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.

A Language-Independent Approach to Automatic Text Difficulty Assessment for Second-Language Learners

DTIC Science & Technology

2013-08-01

best-suited for regression. Our baseline uses z-normalized shallow length features and TF -LOG weighted vectors on bag-of-words for Arabic, Dari...length features and TF -LOG weighted vectors on bag-of-words for Arabic, Dari, English and Pashto. We compare Support Vector Machines and the Margin...football, whereas they are much less common in documents about opera). We used TF -LOG weighted word frequencies on bag-of-words for each document

Initial preclinical safety of non-replicating human endogenous retrovirus envelope protein-coated baculovirus vector-based vaccines against human papillomavirus.

PubMed

Han, Su-Eun; Kim, Mi-Gyeong; Lee, Soondong; Cho, Hee-Jeong; Byun, Youngro; Kim, Sujeong; Kim, Young Bong; Choi, Yongseok; Oh, Yu-Kyoung

2013-12-01

Human endogenous retrovirus (HERV) envelope protein-coated, baculovirus vector-based HPV 16 L1 (AcHERV-HPV16L1) is a non-replicating recombinant baculoviral vaccine. Here, we report an initial evaluation of the preclinical safety of AcHERV-HPV16L1 vaccine. In an acute toxicity study, a single administration of AcHERV-HPV16L1 DNA vaccine given intramuscularly (i.m.) to mice at a dose of 1 × 10(8) plaque-forming units (PFU) did not cause significant changes in body weight compared with vehicle-treated controls. It did cause a brief increase in the weights of some organs on day 15 post-treatment, but by day 30, all organ weights were not significantly different from those in the vehicle-treated control group. No hematological changes were observed on day 30 post-treatment. In a range-finding toxicity study with three doses of 1 × 10(7) , 2 × 10(7) and 5 × 10(7) PFU once daily for 5 days, the group treated with 5 × 10(7) PFU showed a transient decrease in the body weights from day 5 to day 15 post-treatment, but recovery to the levels similar to those in the vehicle-treated control group by post-treatment day 20. Organ weights were slightly higher for lymph nodes, spleen, thymus and liver after repeated dosing with 5 × 10(7) PFU on day 15, but had normalized by day 30. Moreover, repeated administration of AcHERV-HPV16L1 did not induce myosin-specific autoantibody in serum, and did not cause immune complex deposition or tissue damage at injection sites. Taken together, these results provide preliminary evidence of the preclinical safety of AcHERV-based HPV16L1 DNA vaccines in mice. Copyright © 2012 John Wiley & Sons, Ltd.

Large General Purpose Frame for Studying Force Vectors

ERIC Educational Resources Information Center

Heid, Christy; Rampolla, Donald

2011-01-01

Many illustrations and problems on the vector nature of forces have weights and forces in a vertical plane. One of the common devices for studying the vector nature of forces is a horizontal "force table," in which forces are produced by weights hanging vertically and transmitted to cords in a horizontal plane. Because some students have…

Weight Vector Fluctuations in Adaptive Antenna Arrays Tuned Using the Least-Mean-Square Error Algorithm with Quadratic Constraint

NASA Astrophysics Data System (ADS)

Zimina, S. V.

2015-06-01

We present the results of statistical analysis of an adaptive antenna array tuned using the least-mean-square error algorithm with quadratic constraint on the useful-signal amplification with allowance for the weight-coefficient fluctuations. Using the perturbation theory, the expressions for the correlation function and power of the output signal of the adaptive antenna array, as well as the formula for the weight-vector covariance matrix are obtained in the first approximation. The fluctuations are shown to lead to the signal distortions at the antenna-array output. The weight-coefficient fluctuations result in the appearance of additional terms in the statistical characteristics of the antenna array. It is also shown that the weight-vector fluctuations are isotropic, i.e., identical in all directions of the weight-coefficient space.

Weighted K-means support vector machine for cancer prediction.

PubMed

Kim, SungHwan

2016-01-01

To date, the support vector machine (SVM) has been widely applied to diverse bio-medical fields to address disease subtype identification and pathogenicity of genetic variants. In this paper, I propose the weighted K-means support vector machine (wKM-SVM) and weighted support vector machine (wSVM), for which I allow the SVM to impose weights to the loss term. Besides, I demonstrate the numerical relations between the objective function of the SVM and weights. Motivated by general ensemble techniques, which are known to improve accuracy, I directly adopt the boosting algorithm to the newly proposed weighted KM-SVM (and wSVM). For predictive performance, a range of simulation studies demonstrate that the weighted KM-SVM (and wSVM) with boosting outperforms the standard KM-SVM (and SVM) including but not limited to many popular classification rules. I applied the proposed methods to simulated data and two large-scale real applications in the TCGA pan-cancer methylation data of breast and kidney cancer. In conclusion, the weighted KM-SVM (and wSVM) increases accuracy of the classification model, and will facilitate disease diagnosis and clinical treatment decisions to benefit patients. A software package (wSVM) is publicly available at the R-project webpage (https://www.r-project.org).

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.

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

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.

Artificial magnetic-field quenches in synthetic dimensions

NASA Astrophysics Data System (ADS)

Yılmaz, F.; Oktel, M. Ö.

2018-02-01

Recent cold atom experiments have realized models where each hyperfine state at an optical lattice site can be regarded as a separate site in a synthetic dimension. In such synthetic ribbon configurations, manipulation of the transitions between the hyperfine levels provide direct control of the hopping in the synthetic dimension. This effect was used to simulate a magnetic field through the ribbon. Precise control over the hopping matrix elements in the synthetic dimension makes it possible to change this artificial magnetic field much faster than the time scales associated with atomic motion in the lattice. In this paper, we consider such a magnetic-flux quench scenario in synthetic dimensions. Sudden changes have not been considered for real magnetic fields as such changes in a conducting system would result in large induced currents. Hence we first study the difference between a time varying real magnetic field and an artificial magnetic field using a minimal six-site model. This minimal model clearly shows the connection between gauge dependence and the lack of on-site induced scalar potential terms. We then investigate the dynamics of a wave packet in an infinite two- or three-leg ladder following a flux quench and find that the gauge choice has a dramatic effect on the packet dynamics. Specifically, a wave packet splits into a number of smaller packets moving with different velocities. Both the weights and the number of packets depend on the implemented gauge. If an initial packet, prepared under zero flux in an n -leg ladder, is quenched to Hamiltonian with a vector potential parallel to the ladder, it splits into at most n smaller wave packets. The same initial wave packet splits into up to n2 packets if the vector potential is implemented to be along the rungs. Even a trivial difference in the gauge choice such as the addition of a constant to the vector potential produces observable effects. We also calculate the packet weights for arbitrary initial and final fluxes. Finally, we show that edge states in a thick ribbon are robust under the quench only when the same gap supports an edge state for the final Hamiltonian.

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.

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.

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.

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.

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.

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).

Multiple-algorithm parallel fusion of infrared polarization and intensity images based on algorithmic complementarity and synergy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yang, Fengbao; Ji, Linna; Lv, Sheng

2018-01-01

Diverse image fusion methods perform differently. Each method has advantages and disadvantages compared with others. One notion is that the advantages of different image methods can be effectively combined. A multiple-algorithm parallel fusion method based on algorithmic complementarity and synergy is proposed. First, in view of the characteristics of the different algorithms and difference-features among images, an index vector-based feature-similarity is proposed to define the degree of complementarity and synergy. This proposed index vector is a reliable evidence indicator for algorithm selection. Second, the algorithms with a high degree of complementarity and synergy are selected. Then, the different degrees of various features and infrared intensity images are used as the initial weights for the nonnegative matrix factorization (NMF). This avoids randomness of the NMF initialization parameter. Finally, the fused images of different algorithms are integrated using the NMF because of its excellent data fusing performance on independent features. Experimental results demonstrate that the visual effect and objective evaluation index of the fused images obtained using the proposed method are better than those obtained using traditional methods. The proposed method retains all the advantages that individual fusion algorithms have.

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

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

Production of oleanolic acid glycosides by hairy root established cultures of Calendula officinalis L.

PubMed

Długosz, Marek; Wiktorowska, Ewa; Wiśniewska, Anita; Pączkowski, Cezary

2013-01-01

In order to initiate hairy root culture initiation cotyledons and hypocotyls of Calendula officinalis L. were infected with Agrobacterium rhizogenes strain ATCC 15834 or the same strain containing pCAMBIA 1381Z vector with β-glucuronidase reporter gene under control of promoter of NIK (Nematode Induced Kinase) gene. The efficiency of induction of hairy roots reached 33.8% for cotyledons and 66.6% for hypocotyls together for both transformation experiments. Finally, eight control and nine modified lines were established as a long-term culture. The hairy root cultures showed the ability to synthesize oleanolic acid mainly (97%) as glycosides; control lines contained it at the average 8.42 mg · g(-1) dry weight in tissue and 0.23 mg · dm(-3) in medium; modified lines: 4.59 mg · g(-1) for the tissue, and 0.48 mg · dm(-3) for the medium. Additionally lines showed high positive correlation between dry/fresh weight and oleanolic acid concentration in tissue. Using the Killiani mixture in acidic hydrolysis of oleanolic acid glycosides released free aglycones that were partially acetylated in such conditions.

