used as the theoretical basis for traffic accident identification and cause analysis. It can also be used as a theoretical reference for the study of the impact deformation of elastic materials. PMID:28264517

Modeling Vehicle Collision Angle in Traffic Crashes Based on Three-Dimensional Laser Scanning Data.

PubMed

Lyu, Nengchao; Huang, Gang; Wu, Chaozhong; Duan, Zhicheng; Li, Pingfan

2017-02-28

In road traffic accidents, the analysis of a vehicle's collision angle plays a key role in identifying a traffic accident's form and cause. However, because accurate estimation of vehicle collision angle involves many factors, it is difficult to accurately determine it in cases in which less physical evidence is available and there is a lack of monitoring. This paper establishes the mathematical relation model between collision angle, deformation, and normal vector in the collision region according to the equations of particle deformation and force in Hooke's law of classical mechanics. At the same time, the surface reconstruction method suitable for a normal vector solution is studied. Finally, the estimation model of vehicle collision angle is presented. In order to verify the correctness of the model, verification of multi-angle collision experiments and sensitivity analysis of laser scanning precision for the angle have been carried out using three-dimensional (3D) data obtained by a 3D laser scanner in the collision deformation zone. Under the conditions with which the model has been defined, validation results show that the collision angle is a result of the weighted synthesis of the normal vector of the collision point and the weight value is the deformation of the collision point corresponding to normal vectors. These conclusions prove the applicability of the model. The collision angle model proposed in this paper can be used as the theoretical basis for traffic accident identification and cause analysis. It can also be used as a theoretical reference for the study of the impact deformation of elastic materials.

Chemical Modification with High Molecular Weight Polyethylene Glycol Reduces Transduction of Hepatocytes and Increases Efficacy of Intravenously Delivered Oncolytic Adenovirus

PubMed Central

Doronin, Konstantin; Shashkova, Elena V.; May, Shannon M.; Hofherr, Sean E.

2009-01-01

Abstract Oncolytic adenoviruses are anticancer agents that replicate within tumors and spread to uninfected tumor cells, amplifying the anticancer effect of initial transduction. We tested whether coating the viral particle with polyethylene glycol (PEG) could reduce transduction of hepatocytes and hepatotoxicity after systemic (intravenous) administration of oncolytic adenovirus serotype 5 (Ad5). Conjugating Ad5 with high molecular weight 20-kDa PEG but not with 5-kDa PEG reduced hepatocyte transduction and hepatotoxicity after intravenous injection. PEGylation with 20-kDa PEG was as efficient at detargeting adenovirus from Kupffer cells and hepatocytes as virus predosing and warfarin. Bioluminescence imaging of virus distribution in two xenograft tumor models in nude mice demonstrated that PEGylation with 20-kDa PEG reduced liver infection 19- to 90-fold. Tumor transduction levels were similar for vectors PEGylated with 20-kDa PEG and unPEGylated vectors. Anticancer efficacy after a single intravenous injection was retained at the level of unmodified vector in large established prostate carcinoma xenografts, resulting in complete elimination of tumors in all animals and long-term tumor-free survival. Anticancer efficacy after a single intravenous injection was increased in large established hepatocellular carcinoma xenografts, resulting in significant prolongation of survival as compared with unmodified vector. The increase in efficacy was comparable to that obtained with predosing and warfarin pretreatment, significantly extending the median of survival. Shielding adenovirus with 20-kDa PEG may be a useful approach to improve the therapeutic window of oncolytic adenovirus after systemic delivery to primary and metastatic tumor sites. PMID:19469693

Preterm Infant Weight Gain is Increased by Massage Therapy and Exercise Via Different Underlying Mechanisms

PubMed Central

Diego, Miguel A.; Field, Tiffany; Hernandez-Reif, Maria

2014-01-01

Objective To compare the effects of massage therapy (moderate pressure stroking) and exercise (flexion and extension of limbs) on preterm infants’ weight gain and to explore potential underlying mechanisms for those effects. Methods Weight gain and parasympathetic nervous system activity were assessed in 30 preterm infants randomly assigned to a massage therapy group or to an exercise group. Infants received 10 minutes of moderate pressure massage or passive flexion and extension of the limbs 3 times per day for 5 days, and EKGs were collected during the first session to assess vagal activity. Results Both massage and exercise led to increased weight gain. However, while exercise was associated with increased calorie consumption, massage was related to increased vagal activity. Conclusion Taken together, these findings suggest that massage and exercise lead to increased preterm infant weight gain via different underlying mechanisms. PMID:24480603

CONTRIBUTION TO THE THEORY OF MATRICES PARTITIONED INTO BLOCKS.

DTIC Science & Technology

results were obtained on cones of matrices and vectors, and an extension of the well-known Perron - Frobenius theorem was proved. Also a necessary and...sufficient condition was derived, in order that to a given matrix corresponds a cone on which it is a positive operator. Easily computed upper and

ARE THERE PATHOGENS IN YOUR SEWAGE SLUDGE? CHANGING APPROAHCES TO CONTROLLING PATHOGENS IN SEWAGE SLUDGE AND THEIR VECTOR ATTRACTIVENESS.

EPA Science Inventory

This presentation will review the commonly employed Class A & B processes for controlling pathogens; note how extensively they are used; and discuss issues and concerns. Processes presently being researched will also be noted together with EPA's methodology for determining equiva...

Secure Computer Systems: Extensions to the Bell-La Padula Model

DTIC Science & Technology

2009-01-01

countable and n CX ℜ∈ ; V is a finite collection of input variables. We assume ( )CD VVV ∪= with DV countable and nCV ℜ∈ ; XInit ⊆ is a set of...assume ( )CD VVV ∪= with DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states; CXVXf →×: is a vector field, assumed to be globally...built under the Eclipse Swordfish project. As indicated on the project web site,”The goal of the Swordfish project is to provide an extensible SOA

Relativistic extension of the Kay-Moses method for constructing transparent potentials in quantum mechanics

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

Toyama, F.M.; Nogami, Y.; Zhao, Z.

1993-02-01

For the Dirac equation in one space dimension with a potential of the Lorentz scalar type, we present a complete solution for the problem of constructing a transparent potential. This is a relativistic extension of the Kay-Moses method which was developed for the nonrelativistic Schroedinger equation. There is an infinite family of transparent potentials. The potentials are all related to solutions of a class of coupled, nonlinear Dirac equations. In addition, it is argued that an admixture of a Lorentz vector component in the potential impairs perfect transparency.

Cross index for improving cloning selectivity by partially filling in 5'-extensions of DNA produced by type II restriction endonucleases.

PubMed Central

Korch, C

1987-01-01

A cross index is presented for using the improved selectivity offered by the Hung and Wensink (Nucl. Acids Res. 12, 1863-1874, 1984) method of partially filling in 5'-extensions produced by type II restriction endonucleases. After this treatment, DNA fragments which normally cannot be ligated to one another, can be joined providing that complementary cohesive ends have been generated. The uses of this technique, which include the prevention of DNA fragments (both vector and insert) auto-annealing, are discussed. PMID:3033600

Determining areas that require indoor insecticide spraying using Multi Criteria Evaluation, a decision-support tool for malaria vector control programmes in the Central Highlands of Madagascar

PubMed Central

Rakotomanana, Fanjasoa; Randremanana, Rindra V; Rabarijaona, Léon P; Duchemin, Jean Bernard; Ratovonjato, Jocelyn; Ariey, Frédéric; Rudant, Jean Paul; Jeanne, Isabelle

2007-01-01

Background The highlands of Madagascar present an unstable transmission pattern of malaria. The population has no immunity, and the central highlands have been the sites of epidemics with particularly high fatality. The most recent epidemic occurred in the 1980s, and caused about 30,000 deaths. The fight against malaria epidemics in the highlands has been based on indoor insecticide spraying to control malaria vectors. Any preventive programme involving generalised cover in the highlands will require very substantial logistical support. We used multicriteria evaluation, by the method of weighted linear combination, as basis for improved targeting of actions by determining priority zones for intervention. Results Image analysis and field validation showed the accuracy of mapping rice fields to be between 82.3% and 100%, and the Kappa coefficient was 0.86 to 0.99. A significant positive correlation was observed between the abundance of the vector Anopheles funestus and temperature; the correlation coefficient was 0.599 (p < 0.001). A significant negative correlation was observed between vector abundance and human population density: the correlation coefficient was -0.551 (p < 0.003). Factor weights were determined by pair-wise comparison and the consistency ratio was 0.04. Risk maps of the six study zones were obtained according to a gradient of risk. Nine of thirteen results of alert confirmed by the Epidemiological Surveillance Post were in concordance with the risk map. Conclusion This study is particularly valuable for the management of vector control programmes, and particularly the reduction of the vector population with a view to preventing disease. The risk map obtained can be used to identify priority zones for the management of resources, and also help avoid systematic and generalised spraying throughout the highlands: such spraying is particularly difficult and expensive. The accuracy of the mapping, both as concerns time and space, is dependent on the availability of data. Continuous monitoring of malaria transmission factors must be undertaken to detect any changes. A regular case notification allows risk map to be verified. These actions should therefore be implemented so that risk maps can be satisfactorily assessed. PMID:17261177

Vector control in developed countries

PubMed Central

Peters, Richard F.

1963-01-01

The recent rapid growth of California's population, leading to competition for space between residential, industrial and agricultural interests, the development of its water resources and increasing water pollution provide the basic ingredients of its present vector problems. Within the past half-century, the original mosquito habitats provided by nature have gradually given place to even more numerous and productive habitats of man-made character. At the same time, emphasis in mosquito control has shifted from physical to chemical, with the more recent extension to biological approaches as well. The growing domestic fly problem, continuing despite the virtual disappearance of the horse, is attributable to an increasing amount of organic by-products, stemming from growing communities, expanding industries and changing agriculture. The programme for the control of disease vectors and pest insects and animals directs its major effort to the following broad areas: (1) water management (including land preparation), (2) solid organic wastes management (emphasizing utilization), (3) community management (including design, layout, and storage practices of buildings and grounds), and (4) recreational area management (related to wildlife management). It is apparent that vector control can often employ economics as an ally in securing its objectives. Effective organization of the environment to produce maximum economic benefits to industry, agriculture, and the community results generally in conditions unfavourable to the survival of vector and noxious animal species. Hence, vector prevention or suppression is preferable to control as a programme objective. PMID:20604166

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.

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.

PubMed

You, Zhu-Hong; Lei, Ying-Ke; Zhu, Lin; Xia, Junfeng; Wang, Bing

2013-01-01

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time.

Genomic Sequence and Virulence of Clonal Isolates of Vaccinia Virus Tiantan, the Chinese Smallpox Vaccine Strain

PubMed Central

Zhang, Qicheng; Tian, Meijuan; Feng, Yi; Zhao, Kai; Xu, Jing; Liu, Ying; Shao, Yiming

2013-01-01

Despite the worldwide eradication of smallpox in 1979, the potential bioterrorism threat from variola virus and the ongoing use of vaccinia virus (VACV) as a vector for vaccine development argue for continued research on VACV. In China, the VACV Tiantan strain (TT) was used in the smallpox eradication campaign. Its progeny strain is currently being used to develop a human immunodeficiency virus (HIV) vaccine. Here we sequenced the full genomes of five TT clones isolated by plaque purification from the TT (752-1) viral stock. Phylogenetic analysis with other commonly used VACV strains showed that TT (752-1) and its clones clustered and exhibited higher sequence diversity than that found in Dryvax clones. The ∼190 kbp genomes of TT appeared to encode 273 open reading frames (ORFs). ORFs located in the middle of the genome were more conserved than those located at the two termini, where many virulence and immunomodulation associated genes reside. Several patterns of nucleotide changes including point mutations, insertions and deletions were identified. The polymorphisms in seven virulence-associated proteins and six immunomodulation-related proteins were analyzed. We also investigated the neuro- and skin- virulence of TT clones in mice and rabbits, respectively. The TT clones exhibited significantly less virulence than the New York City Board of Health (NYCBH) strain, as evidenced by less extensive weight loss and morbidity in mice as well as produced smaller skin lesions and lower incidence of putrescence in rabbits. The complete genome sequences, ORF annotations, and phenotypic diversity yielded from this study aid our understanding of the Chinese historic TT strain and are useful for HIV vaccine projects employing TT as a vector. PMID:23593246

An efficient scheme for automatic web pages categorization using the support vector machine

NASA Astrophysics Data System (ADS)

Bhalla, Vinod Kumar; Kumar, Neeraj

2016-07-01

In the past few years, with an evolution of the Internet and related technologies, the number of the Internet users grows exponentially. These users demand access to relevant web pages from the Internet within fraction of seconds. To achieve this goal, there is a requirement of an efficient categorization of web page contents. Manual categorization of these billions of web pages to achieve high accuracy is a challenging task. Most of the existing techniques reported in the literature are semi-automatic. Using these techniques, higher level of accuracy cannot be achieved. To achieve these goals, this paper proposes an automatic web pages categorization into the domain category. The proposed scheme is based on the identification of specific and relevant features of the web pages. In the proposed scheme, first extraction and evaluation of features are done followed by filtering the feature set for categorization of domain web pages. A feature extraction tool based on the HTML document object model of the web page is developed in the proposed scheme. Feature extraction and weight assignment are based on the collection of domain-specific keyword list developed by considering various domain pages. Moreover, the keyword list is reduced on the basis of ids of keywords in keyword list. Also, stemming of keywords and tag text is done to achieve a higher accuracy. An extensive feature set is generated to develop a robust classification technique. The proposed scheme was evaluated using a machine learning method in combination with feature extraction and statistical analysis using support vector machine kernel as the classification tool. The results obtained confirm the effectiveness of the proposed scheme in terms of its accuracy in different categories of web pages.

Genomic sequence and virulence of clonal isolates of vaccinia virus Tiantan, the Chinese smallpox vaccine strain.

PubMed

Zhang, Qicheng; Tian, Meijuan; Feng, Yi; Zhao, Kai; Xu, Jing; Liu, Ying; Shao, Yiming

2013-01-01

Despite the worldwide eradication of smallpox in 1979, the potential bioterrorism threat from variola virus and the ongoing use of vaccinia virus (VACV) as a vector for vaccine development argue for continued research on VACV. In China, the VACV Tiantan strain (TT) was used in the smallpox eradication campaign. Its progeny strain is currently being used to develop a human immunodeficiency virus (HIV) vaccine. Here we sequenced the full genomes of five TT clones isolated by plaque purification from the TT (752-1) viral stock. Phylogenetic analysis with other commonly used VACV strains showed that TT (752-1) and its clones clustered and exhibited higher sequence diversity than that found in Dryvax clones. The ∼190 kbp genomes of TT appeared to encode 273 open reading frames (ORFs). ORFs located in the middle of the genome were more conserved than those located at the two termini, where many virulence and immunomodulation associated genes reside. Several patterns of nucleotide changes including point mutations, insertions and deletions were identified. The polymorphisms in seven virulence-associated proteins and six immunomodulation-related proteins were analyzed. We also investigated the neuro- and skin- virulence of TT clones in mice and rabbits, respectively. The TT clones exhibited significantly less virulence than the New York City Board of Health (NYCBH) strain, as evidenced by less extensive weight loss and morbidity in mice as well as produced smaller skin lesions and lower incidence of putrescence in rabbits. The complete genome sequences, ORF annotations, and phenotypic diversity yielded from this study aid our understanding of the Chinese historic TT strain and are useful for HIV vaccine projects employing TT as a vector.

A Fourier dimensionality reduction model for big data interferometric imaging

NASA Astrophysics Data System (ADS)

Vijay Kartik, S.; Carrillo, Rafael E.; Thiran, Jean-Philippe; Wiaux, Yves

2017-06-01

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging methods to the big data setting of the next-generation telescopes. This article sheds new light on dimensionality reduction from the perspective of the compressed sensing theory and studies its interplay with imaging algorithms designed in the context of convex optimization. We propose a post-gridding linear data embedding to the space spanned by the left singular vectors of the measurement operator, providing a dimensionality reduction below image size. This embedding preserves the null space of the measurement operator and hence its sampling properties are also preserved in light of the compressed sensing theory. We show that this can be approximated by first computing the dirty image and then applying a weighted subsampled discrete Fourier transform to obtain the final reduced data vector. This Fourier dimensionality reduction model ensures a fast implementation of the full measurement operator, essential for any iterative image reconstruction method. The proposed reduction also preserves the independent and identically distributed Gaussian properties of the original measurement noise. For convex optimization-based imaging algorithms, this is key to justify the use of the standard ℓ2-norm as the data fidelity term. Our simulations confirm that this dimensionality reduction approach can be leveraged by convex optimization algorithms with no loss in imaging quality relative to reconstructing the image from the complete visibility data set. Reconstruction results in simulation settings with no direction dependent effects or calibration errors show promising performance of the proposed dimensionality reduction. Further tests on real data are planned as an extension of the current work. matlab code implementing the proposed reduction method is available on GitHub.

Off disk-center potential field calculations using vector magnetograms

NASA Technical Reports Server (NTRS)

Venkatakrishnan, P.; Gary, G. Allen

1989-01-01

A potential field calculation for off disk-center vector magnetograms that uses all the three components of the measured field is investigated. There is neither any need for interpolation of grid points between the image plane and the heliographic plane nor for an extension or a truncation to a heliographic rectangle. Hence, the method provides the maximum information content from the photospheric field as well as the most consistent potential field independent of the viewing angle. The introduction of polarimetric noise produces a less tolerant extrapolation procedure than using the line-of-sight extrapolation, but the resultant standard deviation is still small enough for the practical utility of this method.

A modular toolset for recombination transgenesis and neurogenetic analysis of Drosophila.

PubMed

Wang, Ji-Wu; Beck, Erin S; McCabe, Brian D

2012-01-01

Transgenic Drosophila have contributed extensively to our understanding of nervous system development, physiology and behavior in addition to being valuable models of human neurological disease. Here, we have generated a novel series of modular transgenic vectors designed to optimize and accelerate the production and analysis of transgenes in Drosophila. We constructed a novel vector backbone, pBID, that allows both phiC31 targeted transgene integration and incorporates insulator sequences to ensure specific and uniform transgene expression. Upon this framework, we have built a series of constructs that are either backwards compatible with existing restriction enzyme based vectors or utilize Gateway recombination technology for high-throughput cloning. These vectors allow for endogenous promoter or Gal4 targeted expression of transgenic proteins with or without fluorescent protein or epitope tags. In addition, we have generated constructs that facilitate transgenic splice isoform specific RNA inhibition of gene expression. We demonstrate the utility of these constructs to analyze proteins involved in nervous system development, physiology and neurodegenerative disease. We expect that these reagents will facilitate the proficiency and sophistication of Drosophila genetic analysis in both the nervous system and other tissues.

Construction of two Lactococcus lactis expression vectors combining the Gateway and the NIsin Controlled Expression systems.

PubMed

Douillard, François P; Mahony, Jennifer; Campanacci, Valérie; Cambillau, Christian; van Sinderen, Douwe

2011-09-01

Over the last 10 years, the NIsin Controlled Expression (NICE) system has been extensively used in the food-grade bacterium Lactococcus lactis subsp. cremoris to produce homologous and heterologous proteins for academic and biotechnological purposes. Although various L. lactis molecular tools have been developed, no expression vectors harboring the popular Gateway recombination system are currently available for this widely used cloning host. In this study, we constructed two expression vectors that combine the NICE and the Gateway recombination systems and we tested their applicability by recombining and over-expressing genes encoding structural proteins of lactococcal phages Tuc2009 and TP901-1. Over-expressed phage proteins were analyzed by immunoblotting and purified by His-tag affinity chromatography with protein productions yielding 2.8-3.7 mg/l of culture. This therefore is the first description of L. lactis NICE expression vectors which integrate the Gateway cloning technology and which are suitable for the production of sufficient amounts of proteins to facilitate subsequent structural and functional analyses. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

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.

Sparse representation based SAR vehicle recognition along with aspect angle.

PubMed

Xing, Xiangwei; Ji, Kefeng; Zou, Huanxin; Sun, Jixiang

2014-01-01

As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC) has attracted much attention in synthetic aperture radar (SAR) automatic target recognition (ATR) recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA), in which the correlation between the vehicle's aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA) feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle's aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR) dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Precision vector control of a superconducting RF cavity driven by an injection locked magnetron

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

Chase, Brian; Pasquinelli, Ralph; Cullerton, Ed

The technique presented in this paper enables the regulation of both radio frequency amplitude and phase in narrow band devices such as a Superconducting RF (SRF) cavity driven by constant power output devices i.e. magnetrons [1]. The ability to use low cost high efficiency magnetrons for accelerator RF power systems, with tight vector regulation, presents a substantial cost savings in both construction and operating costs - compared to current RF power system technology. An operating CW system at 2.45 GHz has been experimentally developed. Vector control of an injection locked magnetron has been extensively tested and characterized with a SRFmore » cavity as the load. Amplitude dynamic range of 30 dB, amplitude stability of 0.3% r.m.s, and phase stability of 0.26 degrees r.m.s. has been demonstrated.« less

Exclusive diffractive production of real photons and vector mesons in a factorized Regge-pole model with nonlinear Pomeron trajectory

NASA Astrophysics Data System (ADS)

Fazio, S.; Fiore, R.; Jenkovszky, L.; Lavorini, A.

2012-03-01

Exclusive diffractive production of real photons and vector mesons in ep collisions has been studied at HERA in a wide kinematic range. Here we present and discuss a Regge-type model of real photon production (deeply virtual Compton scattering), as well as production of vector mesons treated on the same footing by using an extension of a factorized Regge-pole model proposed earlier. The model has been fitted to the HERA data. Despite the very small number of the free parameters, the model gives a satisfactory description of the experimental data, both for the total cross section as a function of the photon virtuality Q2 or the energy W in the center of mass of the γ*p system, and the differential cross sections as a function of the squared four-momentum transfer t with fixed Q2 and W.

Learning atoms for materials discovery.

PubMed

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

2018-06-26

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

Genetically engineering adenoviral vectors for gene therapy.

PubMed

Coughlan, Lynda

2014-01-01

Adenoviral (Ad) vectors are commonly used for various gene therapy applications. Significant advances in the genetic engineering of Ad vectors in recent years has highlighted their potential for the treatment of metastatic disease. There are several methods to genetically modify the Ad genome to incorporate retargeting peptides which will redirect the natural tropism of the viruses, including homologous recombination in bacteria or yeast. However, homologous recombination in yeast is highly efficient and can be achieved without the need for extensive cloning strategies. In addition, the method does not rely on the presence of unique restriction sites within the Ad genome and the reagents required for this method are widely available and inexpensive. Large plasmids containing the entire adenoviral genome (~36 kbp) can be modified within Saccharomyces cerevisiae yeast and genomes easily rescued in Escherichia coli hosts for analysis or amplification. A method for two-step homologous recombination in yeast is described in this chapter.

A quasi-current representation for information needs inspired by Two-State Vector Formalism

NASA Astrophysics Data System (ADS)

Wang, Panpan; Hou, Yuexian; Li, Jingfei; Zhang, Yazhou; Song, Dawei; Li, Wenjie

2017-09-01

Recently, a number of quantum theory (QT)-based information retrieval (IR) models have been proposed for modeling session search task that users issue queries continuously in order to describe their evolving information needs (IN). However, the standard formalism of QT cannot provide a complete description for users' current IN in a sense that it does not take the 'future' information into consideration. Therefore, to seek a more proper and complete representation for users' IN, we construct a representation of quasi-current IN inspired by an emerging Two-State Vector Formalism (TSVF). With the enlightenment of the completeness of TSVF, a "two-state vector" derived from the 'future' (the current query) and the 'history' (the previous query) is employed to describe users' quasi-current IN in a more complete way. Extensive experiments are conducted on the session tracks of TREC 2013 & 2014, and show that our model outperforms a series of compared IR models.

Molecular Ωc states generated from coupled meson-baryon channels

NASA Astrophysics Data System (ADS)

Debastiani, V. R.; Dias, J. M.; Liang, W. H.; Oset, E.

2018-05-01

We have investigated Ωc states that are dynamically generated from the meson-baryon interaction. We use an extension of the local hidden gauge to obtain the interaction from the exchange of vector mesons. We show that the dominant terms come from the exchange of light vectors, where the heavy quarks are spectators. This has as a consequence that heavy quark symmetry is preserved for the dominant terms in the (1 /mQ ) counting, and also that the interaction in this case can be obtained from the SU(3) chiral Lagrangians. We show that for a standard value for the cutoff regulating the loop, we obtain two states with JP=1/2 - and two more with JP=3/2 -, three of them in remarkable agreement with three experimental states in mass and width. We also make predictions at higher energies for states of vector-baryon nature.

Satellite Angular Rate Estimation From Vector Measurements

NASA Technical Reports Server (NTRS)

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

1996-01-01

This paper presents an algorithm for estimating the angular rate vector of a satellite which is based on the time derivatives of vector measurements expressed in a reference and body coordinate. The computed derivatives are fed into a spacial Kalman filter which yields an estimate of the spacecraft angular velocity. The filter, named Extended Interlaced Kalman Filter (EIKF), is an extension of the Kalman filter which, although being linear, estimates the state of a nonlinear dynamic system. It consists of two or three parallel Kalman filters whose individual estimates are fed to one another and are considered as known inputs by the other parallel filter(s). The nonlinear dynamics stem from the nonlinear differential equation that describes the rotation of a three dimensional body. Initial results, using simulated data, and real Rossi X ray Timing Explorer (RXTE) data indicate that the algorithm is efficient and robust.

Precision vector control of a superconducting RF cavity driven by an injection locked magnetron

DOE PAGES

Chase, Brian; Pasquinelli, Ralph; Cullerton, Ed; ...

2015-03-01

The technique presented in this paper enables the regulation of both radio frequency amplitude and phase in narrow band devices such as a Superconducting RF (SRF) cavity driven by constant power output devices i.e. magnetrons [1]. The ability to use low cost high efficiency magnetrons for accelerator RF power systems, with tight vector regulation, presents a substantial cost savings in both construction and operating costs - compared to current RF power system technology. An operating CW system at 2.45 GHz has been experimentally developed. Vector control of an injection locked magnetron has been extensively tested and characterized with a SRFmore » cavity as the load. Amplitude dynamic range of 30 dB, amplitude stability of 0.3% r.m.s, and phase stability of 0.26 degrees r.m.s. has been demonstrated.« less

MGRA: Motion Gesture Recognition via Accelerometer.

PubMed

Hong, Feng; You, Shujuan; Wei, Meiyu; Zhang, Yongtuo; Guo, Zhongwen

2016-04-13

Accelerometers have been widely embedded in most current mobile devices, enabling easy and intuitive operations. This paper proposes a Motion Gesture Recognition system (MGRA) based on accelerometer data only, which is entirely implemented on mobile devices and can provide users with real-time interactions. A robust and unique feature set is enumerated through the time domain, the frequency domain and singular value decomposition analysis using our motion gesture set containing 11,110 traces. The best feature vector for classification is selected, taking both static and mobile scenarios into consideration. MGRA exploits support vector machine as the classifier with the best feature vector. Evaluations confirm that MGRA can accommodate a broad set of gesture variations within each class, including execution time, amplitude and non-gestural movement. Extensive evaluations confirm that MGRA achieves higher accuracy under both static and mobile scenarios and costs less computation time and energy on an LG Nexus 5 than previous methods.

Quick and clean cloning.

PubMed

Thieme, Frank; Marillonnet, Sylvestre

2014-01-01

Identification of unknown sequences that flank known sequences of interest requires PCR amplification of DNA fragments that contain the junction between the known and unknown flanking sequences. Since amplified products often contain a mixture of specific and nonspecific products, the quick and clean (QC) cloning procedure was developed to clone specific products only. QC cloning is a ligation-independent cloning procedure that relies on the exonuclease activity of T4 DNA polymerase to generate single-stranded extensions at the ends of the vector and insert. A specific feature of QC cloning is the use of vectors that contain a sequence called catching sequence that allows cloning specific products only. QC cloning is performed by a one-pot incubation of insert and vector in the presence of T4 DNA polymerase at room temperature for 10 min followed by direct transformation of the incubation mix in chemo-competent Escherichia coli cells.

Systems and Methods for Derivative-Free Adaptive Control

NASA Technical Reports Server (NTRS)

Calise, Anthony J. (Inventor); Yucelen, Tansel (Inventor); Kim, Kilsoo (Inventor)

2015-01-01

An adaptive control system is disclosed. The control system can control uncertain dynamic systems. The control system can employ one or more derivative-free adaptive control architectures. The control system can further employ one or more derivative-free weight update laws. The derivative-free weight update laws can comprise a time-varying estimate of an ideal vector of weights. The control system of the present invention can therefore quickly stabilize systems that undergo sudden changes in dynamics, caused by, for example, sudden changes in weight. Embodiments of the present invention can also provide a less complex control system than existing adaptive control systems. The control system can control aircraft and other dynamic systems, such as, for example, those with non-minimum phase dynamics.

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

McGill algorithm for precipitation nowcasting by lagrangian extrapolation (MAPLE) applied to the South Korean radar network. Part I: Sensitivity studies of the Variational Echo Tracking (VET) technique

NASA Astrophysics Data System (ADS)

Bellon, Aldo; Zawadzki, Isztar; Kilambi, Alamelu; Lee, Hee Choon; Lee, Yong Hee; Lee, Gyuwon

2010-08-01

A Variational Echo Tracking (VET) technique has been applied to four months of archived data from the South Korean radar network in order to examine the influence of the various user-selectable parameters on the skill of the resulting 20-min to 4-h nowcasts. The latter are computed over a (512 × 512) array at 2-km resolution. After correcting the original algorithm to take into account the motion of precipitation across the boundaries of such a smaller radar network, we concluded that the set of default input parameters initially assumed is very close to the optimum combination. Decreasing to (5 sx 5) or increasing to (50 × 50) the default vector density of (25 × 25), using two or three maps for velocity determination, varying the relative weights for the constraints of conservation of reflectivity and of the smoothing of the velocity vectors, and finally the application of temporal smoothing all had only marginal effects on the skill of the forecasts. The relatively small sensitivity to significant variations of the VET default parameters is a direct consequence of the fact that the major source of the loss in forecast skill cannot be attributed to errors in the forecast motion, but to the unpredictable nature of the storm growth and decay. Changing the time interval between maps, from 20 to 10 minutes, and significantly increasing the reflectivity threshold from 15 to 30 dBZ had a more noticeable reduction on the forecast skill. Comparisons with the Eulerian "zero velocity" forecast and with a "single" vector forecast have also been performed in order to determine the accrued skill of the VET algorithm. Because of the extensive stratiform nature of the precipitation areas affecting the Korean peninsula, the increased skill is not as large as may have been anticipated. This can be explained by the greater extent of the precipitation systems relative to the size of the radar coverage domain.

New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

Simplified Syndrome Decoding of (n, 1) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

Tensorial Minkowski functionals of triply periodic minimal surfaces

PubMed Central

Mickel, Walter; Schröder-Turk, Gerd E.; Mecke, Klaus

2012-01-01

A fundamental understanding of the formation and properties of a complex spatial structure relies on robust quantitative tools to characterize morphology. A systematic approach to the characterization of average properties of anisotropic complex interfacial geometries is provided by integral geometry which furnishes a family of morphological descriptors known as tensorial Minkowski functionals. These functionals are curvature-weighted integrals of tensor products of position vectors and surface normal vectors over the interfacial surface. We here demonstrate their use by application to non-cubic triply periodic minimal surface model geometries, whose Weierstrass parametrizations allow for accurate numerical computation of the Minkowski tensors. PMID:24098847

On estimating gravity anomalies - A comparison of least squares collocation with conventional least squares techniques

NASA Technical Reports Server (NTRS)

Argentiero, P.; Lowrey, B.

1977-01-01

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described.

Evaluation and mechanism studies of PEGylated dendrigraft poly-L-lysines as novel gene delivery vectors.

PubMed

Huang, Rongqin; Liu, Shuhuan; Shao, Kun; Han, Liang; Ke, Weilun; Liu, Yang; Li, Jianfeng; Huang, Shixian; Jiang, Chen

2010-07-02

Dendrimers have attracted great interest in the field of gene delivery due to their synthetic controllability and excellent gene transfection efficiency. In this work, dendrigraft poly-L-lysines (DGLs) were evaluated as a novel gene vector for the first time. Derivatives of DGLs (generation 2 and 3) with different extents of PEGylation were successfully synthesized and used to compact pDNA as complexes. The result of gel retardation assay showed that pDNA could be effectively packed by all the vectors at a DGLs to pDNA weight ratio greater than 2. An increase in the PEGylation extent of vectors resulted in a decrease in the incorporation efficiency and cytotoxicity of complexes in 293 cells, which also decreased the zeta potential a little but did not affect the mean diameter of complexes. Higher generation of DGLs could mediate higher gene transfection in vitro. Confocal microscopy and cellular uptake inhibition studies demonstrated that caveolae-mediated process and macropinocytosis were involved in the cellular uptake of DGLs-based complexes. Also the results indicate that proper PEGylated DGLs could mediate efficient gene transfection, showing their potential as an alternate biodegradable vector in the field of nonviral gene delivery.

Human pose tracking from monocular video by traversing an image motion mapped body pose manifold

NASA Astrophysics Data System (ADS)

Basu, Saurav; Poulin, Joshua; Acton, Scott T.

2010-01-01

Tracking human pose from monocular video sequences is a challenging problem due to the large number of independent parameters affecting image appearance and nonlinear relationships between generating parameters and the resultant images. Unlike the current practice of fitting interpolation functions to point correspondences between underlying pose parameters and image appearance, we exploit the relationship between pose parameters and image motion flow vectors in a physically meaningful way. Change in image appearance due to pose change is realized as navigating a low dimensional submanifold of the infinite dimensional Lie group of diffeomorphisms of the two dimensional sphere S2. For small changes in pose, image motion flow vectors lie on the tangent space of the submanifold. Any observed image motion flow vector field is decomposed into the basis motion vector flow fields on the tangent space and combination weights are used to update corresponding pose changes in the different dimensions of the pose parameter space. Image motion flow vectors are largely invariant to style changes in experiments with synthetic and real data where the subjects exhibit variation in appearance and clothing. The experiments demonstrate the robustness of our method (within +/-4° of ground truth) to style variance.

Application of wavelet-based multi-model Kalman filters to real-time flood forecasting

NASA Astrophysics Data System (ADS)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

This paper presents the application of a multimodel method using a wavelet-based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real-time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet-based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state-estimates, each of which is weighted by its possibility that is also determined on-line, are combined to form an optimal estimate. Validations conducted for the Wu-Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time-varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall-runoff process in the Wu-Tu watershed.

Do vegetated rooftops attract more mosquitoes? Monitoring disease vector abundance on urban green roofs.