Content relatedness in the social web based on social explicit semantic analysis

NASA Astrophysics Data System (ADS)

Ntalianis, Klimis; Otterbacher, Jahna; Mastorakis, Nikolaos

2017-06-01

In this paper a novel content relatedness algorithm for social media content is proposed, based on the Explicit Semantic Analysis (ESA) technique. The proposed scheme takes into consideration social interactions. In particular starting from the vector space representation model, similarity is expressed by a summation of term weight products. In this paper, term weights are estimated by a social computing method, where the strength of each term is calculated by the attention the terms receives. For this reason each post is split into two parts, title and comments area, while attention is defined by the number of social interactions such as likes and shares. The overall approach is named Social Explicit Semantic Analysis. Experimental results on real data show the advantages and limitations of the proposed approach, while an initial comparison between ESA and S-ESA is very promising.

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.

Spatio-temporal evolution of perturbations in ensembles initialized by bred, Lyapunov and singular vectors

NASA Astrophysics Data System (ADS)

Pazó, Diego; Rodríguez, Miguel A.; López, Juan M.

2010-05-01

We study the evolution of finite perturbations in the Lorenz ‘96 model, a meteorological toy model of the atmosphere. The initial perturbations are chosen to be aligned along different dynamic vectors: bred, Lyapunov, and singular vectors. Using a particular vector determines not only the amplification rate of the perturbation but also the spatial structure of the perturbation and its stability under the evolution of the flow. The evolution of perturbations is systematically studied by means of the so-called mean-variance of logarithms diagram that provides in a very compact way the basic information to analyse the spatial structure. We discuss the corresponding advantages of using those different vectors for preparing initial perturbations to be used in ensemble prediction systems, focusing on key properties: dynamic adaptation to the flow, robustness, equivalence between members of the ensemble, etc. Among all the vectors considered here, the so-called characteristic Lyapunov vectors are possibly optimal, in the sense that they are both perfectly adapted to the flow and extremely robust.

Spatio-temporal evolution of perturbations in ensembles initialized by bred, Lyapunov and singular vectors

NASA Astrophysics Data System (ADS)

Pazó, Diego; Rodríguez, Miguel A.; López, Juan M.

2010-01-01

We study the evolution of finite perturbations in the Lorenz `96 model, a meteorological toy model of the atmosphere. The initial perturbations are chosen to be aligned along different dynamic vectors: bred, Lyapunov, and singular vectors. Using a particular vector determines not only the amplification rate of the perturbation but also the spatial structure of the perturbation and its stability under the evolution of the flow. The evolution of perturbations is systematically studied by means of the so-called mean-variance of logarithms diagram that provides in a very compact way the basic information to analyse the spatial structure. We discuss the corresponding advantages of using those different vectors for preparing initial perturbations to be used in ensemble prediction systems, focusing on key properties: dynamic adaptation to the flow, robustness, equivalence between members of the ensemble, etc. Among all the vectors considered here, the so-called characteristic Lyapunov vectors are possibly optimal, in the sense that they are both perfectly adapted to the flow and extremely robust.

Simple automatic strategy for background drift correction in chromatographic data analysis.

PubMed

Fu, Hai-Yan; Li, He-Dong; Yu, Yong-Jie; Wang, Bing; Lu, Peng; Cui, Hua-Peng; Liu, Ping-Ping; She, Yuan-Bin

2016-06-03

Chromatographic background drift correction, which influences peak detection and time shift alignment results, is a critical stage in chromatographic data analysis. In this study, an automatic background drift correction methodology was developed. Local minimum values in a chromatogram were initially detected and organized as a new baseline vector. Iterative optimization was then employed to recognize outliers, which belong to the chromatographic peaks, in this vector, and update the outliers in the baseline until convergence. The optimized baseline vector was finally expanded into the original chromatogram, and linear interpolation was employed to estimate background drift in the chromatogram. The principle underlying the proposed method was confirmed using a complex gas chromatographic dataset. Finally, the proposed approach was applied to eliminate background drift in liquid chromatography quadrupole time-of-flight samples used in the metabolic study of Escherichia coli samples. The proposed method was comparable with three classical techniques: morphological weighted penalized least squares, moving window minimum value strategy and background drift correction by orthogonal subspace projection. The proposed method allows almost automatic implementation of background drift correction, which is convenient for practical use. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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.

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 method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

NASA Astrophysics Data System (ADS)

Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

2011-12-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

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

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.

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.

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.

3D Magnetization Vector Inversion of Magnetic Data: Improving and Comparing Methods

NASA Astrophysics Data System (ADS)

Liu, Shuang; Hu, Xiangyun; Zhang, Henglei; Geng, Meixia; Zuo, Boxin

2017-12-01

Magnetization vector inversion is an useful approach to invert for magnetic anomaly in the presence of significant remanent magnetization and self-demagnetization. However, magnetizations are usually obtained in many different directions under the influences of geophysical non-uniqueness. We propose an iteration algorithm of magnetization vector inversion (M-IDI) that one couple of magnetization direction is iteratively computed after the magnetization intensity is recovered from the magnitude magnetic anomaly. And we compare it with previous methods of (1) three orthogonal components inversion of total magnetization vector at Cartesian framework (MMM), (2) intensity, inclination and declination inversion at spherical framework (MID), (3) directly recovering the magnetization inclination and declination (M-IDCG) and (4) estimating the magnetization direction using correlation method (M-IDC) at the sequential inversion frameworks. The synthetic examples indicate that MMM returns multiply magnetization directions and MID results are strongly dependent on initial model and parameter weights. M-IDI computes faster than M-IDC and achieves a constant magnetization direction compared with M-IDCG. Additional priori information constraints can improve the results of MMM, MID and M-IDCG. Obtaining one magnetization direction, M-IDC and M-IDI are suitable for single and isolated anomaly. Finally, M-IDI and M-IDC are used to invert and interpret the magnetic anomaly of the Galinge iron-ore deposit (NW China) and the results are verified by information from drillholes and physical properties measurements of ore and rock samples. Magnetization vector inversion provides a comprehensive way to evaluate and investigate the remanent magnetization and self-demagnetization.

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.

Limiting similarity and niche theory for structured populations.

PubMed

Szilágyi, András; Meszéna, Géza

2009-05-07

We develop the theory of limiting similarity and niche for structured populations with finite number of individual states (i-state). In line with a previously published theory for unstructured populations, the niche of a species is specified by the impact and sensitivity niche vectors. They describe the population's impact on and sensitivity towards the variables involved in the population regulation. Robust coexistence requires sufficient segregation of the impact, as well as of the sensitivity niche vectors. Connection between the population-level impact and sensitivity and the impact/sensitivity of the specific i-states is developed. Each i-state contributes to the impact of the population proportional to its frequency in the population. Sensitivity of the population is composed of the sensitivity of the rates of demographic transitions, weighted by the frequency and by the reproductive value of the initial and final i-states of the transition, respectively. Coexistence in a multi-patch environment is studied. This analysis is interpreted as spatial niche segregation.

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.

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.

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.

Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination.

PubMed

Stivala, Alex; Robins, Garry; Kashima, Yoshihisa; Kirley, Michael

2014-05-02

The Axelrod model of cultural diffusion is an apparently simple model that is capable of complex behaviour. A recent work used a real-world dataset of opinions as initial conditions, demonstrating the effects of the ultrametric distribution of empirical opinion vectors in promoting cultural diversity in the model. Here we quantify the degree of ultrametricity of the initial culture vectors and investigate the effect of varying degrees of ultrametricity on the absorbing state of both a simple and extended model. Unlike the simple model, ultrametricity alone is not sufficient to sustain long-term diversity in the extended Axelrod model; rather, the initial conditions must also have sufficiently large variance in intervector distances. Further, we find that a scheme for evolving synthetic opinion vectors from cultural "prototypes" shows the same behaviour as real opinion data in maintaining cultural diversity in the extended model; whereas neutral evolution of cultural vectors does not.

Ultrametric distribution of culture vectors in an extended Axelrod model of cultural dissemination

NASA Astrophysics Data System (ADS)

Stivala, Alex; Robins, Garry; Kashima, Yoshihisa; Kirley, Michael

2014-05-01

The Axelrod model of cultural diffusion is an apparently simple model that is capable of complex behaviour. A recent work used a real-world dataset of opinions as initial conditions, demonstrating the effects of the ultrametric distribution of empirical opinion vectors in promoting cultural diversity in the model. Here we quantify the degree of ultrametricity of the initial culture vectors and investigate the effect of varying degrees of ultrametricity on the absorbing state of both a simple and extended model. Unlike the simple model, ultrametricity alone is not sufficient to sustain long-term diversity in the extended Axelrod model; rather, the initial conditions must also have sufficiently large variance in intervector distances. Further, we find that a scheme for evolving synthetic opinion vectors from cultural ``prototypes'' shows the same behaviour as real opinion data in maintaining cultural diversity in the extended model; whereas neutral evolution of cultural vectors does not.

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

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.

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.

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.

A Protein Structure Initiative Approach to Expression, Purification, and In Situ Delivery of Human Cytochrome b5 to Membrane Vesicles†

PubMed Central

Sobrado, Pablo; Goren, Michael A.; James, Declan; Amundson, Carissa K.; Fox, Brian G.

2008-01-01

A specialized vector backbone from the Protein Structure Initiative was used to express full-length human cytochrome b5 as a C-terminal fusion to His8-maltose binding protein in Escherichia coli. The fusion protein could be completely cleaved by tobacco etch virus protease, and a yield of ~18 mg of purified full-length human cytochrome b5 per liter of culture medium was obtained (2.3 mg per]of wet weight bacterial cells). In situ proteolysis of the fusion protein in the presence of chemically defined synthetic liposomes allowed facile spontaneous delivery of the functional peripheral membrane protein into a defined membrane environment without prior exposure to detergents or other lipids. The utility of this approach as a delivery method for production and incorporation of monotopic (peripheral) membrane proteins is discussed. PMID:18226920

A Protein Structure Initiative approach to expression, purification, and in situ delivery of human cytochrome b5 to membrane vesicles.

PubMed

Sobrado, Pablo; Goren, Michael A; James, Declan; Amundson, Carissa K; Fox, Brian G

2008-04-01

A specialized vector backbone from the Protein Structure Initiative was used to express full-length human cytochrome b5 as a C-terminal fusion to His8-maltose binding protein in Escherichia coli. The fusion protein could be completely cleaved by tobacco etch virus protease, and a yield of approximately 18 mg of purified full-length human cytochrome b5 per liter of culture medium was obtained (2.3mg per g of wet weight bacterial cells). In situ proteolysis of the fusion protein in the presence of chemically defined synthetic liposomes allowed facile spontaneous delivery of the functional peripheral membrane protein into a defined membrane environment without prior exposure to detergents or other lipids. The utility of this approach as a delivery method for production and incorporation of monotopic (peripheral) membrane proteins is discussed.

JPRS Report, Science & Technology, USSR: Earth Sciences

DTIC Science & Technology

1988-12-06

Vol 24 No 7, Jul 88] 14 Integral Characteristics of Light Scattering by Large Spherical Particles IE. P. Zege, A. A. Kokhanovskiy; IZVESTIYA AKADEMII...economical that the base not contain a grid model, but the initial contours, represented in vector format, in which case it is called a vector DRM. The...information make it possible to display both screen and vector DRM and from these, retrieve contours in the initial format. The automated forest mapping

Imer-product array processor for retrieval of stored images represented by bipolar binary (+1,-1) pixels using partial input trinary pixels represented by (+1,-1)

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Awwal, Abdul A. S. (Inventor); Karim, Mohammad A. (Inventor)

1993-01-01

An inner-product array processor is provided with thresholding of the inner product during each iteration to make more significant the inner product employed in estimating a vector to be used as the input vector for the next iteration. While stored vectors and estimated vectors are represented in bipolar binary (1,-1), only those elements of an initial partial input vector that are believed to be common with those of a stored vector are represented in bipolar binary; the remaining elements of a partial input vector are set to 0. This mode of representation, in which the known elements of a partial input vector are in bipolar binary form and the remaining elements are set equal to 0, is referred to as trinary representation. The initial inner products corresponding to the partial input vector will then be equal to the number of known elements. Inner-product thresholding is applied to accelerate convergence and to avoid convergence to a negative input product.

Factors Affecting the Initial Adhesion and Retention of the Plant Pathogen Xylella fastidiosa in the Foregut of an Insect Vector

PubMed Central

Almeida, Rodrigo P. P.

2014-01-01

Vector transmission of bacterial plant pathogens involves three steps: pathogen acquisition from an infected host, retention within the vector, and inoculation of cells into susceptible tissue of an uninfected plant. In this study, a combination of plant and artificial diet systems were used to determine the importance of several genes on the initial adhesion and retention of the bacterium Xylella fastidiosa to an efficient insect vector. Mutant strains included fimbrial (fimA and pilB) and afimbrial (hxfA and hxfB) adhesins and three loci involved in regulatory systems (rpfF, rpfC, and cgsA). Transmission assays with variable retention time indicated that HxfA and HxfB were primarily important for early adhesion to vectors, while FimA was necessary for both adhesion and retention. The long pilus protein PilB was not deficient in initial adhesion but may be important for retention. Genes upregulated under the control of rpfF are important for both initial adhesion and retention, as transmission rates of this mutant strain were initially low and decreased over time, while disruption of rpfC and cgsA yielded trends similar to that shown by the wild-type control. Because induction of an X. fastidiosa transmissible state requires pectin, a series of experiments were used to test the roles of a polygalacturonase (pglA) and the pectin and galacturonic acid carbohydrates on the transmission of X. fastidiosa. Results show that galacturonic acid, or PglA activity breaking pectin into its major subunit (galacturonic acid), is required for X. fastidiosa vector transmission using an artificial diet system. This study shows that early adhesion and retention of X. fastidiosa are mediated by different factors. It also illustrates that the interpretation of results of vector transmission experiments, in the context of vector-pathogen interaction studies, is highly dependent on experimental design. PMID:24185853

Factors affecting the initial adhesion and retention of the plant pathogen Xylella fastidiosa in the foregut of an insect vector.

PubMed

Killiny, Nabil; Almeida, Rodrigo P P

2014-01-01

Vector transmission of bacterial plant pathogens involves three steps: pathogen acquisition from an infected host, retention within the vector, and inoculation of cells into susceptible tissue of an uninfected plant. In this study, a combination of plant and artificial diet systems were used to determine the importance of several genes on the initial adhesion and retention of the bacterium Xylella fastidiosa to an efficient insect vector. Mutant strains included fimbrial (fimA and pilB) and afimbrial (hxfA and hxfB) adhesins and three loci involved in regulatory systems (rpfF, rpfC, and cgsA). Transmission assays with variable retention time indicated that HxfA and HxfB were primarily important for early adhesion to vectors, while FimA was necessary for both adhesion and retention. The long pilus protein PilB was not deficient in initial adhesion but may be important for retention. Genes upregulated under the control of rpfF are important for both initial adhesion and retention, as transmission rates of this mutant strain were initially low and decreased over time, while disruption of rpfC and cgsA yielded trends similar to that shown by the wild-type control. Because induction of an X. fastidiosa transmissible state requires pectin, a series of experiments were used to test the roles of a polygalacturonase (pglA) and the pectin and galacturonic acid carbohydrates on the transmission of X. fastidiosa. Results show that galacturonic acid, or PglA activity breaking pectin into its major subunit (galacturonic acid), is required for X. fastidiosa vector transmission using an artificial diet system. This study shows that early adhesion and retention of X. fastidiosa are mediated by different factors. It also illustrates that the interpretation of results of vector transmission experiments, in the context of vector-pathogen interaction studies, is highly dependent on experimental design.

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

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.

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

Region-based automatic building and forest change detection on Cartosat-1 stereo imagery

NASA Astrophysics Data System (ADS)

Tian, J.; Reinartz, P.; d'Angelo, P.; Ehlers, M.

2013-05-01

In this paper a novel region-based method is proposed for change detection using space borne panchromatic Cartosat-1 stereo imagery. In the first step, Digital Surface Models (DSMs) from two dates are generated by semi-global matching. The geometric lateral resolution of the DSMs is 5 m × 5 m and the height accuracy is in the range of approximately 3 m (RMSE). In the second step, mean-shift segmentation is applied on the orthorectified images of two dates to obtain initial regions. A region intersection following a merging strategy is proposed to get minimum change regions and multi-level change vectors are extracted for these regions. Finally change detection is achieved by combining these features with weighted change vector analysis. The result evaluations demonstrate that the applied DSM generation method is well suited for Cartosat-1 imagery, and the extracted height values can largely improve the change detection accuracy, moreover it is shown that the proposed change detection method can be used robustly for both forest and industrial areas.

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.

Applicability of initial optimal maternal and fetal electrocardiogram combination vectors to subsequent recordings

NASA Astrophysics Data System (ADS)

Yan, Hua-Wen; Huang, Xiao-Lin; Zhao, Ying; Si, Jun-Feng; Liu, Tie-Bing; Liu, Hong-Xing

2014-11-01

A series of experiments are conducted to confirm whether the vectors calculated for an early section of a continuous non-invasive fetal electrocardiogram (fECG) recording can be directly applied to subsequent sections in order to reduce the computation required for real-time monitoring. Our results suggest that it is generally feasible to apply the initial optimal maternal and fetal ECG combination vectors to extract the fECG and maternal ECG in subsequent recorded sections.

On a Class of Hairy Square Barriers and Gamow Vectors

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

Fernandez-Garcia, N.

The second order Darboux-Gamow transformation is applied to deform square one dimensional barriers in non-relativistic quantum mechanics. The initial and the new 'hairy' potentials have the same transmission probabilities (for the appropriate parameters). In general, new Gamow vectors are constructed as Darboux deformations of the initial ones.

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

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.

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.

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

DOEpatents

Jiao, Yu; Potok, Thomas E.

2011-05-03

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

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.