PubMed

Wong, Gwendolyn K L; Jim, C Y

2016-12-15

Green roof, an increasingly common constituent of urban green infrastructure, can provide multiple ecosystem services and mitigate climate-change and urban-heat-island challenges. Its adoption has been beset by a longstanding preconception of attracting urban pests like mosquitoes. As more cities may become vulnerable to emerging and re-emerging mosquito-borne infectious diseases, the knowledge gap needs to be filled. This study gauges the habitat preference of vector mosquitoes for extensive green roofs vis-à-vis positive and negative control sites in an urban setting. Seven sites in a university campus were selected to represent three experimental treatments: green roofs (GR), ground-level blue-green spaces as positive controls (PC), and bare roofs as negative controls (NC). Mosquito-trapping devices were deployed for a year from March 2015 to 2016. Human-biting mosquito species known to transmit infectious diseases in the region were identified and recorded as target species. Generalized linear models evaluated the effects of site type, season, and weather on vector-mosquito abundance. Our model revealed site type as a significant predictor of vector mosquito abundance, with considerably more vector mosquitoes captured in PC than in GR and NC. Vector abundance was higher in NC than in GR, attributed to the occasional presence of water pools in depressions of roofing membrane after rainfall. Our data also demonstrated seasonal differences in abundance. Weather variables were evaluated to assess human-vector contact risks under different weather conditions. Culex quinquefasciatus, a competent vector of diseases including lymphatic filariasis and West Nile fever, could be the most adaptable species. Our analysis demonstrates that green roofs are not particularly preferred by local vector mosquitoes compared to bare roofs and other urban spaces in a humid subtropical setting. The findings call for a better understanding of vector ecology in diverse urban landscapes to improve disease control efficacy amidst surging urbanization and changing climate. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Comparison of cervical spine kinematics using a fluoroscopic model for adjacent segment degeneration. Invited submission from the Joint Section on Disorders of the Spine and Peripheral Nerves, March 2007.

PubMed

Cheng, Joseph S; Liu, Fei; Komistek, Richard D; Mahfouz, Mohamed R; Sharma, Adrija; Glaser, Diana

2007-11-01

In this cervical spine kinematics study the authors evaluate the motions and forces in the normal, degenerative, and fused states to assess how alteration in the cervical motion segment affects adjacent segment degeneration and spondylosis. Fluoroscopic images obtained in 30 individuals (10 in each group with disease at C5-6) undergoing flexion/extension motions were collected. Kinematic data were obtained from the fluoroscopic images and analyzed with an inverse dynamic mathematical model of the cervical spine that was developed for this analysis. During 20 degrees flexion to 15 degrees extension, average relative angles at the adjacent levels of C6-7 and C4-5 in the fused patients were 13.4 degrees and 8.8 degrees versus 3.7 degrees and 4.8 degrees in the healthy individuals. Differences at C3-4 averaged only about 1 degrees. Maximum transverse forces in the fused spines were two times the skull weight at C6-7 and one times the skull weight at C4-5, compared with 0.2 times the skull weight and 0.3 times the skull weight in the healthy individuals. Vertical forces ranged from 1.6 to 2.6 times the skull weight at C6-7 and from 1.2 to 2.5 times the skull weight at C4-5 in the patients who had undergone fusion, and from 1.4 to 3.1 times the skull weight and from 0.9 to 3.3 times the skull weight, respectively, in the volunteers. Adjacent-segment degeneration may occur in patients with fusion due to increased motions and forces at both adjacent levels when compared with healthy individuals in a comparable flexion and extension range.

Essential and Dispensable Virus-Encoded Replication Elements Revealed by Efforts To Develop Hypoviruses as Gene Expression Vectors

PubMed Central

Suzuki, Nobuhiro; Geletka, Lynn M.; Nuss, Donald L.

2000-01-01

We have investigated whether hypoviruses, viral agents responsible for virulence attenuation (hypovirulence) of the chestnut blight fungus Cryphonectria parasitica, could serve as gene expression vectors. The infectious cDNA clone of the prototypic hypovirus CHV1-EP713 was modified to generate 20 different vector candidates. Although transient expression was achieved for a subset of vectors that contained the green fluorescent protein gene from Aequorea victoria, long-term expression (past day 8) was not observed for any vector construct. Analysis of viral RNAs recovered from transfected fungal colonies revealed that the foreign genes were readily deleted from the replicating virus, although small portions of foreign sequences were retained by some vectors after months of replication. However, the results of vector viability and progeny characterization provided unexpected new insights into essential and dispensable elements of hypovirus replication. The N-terminal portion (codons 1 to 24) of the 5′-proximal open reading frame (ORF), ORF A, was found to be required for virus replication, while the remaining 598 codons of this ORF were completely dispensable. Substantial alterations were tolerated in the pentanucleotide UAAUG that contains the ORF A termination codon and the overlapping putative initiation codon of the second of the two hypovirus ORFs, ORF B. Replication competence was maintained following either a frameshift mutation that caused a two-codon extension of ORF A or a modification that produced a single-ORF genomic organization. These results are discussed in terms of determinants of hypovirus replication, the potential utility of hypoviruses as gene expression vectors, and possible mechanisms by which hypoviruses recognize and delete foreign sequences. PMID:10906211

Methods of Constructing a Blended Performance Function Suitable for Formation Flight

NASA Technical Reports Server (NTRS)

Ryan, John J.

2017-01-01

This paper presents two methods for constructing an approximate performance function of a desired parameter using correlated parameters. The methods are useful when real-time measurements of a desired performance function are not available to applications such as extremum-seeking control systems. The first method approximates an a priori measured or estimated desired performance function by combining real-time measurements of readily available correlated parameters. The parameters are combined using a weighting vector determined from a minimum-squares optimization to form a blended performance function. The blended performance function better matches the desired performance function mini- mum than single-measurement performance functions. The second method expands upon the first by replacing the a priori data with near-real-time measurements of the desired performance function. The resulting blended performance function weighting vector is up- dated when measurements of the desired performance function are available. Both methods are applied to data collected during formation- flight-for-drag-reduction flight experiments.

Intraventricular Flow Velocity Vector Visualization Based on the Continuity Equation and Measurements of Vorticity and Wall Shear Stress

NASA Astrophysics Data System (ADS)

Itatani, Keiichi; Okada, Takashi; Uejima, Tokuhisa; Tanaka, Tomohiko; Ono, Minoru; Miyaji, Kagami; Takenaka, Katsu

2013-07-01

We have developed a system to estimate velocity vector fields inside the cardiac ventricle by echocardiography and to evaluate several flow dynamical parameters to assess the pathophysiology of cardiovascular diseases. A two-dimensional continuity equation was applied to color Doppler data using speckle tracking data as boundary conditions, and the velocity component perpendicular to the echo beam line was obtained. We determined the optimal smoothing method of the color Doppler data, and the 8-pixel standard deviation of the Gaussian filter provided vorticity without nonphysiological stripe shape noise. We also determined the weight function at the bilateral boundaries given by the speckle tracking data of the ventricle or vascular wall motion, and the weight function linear to the distance from the boundary provided accurate flow velocities not only inside the vortex flow but also around near-wall regions on the basis of the results of the validation of a digital phantom of a pipe flow model.

Matching algorithm of missile tail flame based on back-propagation neural network

NASA Astrophysics Data System (ADS)

Huang, Da; Huang, Shucai; Tang, Yidong; Zhao, Wei; Cao, Wenhuan

2018-02-01

This work presents a spectral matching algorithm of missile plume detection that based on neural network. The radiation value of the characteristic spectrum of the missile tail flame is taken as the input of the network. The network's structure including the number of nodes and layers is determined according to the number of characteristic spectral bands and missile types. We can get the network weight matrixes and threshold vectors through training the network using training samples, and we can determine the performance of the network through testing the network using the test samples. A small amount of data cause the network has the advantages of simple structure and practicality. Network structure composed of weight matrix and threshold vector can complete task of spectrum matching without large database support. Network can achieve real-time requirements with a small quantity of data. Experiment results show that the algorithm has the ability to match the precise spectrum and strong robustness.

Control method and system for hydraulic machines employing a dynamic joint motion model

DOEpatents

Danko, George [Reno, NV

2011-11-22

A control method and system for controlling a hydraulically actuated mechanical arm to perform a task, the mechanical arm optionally being a hydraulically actuated excavator arm. The method can include determining a dynamic model of the motion of the hydraulic arm for each hydraulic arm link by relating the input signal vector for each respective link to the output signal vector for the same link. Also the method can include determining an error signal for each link as the weighted sum of the differences between a measured position and a reference position and between the time derivatives of the measured position and the time derivatives of the reference position for each respective link. The weights used in the determination of the error signal can be determined from the constant coefficients of the dynamic model. The error signal can be applied in a closed negative feedback control loop to diminish or eliminate the error signal for each respective link.

An IPSO-SVM algorithm for security state prediction of mine production logistics system

NASA Astrophysics Data System (ADS)

Zhang, Yanliang; Lei, Junhui; Ma, Qiuli; Chen, Xin; Bi, Runfang

2017-06-01

A theoretical basis for the regulation of corporate security warning and resources was provided in order to reveal the laws behind the security state in mine production logistics. Considering complex mine production logistics system and the variable is difficult to acquire, a superior security status predicting model of mine production logistics system based on the improved particle swarm optimization and support vector machine (IPSO-SVM) is proposed in this paper. Firstly, through the linear adjustments of inertia weight and learning weights, the convergence speed and search accuracy are enhanced with the aim to deal with situations associated with the changeable complexity and the data acquisition difficulty. The improved particle swarm optimization (IPSO) is then introduced to resolve the problem of parameter settings in traditional support vector machines (SVM). At the same time, security status index system is built to determine the classification standards of safety status. The feasibility and effectiveness of this method is finally verified using the experimental results.

Ranking support vector machine for multiple kernels output combination in protein-protein interaction extraction from biomedical literature.

PubMed

Yang, Zhihao; Lin, Yuan; Wu, Jiajin; Tang, Nan; Lin, Hongfei; Li, Yanpeng

2011-10-01

Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. However, the volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database curators to detect and curate protein interaction information manually. We present a multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, and graph and combines their output with Ranking support vector machine (SVM). Experimental evaluations show that the features in individual kernels are complementary and the kernel combined with Ranking SVM achieves better performance than those of the individual kernels, equal weight combination and optimal weight combination. Our approach can achieve state-of-the-art performance with respect to the comparable evaluations, with 64.88% F-score and 88.02% AUC on the AImed corpus. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Unsupervised learning of discriminative edge measures for vehicle matching between nonoverlapping cameras.

PubMed

Shan, Ying; Sawhney, Harpreet S; Kumar, Rakesh

2008-04-01

This paper proposes a novel unsupervised algorithm learning discriminative features in the context of matching road vehicles between two non-overlapping cameras. The matching problem is formulated as a same-different classification problem, which aims to compute the probability of vehicle images from two distinct cameras being from the same vehicle or different vehicle(s). We employ a novel measurement vector that consists of three independent edge-based measures and their associated robust measures computed from a pair of aligned vehicle edge maps. The weight of each measure is determined by an unsupervised learning algorithm that optimally separates the same-different classes in the combined measurement space. This is achieved with a weak classification algorithm that automatically collects representative samples from same-different classes, followed by a more discriminative classifier based on Fisher' s Linear Discriminants and Gibbs Sampling. The robustness of the match measures and the use of unsupervised discriminant analysis in the classification ensures that the proposed method performs consistently in the presence of missing/false features, temporally and spatially changing illumination conditions, and systematic misalignment caused by different camera configurations. Extensive experiments based on real data of over 200 vehicles at different times of day demonstrate promising results.

A flight investigation of the stability, control, and handling qualities of an augmented jet flap STOL airplane

NASA Technical Reports Server (NTRS)

Vomaske, R. F.; Innis, R. C.; Swan, B. E.; Grossmith, S. W.

1978-01-01

The stability, control, and handling qualities of an augmented jet flap STOL airplane are presented. The airplane is an extensively modified de Havilland Buffalo military transport. The modified airplane has two fan-jet engines which provide vectorable thrust and compressed air for the augmentor jet flap and Boundary-Layer Control (BLC). The augmentor and BLC air is cross ducted to minimize asymmetric moments produced when one engine is inoperative. The modifications incorporated in the airplane include a Stability Augmentation System (SAS), a powered elevator, and a powered lateral control system. The test gross weight of the airplane was between 165,000 and 209,000 N (37,000 and 47,000 lb). Stability, control, and handling qualities are presented for the airspeed range of 40 to 180 knots. The lateral-directional handling qualities are considered satisfactory for the normal operating range of 65 to 160 knots airspeed when the SAS is functioning. With the SAS inoperative, poor turn coordination and spiral instability are primary deficiencies contributing to marginal handling qualities in the landing approach. The powered elevator control system enhanced the controllability in pitch, particularly in the landing flare and stall recovery.

Technical note: An approach to derive breeding goals from the preferences of decision makers.

PubMed

Alfonso, L

2016-11-01

This paper deals with the use of the Choquet integral to identify breeding objectives and construct an aggregate genotype. The Choquet integral can be interpreted as an extension of the aggregate genotype based on profit equations, substituting the vector of economic weights by a monotone function, called capacity, which allows the aggregation of traits based, for instance, on the preferences of decision makers. It allows the aggregation of traits with or without economic value, taking into account not only the importance of the breeding value of each trait but also the interaction among them. Two examples have been worked out for pig and dairy cattle breeding scenarios to illustrate its application. It is shown that the expression of stakeholders' or decision makers' preferences, as a single ranking of animals or groups of animals, could be sufficient to extract information to derive breeding objectives. It is also shown that coalitions among traits can be identified to evaluate whether a linear additive function, equivalent of the Hazel aggregate genotype where economic values are replaced by Shapley values, could be adequate to define the net merit of breeding animals.

Vectors as Epidemiological Sentinels: Patterns of Within-Tick Borrelia burgdorferi Diversity

PubMed Central

Walter, Katharine S.; Carpi, Giovanna; Evans, Benjamin R.; Caccone, Adalgisa; Diuk-Wasser, Maria A.

2016-01-01

Hosts including humans, other vertebrates, and arthropods, are frequently infected with heterogeneous populations of pathogens. Within-host pathogen diversity has major implications for human health, epidemiology, and pathogen evolution. However, pathogen diversity within-hosts is difficult to characterize and little is known about the levels and sources of within-host diversity maintained in natural populations of disease vectors. Here, we examine genomic variation of the Lyme disease bacteria, Borrelia burgdorferi (Bb), in 98 individual field-collected tick vectors as a model for study of within-host processes. Deep population sequencing reveals extensive and previously undocumented levels of Bb variation: the majority (~70%) of ticks harbor mixed strain infections, which we define as levels Bb diversity pre-existing in a diverse inoculum. Within-tick diversity is thus a sample of the variation present within vertebrate hosts. Within individual ticks, we detect signatures of positive selection. Genes most commonly under positive selection across ticks include those involved in dissemination in vertebrate hosts and evasion of the vertebrate immune complement. By focusing on tick-borne Bb, we show that vectors can serve as epidemiological and evolutionary sentinels: within-vector pathogen diversity can be a useful and unbiased way to survey circulating pathogen diversity and identify evolutionary processes occurring in natural transmission cycles. PMID:27414806

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.

A comprehensive analysis of filamentous phage display vectors for cytoplasmic proteins: an analysis with different fluorescent proteins.

PubMed

Velappan, Nileena; Fisher, Hugh E; Pesavento, Emanuele; Chasteen, Leslie; D'Angelo, Sara; Kiss, Csaba; Longmire, Michelle; Pavlik, Peter; Bradbury, Andrew R M

2010-03-01

Filamentous phage display has been extensively used to select proteins with binding properties of specific interest. Although many different display platforms using filamentous phage have been described, no comprehensive comparison of their abilities to display similar proteins has been conducted. This is particularly important for the display of cytoplasmic proteins, which are often poorly displayed with standard filamentous phage vectors. In this article, we have analyzed the ability of filamentous phage to display a stable form of green fluorescent protein and modified variants in nine different display vectors, a number of which have been previously proposed as being suitable for cytoplasmic protein display. Correct folding and display were assessed by phagemid particle fluorescence, and with anti-GFP antibodies. The poor correlation between phagemid particle fluorescence and recognition of GFP by antibodies, indicates that proteins may fold correctly without being accessible for display. The best vector used a twin arginine transporter leader to transport the displayed protein to the periplasm, and a coil-coil arrangement to link the displayed protein to g3p. This vector was able to display less robust forms of GFP, including ones with inserted epitopes, as well as fluorescent proteins of the Azami green series. It was also functional in mock selection experiments.

RNA Interference in Infectious Tropical Diseases

PubMed Central

Hong, Young S.

2008-01-01

Introduction of double-stranded RNA (dsRNA) into some cells or organisms results in degradation of its homologous mRNA, a process called RNA interference (RNAi). The dsRNAs are processed into short interfering RNAs (siRNAs) that subsequently bind to the RNA-induced silencing complex (RISC), causing degradation of target mRNAs. Because of this sequence-specific ability to silence target genes, RNAi has been extensively used to study gene functions and has the potential to control disease pathogens or vectors. With this promise of RNAi to control pathogens and vectors, this paper reviews the current status of RNAi in protozoans, animal parasitic helminths and disease-transmitting vectors, such as insects. Many pathogens and vectors cause severe parasitic diseases in tropical regions and it is difficult to control once the host has been invaded. Intracellularly, RNAi can be highly effective in impeding parasitic development and proliferation within the host. To fully realize its potential as a means to control tropical diseases, appropriate delivery methods for RNAi should be developed, and possible off-target effects should be minimized for specific gene suppression. RNAi can also be utilized to reduce vector competence to interfere with disease transmission, as genes critical for pathogenesis of tropical diseases are knockdowned via RNAi. PMID:18344671

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

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

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.

2013-12-01

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

76 FR 3135 - Pesticide Experimental Use Permit; Receipt of Extension Application;

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-19

... ENVIRONMENTAL PROTECTION AGENCY [EPA-HQ-OPP-2009-0608; FRL-8855-3] Pesticide Experimental Use... (PIP) [Event 5307] Bacillus thuringiensis eCry3.1Ab protein and the genetic material necessary for its production (vector pSYN12274) in Event 5307 corn (SYN-[Oslash]53[Oslash]7-1) and combined and single trait...

Study of a homotopy continuation method for early orbit determination with the Tracking and Data Relay Satellite System (TDRSS)

NASA Technical Reports Server (NTRS)

Smith, R. L.; Huang, C.