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

PubMed Central

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate. PMID:22368464

Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

PubMed

Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

2012-01-01

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

Estimation of chaotic coupled map lattices using symbolic vector dynamics

NASA Astrophysics Data System (ADS)

Wang, Kai; Pei, Wenjiang; Cheung, Yiu-ming; Shen, Yi; He, Zhenya

2010-01-01

In [K. Wang, W.J. Pei, Z.Y. He, Y.M. Cheung, Phys. Lett. A 367 (2007) 316], an original symbolic vector dynamics based method has been proposed for initial condition estimation in additive white Gaussian noisy environment. The estimation precision of this estimation method is determined by symbolic errors of the symbolic vector sequence gotten by symbolizing the received signal. This Letter further develops the symbolic vector dynamical estimation method. We correct symbolic errors with backward vector and the estimated values by using different symbols, and thus the estimation precision can be improved. Both theoretical and experimental results show that this algorithm enables us to recover initial condition of coupled map lattice exactly in both noisy and noise free cases. Therefore, we provide novel analytical techniques for understanding turbulences in coupled map lattice.

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.

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.

Sex Differences and Neurodevelopmental Variables: A Vector Model

ERIC Educational Resources Information Center

Languis, Marlin; Naour, Paul

For the individual, gender difference falls along the feminine-masculine continuum with strong neurodevelopmental influences at various points throughout the lifespan. Neurodevelopmental influences are conceptualized in a vector model of sex difference. Vector attributes, direction and magnitude, are influenced initially by differences in levels…

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

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1977-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

VectorBase: a data resource for invertebrate vector genomics

PubMed Central

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

2009-01-01

VectorBase (http://www.vectorbase.org) is an NIAID-funded Bioinformatic Resource Center focused on invertebrate vectors of human pathogens. VectorBase annotates and curates vector genomes providing a web accessible integrated resource for the research community. Currently, VectorBase contains genome information for three mosquito species: Aedes aegypti, Anopheles gambiae and Culex quinquefasciatus, a body louse Pediculus humanus and a tick species Ixodes scapularis. Since our last report VectorBase has initiated a community annotation system, a microarray and gene expression repository and controlled vocabularies for anatomy and insecticide resistance. We have continued to develop both the software infrastructure and tools for interrogating the stored data. PMID:19028744

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.

The Vertical Linear Fractional Initialization Problem

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Hartley, Tom T.

1999-01-01

This paper presents a solution to the initialization problem for a system of linear fractional-order differential equations. The scalar problem is considered first, and solutions are obtained both generally and for a specific initialization. Next the vector fractional order differential equation is considered. In this case, the solution is obtained in the form of matrix F-functions. Some control implications of the vector case are discussed. The suggested method of problem solution is shown via an example.

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.

Energy-exchange collisions of dark-bright-bright vector solitons.

PubMed

Radhakrishnan, R; Manikandan, N; Aravinthan, K

2015-12-01

We find a dark component guiding the practically interesting bright-bright vector one-soliton to two different parametric domains giving rise to different physical situations by constructing a more general form of three-component dark-bright-bright mixed vector one-soliton solution of the generalized Manakov model with nine free real parameters. Moreover our main investigation of the collision dynamics of such mixed vector solitons by constructing the multisoliton solution of the generalized Manakov model with the help of Hirota technique reveals that the dark-bright-bright vector two-soliton supports energy-exchange collision dynamics. In particular the dark component preserves its initial form and the energy-exchange collision property of the bright-bright vector two-soliton solution of the Manakov model during collision. In addition the interactions between bound state dark-bright-bright vector solitons reveal oscillations in their amplitudes. A similar kind of breathing effect was also experimentally observed in the Bose-Einstein condensates. Some possible ways are theoretically suggested not only to control this breathing effect but also to manage the beating, bouncing, jumping, and attraction effects in the collision dynamics of dark-bright-bright vector solitons. The role of multiple free parameters in our solution is examined to define polarization vector, envelope speed, envelope width, envelope amplitude, grayness, and complex modulation of our solution. It is interesting to note that the polarization vector of our mixed vector one-soliton evolves in sphere or hyperboloid depending upon the initial parametric choices.

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.

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…

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).

Effects of EPI distortion correction pipelines on the connectome in Parkinson's Disease

NASA Astrophysics Data System (ADS)

Galvis, Justin; Mezher, Adam F.; Ragothaman, Anjanibhargavi; Villalon-Reina, Julio E.; Fletcher, P. Thomas; Thompson, Paul M.; Prasad, Gautam

2016-03-01

Echo-planar imaging (EPI) is commonly used for diffusion-weighted imaging (DWI) but is susceptible to nonlinear geometric distortions arising from inhomogeneities in the static magnetic field. These inhomogeneities can be measured and corrected using a fieldmap image acquired during the scanning process. In studies where the fieldmap image is not collected, these distortions can be corrected, to some extent, by nonlinearly registering the diffusion image to a corresponding anatomical image, either a T1- or T2-weighted image. Here we compared two EPI distortion correction pipelines, both based on nonlinear registration, which were optimized for the particular weighting of the structural image registration target. The first pipeline used a 3D nonlinear registration to a T1-weighted target, while the second pipeline used a 1D nonlinear registration to a T2-weighted target. We assessed each pipeline in its ability to characterize high-level measures of brain connectivity in Parkinson's disease (PD) in 189 individuals (58 healthy controls, 131 people with PD) from the Parkinson's Progression Markers Initiative (PPMI) dataset. We computed a structural connectome (connectivity map) for each participant using regions of interest from a cortical parcellation combined with DWI-based whole-brain tractography. We evaluated test-retest reliability of the connectome for each EPI distortion correction pipeline using a second diffusion scan acquired directly after the participants' first. Finally, we used support vector machine (SVM) classification to assess how accurately each pipeline classified PD versus healthy controls using each participants' structural connectome.

Low Lunar Orbit Design via Graphical Manipulation of Eccentricity Vector Evolution

NASA Technical Reports Server (NTRS)

Wallace, Mark S.; Sweetser, Theodore H.; Roncoli, Ralph B.

2012-01-01

Low lunar orbits, such as those used by GRAIL and LRO, experience predictable variations in the evolution of their eccentricity vectors. These variations are nearly invariant with respect to the initial eccentricity and argument of periapse and change only in the details with respect to the initial semi-major axis. These properties suggest that manipulating the eccentricity vector evolution directly can give insight into orbit maintenance designs and can reduce the number of propagations required. A trio of techniques for determining the desired maneuvers is presented in the context of the GRAIL extended mission.

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

Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.

PubMed

Kunimatsu, Akira; Kunimatsu, Natsuko; Yasaka, Koichiro; Akai, Hiroyuki; Kamiya, Kouhei; Watadani, Takeyuki; Mori, Harushi; Abe, Osamu

2018-05-16

Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classification by support vector machine, a method of traditional machine learning, using texture features computed from contrast-enhanced T 1 -weighted images. This retrospective study on preoperative brain tumor MRI included 76 consecutives, initially treated patients with glioblastoma (n = 55) or PCNSL (n = 21) from one institution, consisting of independent training group (n = 60: 44 glioblastomas and 16 PCNSLs) and test group (n = 16: 11 glioblastomas and 5 PCNSLs) sequentially separated by time periods. A total set of 67 texture features was computed on routine contrast-enhanced T 1 -weighted images of the training group, and the top four most discriminating features were selected as input variables to train support vector machine classifiers. These features were then evaluated on the test group with subsequent image classification. The area under the receiver operating characteristic curves on the training data was calculated at 0.99 (95% confidence interval [CI]: 0.96-1.00) for the classifier with a Gaussian kernel and 0.87 (95% CI: 0.77-0.95) for the classifier with a linear kernel. On the test data, both of the classifiers showed prediction accuracy of 75% (12/16) of the test images. Although further improvement is needed, our preliminary results suggest that machine learning-based image classification may provide complementary diagnostic information on routine brain MRI.

An efficient sparse matrix multiplication scheme for the CYBER 205 computer

NASA Technical Reports Server (NTRS)

Lambiotte, Jules J., Jr.

1988-01-01

This paper describes the development of an efficient algorithm for computing the product of a matrix and vector on a CYBER 205 vector computer. The desire to provide software which allows the user to choose between the often conflicting goals of minimizing central processing unit (CPU) time or storage requirements has led to a diagonal-based algorithm in which one of four types of storage is selected for each diagonal. The candidate storage types employed were chosen to be efficient on the CYBER 205 for diagonals which have nonzero structure which is dense, moderately sparse, very sparse and short, or very sparse and long; however, for many densities, no diagonal type is most efficient with respect to both resource requirements, and a trade-off must be made. For each diagonal, an initialization subroutine estimates the CPU time and storage required for each storage type based on results from previously performed numerical experimentation. These requirements are adjusted by weights provided by the user which reflect the relative importance the user places on the two resources. The adjusted resource requirements are then compared to select the most efficient storage and computational scheme.

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.

Strategy to approach stable production of recombinant nattokinase in Bacillus subtilis.