1986-01-01

A recent mathematical technique for solving systems of equations is applied in a very general way to the orbit determination problem. The study of this technique, the homotopy continuation method, was motivated by the possible need to perform early orbit determination with the Tracking and Data Relay Satellite System (TDRSS), using range and Doppler tracking alone. Basically, a set of six tracking observations is continuously transformed from a set with known solution to the given set of observations with unknown solutions, and the corresponding orbit state vector is followed from the a priori estimate to the solutions. A numerical algorithm for following the state vector is developed and described in detail. Numerical examples using both real and simulated TDRSS tracking are given. A prototype early orbit determination algorithm for possible use in TDRSS orbit operations was extensively tested, and the results are described. Preliminary studies of two extensions of the method are discussed: generalization to a least-squares formulation and generalization to an exhaustive global method.

Extensions to the Dynamic Aerospace Vehicle Exchange Markup Language

NASA Technical Reports Server (NTRS)

Brian, Geoffrey J.; Jackson, E. Bruce

2011-01-01

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It provides a framework for encoding entire flight vehicle dynamic model data packages for exchange and/or long-term archiving. Version 2.0.1 of DAVE-ML provides much of the functionality envisioned for exchanging aerospace vehicle data; however, it is limited in only supporting scalar time-independent data. Additional functionality is required to support vector and matrix data, abstracting sub-system models, detailing dynamics system models (both discrete and continuous), and defining a dynamic data format (such as time sequenced data) for validation of dynamics system models and vehicle simulation packages. Extensions to DAVE-ML have been proposed to manage data as vectors and n-dimensional matrices, and record dynamic data in a compatible form. These capabilities will improve the clarity of data being exchanged, simplify the naming of parameters, and permit static and dynamic data to be stored using a common syntax within a single file; thereby enhancing the framework provided by DAVE-ML for exchanging entire flight vehicle dynamic simulation models.

Web Extensible Display Manager

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

Slominski, Ryan; Larrieu, Theodore L.

Jefferson Lab's Web Extensible Display Manager (WEDM) allows staff to access EDM control system screens from a web browser in remote offices and from mobile devices. Native browser technologies are leveraged to avoid installing and managing software on remote clients such as browser plugins, tunnel applications, or an EDM environment. Since standard network ports are used firewall exceptions are minimized. To avoid security concerns from remote users modifying a control system, WEDM exposes read-only access and basic web authentication can be used to further restrict access. Updates of monitored EPICS channels are delivered via a Web Socket using a webmore » gateway. The software translates EDM description files (denoted with the edl suffix) to HTML with Scalable Vector Graphics (SVG) following the EDM's edl file vector drawing rules to create faithful screen renderings. The WEDM server parses edl files and creates the HTML equivalent in real-time allowing existing screens to work without modification. Alternatively, the familiar drag and drop EDM screen creation tool can be used to create optimized screens sized specifically for smart phones and then rendered by WEDM.« less

Image Coding Based on Address Vector Quantization.

NASA Astrophysics Data System (ADS)

Feng, Yushu

Image coding is finding increased application in teleconferencing, archiving, and remote sensing. This thesis investigates the potential of Vector Quantization (VQ), a relatively new source coding technique, for compression of monochromatic and color images. Extensions of the Vector Quantization technique to the Address Vector Quantization method have been investigated. In Vector Quantization, the image data to be encoded are first processed to yield a set of vectors. A codeword from the codebook which best matches the input image vector is then selected. Compression is achieved by replacing the image vector with the index of the code-word which produced the best match, the index is sent to the channel. Reconstruction of the image is done by using a table lookup technique, where the label is simply used as an address for a table containing the representative vectors. A code-book of representative vectors (codewords) is generated using an iterative clustering algorithm such as K-means, or the generalized Lloyd algorithm. A review of different Vector Quantization techniques are given in chapter 1. Chapter 2 gives an overview of codebook design methods including the Kohonen neural network to design codebook. During the encoding process, the correlation of the address is considered and Address Vector Quantization is developed for color image and monochrome image coding. Address VQ which includes static and dynamic processes is introduced in chapter 3. In order to overcome the problems in Hierarchical VQ, Multi-layer Address Vector Quantization is proposed in chapter 4. This approach gives the same performance as that of the normal VQ scheme but the bit rate is about 1/2 to 1/3 as that of the normal VQ method. In chapter 5, a Dynamic Finite State VQ based on a probability transition matrix to select the best subcodebook to encode the image is developed. In chapter 6, a new adaptive vector quantization scheme, suitable for color video coding, called "A Self -Organizing Adaptive VQ Technique" is presented. In addition to chapters 2 through 6 which report on new work, this dissertation includes one chapter (chapter 1) and part of chapter 2 which review previous work on VQ and image coding, respectively. Finally, a short discussion of directions for further research is presented in conclusion.

THRESHOLD ELEMENTS AND THE DESIGN OF SEQUENTIAL SWITCHING NETWORKS.

DTIC Science & Technology

The report covers research performed from March 1966 to March 1967. The major topics treated are: (1) methods for finding weight- threshold vectors...that realize a given switching function in multi- threshold linear logic; (2) synthesis of sequential machines by means of shift registers and simple

Convergence analyses on on-line weight noise injection-based training algorithms for MLPs.

PubMed

Sum, John; Leung, Chi-Sing; Ho, Kevin

2012-11-01

Injecting weight noise during training is a simple technique that has been proposed for almost two decades. However, little is known about its convergence behavior. This paper studies the convergence of two weight noise injection-based training algorithms, multiplicative weight noise injection with weight decay and additive weight noise injection with weight decay. We consider that they are applied to multilayer perceptrons either with linear or sigmoid output nodes. Let w(t) be the weight vector, let V(w) be the corresponding objective function of the training algorithm, let α >; 0 be the weight decay constant, and let μ(t) be the step size. We show that if μ(t)→ 0, then with probability one E[||w(t)||2(2)] is bound and lim(t) → ∞ ||w(t)||2 exists. Based on these two properties, we show that if μ(t)→ 0, Σtμ(t)=∞, and Σtμ(t)(2) <; ∞, then with probability one these algorithms converge. Moreover, w(t) converges with probability one to a point where ∇wV(w)=0.

In vivo Loads in the Lumbar L3-4 Disc during a Weight Lifting Extension

PubMed Central

Wang, Shaobai; Park, Won Man; Kim, Yoon Hyuk; Cha, Thomas; Wood, Kirkham; Li, Guoan

2014-01-01

Background Knowledge of in vivo human lumbar loading is critical for understanding the lumbar function and for improving surgical treatments of lumbar pathology. Although numerous experimental measurements and computational simulations have been reported, non-invasive determination of in vivo spinal disc loads is still a challenge in biomedical engineering. The object of the study is to investigate the in vivo human lumbar disc loads using a subject-specific and kinematic driven finite element approach. Methods Three dimensional (3D) lumbar spine models of three living subjects were created using MR images. A 3D finite element model of the L3-4 disc, including the annulus fibrosus and nucleus pulposus, was built for each subject. The endplate kinematics of the L3-4 segment of each subject during a dynamic weight lifting extension was determined using a dual fluoroscopic imaging technique. The endplate kinematics was used as displacement boundary conditions of the subject specific finite element model of the L3-4 disc to calculate the in-vivo disc forces and moments during the weight lifting activity. Findings During the weight lifting extension, the L3-4 disc experienced maximum shear load of about 230 N or 0.34 bodyweight at the flexion position and maximum compressive load of 1500 N or 2.28 bodyweight at the upright position. The disc experienced a primary flexion-extension moment during the motion which reached a maximum of 4.2 Nm at upright position with stretched arms holding the weight. Interpretation This study provided quantitative data on in vivo disc loading that could help understand intrinsic biomechanics of the spine and improve surgical treatment of pathological discs using fusion or arthroplasty techniques. PMID:24345591

Predictive classification of pediatric bipolar disorder using atlas-based diffusion weighted imaging and support vector machines.

PubMed

Mwangi, Benson; Wu, Mon-Ju; Bauer, Isabelle E; Modi, Haina; Zeni, Cristian P; Zunta-Soares, Giovana B; Hasan, Khader M; Soares, Jair C

2015-11-30

Previous studies have reported abnormalities of white-matter diffusivity in pediatric bipolar disorder. However, it has not been established whether these abnormalities are able to distinguish individual subjects with pediatric bipolar disorder from healthy controls with a high specificity and sensitivity. Diffusion-weighted imaging scans were acquired from 16 youths diagnosed with DSM-IV bipolar disorder and 16 demographically matched healthy controls. Regional white matter tissue microstructural measurements such as fractional anisotropy, axial diffusivity and radial diffusivity were computed using an atlas-based approach. These measurements were used to 'train' a support vector machine (SVM) algorithm to predict new or 'unseen' subjects' diagnostic labels. The SVM algorithm predicted individual subjects with specificity=87.5%, sensitivity=68.75%, accuracy=78.12%, positive predictive value=84.62%, negative predictive value=73.68%, area under receiver operating characteristic curve (AUROC)=0.7812 and chi-square p-value=0.0012. A pattern of reduced regional white matter fractional anisotropy was observed in pediatric bipolar disorder patients. These results suggest that atlas-based diffusion weighted imaging measurements can distinguish individual pediatric bipolar disorder patients from healthy controls. Notably, from a clinical perspective these findings will contribute to the pathophysiological understanding of pediatric bipolar disorder. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Three learning phases for radial-basis-function networks.

PubMed

Schwenker, F; Kestler, H A; Palm, G

2001-05-01

In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase learning schemes. Two-phase RBF learning is a very common learning scheme. The two layers of an RBF network are learnt separately; first the RBF layer is trained, including the adaptation of centers and scaling parameters, and then the weights of the output layer are adapted. RBF centers may be trained by clustering, vector quantization and classification tree algorithms, and the output layer by supervised learning (through gradient descent or pseudo inverse solution). Results from numerical experiments of RBF classifiers trained by two-phase learning are presented in three completely different pattern recognition applications: (a) the classification of 3D visual objects; (b) the recognition hand-written digits (2D objects); and (c) the categorization of high-resolution electrocardiograms given as a time series (ID objects) and as a set of features extracted from these time series. In these applications, it can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously. This, we call three-phase learning in RBF networks. A practical advantage of two- and three-phase learning in RBF networks is the possibility to use unlabeled training data for the first training phase. Support vector (SV) learning in RBF networks is a different learning approach. SV learning can be considered, in this context of learning, as a special type of one-phase learning, where only the output layer weights of the RBF network are calculated, and the RBF centers are restricted to be a subset of the training data. Numerical experiments with several classifier schemes including k-nearest-neighbor, learning vector quantization and RBF classifiers trained through two-phase, three-phase and support vector learning are given. The performance of the RBF classifiers trained through SV learning and three-phase learning are superior to the results of two-phase learning, but SV learning often leads to complex network structures, since the number of support vectors is not a small fraction of the total number of data points.

AAV vector-mediated secretion of chondroitinase provides a sensitive tracer for axonal arborisations.

PubMed

Alves, João Nuno; Muir, Elizabeth M; Andrews, Melissa R; Ward, Anneliese; Michelmore, Nicholas; Dasgupta, Debayan; Verhaagen, Joost; Moloney, Elizabeth B; Keynes, Roger J; Fawcett, James W; Rogers, John H

2014-04-30

As part of a project to express chondroitinase ABC (ChABC) in neurons of the central nervous system, we have inserted a modified ChABC gene into an adeno-associated viral (AAV) vector and injected it into the vibrissal motor cortex in adult rats to determine the extent and distribution of expression of the enzyme. A similar vector for expression of green fluorescent protein (GFP) was injected into the same location. For each vector, two versions with minor differences were used, giving similar results. After 4 weeks, the brains were stained to show GFP and products of chondroitinase digestion. Chondroitinase was widely expressed, and the AAV-ChABC and AAV-GFP vectors gave similar expression patterns in many respects, consistent with the known projections from the directly transduced neurons in vibrissal motor cortex and adjacent cingulate cortex. In addition, diffusion of vector to deeper neuronal populations led to labelling of remote projection fields which was much more extensive with AAV-ChABC than with AAV-GFP. The most notable of these populations are inferred to be neurons of cortical layer 6, projecting widely in the thalamus, and neurons of the anterior pole of the hippocampus, projecting through most of the hippocampus. We conclude that, whereas GFP does not label the thinnest axonal branches of some neuronal types, chondroitinase is efficiently secreted from these arborisations and enables their extent to be sensitively visualised. After 12 weeks, chondroitinase expression was undiminished. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Evaluation of chemical spraying and environmental management efficacy in areas with minor previous application of integrated control actions for visceral leishmaniasis in Brazil.

PubMed

Lara-Silva, Fabiana de Oliveira; Michalsky, Érika Monteiro; Fortes-Dias, Consuelo Latorre; Fiuza, Vanessa de Oliveira Pires; Dias, Edelberto Santos

2017-12-01

Leishmaniases are vector-borne diseases that are transmitted to humans through the bite of Leishmania-infected phlebotomine sand flies (Diptera:Psychodidae). The main proved vector of visceral leishmaniais (VL) in the New World - Lutzomyia longipalpis - is well-adapted to urban areas and has extensive distribution within the five geographical regions of Brazil. Integrated public health actions directed for the vector, domestic reservoir and humans for the control of VL are preferentially applied in municipalities with higher epidemiological risk of transmission. In this study, we evaluated the individual impact of two main vector control actions - chemical spraying and environmental management - in two districts with no reported cases of human VL. Although belonging to an endemic municipality for VL in Brazil, the integrated control actions have not been applied in these districts due to the absence of human cases. The number of L. longipalpis captured in a two-year period was used as indicator of the population density of the vector. After chemical spraying a tendency of reduction in L. longipalpis was observed but with no statistical significance compared to the control. Environmental management was effective in that reduction and it may help in the control of VL by reducing the population density of the vector in a preventive and more permanent action, perhaps associated with chemical spraying. Copyright © 2017 Elsevier B.V. All rights reserved.

[Range of Hip Joint Motion and Weight of Lower Limb Function under 3D Dynamic Marker].

PubMed

Xia, Q; Zhang, M; Gao, D; Xia, W T

2017-12-01

To explore the range of reasonable weight coefficient of hip joint in lower limb function. When the hip joints of healthy volunteers under normal conditions or fixed at three different positions including functional, flexed and extension positions, the movements of lower limbs were recorded by LUKOtronic motion capture and analysis system. The degree of lower limb function loss was calculated using Fugl-Meyer lower limb function assessment form when the hip joints were fixed at the aforementioned positions. One-way analysis of variance and Tamhane's T2 method were used to proceed statistics analysis and calculate the range of reasonable weight coefficient of hip joint. There were significant differences between the degree of lower limb function loss when the hip joints fixed at flexed and extension positions and at functional position. While the differences between the degree of lower limb function loss when the hip joints fixed at flexed position and extension position had no statistical significance. In 95% confidence interval, the reasonable weight coefficient of hip joint in lower limb function was between 61.05% and 73.34%. Expect confirming the reasonable weight coefficient, the effects of functional and non-functional positions on the degree of lower limb function loss should also be considered for the assessment of hip joint function loss. Copyright© by the Editorial Department of Journal of Forensic Medicine

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

NASA Technical Reports Server (NTRS)

Wing, David J.

1994-01-01

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

Optical modular arithmetic

NASA Astrophysics Data System (ADS)

Pavlichin, Dmitri S.; Mabuchi, Hideo

2014-06-01

Nanoscale integrated photonic devices and circuits offer a path to ultra-low power computation at the few-photon level. Here we propose an optical circuit that performs a ubiquitous operation: the controlled, random-access readout of a collection of stored memory phases or, equivalently, the computation of the inner product of a vector of phases with a binary selector" vector, where the arithmetic is done modulo 2pi and the result is encoded in the phase of a coherent field. This circuit, a collection of cascaded interferometers driven by a coherent input field, demonstrates the use of coherence as a computational resource, and of the use of recently-developed mathematical tools for modeling optical circuits with many coupled parts. The construction extends in a straightforward way to the computation of matrix-vector and matrix-matrix products, and, with the inclusion of an optical feedback loop, to the computation of a weighted" readout of stored memory phases. We note some applications of these circuits for error correction and for computing tasks requiring fast vector inner products, e.g. statistical classification and some machine learning algorithms.

VLSI realization of learning vector quantization with hardware/software co-design for different applications

NASA Astrophysics Data System (ADS)

An, Fengwei; Akazawa, Toshinobu; Yamasaki, Shogo; Chen, Lei; Jürgen Mattausch, Hans

2015-04-01

This paper reports a VLSI realization of learning vector quantization (LVQ) with high flexibility for different applications. It is based on a hardware/software (HW/SW) co-design concept for on-chip learning and recognition and designed as a SoC in 180 nm CMOS. The time consuming nearest Euclidean distance search in the LVQ algorithm’s competition layer is efficiently implemented as a pipeline with parallel p-word input. Since neuron number in the competition layer, weight values, input and output number are scalable, the requirements of many different applications can be satisfied without hardware changes. Classification of a d-dimensional input vector is completed in n × \\lceil d/p \\rceil + R clock cycles, where R is the pipeline depth, and n is the number of reference feature vectors (FVs). Adjustment of stored reference FVs during learning is done by the embedded 32-bit RISC CPU, because this operation is not time critical. The high flexibility is verified by the application of human detection with different numbers for the dimensionality of the FVs.

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.

Mode of Infection of Metarhizium spp. Fungus and Their Potential as Biological Control Agents

PubMed Central

Aw, Kimberly Moon San; Hue, Seow Mun

2017-01-01

Chemical insecticides have been commonly used to control agricultural pests, termites, and biological vectors such as mosquitoes and ticks. However, the harmful impacts of toxic chemical insecticides on the environment, the development of resistance in pests and vectors towards chemical insecticides, and public concern have driven extensive research for alternatives, especially biological control agents such as fungus and bacteria. In this review, the mode of infection of Metarhizium fungus on both terrestrial and aquatic insect larvae and how these interactions have been widely employed will be outlined. The potential uses of Metarhizium anisopliae and Metarhizium acridum biological control agents and molecular approaches to increase their virulence will be discussed. PMID:29371548

High frequency vibration analysis by the complex envelope vectorization.

PubMed

Giannini, O; Carcaterra, A; Sestieri, A

2007-06-01

The complex envelope displacement analysis (CEDA) is a procedure to solve high frequency vibration and vibro-acoustic problems, providing the envelope of the physical solution. CEDA is based on a variable transformation mapping the high frequency oscillations into signals of low frequency content and has been successfully applied to one-dimensional systems. However, the extension to plates and vibro-acoustic fields met serious difficulties so that a general revision of the theory was carried out, leading finally to a new method, the complex envelope vectorization (CEV). In this paper the CEV method is described, underlying merits and limits of the procedure, and a set of applications to vibration and vibro-acoustic problems of increasing complexity are presented.

A vectorized Lanczos eigensolver for high-performance computers

NASA Technical Reports Server (NTRS)

Bostic, Susan W.

1990-01-01

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

Alterations to the relativistic Love-Franey model and their application to inelastic scattering

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

Zeile, J.R.

The fictitious axial-vector and tensor mesons for the real part of the relativistic Love-Franey interaction are removed. In an attempt to make up for this loss, derivative couplings are used for the {pi} and {rho} mesons. Such derivative couplings require the introduction of axial-vector and tensor contact term corrections. Meson parameters are then fit to free nucleon-nucleon scattering data. The resulting fits are comparable to those of the relativistic Love-Franey model provided that the contact term corrections are included and the fits are weighted over the physically significant quantity of twice the tensor minus the axial-vector Lorentz invariants. Failure tomore » include contact term corrections leads to poor fits at higher energies. The off-shell behavior of this model is then examined by looking at several applications from inelastic proton-nucleus scattering.« less

A semisupervised support vector regression method to estimate biophysical parameters from remotely sensed images

NASA Astrophysics Data System (ADS)

Castelletti, Davide; Demir, Begüm; Bruzzone, Lorenzo

2014-10-01

This paper presents a novel semisupervised learning (SSL) technique defined in the context of ɛ-insensitive support vector regression (SVR) to estimate biophysical parameters from remotely sensed images. The proposed SSL method aims to mitigate the problems of small-sized biased training sets without collecting any additional samples with reference measures. This is achieved on the basis of two consecutive steps. The first step is devoted to inject additional priors information in the learning phase of the SVR in order to adapt the importance of each training sample according to distribution of the unlabeled samples. To this end, a weight is initially associated to each training sample based on a novel strategy that defines higher weights for the samples located in the high density regions of the feature space while giving reduced weights to those that fall into the low density regions of the feature space. Then, in order to exploit different weights for training samples in the learning phase of the SVR, we introduce a weighted SVR (WSVR) algorithm. The second step is devoted to jointly exploit labeled and informative unlabeled samples for further improving the definition of the WSVR learning function. To this end, the most informative unlabeled samples that have an expected accurate target values are initially selected according to a novel strategy that relies on the distribution of the unlabeled samples in the feature space and on the WSVR function estimated at the first step. Then, we introduce a restructured WSVR algorithm that jointly uses labeled and unlabeled samples in the learning phase of the WSVR algorithm and tunes their importance by different values of regularization parameters. Experimental results obtained for the estimation of single-tree stem volume show the effectiveness of the proposed SSL method.

A GPCR-focused investigation of the R. microplus transcriptome

USDA-ARS?s Scientific Manuscript database

Rhipicephalus microplus, also known as the southern cattle tick, has been found in tropical and subtropical regions all over the world, including Mexico. It is a vector for parasites responsible for cattle diseases that can lead to decreased weight, anemia, loss of milk/meat production, and death. T...

77 FR 69866 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-21

... for Diabetes and Obesity Description of Technology: This invention is directed to adeno- associated virus (AAV) vector delivery of exendin-4 (Ex-4) to salivary glands as treatment for diabetes and obesity... and weight profile in two rat models of obesity and type 2 diabetes. Further, AAV-mediated delivery of...

Machine parts recognition using a trinary associative memory

NASA Technical Reports Server (NTRS)

Awwal, Abdul Ahad S.; Karim, Mohammad A.; Liu, Hua-Kuang

1989-01-01

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Machine Parts Recognition Using A Trinary Associative Memory

NASA Astrophysics Data System (ADS)

Awwal, Abdul A. S.; Karim, Mohammad A.; Liu, Hua-Kuang

1989-05-01

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

New syndrome decoding techniques for the (n, k) convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

This paper presents a new syndrome decoding algorithm for the (n, k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3, 1)CC. Previously announced in STAR as N83-34964

Gradient-based controllers for timed continuous Petri nets

NASA Astrophysics Data System (ADS)

Lefebvre, Dimitri; Leclercq, Edouard; Druaux, Fabrice; Thomas, Philippe

2015-07-01

This paper is about control design for timed continuous Petri nets that are described as piecewise affine systems. In this context, the marking vector is considered as the state space vector, weighted marking of place subsets are defined as the model outputs and the model inputs correspond to multiplicative control actions that slow down the firing rate of some controllable transitions. Structural and functional sensitivity of the outputs with respect to the inputs are discussed in terms of Petri nets. Then, gradient-based controllers (GBC) are developed in order to adapt the control actions of the controllable transitions according to desired trajectories of the outputs.

Cophenetic metrics for phylogenetic trees, after Sokal and Rohlf.

PubMed

Cardona, Gabriel; Mir, Arnau; Rosselló, Francesc; Rotger, Lucía; Sánchez, David

2013-01-16

Phylogenetic tree comparison metrics are an important tool in the study of evolution, and hence the definition of such metrics is an interesting problem in phylogenetics. In a paper in Taxon fifty years ago, Sokal and Rohlf proposed to measure quantitatively the difference between a pair of phylogenetic trees by first encoding them by means of their half-matrices of cophenetic values, and then comparing these matrices. This idea has been used several times since then to define dissimilarity measures between phylogenetic trees but, to our knowledge, no proper metric on weighted phylogenetic trees with nested taxa based on this idea has been formally defined and studied yet. Actually, the cophenetic values of pairs of different taxa alone are not enough to single out phylogenetic trees with weighted arcs or nested taxa. For every (rooted) phylogenetic tree T, let its cophenetic vectorφ(T) consist of all pairs of cophenetic values between pairs of taxa in T and all depths of taxa in T. It turns out that these cophenetic vectors single out weighted phylogenetic trees with nested taxa. We then define a family of cophenetic metrics dφ,p by comparing these cophenetic vectors by means of Lp norms, and we study, either analytically or numerically, some of their basic properties: neighbors, diameter, distribution, and their rank correlation with each other and with other metrics. The cophenetic metrics can be safely used on weighted phylogenetic trees with nested taxa and no restriction on degrees, and they can be computed in O(n2) time, where n stands for the number of taxa. The metrics dφ,1 and dφ,2 have positive skewed distributions, and they show a low rank correlation with the Robinson-Foulds metric and the nodal metrics, and a very high correlation with each other and with the splitted nodal metrics. The diameter of dφ,p, for p⩾1 , is in O(n(p+2)/p), and thus for low p they are more discriminative, having a wider range of values.

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.

Polarized light use in the nocturnal bull ant, Myrmecia midas.

PubMed

Freas, Cody A; Narendra, Ajay; Lemesle, Corentin; Cheng, Ken

2017-08-01

Solitary foraging ants have a navigational toolkit, which includes the use of both terrestrial and celestial visual cues, allowing individuals to successfully pilot between food sources and their nest. One such celestial cue is the polarization pattern in the overhead sky. Here, we explore the use of polarized light during outbound and inbound journeys and with different home vectors in the nocturnal bull ant, Myrmecia midas . We tested foragers on both portions of the foraging trip by rotating the overhead polarization pattern by ±45°. Both outbound and inbound foragers responded to the polarized light change, but the extent to which they responded to the rotation varied. Outbound ants, both close to and further from the nest, compensated for the change in the overhead e-vector by about half of the manipulation, suggesting that outbound ants choose a compromise heading between the celestial and terrestrial compass cues. However, ants returning home compensated for the change in the e-vector by about half of the manipulation when the remaining home vector was short (1-2 m) and by more than half of the manipulation when the remaining vector was long (more than 4 m). We report these findings and discuss why weighting on polarization cues change in different contexts.

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.

Vector method for strain estimation in phase-sensitive optical coherence elastography

NASA Astrophysics Data System (ADS)

Matveyev, A. L.; Matveev, L. A.; Sovetsky, A. A.; Gelikonov, G. V.; Moiseev, A. A.; Zaitsev, V. Y.

2018-06-01

A noise-tolerant approach to strain estimation in phase-sensitive optical coherence elastography, robust to decorrelation distortions, is discussed. The method is based on evaluation of interframe phase-variation gradient, but its main feature is that the phase is singled out at the very last step of the gradient estimation. All intermediate steps operate with complex-valued optical coherence tomography (OCT) signals represented as vectors in the complex plane (hence, we call this approach the ‘vector’ method). In comparison with such a popular method as least-square fitting of the phase-difference slope over a selected region (even in the improved variant with amplitude weighting for suppressing small-amplitude noisy pixels), the vector approach demonstrates superior tolerance to both additive noise in the receiving system and speckle-decorrelation caused by tissue straining. Another advantage of the vector approach is that it obviates the usual necessity of error-prone phase unwrapping. Here, special attention is paid to modifications of the vector method that make it especially suitable for processing deformations with significant lateral inhomogeneity, which often occur in real situations. The method’s advantages are demonstrated using both simulated and real OCT scans obtained during reshaping of a collagenous tissue sample irradiated by an IR laser beam producing complex spatially inhomogeneous deformations.

Polarized light use in the nocturnal bull ant, Myrmecia midas

PubMed Central

Lemesle, Corentin; Cheng, Ken

2017-01-01

Solitary foraging ants have a navigational toolkit, which includes the use of both terrestrial and celestial visual cues, allowing individuals to successfully pilot between food sources and their nest. One such celestial cue is the polarization pattern in the overhead sky. Here, we explore the use of polarized light during outbound and inbound journeys and with different home vectors in the nocturnal bull ant, Myrmecia midas. We tested foragers on both portions of the foraging trip by rotating the overhead polarization pattern by ±45°. Both outbound and inbound foragers responded to the polarized light change, but the extent to which they responded to the rotation varied. Outbound ants, both close to and further from the nest, compensated for the change in the overhead e-vector by about half of the manipulation, suggesting that outbound ants choose a compromise heading between the celestial and terrestrial compass cues. However, ants returning home compensated for the change in the e-vector by about half of the manipulation when the remaining home vector was short (1−2 m) and by more than half of the manipulation when the remaining vector was long (more than 4 m). We report these findings and discuss why weighting on polarization cues change in different contexts. PMID:28879002

Targeted Modifications in Adeno-Associated Virus Serotype 8 Capsid Improves Its Hepatic Gene Transfer Efficiency In Vivo

PubMed Central

Sen, Dwaipayan; Gadkari, Rupali A; Sudha, Govindarajan; Gabriel, Nishanth; Kumar, Yesupatham Sathish; Selot, Ruchita; Samuel, Rekha; Rajalingam, Sumathi; Ramya, V.; Nair, Sukesh C.; Srinivasan, Narayanaswamy; Srivastava, Alok

2013-01-01

Abstract Recombinant adeno-associated virus vectors based on serotype 8 (AAV8) have shown significant promise for liver-directed gene therapy. However, to overcome the vector dose dependent immunotoxicity seen with AAV8 vectors, it is important to develop better AAV8 vectors that provide enhanced gene expression at significantly low vector doses. Since it is known that AAV vectors during intracellular trafficking are targeted for destruction in the cytoplasm by the host–cellular kinase/ubiquitination/proteasomal machinery, we modified specific serine/threonine kinase or ubiquitination targets on the AAV8 capsid to augment its transduction efficiency. Point mutations at specific serine (S)/threonine (T)/lysine (K) residues were introduced in the AAV8 capsid at the positions equivalent to that of the effective AAV2 mutants, generated successfully earlier. Extensive structure analysis was carried out subsequently to evaluate the structural equivalence between the two serotypes. scAAV8 vectors with the wild-type (WT) and each one of the S/T→Alanine (A) or K-Arginine (R) mutant capsids were evaluated for their liver transduction efficiency in C57BL/6 mice in vivo. Two of the AAV8-S→A mutants (S279A and S671A), and a K137R mutant vector, demonstrated significantly higher enhanced green fluorescent protein (EGFP) transcript levels (∼9- to 46-fold) in the liver compared to animals that received WT-AAV8 vectors alone. The best performing AAV8 mutant (K137R) vector also had significantly reduced ubiquitination of the viral capsid, reduced activation of markers of innate immune response, and a concomitant two-fold reduction in the levels of neutralizing antibody formation in comparison to WT-AAV8 vectors. Vector biodistribution studies revealed that the K137R mutant had a significantly higher and preferential transduction of the liver (106 vs. 7.7 vector copies/mouse diploid genome) when compared to WT-AAV8 vectors. To further study the utility of the K137R-AAV8 mutant in therapeutic gene transfer, we delivered human coagulation factor IX (h.FIX) under the control of liver-specific promoters (LP1 or hAAT) into C57BL/6 mice. The circulating levels of h.FIX:Ag were higher in all the K137R-AAV8 treated groups up to 8 weeks post-hepatic gene transfer. These studies demonstrate the feasibility of the use of this novel AAV8 vectors for potential gene therapy of hemophilia B. PMID:23442071

77 FR 26547 - Amendment/Extension of an Experimental Use Permit

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-04

...-incorporated protectant (PIP) [Event 5307] Bacillus thuringiensis eCry3.1Ab protein and the genetic material necessary for its production (vector pSYN12274) in Event 5307 corn (SYN-[Oslash]53[Oslash]7-1) and combined and single trait hybrids with one or more of the following additional PIPs: (1) [Bt11] Bacillus...

A simplified approach to construct infectious cDNA clones of a tobamovirus in a binary vector.

PubMed

Junqueira, Bruna Rayane Teodoro; Nicolini, Cícero; Lucinda, Natalia; Orílio, Anelise Franco; Nagata, Tatsuya

2014-03-01

Infectious cDNA clones of RNA viruses are important tools to study molecular processes such as replication and host-virus interactions. However, the cloning steps necessary for construction of cDNAs of viral RNA genomes in binary vectors are generally laborious. In this study, a simplified method of producing an agro-infectious Pepper mild mottle virus (PMMoV) clone is described in detail. Initially, the complete genome of PMMoV was amplified by a single-step RT-PCR, cloned, and subcloned into a small plasmid vector under the T7 RNA polymerase promoter to confirm the infectivity of the cDNA clone through transcript inoculation. The complete genome was then transferred to a binary vector using a single-step, overlap-extension PCR. The selected clones were agro-infiltrated to Nicotiana benthamiana plants and showed to be infectious, causing typical PMMoV symptoms. No differences in host responses were observed when the wild-type PMMoV isolate, the T7 RNA polymerase-derived transcripts and the agroinfiltration-derived viruses were inoculated to N. benthamiana, Capsicum chinense PI 159236 and Capsicum annuum plants. Copyright © 2013 Elsevier B.V. All rights reserved.

A Modular Toolset for Recombination Transgenesis and Neurogenetic Analysis of Drosophila

PubMed Central

Wang, Ji-Wu; Beck, Erin S.; McCabe, Brian D.

2012-01-01

Transgenic Drosophila have contributed extensively to our understanding of nervous system development, physiology and behavior in addition to being valuable models of human neurological disease. Here, we have generated a novel series of modular transgenic vectors designed to optimize and accelerate the production and analysis of transgenes in Drosophila. We constructed a novel vector backbone, pBID, that allows both phiC31 targeted transgene integration and incorporates insulator sequences to ensure specific and uniform transgene expression. Upon this framework, we have built a series of constructs that are either backwards compatible with existing restriction enzyme based vectors or utilize Gateway recombination technology for high-throughput cloning. These vectors allow for endogenous promoter or Gal4 targeted expression of transgenic proteins with or without fluorescent protein or epitope tags. In addition, we have generated constructs that facilitate transgenic splice isoform specific RNA inhibition of gene expression. We demonstrate the utility of these constructs to analyze proteins involved in nervous system development, physiology and neurodegenerative disease. We expect that these reagents will facilitate the proficiency and sophistication of Drosophila genetic analysis in both the nervous system and other tissues. PMID:22848718

Reproductive and developmental costs of deltamethrin resistance in the Chagas disease vector Triatoma infestans.

PubMed

Germano, Mónica Daniela; Inés Picollo, María

2015-06-01

Effective chemical control relies on reducing vector population size. However, insecticide selection pressure is often associated with the development of resistant populations that reduce control success. In treated areas, these resistant individuals present an adaptive advantage due to enhanced survival. Resistance can also lead to negative effects when the insecticide pressure ceases. In this study, the biological effects of deltamethrin resistance were assessed in the Chagas disease vector Triatoma infestans. The length of each developmental stage and complete life cycle, mating rate, and fecundity were evaluated. Susceptible and resistant insects presented similar mating rates. A reproductive cost of resistance was expressed as a lower fecundity in the resistant colony. Developmental costs in the resistant colony were in the form of a shortening of the second and third nymph stage duration and an extension of the fifth stage. A maternal effect of deltamethrin resistance is suggested as these effects were identified in resistant females and their progeny independently of the mated male's deltamethrin response. Our results suggest the presence of pleiotropic effects of deltamethrin resistance. Possible associations of these characters to other traits such as developmental delays and behavioral resistance are discussed. © 2015 The Society for Vector Ecology.

Environmental Drivers of West Nile Fever Epidemiology in Europe and Western Asia—A Review

PubMed Central

Paz, Shlomit; Semenza, Jan C.