PubMed

Chen, Po Ting; Chiang, Chung-Jen; Chao, Yun-Peng

2007-01-01

Bacillus subtilis (B. subtilis) is widely accepted as an excellent host cell for the secretory production of recombinant proteins. In this study, a shuttle vector was constructed by fusion of Staphylococcus aureus (S. aureus) plasmid pUB110 with Escherichia coli (E. coli) plasmid pUC18 and used for the expression of nattokinase in B. subtilis. The pUB110/pUC-based plasmid was found to exhibit high structural instability with the identification of a DNA deletion between two repeated regions. An initial attempt was made to eliminate the homologous site in the plasmid, whereas the stability of the resulting plasmid was not improved. In an alternative way, the pUC18-derived region in this hybrid vector was replaced by the suicidal R6K plasmid origin of E. coli. As a consequence, the pUB110/R6K-based plasmid displayed full structural stability, leading to a high-level production of recombinant nattokinase in the culture broth. This was mirrored by the detection of a very low level of high molecular weight DNAs generated by the plasmid. Moreover, 2-fold higher nattokinase production was obtained by B. subtilis strain carrying the pUB110/R6K-based plasmid as compared to the cell with the pAMbeta1-derived vector, a plasmid known to have high structural stability. Overall, it indicates the feasibility of the approach by fusing two compatible plasmid origins for stable and efficient production of recombinant nattokinase in B. subtilis.

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.

Three-dimensional Hybrid Simulation Study of Anisotropic Turbulence in the Proton Kinetic Regime

NASA Astrophysics Data System (ADS)

Vasquez, Bernard J.; Markovskii, Sergei A.; Chandran, Benjamin D. G.

2014-06-01

Three-dimensional numerical hybrid simulations with particle protons and quasi-neutralizing fluid electrons are conducted for a freely decaying turbulence that is anisotropic with respect to the background magnetic field. The turbulence evolution is determined by both the combined root-mean-square (rms) amplitude for fluctuating proton bulk velocity and magnetic field and by the ratio of perpendicular to parallel wavenumbers. This kind of relationship had been considered in the past with regard to interplanetary turbulence. The fluctuations nonlinearly evolve to a turbulent phase whose net wave vector anisotropy is usually more perpendicular than the initial one, irrespective of the initial ratio of perpendicular to parallel wavenumbers. Self-similar anisotropy evolution is found as a function of the rms amplitude and parallel wavenumber. Proton heating rates in the turbulent phase vary strongly with the rms amplitude but only weakly with the initial wave vector anisotropy. Even in the limit where wave vectors are confined to the plane perpendicular to the background magnetic field, the heating rate remains close to the corresponding case with finite parallel wave vector components. Simulation results obtained as a function of proton plasma to background magnetic pressure ratio β p in the range 0.1-0.5 show that the wave vector anisotropy also weakly depends on β p .

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.

SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method.

PubMed

Bernal, Javier; Torres-Jimenez, Jose

2015-01-01

SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.

A Visualization Case Study of Feature Vector and Stemmer Effects on TREC Topic-document Subsets.

ERIC Educational Resources Information Center

Rorvig, Mark T.; Sullivan, Terry; Oyarce, Guillermo

1998-01-01

Demonstrates a method of visual analysis which takes advantage of the pooling technique of topic-document set creation in the TREC collection. Describes the procedures used to create the initial visual fields, and their respective treatments as vectors without stemming and vectors with stemming; discusses results of these treatments and…

Simulation of an epidemic model with vector transmission

NASA Astrophysics Data System (ADS)

Dickman, Adriana G.; Dickman, Ronald

2015-03-01

We study a lattice model for vector-mediated transmission of a disease in a population consisting of two species, A and B, which contract the disease from one another. Individuals of species A are sedentary, while those of species B (the vector) diffuse in space. Examples of such diseases are malaria, dengue fever, and Pierce's disease in vineyards. The model exhibits a phase transition between an absorbing (infection free) phase and an active one as parameters such as infection rates and vector density are varied. We study the static and dynamic critical behavior of the model using initial spreading, initial decay, and quasistationary simulations. Simulations are checked against mean-field analysis. Although phase transitions to an absorbing state fall generically in the directed percolation universality class, this appears not to be the case for the present model.

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.

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

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).

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…

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.

System Finds Horizontal Location of Center of Gravity

NASA Technical Reports Server (NTRS)

Johnston, Albert S.; Howard, Richard T.; Brewster, Linda L.

2006-01-01

An instrumentation system rapidly and repeatedly determines the horizontal location of the center of gravity of a laboratory vehicle that slides horizontally on three air bearings (see Figure 1). Typically, knowledge of the horizontal center-of-mass location of such a vehicle is needed in order to balance the vehicle properly for an experiment and/or to assess the dynamic behavior of the vehicle. The system includes a load cell above each air bearing, electronic circuits that generate digital readings of the weight on each load cell, and a computer equipped with software that processes the readings. The total weight and, hence, the mass of the vehicle are computed from the sum of the load-cell weight readings. Then the horizontal position of the center of gravity is calculated straightforwardly as the weighted sum of the known position vectors of the air bearings, the contribution of each bearing being proportional to the weight on that bearing. In the initial application for which this system was devised, the center- of-mass calculation is particularly simple because the air bearings are located at corners of an equilateral triangle. However, the system is not restricted to this simple geometry. The system acquires and processes weight readings at a rate of 800 Hz for each load cell. The total weight and the horizontal location of the center of gravity are updated at a rate of 800/3 approx. equals 267 Hz. In a typical application, a technician would use the center-of-mass output of this instrumentation system as a guide to the manual placement of small weights on the vehicle to shift the center of gravity to a desired horizontal position. Usually, the desired horizontal position is that of the geometric center. Alternatively, this instrumentation system could be used to provide position feedback for a control system that would cause weights to be shifted automatically (see Figure 2) in an effort to keep the center of gravity at the geometric center.

Two-spoke placement optimization under explicit specific absorption rate and power constraints in parallel transmission at ultra-high field.

PubMed

Dupas, Laura; Massire, Aurélien; Amadon, Alexis; Vignaud, Alexandre; Boulant, Nicolas

2015-06-01

The spokes method combined with parallel transmission is a promising technique to mitigate the B1(+) inhomogeneity at ultra-high field in 2D imaging. To date however, the spokes placement optimization combined with the magnitude least squares pulse design has never been done in direct conjunction with the explicit Specific Absorption Rate (SAR) and hardware constraints. In this work, the joint optimization of 2-spoke trajectories and RF subpulse weights is performed under these constraints explicitly and in the small tip angle regime. The problem is first considerably simplified by making the observation that only the vector between the 2 spokes is relevant in the magnitude least squares cost-function, thereby reducing the size of the parameter space and allowing a more exhaustive search. The algorithm starts from a set of initial k-space candidates and performs in parallel for all of them optimizations of the RF subpulse weights and the k-space locations simultaneously, under explicit SAR and power constraints, using an active-set algorithm. The dimensionality of the spoke placement parameter space being low, the RF pulse performance is computed for every location in k-space to study the robustness of the proposed approach with respect to initialization, by looking at the probability to converge towards a possible global minimum. Moreover, the optimization of the spoke placement is repeated with an increased pulse bandwidth in order to investigate the impact of the constraints on the result. Bloch simulations and in vivo T2(∗)-weighted images acquired at 7 T validate the approach. The algorithm returns simulated normalized root mean square errors systematically smaller than 5% in 10 s. Copyright © 2015 Elsevier Inc. All rights reserved.

Manufacturing in space: Fluid dynamics numerical analysis

NASA Technical Reports Server (NTRS)

Robertson, S. J.; Nicholson, L. A.; Spradley, L. W.

1982-01-01

Numerical computations were performed for natural convection in circular enclosures under various conditions of acceleration. It was found that subcritical acceleration vectors applied in the direction of the temperature gradient will lead to an eventual state of rest regardless of the initial state of motion. Supercritical acceleration vectors will lead to the same steady state condition of motion regardless of the initial state of motion. Convection velocities were computed for acceleration vectors at various angles of the initial temperature gradient. The results for Rayleigh numbers of 1000 or less were found to closely follow Weinbaum's first order theory. Higher Rayleigh number results were shown to depart significantly from the first order theory. Supercritical behavior was confirmed for Rayleigh numbers greater than the known supercritical value of 9216. Response times were determined to provide an indication of the time required to change states of motion for the various cases considered.

A Self-Alignment Algorithm for SINS Based on Gravitational Apparent Motion and Sensor Data Denoising

PubMed Central

Liu, Yiting; Xu, Xiaosu; Liu, Xixiang; Yao, Yiqing; Wu, Liang; Sun, Jin

2015-01-01

Initial alignment is always a key topic and difficult to achieve in an inertial navigation system (INS). In this paper a novel self-initial alignment algorithm is proposed using gravitational apparent motion vectors at three different moments and vector-operation. Simulation and analysis showed that this method easily suffers from the random noise contained in accelerometer measurements which are used to construct apparent motion directly. Aiming to resolve this problem, an online sensor data denoising method based on a Kalman filter is proposed and a novel reconstruction method for apparent motion is designed to avoid the collinearity among vectors participating in the alignment solution. Simulation, turntable tests and vehicle tests indicate that the proposed alignment algorithm can fulfill initial alignment of strapdown INS (SINS) under both static and swinging conditions. The accuracy can either reach or approach the theoretical values determined by sensor precision under static or swinging conditions. PMID:25923932

9 CFR 130.4 - User fees for processing import permit applications.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., vectors, or germ plasm (embryos or semen) or to transport organisms or vectors1 Initial permit Per... Transit Permit (Animals, Animal Semen, Animal Embryos, Birds, Poultry, or Hatching Eggs).” 2 Permits to...