2013-01-01

Abiotic and biotic conditions are both important determinants of West Nile Fever (WNF) epidemiology. Ambient temperature plays an important role in the growth rates of vector populations, the interval between blood meals, viral replication rates and transmission of West Nile Virus (WNV). The contribution of precipitation is more complex and less well understood. In this paper we discuss impacts of climatic parameters (temperature, relative humidity, precipitation) and other environmental drivers (such as bird migration, land use) on WNV transmission in Europe. WNV recently became established in southeastern Europe, with a large outbreak in the summer of 2010 and recurrent outbreaks in 2011 and 2012. Abundant competent mosquito vectors, bridge vectors, infected (viremic) migrating and local (amplifying) birds are all important characteristics of WNV transmission. In addition, certain key climatic factors, such as increased ambient temperatures, and by extension climate change, may also favor WNF transmission, and they should be taken into account when evaluating the risk of disease spread in the coming years. Monitoring epidemic precursors of WNF, such as significant temperature deviations in high risk areas, could be used to trigger vector control programs and public education campaigns. PMID:23939389

Vector magnetometer based on synchronous manipulation of nitrogen-vacancy centers in all crystal directions

NASA Astrophysics Data System (ADS)

Zhang, Chen; Yuan, Heng; Zhang, Ning; Xu, Lixia; Zhang, Jixing; Li, Bo; Fang, Jiancheng

2018-04-01

Negatively charged nitrogen vacancy (NV‑) centers in diamond have been extensively studied as high-sensitivity magnetometers, showcasing a wide range of applications. This study experimentally demonstrates a vector magnetometry scheme based on synchronous manipulation of NV‑ center ensembles in all crystal directions using double frequency microwaves (MWs) and multi-coupled-strip-lines (mCSL) waveguide. The application of the mCSL waveguide ensures a high degree of synchrony (99%) for manipulating NV‑ centers in multiple orientations in a large volume. Manipulation with double frequency MWs makes NV‑ centers of all four crystal directions involved, and additionally leads to an enhancement of the manipulation field. In this work, by monitoring the changes in the slope of the resonance line consisting of multi-axes NV‑ centers, measurement of the direction of the external field vector was demonstrated with a sensitivity of {{10}\\prime}/\\sqrt{Hz} . Based on the scheme, the fluorescence signal contrast was improved by four times higher and the sensitivity to the magnetic field strength was improved by two times. The method provides a more practical way of achieving vector sensors based on NV‑ center ensembles in diamond.

Sequence and immunogenicity of a clinically approved novel measles virus vaccine vector

PubMed Central

Zuniga, Amando; Liniger, Mathias; Morin, Teldja Neige Azzouz; Marty, René R.; Wiegand, Marian; Ilter, Orhan; Weibel, Sara; Billeter, Martin A.; Knuchel, Marlyse C.; Naim, Hussein Y.

2013-01-01

The measles virus vaccine (MVbv) is a clinically certified and well-tolerated vaccine strain that has been given both parenterally and mucosally. It has been extensively used in children and has proven to be safe and effective in eliciting protective immunity. This specific strain was therefore chosen to generate a measles viral vector. The genome of the commercial MVbv vaccine strain was isolated, sequenced and a plasmid, p(+)MVb, enabling transcription of the viral antigenome and rescue of MVb, was constructed. Phylogenic and phenotypic analysis revealed that MVbv and the rescued MVb constitute another evolutionary branch within the hitherto classified measles vaccines. Plasmid p(+)MVb was modified by insertion of artificial MV-type transcription units (ATUs) for the generation of recombinant viruses (rMVb) expressing additional proteins. Replication characteristics and immunogenicity of rMVb vectors were similar to the parental MVbv and to other vaccine strains. The expression of the additional proteins was stable over 10 serial virus transfers, which corresponds to an amplification greater than 1020. The excellent safety record and its efficient application as aerosol may add to the usefulness of the derived vectors. PMID:23324616

An Extension of RSS-based Model Comparison Tests for Weighted Least Squares

DTIC Science & Technology

2012-08-22

use the model comparison test statistic to analyze the null hypothesis. Under the null hypothesis, the weighted least squares cost functional is JWLS ...q̂WLSH ) = 10.3040×106. Under the alternative hypothesis, the weighted least squares cost functional is JWLS (q̂WLS) = 8.8394 × 106. Thus the model

DESIGN OF MINIMUM-WEIGHT DIFFUSION BATTERIES

EPA Science Inventory

Until recently, the measurement of particle sizes in aerosols was largely a laboratory exercise. Currently, however, particulates in the atmosphere and in the industrial exhaust gases are being monitored extensively in the field. While the weight and volume of laboratory apparatu...

The reference transcriptome of the adult female biting midge (Culicoides sonorensis) and differential gene expression profiling during teneral, blood, and sucrose feeding conditions.

PubMed

Nayduch, Dana; Lee, Matthew B; Saski, Christopher A

2014-01-01

Unlike other important vectors such as mosquitoes and sandflies, genetic and genomic tools for Culicoides biting midges are lacking, despite the fact that they vector a large number of arboviruses and other pathogens impacting humans and domestic animals world-wide. In North America, female Culicoides sonorensis midges are important vectors of bluetongue virus (BTV) and epizootic hemorrhagic disease virus (EHDV), orbiviruses that cause significant disease in livestock and wildlife. Libraries of tissue-specific transcripts expressed in response to feeding and oral orbivirus challenge in C. sonorensis have previously been reported, but extensive genome-wide expression profiling in the midge has not. Here, we successfully used deep sequencing technologies to construct the first adult female C. sonorensis reference transcriptome, and utilized genome-wide expression profiling to elucidate the genetic response to blood and sucrose feeding over time. The adult female midge unigene consists of 19,041 genes, of which less than 7% are differentially expressed during the course of a sucrose meal, while up to 52% of the genes respond significantly in blood-fed midges, indicating hematophagy induces complex physiological processes. Many genes that were differentially expressed during blood feeding were associated with digestion (e.g. proteases, lipases), hematophagy (e.g., salivary proteins), and vitellogenesis, revealing many major metabolic and biological factors underlying these critical processes. Additionally, key genes in the vitellogenesis pathway were identified, which provides the first glimpse into the molecular basis of anautogeny for C. sonorensis. This is the first extensive transcriptome for this genus, which will serve as a framework for future expression studies, RNAi, and provide a rich dataset contributing to the ultimate goal of informing a reference genome assembly and annotation. Moreover, this study will serve as a foundation for subsequent studies of genome-wide expression analyses during early orbivirus infection and dissecting the molecular mechanisms behind vector competence in midges.

Beyond generalized Proca theories

NASA Astrophysics Data System (ADS)

Heisenberg, Lavinia; Kase, Ryotaro; Tsujikawa, Shinji

2016-09-01

We consider higher-order derivative interactions beyond second-order generalized Proca theories that propagate only the three desired polarizations of a massive vector field besides the two tensor polarizations from gravity. These new interactions follow the similar construction criteria to those arising in the extension of scalar-tensor Horndeski theories to Gleyzes-Langlois-Piazza-Vernizzi (GLPV) theories. On the isotropic cosmological background, we show the existence of a constraint with a vanishing Hamiltonian that removes the would-be Ostrogradski ghost. We study the behavior of linear perturbations on top of the isotropic cosmological background in the presence of a matter perfect fluid and find the same number of propagating degrees of freedom as in generalized Proca theories (two tensor polarizations, two transverse vector modes, and two scalar modes). Moreover, we obtain the conditions for the avoidance of ghosts and Laplacian instabilities of tensor, vector, and scalar perturbations. We observe key differences in the scalar sound speed, which is mixed with the matter sound speed outside the domain of generalized Proca theories.

Evaluation of vector coastline features extracted from 'structure from motion'-derived elevation data

USGS Publications Warehouse

Kinsman, Nicole; Gibbs, Ann E.; Nolan, Matt

2015-01-01

For extensive and remote coastlines, the absence of high-quality elevation models—for example, those produced with lidar—leaves some coastal populations lacking one of the essential elements for mapping shoreline positions or flood extents. Here, we compare seven different elevation products in a lowlying area in western Alaska to establish their appropriateness for coastal mapping applications that require the delineation of elevation-based vectors. We further investigate the effective use of a Structure from Motion (SfM)-derived surface model (vertical RMSE<20 cm) by generating a tidal datum-based shoreline and an inundation extent map for a 2011 flood event. Our results suggest that SfM-derived elevation products can yield elevation-based vector features that have horizontal positional uncertainties comparable to those derived from other techniques. We also provide a rule-of-thumb equation to aid in the selection of minimum elevation model specifications based on terrain slope, vertical uncertainties, and desired horizontal accuracy.

Extending the Fellegi-Sunter probabilistic record linkage method for approximate field comparators.

PubMed

DuVall, Scott L; Kerber, Richard A; Thomas, Alun

2010-02-01

Probabilistic record linkage is a method commonly used to determine whether demographic records refer to the same person. The Fellegi-Sunter method is a probabilistic approach that uses field weights based on log likelihood ratios to determine record similarity. This paper introduces an extension of the Fellegi-Sunter method that incorporates approximate field comparators in the calculation of field weights. The data warehouse of a large academic medical center was used as a case study. The approximate comparator extension was compared with the Fellegi-Sunter method in its ability to find duplicate records previously identified in the data warehouse using different demographic fields and matching cutoffs. The approximate comparator extension misclassified 25% fewer pairs and had a larger Welch's T statistic than the Fellegi-Sunter method for all field sets and matching cutoffs. The accuracy gain provided by the approximate comparator extension grew as less information was provided and as the matching cutoff increased. Given the ubiquity of linkage in both clinical and research settings, the incremental improvement of the extension has the potential to make a considerable impact.

Evaluation of Spatially Targeted Strategies to Control Non-Domiciliated Triatoma dimidiata Vector of Chagas Disease

PubMed Central

Barbu, Corentin; Dumonteil, Eric; Gourbière, Sébastien

2011-01-01

Background Chagas disease is a major neglected tropical disease with deep socio-economical effects throughout Central and South America. Vector control programs have consistently reduced domestic populations of triatomine vectors, but non-domiciliated vectors still have to be controlled efficiently. Designing control strategies targeting these vectors is challenging, as it requires a quantitative description of the spatio-temporal dynamics of village infestation, which can only be gained from combinations of extensive field studies and spatial population dynamic modelling. Methodology/Principal Findings A spatially explicit population dynamic model was combined with a two-year field study of T. dimidiata infestation dynamics in the village of Teya, Mexico. The parameterized model fitted and predicted accurately both intra-annual variation and the spatial gradient in vector abundance. Five different control strategies were then applied in concentric rings to mimic spatial design targeting the periphery of the village, where vectors were most abundant. Indoor insecticide spraying and insect screens reduced vector abundance by up to 80% (when applied to the whole village), and half of this effect was obtained when control was applied only to the 33% of households closest to the village periphery. Peri-domicile cleaning was able to eliminate up to 60% of the vectors, but at the periphery of the village it has a low effect, as it is ineffective against sylvatic insects. The use of lethal traps and the management of house attractiveness provided similar levels of control. However this required either house attractiveness to be null, or ≥5 lethal traps, at least as attractive as houses, to be installed in each household. Conclusion/Significance Insecticide and insect screens used in houses at the periphery of the village can contribute to reduce house infestation in more central untreated zones. However, this beneficial effect remains insufficient to allow for a unique spatially targeted strategy to offer protection to all households. Most efficiently, control should combine the use of insect screens in outer zones to reduce infestation by both sylvatic and peri-domiciliated vectors, and cleaning of peri-domicile in the centre of the village where sylvatic vectors are absent. The design of such spatially mixed strategies of control offers a promising avenue to reduce the economic cost associated with the control of non-domiciliated vectors. PMID:21610862

Postnatal Weight Gain Modifies Severity and Functional Outcome of Oxygen-Induced Proliferative Retinopathy

PubMed Central

Stahl, Andreas; Chen, Jing; Sapieha, Przemyslaw; Seaward, Molly R.; Krah, Nathan M.; Dennison, Roberta J.; Favazza, Tara; Bucher, Felicitas; Löfqvist, Chatarina; Ong, Huy; Hellström, Ann; Chemtob, Sylvain; Akula, James D.; Smith, Lois E.H.

2010-01-01

In clinical studies, postnatal weight gain is strongly associated with retinopathy of prematurity (ROP). However, animal studies are needed to investigate the pathophysiological mechanisms of how postnatal weight gain affects the severity of ROP. In the present study, we identify nutritional supply as one potent parameter that affects the extent of retinopathy in mice with identical birth weights and the same genetic background. Wild-type pups with poor postnatal nutrition and poor weight gain (PWG) exhibit a remarkably prolonged phase of retinopathy compared to medium weight gain or extensive weight gain pups. A high (r2 = 0.83) parabolic association between postnatal weight gain and oxygen-induced retinopathy severity is observed, as is a significantly prolonged phase of proliferative retinopathy in PWG pups (20 days) compared with extensive weight gain pups (6 days). The extended retinopathy is concomitant with prolonged overexpression of retinal vascular endothelial growth factor in PWG pups. Importantly, PWG pups show low serum levels of nonfasting glucose, insulin, and insulin-like growth factor-1 as well as high levels of ghrelin in the early postoxygen-induced retinopathy phase, a combination indicative of poor metabolic supply. These differences translate into visual deficits in adult PWG mice, as demonstrated by impaired bipolar and proximal neuronal function. Together, these results provide evidence for a pathophysiological correlation between poor postnatal nutritional supply, slow weight gain, prolonged retinal vascular endothelial growth factor overexpression, protracted retinopathy, and reduced final visual outcome. PMID:21056995

Postnatal weight gain modifies severity and functional outcome of oxygen-induced proliferative retinopathy.

PubMed

Stahl, Andreas; Chen, Jing; Sapieha, Przemyslaw; Seaward, Molly R; Krah, Nathan M; Dennison, Roberta J; Favazza, Tara; Bucher, Felicitas; Löfqvist, Chatarina; Ong, Huy; Hellström, Ann; Chemtob, Sylvain; Akula, James D; Smith, Lois E H

2010-12-01

In clinical studies, postnatal weight gain is strongly associated with retinopathy of prematurity (ROP). However, animal studies are needed to investigate the pathophysiological mechanisms of how postnatal weight gain affects the severity of ROP. In the present study, we identify nutritional supply as one potent parameter that affects the extent of retinopathy in mice with identical birth weights and the same genetic background. Wild-type pups with poor postnatal nutrition and poor weight gain (PWG) exhibit a remarkably prolonged phase of retinopathy compared to medium weight gain or extensive weight gain pups. A high (r(2) = 0.83) parabolic association between postnatal weight gain and oxygen-induced retinopathy severity is observed, as is a significantly prolonged phase of proliferative retinopathy in PWG pups (20 days) compared with extensive weight gain pups (6 days). The extended retinopathy is concomitant with prolonged overexpression of retinal vascular endothelial growth factor in PWG pups. Importantly, PWG pups show low serum levels of nonfasting glucose, insulin, and insulin-like growth factor-1 as well as high levels of ghrelin in the early postoxygen-induced retinopathy phase, a combination indicative of poor metabolic supply. These differences translate into visual deficits in adult PWG mice, as demonstrated by impaired bipolar and proximal neuronal function. Together, these results provide evidence for a pathophysiological correlation between poor postnatal nutritional supply, slow weight gain, prolonged retinal vascular endothelial growth factor overexpression, protracted retinopathy, and reduced final visual outcome.

Automatic Cataloguing and Searching for Retrospective Data by Use of OCR Text.

ERIC Educational Resources Information Center

Tseng, Yuen-Hsien

2001-01-01

Describes efforts in supporting information retrieval from OCR (optical character recognition) degraded text. Reports on approaches used in an automatic cataloging and searching contest for books in multiple languages, including a vector space retrieval model, an n-gram indexing method, and a weighting scheme; and discusses problems of Asian…

Markov random field model-based edge-directed image interpolation.

PubMed

Li, Min; Nguyen, Truong Q

2008-07-01

This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.

MONSS: A multi-objective nonlinear simplex search approach

NASA Astrophysics Data System (ADS)

Zapotecas-Martínez, Saúl; Coello Coello, Carlos A.

2016-01-01

This article presents a novel methodology for dealing with continuous box-constrained multi-objective optimization problems (MOPs). The proposed algorithm adopts a nonlinear simplex search scheme in order to obtain multiple elements of the Pareto optimal set. The search is directed by a well-distributed set of weight vectors, each of which defines a scalarization problem that is solved by deforming a simplex according to the movements described by Nelder and Mead's method. Considering an MOP with n decision variables, the simplex is constructed using n+1 solutions which minimize different scalarization problems defined by n+1 neighbor weight vectors. All solutions found in the search are used to update a set of solutions considered to be the minima for each separate problem. In this way, the proposed algorithm collectively obtains multiple trade-offs among the different conflicting objectives, while maintaining a proper representation of the Pareto optimal front. In this article, it is shown that a well-designed strategy using just mathematical programming techniques can be competitive with respect to the state-of-the-art multi-objective evolutionary algorithms against which it was compared.

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

PubMed

Cohen, Aaron M

2008-01-01

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

Non-specific Patterns of Vector, Host, and Avian Malaria Parasite Associations in a Central African Rainforest

PubMed Central

Njabo, Kevin Y; Cornel, Anthony J.; Bonneaud, Camille; Toffelmier, Erin; Sehgal, R.N.M.; Valkiūnas, Gediminas; Russell, Andrew F.; Smith, Thomas B.