9 CFR 130.4 - User fees for processing import permit applications.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., vectors, or germ plasm (embryos or semen) or to transport organisms or vectors1 Initial permit Per... Transit Permit (Animals, Animal Semen, Animal Embryos, Birds, Poultry, or Hatching Eggs).” 2 Permits to...

9 CFR 130.4 - User fees for processing import permit applications.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., vectors, or germ plasm (embryos or semen) or to transport organisms or vectors1 Initial permit Per... Transit Permit (Animals, Animal Semen, Animal Embryos, Birds, Poultry, or Hatching Eggs).” 2 Permits to...

9 CFR 130.4 - User fees for processing import permit applications.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., vectors, or germ plasm (embryos or semen) or to transport organisms or vectors1 Initial permit Per... Transit Permit (Animals, Animal Semen, Animal Embryos, Birds, Poultry, or Hatching Eggs).” 2 Permits to...

9 CFR 130.4 - User fees for processing import permit applications.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., vectors, or germ plasm (embryos or semen) or to transport organisms or vectors1 Initial permit Per... Transit Permit (Animals, Animal Semen, Animal Embryos, Birds, Poultry, or Hatching Eggs).” 2 Permits to...

Predicting the effect of angular momentum on the dissociation dynamics of highly rotationally excited radical intermediates.

PubMed

Brynteson, Matthew D; Butler, Laurie J

2015-02-07

We present a model which accurately predicts the net speed distributions of products resulting from the unimolecular decomposition of rotationally excited radicals. The radicals are produced photolytically from a halogenated precursor under collision-free conditions so they are not in a thermal distribution of rotational states. The accuracy relies on the radical dissociating with negligible energetic barrier beyond the endoergicity. We test the model predictions using previous velocity map imaging and crossed laser-molecular beam scattering experiments that photolytically generated rotationally excited CD2CD2OH and C3H6OH radicals from brominated precursors; some of those radicals then undergo further dissociation to CD2CD2 + OH and C3H6 + OH, respectively. We model the rotational trajectories of these radicals, with high vibrational and rotational energy, first near their equilibrium geometry, and then by projecting each point during the rotation to the transition state (continuing the rotational dynamics at that geometry). This allows us to accurately predict the recoil velocity imparted in the subsequent dissociation of the radical by calculating the tangential velocities of the CD2CD2/C3H6 and OH fragments at the transition state. The model also gives a prediction for the distribution of angles between the dissociation fragments' velocity vectors and the initial radical's velocity vector. These results are used to generate fits to the previously measured time-of-flight distributions of the dissociation fragments; the fits are excellent. The results demonstrate the importance of considering the precession of the angular velocity vector for a rotating radical. We also show that if the initial angular momentum of the rotating radical lies nearly parallel to a principal axis, the very narrow range of tangential velocities predicted by this model must be convoluted with a J = 0 recoil velocity distribution to achieve a good result. The model relies on measuring the kinetic energy release when the halogenated precursor is photodissociated via a repulsive excited state but does not include any adjustable parameters. Even when different conformers of the photolytic precursor are populated, weighting the prediction by a thermal conformer population gives an accurate prediction for the relative velocity vectors of the fragments from the highly rotationally excited radical intermediates.

Tribal and Locality Dynamics in Afghanistan: A View from the National Military Academy of Afghanistan

DTIC Science & Technology

2009-01-01

CD VVV ∪= with DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states; CXVXf →×: is a vector field, assumed to be 4 globally...DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states; CXVXf →×: is a vector field, assumed to be globally Lipschitz in CX and...8217 ; V is a finite collection of input variables. We assume ( )CD VVV ∪= with DV countable and nCV ℜ∈ ; XInit ⊆ is a set of initial states

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.

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.

Regulated release of a novel non-viral gene delivery vector from electrospun coaxial fiber mesh scaffolds

NASA Astrophysics Data System (ADS)

Saraf, Anita

The development of novel strategies for tissue engineering entails the evolution of biopolymers into multifunctional constructs that can support the proliferation of cells and stimulate their differentiation into functional tissues. With that in mind, biocompatible polymers were fabricated into a novel gene delivery agent as well as three dimensional scaffolds that act as reservoirs and controlled release constructs. To fabricate a novel gene delivery agent a commercially available cationic polymer, poly(ethylenimine), PEI, was chemically conjugated to a ubiquitous glycosaminoglycan, hyaluronic acid (HA). The novel polymer, PEI-HA, had significantly reduced toxicity and improved transfection efficiency with multipotent human mesenchymal stem cells. This transfection efficiency could further be modulated by changing the concentration of sodium chloride and temperature used to assemble PEI-HA/DNA complexes. To facilitate the regulated delivery of these complexes in the context of tissue engineering, an emerging technology for scaffold fabrication, coaxial electrospinning was adapted to include PEI-HA and plasmid DNA within the scaffold fibers. Initially, a factorial design was employed to assess the influence of processing parameters in the absence of gene delivery vectors and plasmids. The study elucidated the role of sheath polymer concentration and core polymer concentration and molecular weight and the presence of sodium chloride on fiber diameters and morphologies. Subsequently, PEI-HA and plasmid DNA were entrapped within the sheath and core compartments of these fibers and the influence of processing parameters was assessed in the context of fiber diameter, release kinetics and transfection efficiency over a period of 60 days. The release of PEI-HA was found to be dependent upon the loading dose of the vector and plasmid. However, the transfection efficiency correlated to the core polymer properties, concentration and molecular weight. The processing parameters could modulate cell transfection for up to 21 days and continue to transfect cells for up to 60 days. Thus, scaffolds with tunable release kinetics and transfection efficiencies can be fabricated using coaxial electrospinning, which can further be used for tissue engineering and gene delivery applications.

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

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.

Degradation mechanisms of bioresorbable polyesters. Part 2. Effects of initial molecular weight and residual monomer.

PubMed

Gleadall, Andrew; Pan, Jingzhe; Kruft, Marc-Anton; Kellomäki, Minna

2014-05-01

This paper presents an understanding of how initial molecular weight and initial monomer fraction affect the degradation of bioresorbable polymers in terms of the underlying hydrolysis mechanisms. A mathematical model was used to analyse the effects of initial molecular weight for various hydrolysis mechanisms including noncatalytic random scission, autocatalytic random scission, noncatalytic end scission or autocatalytic end scission. Different behaviours were identified to relate initial molecular weight to the molecular weight half-life and to the time until the onset of mass loss. The behaviours were validated by fitting the model to experimental data for molecular weight reduction and mass loss of samples with different initial molecular weights. Several publications that consider initial molecular weight were reviewed. The effect of residual monomer on degradation was also analysed, and shown to accelerate the reduction of molecular weight and mass loss. An inverse square root law relationship was found between molecular weight half-life and initial monomer fraction for autocatalytic hydrolysis. The relationship was tested by fitting the model to experimental data with various residual monomer contents. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Eco-bio-social research on community-based approaches for Chagas disease vector control in Latin America.

PubMed

Gürtler, Ricardo E; Yadon, Zaida E

2015-02-01

This article provides an overview of three research projects which designed and implemented innovative interventions for Chagas disease vector control in Bolivia, Guatemala and Mexico. The research initiative was based on sound principles of community-based ecosystem management (ecohealth), integrated vector management, and interdisciplinary analysis. The initial situational analysis achieved a better understanding of ecological, biological and social determinants of domestic infestation. The key factors identified included: housing quality; type of peridomestic habitats; presence and abundance of domestic dogs, chickens and synanthropic rodents; proximity to public lights; location in the periphery of the village. In Bolivia, plastering of mud walls with appropriate local materials and regular cleaning of beds and of clothes next to the walls, substantially decreased domestic infestation and abundance of the insect vector Triatoma infestans. The Guatemalan project revealed close links between house infestation by rodents and Triatoma dimidiata, and vector infection with Trypanosoma cruzi. A novel community-operated rodent control program significantly reduced rodent infestation and bug infection. In Mexico, large-scale implementation of window screens translated into promising reductions in domestic infestation. A multi-pronged approach including community mobilisation and empowerment, intersectoral cooperation and adhesion to integrated vector management principles may be the key to sustainable vector and disease control in the affected regions. © World Health Organization 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

Multidimensional density shaping by sigmoids.

PubMed

Roth, Z; Baram, Y

1996-01-01

An estimate of the probability density function of a random vector is obtained by maximizing the output entropy of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's optimization method, applied to the estimated density, yields a recursive estimator for a random variable or a random sequence. A constrained connectivity structure yields a linear estimator, which is particularly suitable for "real time" prediction. A Gaussian nonlinearity yields a closed-form solution for the network's parameters, which may also be used for initializing the optimization algorithm when other nonlinearities are employed. A triangular connectivity between the neurons and the input, which is naturally suggested by the statistical setting, reduces the number of parameters. Applications to classification and forecasting problems are demonstrated.

Adaptive model predictive process control using neural networks

DOEpatents

Buescher, K.L.; Baum, C.C.; Jones, R.D.

1997-08-19

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

Adaptive model predictive process control using neural networks

DOEpatents

Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

1997-01-01

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

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.

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.

Vector excitation speech or audio coder for transmission or storage

NASA Technical Reports Server (NTRS)

Davidson, Grant (Inventor); Gersho, Allen (Inventor)

1989-01-01

A vector excitation coder compresses vectors by using an optimum codebook designed off line, using an initial arbitrary codebook and a set of speech training vectors exploiting codevector sparsity (i.e., by making zero all but a selected number of samples of lowest amplitude in each of N codebook vectors). A fast-search method selects a number N.sub.c of good excitation vectors from the codebook, where N.sub.c is much smaller tha ORIGIN OF INVENTION The invention described herein was made in the performance of work under a NASA contract, and is subject to the provisions of Public Law 96-517 (35 USC 202) under which the inventors were granted a request to retain title.

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.

Rescue administration of a helper-dependent adenovirus vector with long-term efficacy in dogs with glycogen storage disease type Ia.

PubMed

Crane, B; Luo, X; Demaster, A; Williams, K D; Kozink, D M; Zhang, P; Brown, T T; Pinto, C R; Oka, K; Sun, F; Jackson, M W; Chan, L; Koeberl, D D

2012-04-01

Glycogen storage disease type Ia (GSD-Ia) stems from glucose-6-phosphatase (G6Pase) deficiency and causes hypoglycemia, hepatomegaly, hypercholesterolemia and lactic acidemia. Three dogs with GSD-Ia were initially treated with a helper-dependent adenovirus encoding a human G6Pase transgene (HDAd-cG6Pase serotype 5) on postnatal day 3. Unlike untreated dogs with GSD-Ia, all three dogs initially maintained normal blood glucose levels. After 6-22 months, vector-treated dogs developed hypoglycemia, anorexia and lethargy, suggesting that the HDAd-cG6Pase serotype 5 vector had lost efficacy. Liver biopsies collected at this time revealed significantly elevated hepatic G6Pase activity and reduced glycogen content, when compared with affected dogs treated only by frequent feeding. Subsequently, the HDAd-cG6Pase serotype 2 vector was administered to two dogs, and hypoglycemia was reversed; however, renal dysfunction and recurrent hypoglycemia complicated their management. Administration of a serotype 2 HDAd vector prolonged survival in one GSD-Ia dog to 12 months of age and 36 months of age in the other, but the persistence of long-term complications limited HDAd vectors in the canine model for GSD-Ia.

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

Devising novel strategies against vector mosquitoes and house flies

USDA-ARS?s Scientific Manuscript database

In 1932, the United States Department of Agriculture established an entomological research laboratory in Orlando, Florida. The initial focus of the program was on investigations of mosquitoes (including malaria vectors under conditions “simulating those of South Pacific jungles”) and other insects ...

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.

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.

Optimal four-impulse rendezvous between coplanar elliptical orbits

NASA Astrophysics Data System (ADS)

Wang, JianXia; Baoyin, HeXi; Li, JunFeng; Sun, FuChun

2011-04-01

Rendezvous in circular or near circular orbits has been investigated in great detail, while rendezvous in arbitrary eccentricity elliptical orbits is not sufficiently explored. Among the various optimization methods proposed for fuel optimal orbital rendezvous, Lawden's primer vector theory is favored by many researchers with its clear physical concept and simplicity in solution. Prussing has applied the primer vector optimization theory to minimum-fuel, multiple-impulse, time-fixed orbital rendezvous in a near circular orbit and achieved great success. Extending Prussing's work, this paper will employ the primer vector theory to study trajectory optimization problems of arbitrary eccentricity elliptical orbit rendezvous. Based on linearized equations of relative motion on elliptical reference orbit (referred to as T-H equations), the primer vector theory is used to deal with time-fixed multiple-impulse optimal rendezvous between two coplanar, coaxial elliptical orbits with arbitrary large eccentricity. A parameter adjustment method is developed for the prime vector to satisfy the Lawden's necessary condition for the optimal solution. Finally, the optimal multiple-impulse rendezvous solution including the time, direction and magnitudes of the impulse is obtained by solving the two-point boundary value problem. The rendezvous error of the linearized equation is also analyzed. The simulation results confirmed the analyzed results that the rendezvous error is small for the small eccentricity case and is large for the higher eccentricity. For better rendezvous accuracy of high eccentricity orbits, a combined method of multiplier penalty function with the simplex search method is used for local optimization. The simplex search method is sensitive to the initial values of optimization variables, but the simulation results show that initial values with the primer vector theory, and the local optimization algorithm can improve the rendezvous accuracy effectively with fast convergence, because the optimal results obtained by the primer vector theory are already very close to the actual optimal solution. If the initial values are taken randomly, it is difficult to converge to the optimal solution.

Predicting areas of sustainable error growth in quasigeostrophic flows using perturbation alignment properties

NASA Astrophysics Data System (ADS)

Rivière, G.; Hua, B. L.

2004-10-01

A new perturbation initialization method is used to quantify error growth due to inaccuracies of the forecast model initial conditions in a quasigeostrophic box ocean model describing a wind-driven double gyre circulation. This method is based on recent analytical results on Lagrangian alignment dynamics of the perturbation velocity vector in quasigeostrophic flows. More specifically, it consists in initializing a unique perturbation from the sole knowledge of the control flow properties at the initial time of the forecast and whose velocity vector orientation satisfies a Lagrangian equilibrium criterion. This Alignment-based Initialization method is hereafter denoted as the AI method.In terms of spatial distribution of the errors, we have compared favorably the AI error forecast with the mean error obtained with a Monte-Carlo ensemble prediction. It is shown that the AI forecast is on average as efficient as the error forecast initialized with the leading singular vector for the palenstrophy norm, and significantly more efficient than that for total energy and enstrophy norms. Furthermore, a more precise examination shows that the AI forecast is systematically relevant for all control flows whereas the palenstrophy singular vector forecast leads sometimes to very good scores and sometimes to very bad ones.A principal component analysis at the final time of the forecast shows that the AI mode spatial structure is comparable to that of the first eigenvector of the error covariance matrix for a "bred mode" ensemble. Furthermore, the kinetic energy of the AI mode grows at the same constant rate as that of the "bred modes" from the initial time to the final time of the forecast and is therefore characterized by a sustained phase of error growth. In this sense, the AI mode based on Lagrangian dynamics of the perturbation velocity orientation provides a rationale of the "bred mode" behavior.

Weak localization of magnons in chiral magnets

NASA Astrophysics Data System (ADS)

Evers, Martin; Müller, Cord A.; Nowak, Ulrich

2018-05-01

We report on the impact of the Dzyaloshinskii-Moriya interaction on the coherent backscattering of spin waves in a disordered magnetic material. This interaction breaks the inversion symmetry of the spin-wave dispersion relation, such that ωk=ω2 KI-k≠ω-k , where KI is related to the Dzyaloshinskii-Moriya vectors. The nonequivalence of k and -k also means that time-reversal symmetry is broken. As a result of numerical investigations we find that the backscattering peak of a wave packet with initial wave vector k0 shifts from -k0 to 2 KI-k0 , such that the backscattering wave vector and the initial wave vector are in general no longer antiparallel. The shifted coherence condition is explained by a diagrammatic approach and opens up an avenue to measure sign and magnitude of the Dzyaloshinskii-Moriya interaction in weakly disordered chiral magnets. Surprisingly, although time-reversal symmetry is broken, our system shows coherent backscattering as a manifestation of weak localization, which is due to the fact that reciprocity is still preserved.

Shape Sensing Using a Multi-Core Optical Fiber Having an Arbitrary Initial Shape in the Presence of Extrinsic Forces

NASA Technical Reports Server (NTRS)

Rogge, Matthew D. (Inventor); Moore, Jason P. (Inventor)

2014-01-01

Shape of a multi-core optical fiber is determined by positioning the fiber in an arbitrary initial shape and measuring strain over the fiber's length using strain sensors. A three-coordinate p-vector is defined for each core as a function of the distance of the corresponding cores from a center point of the fiber and a bending angle of the cores. The method includes calculating, via a controller, an applied strain value of the fiber using the p-vector and the measured strain for each core, and calculating strain due to bending as a function of the measured and the applied strain values. Additionally, an apparent local curvature vector is defined for each core as a function of the calculated strain due to bending. Curvature and bend direction are calculated using the apparent local curvature vector, and fiber shape is determined via the controller using the calculated curvature and bend direction.

Predictors of initial weight loss among women with abdominal obesity: a path model using self-efficacy and health-promoting behaviour.

PubMed

Choo, Jina; Kang, Hyuncheol

2015-05-01

To identify predictors of initial weight loss among women with abdominal obesity by using a path model. Successful weight loss in the initial stages of long-term weight management may promote weight loss maintenance. A longitudinal study design. Study participants were 75 women with abdominal obesity, who were enrolled in a 12-month Community-based Heart and Weight Management Trial and followed until a 6-month assessment. The Weight Efficacy Lifestyle, Exercise Self-Efficacy and Health Promoting Lifestyle Profile-II measured diet self-efficacy, exercise self-efficacy and health-promoting behaviour respectively. All endogenous and exogenous variables used in our path model were change variables from baseline to 6 months. Data were collected between May 2011-May 2012. Based on the path model, increases in both diet and exercise self-efficacy had significant effects on increases in health-promoting behaviour. Increases in diet self-efficacy had a significant indirect effect on initial weight loss via increases in health-promoting behaviour. Increases in health-promoting behaviour had a significant effect on initial weight loss. Among women with abdominal obesity, increased diet self-efficacy and health-promoting behaviour were predictors of initial weight loss. A mechanism by which increased diet self-efficacy predicts initial weight loss may be partially attributable to health-promoting behavioural change. However, more work is still needed to verify causality. Based on the current findings, intensive nursing strategies for increasing self-efficacy for weight control and health-promoting behaviour may be essential components for better weight loss in the initial stage of a weight management intervention. © 2015 John Wiley & Sons Ltd.