2010-01-01

Malaria parasites use vertebrate hosts for asexual multiplication and Culicidae mosquitoes for sexual and asexual development, yet the literature on avian malaria remains biased towards examining the asexual stages of the life cycle in birds. To fully understand parasite evolution and mechanism of malaria transmission, knowledge of all three components of the vector-host-parasite system is essential. Little is known about avian parasite-vector associations in African rainforests where numerous species of birds are infected with avian haemosporidians of the genera Plasmodium and Haemoproteus. Here we applied high resolution melt qPCR-based techniques and nested PCR to examine the occurrence and diversity of mitochondrial cytochrome b gene sequences of haemosporidian parasites in wild-caught mosquitoes sampled across 12 sites in Cameroon. In all, 3134 mosquitoes representing 27 species were screened. Mosquitoes belonging to four genera (Aedes, Coquillettidia, Culex, and Mansonia) were infected with twenty-two parasite lineages (18 Plasmodium spp. and 4 Haemoproteus spp.). Presence of Plasmodium sporozoites in salivary glands of Coquillettidia aurites further established these mosquitoes as likely vectors. Occurrence of parasite lineages differed significantly among genera, as well as their probability of being infected with malaria across species and sites. Approximately one-third of these lineages were previously detected in other avian host species from the region, indicating that vertebrate host sharing is a common feature and that avian Plasmodium spp. vector breadth does not always accompany vertebrate-host breadth. This study suggests extensive invertebrate host shifts in mosquito-parasite interactions and that avian Plasmodium species are most likely not tightly coevolved with vector species. PMID:21134011

Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population.

PubMed

Alimi, Temitope O; Fuller, Douglas O; Qualls, Whitney A; Herrera, Socrates V; Arevalo-Herrera, Myriam; Quinones, Martha L; Lacerda, Marcus V G; Beier, John C

2015-08-20

Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts. Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent. Results from our land change modeling indicate that about 70,000 km(2) of forest land would be lost by 2050 and 78,000 km(2) by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution. As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

A Comparison between the Use of Beta Weights and Structure Coefficients in Interpreting Regression Results

ERIC Educational Resources Information Center

Tong, Fuhui

2006-01-01

Background: An extensive body of researches has favored the use of regression over other parametric analyses that are based on OVA. In case of noteworthy regression results, researchers tend to explore magnitude of beta weights for the respective predictors. Purpose: The purpose of this paper is to examine both beta weights and structure…

Weight-Control Practices Reported by Students in a Maine Middle School

ERIC Educational Resources Information Center

Majka, Alan

2011-01-01

Extension professionals who work with youth are often faced with issues of body weight, diet and/or body image. How we handle these topics has the potential to either help or harm. The goal of the study reported here was to explore the prevalence and types of weight-control methods practiced by middle school students. The majority of students…

75 FR 61815 - Agency Information Collection Activities: Notice of Request for Extension of Currently Approved...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-06

... Street, NW., Washington, DC 20503, Attention DOT Desk Officer. You are asked to comment on any aspect of... Vehicle Size and Weight Laws. OMB Control Number: 2125-0034. Background: Title 23, U.S.C., section 141... enforcing their size and weight laws on Federal-aid highways and that their Interstate System weight limits...

Maximum acceptable weight of lift reflects peak lumbosacral extension moments in a functional capacity evaluation test using free style, stoop and squat lifting.

PubMed

Kuijer, P P F M; van Oostrom, S H; Duijzer, K; van Dieën, J H

2012-01-01

It is unclear whether the maximum acceptable weight of lift (MAWL), a common psychophysical method, reflects joint kinetics when different lifting techniques are employed. In a within-participants study (n = 12), participants performed three lifting techniques--free style, stoop and squat lifting from knee to waist level--using the same dynamic functional capacity evaluation lifting test to assess MAWL and to calculate low back and knee kinetics. We assessed which knee and back kinetic parameters increased with the load mass lifted, and whether the magnitudes of the kinetic parameters were consistent across techniques when lifting MAWL. MAWL was significantly different between techniques (p = 0.03). The peak lumbosacral extension moment met both criteria: it had the highest association with the load masses lifted (r > 0.9) and was most consistent between the three techniques when lifting MAWL (ICC = 0.87). In conclusion, MAWL reflects the lumbosacral extension moment across free style, stoop and squat lifting in healthy young males, but the relation between the load mass lifted and lumbosacral extension moment is different between techniques. Tests of maximum acceptable weight of lift (MAWL) from knee to waist height are used to assess work capacity of individuals with low-back disorders. This article shows that the MAWL reflects the lumbosacral extension moment across free style, stoop and squat lifting in healthy young males, but the relation between the load mass lifted and lumbosacral extension moment is different between techniques. This suggests that standardisation of lifting technique used in tests of the MAWL would be indicated if the aim is to assess the capacity of the low back.

Revalidation of the Score for Neonatal Acute Physiology in the Vermont Oxford Network.

PubMed

Zupancic, John A F; Richardson, Douglas K; Horbar, Jeffrey D; Carpenter, Joseph H; Lee, Shoo K; Escobar, Gabriel J

2007-01-01

Our specific objectives were (1) to document the performance of the revised Score for Neonatal Acute Physiology and the revised Score for Neonatal Acute Physiology Perinatal Extension in predicting death in the Vermont Oxford Network, compared with published normative values; (2) to determine whether this performance could be improved through recalibration of the weights for individual score items; (3) to determine the impact of including congenital anomalies in the predictive model; and (4) to compare performance against that of the Vermont Oxford Network risk adjustment, separately and in combination. Fifty-eight Vermont Oxford Network centers collected data prospectively for the revised Score for Neonatal Acute Physiology in the first 12 hours after admission of infants in 2002. Data were collected for 10,469 infants, and analyses were undertaken for 9897 who met inclusion criteria. The median revised Score for Neonatal Acute Physiology was 5, and the mean birth weight was 1951 g. Recalibration of the revised Score for Neonatal Acute Physiology and revised Score for Neonatal Acute Physiology Perinatal Extension resulted in minimal changes in their discriminatory abilities. The Vermont Oxford Network risk adjustment performed similarly, compared with the revised Score for Neonatal Acute Physiology Perinatal Extension. Current score performance was similar to that observed previously, which suggests that the revised Score for Neonatal Acute Physiology and revised Score for Neonatal Acute Physiology Perinatal Extension have not decalibrated over the 7 years since the first cohort was assembled, despite advances in neonatal care during that period. Addition of congenital anomalies to the revised Score for Neonatal Acute Physiology Perinatal Extension improved discrimination significantly, particularly for infants with birth weights of >1500 g. The Vermont Oxford Network risk adjustment performed similarly, compared with the revised Score for Neonatal Acute Physiology Perinatal Extension.

New Typical Vector of Neurotoxin β-N-Methylamino-l-Alanine (BMAA) in the Marine Benthic Ecosystem.

PubMed

Li, Aifeng; Song, Jialiang; Hu, Yang; Deng, Longji; Ding, Ling; Li, Meihui

2016-11-04

The neurotoxin β- N -methylamino-l-alanine (BMAA) has been identified as an environmental factor triggering neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS) and Alzheimer's disease (AD). We investigated the possible vectors of BMAA and its isomers 2,4-diaminobutyric acid (DAB) and N -2(aminoethyl)glycine (AEG) in marine mollusks collected from the Chinese coast. Sixty-eight samples of marine mollusks were collected along the Chinese coast in 2016, and were analyzed by an HILIC-MS/MS (hydrophilic interaction liquid chromatography with tandem quadrupole mass spectrometer) method without derivatization. BMAA was detected in a total of five samples from three species: Neverita didyma , Solen strictus , and Mytilus coruscus . The top three concentrations of free-form BMAA (0.99~3.97 μg·g -1 wet weight) were detected in N. didyma . DAB was universally detected in most of the mollusk samples (53/68) with no species-specific or regional differences (0.051~2.65 μg·g -1 wet weight). No AEG was detected in any mollusk samples tested here. The results indicate that the gastropod N. didyma might be an important vector of the neurotoxin BMAA in the Chinese marine ecosystem. The neurotoxin DAB was universally present in marine bivalve and gastropod mollusks. Since N. didyma is consumed by humans, we suggest that the origin and risk of BMAA and DAB toxins in the marine ecosystem should be further investigated in the future.

Behaviour and molecular identification of Anopheles malaria vectors in Jayapura district, Papua province, Indonesia.

PubMed

St Laurent, Brandy; Supratman, Sukowati; Asih, Puji Budi Setia; Bretz, David; Mueller, John; Miller, Helen Catherine; Baharuddin, Amirullah; Shinta; Surya, Asik; Ngai, Michelle; Laihad, Ferdinand; Syafruddin, Din; Hawley, William A; Collins, Frank H; Lobo, Neil F

2016-04-08

Members of the Anopheles punctulatus group dominate Papua, Indonesia and Papua New Guinea (PNG), with a geographic range that extends south through Vanuatu. An. farauti and An. punctulatus are the presumed major vectors in this region. Although this group of species has been extensively studied in PNG and the southern archipelagoes within their range, their distribution, ecology and vector behaviours have not been well characterized in eastern Indonesia. Mosquitoes were collected in five villages in Jayapura province, Papua, Indonesia using human-landing collections, animal-baited tents and backpack aspirators. Mosquitoes were morphologically typed and then molecularly distinguished based on ribosomal ITS2 sequences and tested for Plasmodium falciparum and P. vivax infection using circumsporozoite ELISA and PCR. The presence and vector status of An. farauti 4 in Papua, Indonesia is confirmed here for the first time. The data indicate that this species is entering houses at a rate that increases its potential to come into contact with humans and act as a major malaria vector. An. farauti 4 was also abundant outdoors and biting humans during early evening hours. Other species collected in this area include An. farauti 1, An. hinesorum, An. koliensis, An. punctulatus, and An. tessellatus. Proboscis morphology was highly variable within each species, lending support to the notion that this characteristic is not a reliable indicator to distinguish species within the An. punctulatus group. The vector composition in Papua, Indonesia is consistent with certain northern areas of PNG, but the behaviours of anophelines sampled in this region, such as early and indoor human biting of An. farauti 4, may enable them to act as major vectors of malaria. Presumed major vectors An. farauti and An. punctulatus were not abundant among these samples. Morphological identification of anophelines in this sample was often inaccurate, highlighting the importance of using molecular analysis in conjunction with morphological investigations to update keys and training tools.

COHERENT constraints to conventional and exotic neutrino physics

NASA Astrophysics Data System (ADS)

Papoulias, D. K.; Kosmas, T. S.

2018-02-01

The process of neutral-current coherent elastic neutrino-nucleus scattering, consistent with the Standard Model (SM) expectation, has been recently measured by the COHERENT experiment at the Spallation Neutron Source. On the basis of the observed signal and our nuclear calculations for the relevant Cs and I isotopes, the extracted constraints on both conventional and exotic neutrino physics are updated. The present study concentrates on various SM extensions involving vector and tensor nonstandard interactions as well as neutrino electromagnetic properties, with an emphasis on the neutrino magnetic moment and the neutrino charge radius. Furthermore, models addressing a light sterile neutrino state and scenarios with new propagator fields—such as vector Z' and scalar bosons—are examined, and the corresponding regions excluded by the COHERENT experiment are presented.

Sorted Index Numbers for Privacy Preserving Face Recognition

NASA Astrophysics Data System (ADS)

Wang, Yongjin; Hatzinakos, Dimitrios

2009-12-01

This paper presents a novel approach for changeable and privacy preserving face recognition. We first introduce a new method of biometric matching using the sorted index numbers (SINs) of feature vectors. Since it is impossible to recover any of the exact values of the original features, the transformation from original features to the SIN vectors is noninvertible. To address the irrevocable nature of biometric signals whilst obtaining stronger privacy protection, a random projection-based method is employed in conjunction with the SIN approach to generate changeable and privacy preserving biometric templates. The effectiveness of the proposed method is demonstrated on a large generic data set, which contains images from several well-known face databases. Extensive experimentation shows that the proposed solution may improve the recognition accuracy.

Vector wind profile gust model

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1981-01-01

To enable development of a vector wind gust model suitable for orbital flight test operations and trade studies, hypotheses concerning the distributions of gust component variables were verified. Methods for verification of hypotheses that observed gust variables, including gust component magnitude, gust length, u range, and L range, are gamma distributed and presented. Observed gust modulus has been drawn from a bivariate gamma distribution that can be approximated with a Weibull distribution. Zonal and meridional gust components are bivariate gamma distributed. An analytical method for testing for bivariate gamma distributed variables is presented. Two distributions for gust modulus are described and the results of extensive hypothesis testing of one of the distributions are presented. The validity of the gamma distribution for representation of gust component variables is established.

Vector wind profile gust model

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1979-01-01

Work towards establishing a vector wind profile gust model for the Space Transportation System flight operations and trade studies is reported. To date, all the statistical and computational techniques required were established and partially implemented. An analysis of wind profile gust at Cape Kennedy within the theoretical framework is presented. The variability of theoretical and observed gust magnitude with filter type, altitude, and season is described. Various examples are presented which illustrate agreement between theoretical and observed gust percentiles. The preliminary analysis of the gust data indicates a strong variability with altitude, season, and wavelength regime. An extension of the analyses to include conditional distributions of gust magnitude given gust length, distributions of gust modulus, and phase differences between gust components has begun.

Targeted Gene Knock Out Using Nuclease-Assisted Vector Integration: Hemi- and Homozygous Deletion of JAG1.

PubMed

Gapinske, Michael; Tague, Nathan; Winter, Jackson; Underhill, Gregory H; Perez-Pinera, Pablo

2018-01-01

Gene editing technologies are revolutionizing fields such as biomedicine and biotechnology by providing a simple means to manipulate the genetic makeup of essentially any organism. Gene editing tools function by introducing double-stranded breaks at targeted sites within the genome, which the host cells repair preferentially by Non-Homologous End Joining. While the technologies to introduce double-stranded breaks have been extensively optimized, this progress has not been matched by the development of methods to integrate heterologous DNA at the target sites or techniques to detect and isolate cells that harbor the desired modification. We present here a technique for rapid introduction of vectors at target sites in the genome that enables efficient isolation of successfully edited cells.

DDML Schema Validation

DTIC Science & Technology

2016-02-08

Data Display Markup Language HUD heads-up display IRIG Inter-Range Instrumentation Group RCC Range Commanders Council SVG Scalable Vector Graphics...T&E test and evaluation TMATS Telemetry Attributes Transfer Standard XML eXtensible Markup Language DDML Schema Validation, RCC 126-16, February...2016 viii This page intentionally left blank. DDML Schema Validation, RCC 126-16, February 2016 1 1. Introduction This Data Display Markup

Scalability, Complexity and Reliability in Quantum Information Processing

DTIC Science & Technology

2007-03-01

hidden subgroup framework to abelian groups which are not finitely generated. An extension of the basic algorithm breaks the Buchmann-Williams...finding short lattice vectors . In [2], we showed that the generalization of the standard method --- random coset state preparation followed by fourier...sampling --- required exponential time for sufficiently non-abelian groups including the symmetric group , at least when the fourier transforms are

Eigenenergies of a Relativistic Particle in an Infinite Range Linear Potential Using WKB Method

ERIC Educational Resources Information Center

Shivalingaswamy, T.; Kagali, B. A.

2011-01-01

Energy eigenvalues for a non-relativistic particle in a linear potential well are available. In this paper we obtain the eigenenergies for a relativistic spin less particle in a similar potential using an extension of the well-known WKB method treating the potential as the time component of a four-vector potential. Since genuine bound states do…

Derivation of improved load transformation matrices for launchers-spacecraft coupled analysis, and direct computation of margins of safety

NASA Technical Reports Server (NTRS)

Klein, M.; Reynolds, J.; Ricks, E.

1989-01-01

Load and stress recovery from transient dynamic studies are improved upon using an extended acceleration vector in the modal acceleration technique applied to structural analysis. Extension of the normal LTM (load transformation matrices) stress recovery to automatically compute margins of safety is presented with an application to the Hubble space telescope.

Good Practices for Learning to Recognize Actions Using FV and VLAD.

PubMed

Wu, Jianxin; Zhang, Yu; Lin, Weiyao

2016-12-01

High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.

N -loop running should be combined with N -loop matching

NASA Astrophysics Data System (ADS)

Braathen, Johannes; Goodsell, Mark D.; Krauss, Manuel E.; Opferkuch, Toby; Staub, Florian

2018-01-01

We investigate the high-scale behavior of Higgs sectors beyond the Standard Model, pointing out that the proper matching of the quartic couplings before applying the renormalization group equations (RGEs) is of crucial importance for reliable predictions at larger energy scales. In particular, the common practice of leading-order parameters in the RGE evolution is insufficient to make precise statements on a given model's UV behavior, typically resulting in uncertainties of many orders of magnitude. We argue that, before applying N -loop RGEs, a matching should even be performed at N -loop order in contrast to common lore. We show both analytical and numerical results where the impact is sizable for three minimal extensions of the Standard Model: a singlet extension, a second Higgs doublet and finally vector-like quarks. We highlight that the known two-loop RGEs tend to moderate the running of their one-loop counterparts, typically delaying the appearance of Landau poles. For the addition of vector-like quarks we show that the complete two-loop matching and RGE evolution hints at a stabilization of the electroweak vacuum at high energies, in contrast to results in the literature.

Molecular Therapy of Melanocortin-4-Receptor Obesity by an Autoregulatory BDNF Vector.

PubMed

Siu, Jason J; Queen, Nicholas J; Liu, Xianglan; Huang, Wei; McMurphy, Travis; Cao, Lei

2017-12-15

Mutations in the melanocortin-4-receptor ( MC4R ) comprise the most common monogenic form of severe early-onset obesity, and conventional treatments are either ineffective long-term or contraindicated. Immediately downstream of MC4R-in the pathway for regulating energy balance-is brain-derived neurotrophic factor (BDNF). Our previous studies show that adeno-associated virus (AAV)-mediated hypothalamic BDNF gene transfer alleviates obesity and diabetes in both diet-induced and genetic models. To facilitate clinical translation, we developed a built-in autoregulatory system to control therapeutic gene expression mimicking the body's natural feedback systems. This autoregulatory approach leads to a sustainable plateau of body weight after substantial weight loss is achieved. Here, we examined the efficacy and safety of autoregulatory BDNF gene therapy in Mc4r heterozygous mice, which best resemble MC4R obese patients. Mc4r heterozygous mice were treated with either autoregulatory BDNF vector or YFP control and monitored for 30 weeks. BDNF gene therapy prevented the development of obesity and metabolic syndromes characterized by decreasing body weight and adiposity, suppressing food intake, alleviating hyperleptinemia and hyperinsulinemia, improving glucose and insulin tolerance, and increasing energy expenditure, without adverse cardiovascular function or behavioral disturbances. These safety and efficacy data provide preclinical evidence that BDNF gene therapy is a compelling treatment option for MC4R -deficient obese patients.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

Regularity gradient estimates for weak solutions of singular quasi-linear parabolic equations

NASA Astrophysics Data System (ADS)

Phan, Tuoc

2017-12-01

This paper studies the Sobolev regularity for weak solutions of a class of singular quasi-linear parabolic problems of the form ut -div [ A (x , t , u , ∇u) ] =div [ F ] with homogeneous Dirichlet boundary conditions over bounded spatial domains. Our main focus is on the case that the vector coefficients A are discontinuous and singular in (x , t)-variables, and dependent on the solution u. Global and interior weighted W 1 , p (ΩT , ω)-regularity estimates are established for weak solutions of these equations, where ω is a weight function in some Muckenhoupt class of weights. The results obtained are even new for linear equations, and for ω = 1, because of the singularity of the coefficients in (x , t)-variables.

A Meinardus Theorem with Multiple Singularities

NASA Astrophysics Data System (ADS)

Granovsky, Boris L.; Stark, Dudley

2012-09-01

Meinardus proved a general theorem about the asymptotics of the number of weighted partitions, when the Dirichlet generating function for weights has a single pole on the positive real axis. Continuing (Granovsky et al., Adv. Appl. Math. 41:307-328, 2008), we derive asymptotics for the numbers of three basic types of decomposable combinatorial structures (or, equivalently, ideal gas models in statistical mechanics) of size n, when their Dirichlet generating functions have multiple simple poles on the positive real axis. Examples to which our theorem applies include ones related to vector partitions and quantum field theory. Our asymptotic formula for the number of weighted partitions disproves the belief accepted in the physics literature that the main term in the asymptotics is determined by the rightmost pole.

Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media

USGS Publications Warehouse

Cooley, R.L.; Christensen, S.

2006-01-01

Groundwater models need to account for detailed but generally unknown spatial variability (heterogeneity) of the hydrogeologic model inputs. To address this problem we replace the large, m-dimensional stochastic vector ?? that reflects both small and large scales of heterogeneity in the inputs by a lumped or smoothed m-dimensional approximation ????*, where ?? is an interpolation matrix and ??* is a stochastic vector of parameters. Vector ??* has small enough dimension to allow its estimation with the available data. The consequence of the replacement is that model function f(????*) written in terms of the approximate inputs is in error with respect to the same model function written in terms of ??, ??,f(??), which is assumed to be nearly exact. The difference f(??) - f(????*), termed model error, is spatially correlated, generates prediction biases, and causes standard confidence and prediction intervals to be too small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate ??* and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear regression methods are extended to analyze the revised method. The analysis develops analytical expressions for bias terms reflecting the interaction of model nonlinearity and model error, for correction factors needed to adjust the sizes of confidence and prediction intervals for this interaction, and for correction factors needed to adjust the sizes of confidence and prediction intervals for possible use of a diagonal weight matrix in place of the correct one. If terms expressing the degree of intrinsic nonlinearity for f(??) and f(????*) are small, then most of the biases are small and the correction factors are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis. ?? 2005 Elsevier Ltd. All rights reserved.

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.

PubMed

Xu, Jingting; Hu, Hong; Dai, Yang

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

Computation of repetitions and regularities of biologically weighted sequences.

PubMed

Christodoulakis, M; Iliopoulos, C; Mouchard, L; Perdikuri, K; Tsakalidis, A; Tsichlas, K

2006-01-01

Biological weighted sequences are used extensively in molecular biology as profiles for protein families, in the representation of binding sites and often for the representation of sequences produced by a shotgun sequencing strategy. In this paper, we address three fundamental problems in the area of biologically weighted sequences: (i) computation of repetitions, (ii) pattern matching, and (iii) computation of regularities. Our algorithms can be used as basic building blocks for more sophisticated algorithms applied on weighted sequences.

On estimating gravity anomalies: A comparison of least squares collocation with least squares techniques

NASA Technical Reports Server (NTRS)

Argentiero, P.; Lowrey, B.

1976-01-01

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described, and its numerical properties are compared with the numerical properties of the conventional least squares estimator.

Guiding automated left ventricular chamber segmentation in cardiac imaging using the concept of conserved myocardial volume.

PubMed

Garson, Christopher D; Li, Bing; Acton, Scott T; Hossack, John A

2008-06-01

The active surface technique using gradient vector flow allows semi-automated segmentation of ventricular borders. The accuracy of the algorithm depends on the optimal selection of several key parameters. We investigated the use of conservation of myocardial volume for quantitative assessment of each of these parameters using synthetic and in vivo data. We predicted that for a given set of model parameters, strong conservation of volume would correlate with accurate segmentation. The metric was most useful when applied to the gradient vector field weighting and temporal step-size parameters, but less effective in guiding an optimal choice of the active surface tension and rigidity parameters.

Matching weights to simultaneously compare three treatment groups: Comparison to three-way matching

PubMed Central

Yoshida, Kazuki; Hernández-Díaz, Sonia; Solomon, Daniel H.; Jackson, John W.; Gagne, Joshua J.; Glynn, Robert J.; Franklin, Jessica M.

2017-01-01

BACKGROUND Propensity score matching is a commonly used tool. However, its use in settings with more than two treatment groups has been less frequent. We examined the performance of a recently developed propensity score weighting method in the three treatment group setting. METHODS The matching weight method is an extension of inverse probability of treatment weighting (IPTW) that reweights both exposed and unexposed groups to emulate a propensity score matched population. Matching weights can generalize to multiple treatment groups. The performance of matching weights in the three-group setting was compared via simulation to three-way 1:1:1 propensity score matching and IPTW. We also applied these methods to an empirical example that compared the safety of three analgesics. RESULTS Matching weights had similar bias, but better mean squared error (MSE) compared to three-way matching in all scenarios. The benefits were more pronounced in scenarios with a rare outcome, unequally sized treatment groups, or poor covariate overlap. IPTW’s performance was highly dependent on covariate overlap. In the empirical example, matching weights achieved the best balance for 24 out of 35 covariates. Hazard ratios were numerically similar to matching. However, the confidence intervals were narrower for matching weights. CONCLUSIONS Matching weights demonstrated improved performance over three-way matching in terms of MSE, particularly in simulation scenarios where finding matched subjects was difficult. Given its natural extension to settings with even more than three groups, we recommend matching weights for comparing outcomes across multiple treatment groups, particularly in settings with rare outcomes or unequal exposure distributions. PMID:28151746

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.

[Effect of extensively hydrolyzed formula on growth and development of infants with very/extremely low birth weight].

PubMed

Gu, Chun-Yan; Jiang, Hui-Fen; Wang, Jin-Xiu

2017-08-01

To study the effect of extensively hydrolyzed formula on the growth and development in very low birth weight (VLBW) and extremely low birth weight (ELBW) infants. A total of 375 VLBW or ELBW infants were enrolled and divided into an observation group (187 infants) and a control group (188 infants) using a random number table. The infants in the observation group were given extensively hydrolyzed formula, and when the amount of extensively hydrolyzed formula reached 10 mL/time, it was changed to the standard formula for preterm infants. The infants in the control group were given standard formula for preterm infants. Both groups were fed for 4 consecutive weeks and were compared in terms of incidence rate of feeding intolerance, time to establish full enteral feeding, time to complete meconium excretion, number of spontaneous bowel movements, growth and development, motilin level at 4 and 10 days after feeding, and incidence rate of infection. Compared with the control group, the observation group had a lower rate of feeding intolerance (P<0.05), a shorter duration to full enteral feeding and time to complete meconium excretion (P<0.05), a higher mean number of daily spontaneous bowel movements (P<0.05), higher body weight (1 793±317 g vs 1 621±138 g; P<0.05), head circumference (30.5±1.1 cm vs 30.0±1.6 cm; P<0.05), and body length (43.9±1.2 cm vs 42.1±2.0 cm; P<0.05), a higher motilin level at 4 and 10 days after feeding (P<0.05), and a significantly lower infection rate (P<0.05). Extensively hydrolyzed formula can increase motilin level, improve gastrointestinal feeding tolerance, promote early growth and development, and reduce the incidence of infection in VLBW and ELBW infants.

CR extension from hypersurfaces of higher type

NASA Astrophysics Data System (ADS)

Baracco, Luca

2007-07-01

We prove extension of CR functions from a hypersurface M of in presence of the so-called sector property. If M has finite type in the Bloom-Graham sense, then our result is already contained in [C. Rea, Prolongement holomorphe des fonctions CR, conditions suffisantes, C. R. Acad. Sci. Paris 297 (1983) 163-166] by Rea. We think however, that the argument of our proof carries an expressive geometric meaning and deserves interest on its own right. Also, our method applies in some case to hypersurfaces of infinite type; note that for these, the classical methods fail. CR extension is treated by many authors mainly in two frames: extension in directions of iterated of commutators of CR vector fields (cf., for instance, [A. Boggess, J. Pitts, CR extension near a point of higher type, Duke Math. J. 52 (1) (1985) 67-102; A. Boggess, J.C. Polking, Holomorphic extension of CR functions, Duke Math. J. 49 (1982) 757-784. ; M.S. Baouendi, L. Rothschild, Normal forms for generic manifolds and holomorphic extension of CR functions, J. Differential Geom. 25 (1987) 431-467. ]); extension through minimality towards unprecised directions [A.E. Tumanov, Extension of CR-functions into a wedge, Mat. Sb. 181 (7) (1990) 951-964. ; A.E. Tumanov, Analytic discs and the extendibility of CR functions, in: Integral Geometry, Radon Transforms and Complex Analysis, Venice, 1996, in: Lecture Notes in Math., vol. 1684, Springer, Berlin, 1998, pp. 123-141].

Lightweight High Efficiency Electric Motors for Space Applications

NASA Technical Reports Server (NTRS)

Robertson, Glen A.; Tyler, Tony R.; Piper, P. J.

2011-01-01

Lightweight high efficiency electric motors are needed across a wide range of space applications from - thrust vector actuator control for launch and flight applications to - general vehicle, base camp habitat and experiment control for various mechanisms to - robotics for various stationary and mobile space exploration missions. QM Power?s Parallel Path Magnetic Technology Motors have slowly proven themselves to be a leading motor technology in this area; winning a NASA Phase II for "Lightweight High Efficiency Electric Motors and Actuators for Low Temperature Mobility and Robotics Applications" a US Army Phase II SBIR for "Improved Robot Actuator Motors for Medical Applications", an NSF Phase II SBIR for "Novel Low-Cost Electric Motors for Variable Speed Applications" and a DOE SBIR Phase I for "High Efficiency Commercial Refrigeration Motors" Parallel Path Magnetic Technology obtains the benefits of using permanent magnets while minimizing the historical trade-offs/limitations found in conventional permanent magnet designs. The resulting devices are smaller, lower weight, lower cost and have higher efficiency than competitive permanent magnet and non-permanent magnet designs. QM Power?s motors have been extensively tested and successfully validated by multiple commercial and aerospace customers and partners as Boeing Research and Technology. Prototypes have been made between 0.1 and 10 HP. They are also in the process of scaling motors to over 100kW with their development partners. In this paper, Parallel Path Magnetic Technology Motors will be discussed; specifically addressing their higher efficiency, higher power density, lighter weight, smaller physical size, higher low end torque, wider power zone, cooler temperatures, and greater reliability with lower cost and significant environment benefit for the same peak output power compared to typically motors. A further discussion on the inherent redundancy of these motors for space applications will be provided.

A pretargeting system for tumor PET imaging and radioimmunotherapy

PubMed Central

Kraeber-Bodéré, Françoise; Rousseau, Caroline; Bodet-Milin, Caroline; Frampas, Eric; Faivre-Chauvet, Alain; Rauscher, Aurore; Sharkey, Robert M.; Goldenberg, David M.; Chatal, Jean-François; Barbet, Jacques

2015-01-01

Labeled antibodies, as well as their fragments and antibody-derived recombinant constructs, have long been proposed as general vectors to target radionuclides to tumor lesions for imaging and therapy. They have indeed shown promise in both imaging and therapeutic applications, but they have not fulfilled the original expectations of achieving sufficient image contrast for tumor detection or sufficient radiation dose delivered to tumors for therapy. Pretargeting was originally developed for tumor immunoscintigraphy. It was assumed that directly-radiolabled antibodies could be replaced by an unlabeled immunoconjugate capable of binding both a tumor-specific antigen and a small molecular weight molecule. The small molecular weight molecule would carry the radioactive payload and would be injected after the bispecific immunoconjugate. It has been demonstrated that this approach does allow for both antibody-specific recognition and fast clearance of the radioactive molecule, thus resulting in improved tumor-to-normal tissue contrast ratios. It was subsequently shown that pretargeting also held promise for tumor therapy, translating improved tumor-to-normal tissue contrast ratios into more specific delivery of absorbed radiation doses. Many technical approaches have been proposed to implement pretargeting, and two have been extensively documented. One is based on the avidin-biotin system, and the other on bispecific antibodies binding a tumor-specific antigen and a hapten. Both have been studied in preclinical models, as well as in several clinical studies, and have shown improved targeting efficiency. This article reviews the historical and recent preclinical and clinical advances in the use of bispecific-antibody-based pretargeting for radioimmunodetection and radioimmunotherapy of cancer. The results of recent evaluation of pretargeting in PET imaging also are discussed. PMID:25873896

Fine tangled pili expressed by Haemophilus ducreyi are a novel class of pili.

PubMed Central

Brentjens, R J; Ketterer, M; Apicella, M A; Spinola, S M

1996-01-01

Haemophilus ducreyi synthesizes fine, tangled pili composed predominantly of a protein whose apparent molecular weight is 24,000 (24K). A hybridoma, 2D8, produced a monoclonal antibody (MAb) that bound to a 24K protein in H. ducreyi strains isolated from diverse geographic locations. A lambda gt11 H. ducreyi library was screened with MAb 2D8. A 3.5-kb chromosomal insert from one reactive plaque was amplified and ligated into the pCRII vector. The recombinant plasmid, designated pHD24, expressed a 24K protein in Escherichia coli INV alpha F that bound MAb 2D8. The coding sequence of the 24K gene was localized by exonuclease III digestion. The insert contained a 570-bp open reading frame, designated ftpA (fine, tangled pili). Translation of ftpA predicted a polypeptide with a molecular weight of 21.1K. The predicted N-terminal amino acid sequence of the polypeptide encoded by ftpA was identical to the N-terminal amino acid sequence of purified pilin and lacked a cleavable signal sequence. Primer extension analysis of ftpA confirmed the lack of a leader peptide. The predicted amino acid sequence lacked homology to known pilin sequences but shared homology with the sequences of E. coli Dps and Treponema pallidum antigen TpF1 or 4D, proteins which associate to form ordered rings. An isogenic pilin mutant, H. ducreyi 35000ftpA::mTn3(Cm), was constructed by shuttle mutagenesis and did not contain pili when examined by electron microscopy. We conclude that H. ducreyi synthesizes fine, tangled pili that are composed of a unique major subunit, which may be exported by a signal sequence independent mechanism. PMID:8550517

Saturn Ring Mass and Zonal Gravitational Harmonics Estimate at the End of the Cassini "Grand Finale"

NASA Astrophysics Data System (ADS)

Brozovic, M.; Jacobson, R. A.; Roth, D. C.

2015-12-01

"Solstice" mission is the 7-year extension of the Cassini-Huygens spacecraft exploration of the Saturn system that will culminate with the "Grand Finale". Beginning in mid-2017, the spacecraft is scheduled to execute 22 orbits that have their periapses between the innermost D-ring and the upper layers of Saturn's atmosphere. These orbits will be perturbed by the gravitational field of Saturn as well as by the rings. We present an analysis of simulated "Grand Finale" radiometric data, and we investigate their sensitivity to the ring mass and higher zonal gravitational harmonics of the planet. We model the data quantity with respect to the available coverage of the tracking stations on Earth, and we account for the times when the spacecraft is occulted either by Saturn or the rings. We also use different data weights to simulate changes in the data quality. The dynamical model of the spacecraft motion includes both gravitational and non-gravitational forces, such as the daily momentum management due to Reaction Wheel Assembly and radioisotope thermo-electric generator accelerations. We solve the equations of motion and use a weighted-least squares fit to obtain spacecraft's state vector, mass(es) of the ring or the individual rings, zonal harmonics, and non-gravitational accelerations. We also investigate some a-priori values of the A- and B-ring masses from Tiscareno et al. (2007) and Hedman et al. (2015) analyses. The preliminary results suggest that the "Grand Finale" orbits should remain sensitive to the ring mass even for GMring<2 km3/s2 and that they will also provide high accuracy estimates of the zonal harmonics J8, J10, and J12.

Effect of mahlep on molecular weight distribution of cookie flour gluten proteins

USDA-ARS?s Scientific Manuscript database

Size Exclusion-High performance Chromatography (SE-HPLC) has been extensively used in molecular weight distribution analysis of wheat proteins. In this study the protein analysis was conducted on different cookie dough blends with different percentages of some ingredients. The mean chromatography ...

Robust inverse kinematics using damped least squares with dynamic weighting

NASA Technical Reports Server (NTRS)

Schinstock, D. E.; Faddis, T. N.; Greenway, R. B.

1994-01-01

This paper presents a general method for calculating the inverse kinematics with singularity and joint limit robustness for both redundant and non-redundant serial-link manipulators. Damped least squares inverse of the Jacobian is used with dynamic weighting matrices in approximating the solution. This reduces specific joint differential vectors. The algorithm gives an exact solution away from the singularities and joint limits, and an approximate solution at or near the singularities and/or joint limits. The procedure is here implemented for a six d.o.f. teleoperator and a well behaved slave manipulator resulted under teleoperational control.