SAGRAD: A Program for Neural Network Training with Simulated Annealing and the Conjugate Gradient Method

PubMed Central

Bernal, Javier; Torres-Jimenez, Jose

2015-01-01

SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller’s scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller’s algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller’s algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller’s algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data. PMID:26958442

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

PubMed

Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting

PubMed Central

Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an “optimal” weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds. PMID:27382627

Simple algorithm for improved security in the FDDI protocol

NASA Astrophysics Data System (ADS)

Lundy, G. M.; Jones, Benjamin

1993-02-01

We propose a modification to the Fiber Distributed Data Interface (FDDI) protocol based on a simple algorithm which will improve confidential communication capability. This proposed modification provides a simple and reliable system which exploits some of the inherent security properties in a fiber optic ring network. This method differs from conventional methods in that end to end encryption can be facilitated at the media access control sublayer of the data link layer in the OSI network model. Our method is based on a variation of the bit stream cipher method. The transmitting station takes the intended confidential message and uses a simple modulo two addition operation against an initialization vector. The encrypted message is virtually unbreakable without the initialization vector. None of the stations on the ring will have access to both the encrypted message and the initialization vector except the transmitting and receiving stations. The generation of the initialization vector is unique for each confidential transmission and thus provides a unique approach to the key distribution problem. The FDDI protocol is of particular interest to the military in terms of LAN/MAN implementations. Both the Army and the Navy are considering the standard as the basis for future network systems. A simple and reliable security mechanism with the potential to support realtime communications is a necessary consideration in the implementation of these systems. The proposed method offers several advantages over traditional methods in terms of speed, reliability, and standardization.

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.

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.

78 FR 732 - Disease, Disability, and Injury Prevention and Control Special Emphasis Panel (SEP): Initial Review

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-04

... announced below concerns Identification, Surveillance, and Control of Vector-Borne and Zoonotic Infectious... in response to ``Identification, Surveillance, and Control of Vector- Borne and Zoonotic Infectious... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Disease...

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.

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…

Recruitment and Retention for a Weight Loss Maintenance Trial Involving Weight Loss Prior to Randomization

PubMed Central

Grubber, J. M.; McVay, M. A.; Olsen, M. K.; Bolton, J.; Gierisch, J. M.; Taylor, S. S.; Maciejewski, M. L.; Yancy, W. S.

2016-01-01

Abstract Objective A weight loss maintenance trial involving weight loss prior to randomization is challenging to implement due to the potential for dropout and insufficient weight loss. We examined rates and correlates of non‐initiation, dropout, and insufficient weight loss during a weight loss maintenance trial. Methods The MAINTAIN trial involved a 16‐week weight loss program followed by randomization among participants losing at least 4 kg. Psychosocial measures were administered during a screening visit. Weight was obtained at the first group session and 16 weeks later to determine eligibility for randomization. Results Of 573 patients who screened as eligible, 69 failed to initiate the weight loss program. In adjusted analyses, failure to initiate was associated with lower age, lack of a support person, and less encouragement for making dietary changes. Among participants who initiated, 200 dropped out, 82 lost insufficient weight, and 222 lost sufficient weight for randomization. Compared to losing sufficient weight, dropping out was associated with younger age and tobacco use, whereas losing insufficient weight was associated with non‐White race and controlled motivation for physical activity. Conclusions Studies should be conducted to evaluate strategies to maximize recruitment and retention of subgroups that are less likely to initiate and be retained in weight loss maintenance trials. PMID:28090340

A semi-automatic method for analysis of landscape elements using Shuttle Radar Topography Mission and Landsat ETM+ data

NASA Astrophysics Data System (ADS)

Ehsani, Amir Houshang; Quiel, Friedrich

2009-02-01

In this paper, we demonstrate artificial neural networks—self-organizing map (SOM)—as a semi-automatic method for extraction and analysis of landscape elements in the man and biosphere reserve "Eastern Carpathians". The Shuttle Radar Topography Mission (SRTM) collected data to produce generally available digital elevation models (DEM). Together with Landsat Thematic Mapper data, this provides a unique, consistent and nearly worldwide data set. To integrate the DEM with Landsat data, it was re-projected from geographic coordinates to UTM with 28.5 m spatial resolution using cubic convolution interpolation. To provide quantitative morphometric parameters, first-order (slope) and second-order derivatives of the DEM—minimum curvature, maximum curvature and cross-sectional curvature—were calculated by fitting a bivariate quadratic surface with a window size of 9×9 pixels. These surface curvatures are strongly related to landform features and geomorphological processes. Four morphometric parameters and seven Landsat-enhanced thematic mapper (ETM+) bands were used as input for the SOM algorithm. Once the network weights have been randomly initialized, different learning parameter sets, e.g. initial radius, final radius and number of iterations, were investigated. An optimal SOM with 20 classes using 1000 iterations and a final neighborhood radius of 0.05 provided a low average quantization error of 0.3394 and was used for further analysis. The effect of randomization of initial weights for optimal SOM was also studied. Feature space analysis, three-dimensional inspection and auxiliary data facilitated the assignment of semantic meaning to the output classes in terms of landform, based on morphometric analysis, and land use, based on spectral properties. Results were displayed as thematic map of landscape elements according to form, cover and slope. Spectral and morphometric signature analysis with corresponding zoom samples superimposed by contour lines were compared in detail to clarify the role of morphometric parameters to separate landscape elements. The results revealed the efficiency of SOM to integrate SRTM and Landsat data in landscape analysis. Despite the stochastic nature of SOM, the results in this particular study are not sensitive to randomization of initial weight vectors if many iterations are used. This procedure is reproducible for the same application with consistent results.

Linear Transformation Method for Multinuclide Decay Calculation

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

Ding Yuan

2010-12-29

A linear transformation method for generic multinuclide decay calculations is presented together with its properties and implications. The method takes advantage of the linear form of the decay solution N(t) = F(t)N{sub 0}, where N(t) is a column vector that represents the numbers of atoms of the radioactive nuclides in the decay chain, N{sub 0} is the initial value vector of N(t), and F(t) is a lower triangular matrix whose time-dependent elements are independent of the initial values of the system.

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.

Predictability of a Coupled Model of ENSO Using Singular Vector Analysis: Optimal Growth and Forecast Skill.

NASA Astrophysics Data System (ADS)

Xue, Yan

The optimal growth and its relationship with the forecast skill of the Zebiak and Cane model are studied using a simple statistical model best fit to the original nonlinear model and local linear tangent models about idealized climatic states (the mean background and ENSO cycles in a long model run), and the actual forecast states, including two sets of runs using two different initialization procedures. The seasonally varying Markov model best fit to a suite of 3-year forecasts in a reduced EOF space (18 EOFs) fits the original nonlinear model reasonably well and has comparable or better forecast skill. The initial error growth in a linear evolution operator A is governed by the eigenvalues of A^{T}A, and the square roots of eigenvalues and eigenvectors of A^{T}A are named singular values and singular vectors. One dominant growing singular vector is found, and the optimal 6 month growth rate is largest for a (boreal) spring start and smallest for a fall start. Most of the variation in the optimal growth rate of the two forecasts is seasonal, attributable to the seasonal variations in the mean background, except that in the cold events it is substantially suppressed. It is found that the mean background (zero anomaly) is the most unstable state, and the "forecast IC states" are more unstable than the "coupled model states". One dominant growing singular vector is found, characterized by north-south and east -west dipoles, convergent winds on the equator in the eastern Pacific and a deepened thermocline in the whole equatorial belt. This singular vector is insensitive to initial time and optimization time, but its final pattern is a strong function of initial states. The ENSO system is inherently unpredictable for the dominant singular vector can amplify 5-fold to 24-fold in 6 months and evolve into the large scales characteristic of ENSO. However, the inherent ENSO predictability is only a secondary factor, while the mismatches between the model and data is a primary factor controlling the current forecast skill.

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.

Multi-modulus algorithm based on global artificial fish swarm intelligent optimization of DNA encoding sequences.

PubMed

Guo, Y C; Wang, H; Wu, H P; Zhang, M Q

2015-12-21

Aimed to address the defects of the large mean square error (MSE), and the slow convergence speed in equalizing the multi-modulus signals of the constant modulus algorithm (CMA), a multi-modulus algorithm (MMA) based on global artificial fish swarm (GAFS) intelligent optimization of DNA encoding sequences (GAFS-DNA-MMA) was proposed. To improve the convergence rate and reduce the MSE, this proposed algorithm adopted an encoding method based on DNA nucleotide chains to provide a possible solution to the problem. Furthermore, the GAFS algorithm, with its fast convergence and global search ability, was used to find the best sequence. The real and imaginary parts of the initial optimal weight vector of MMA were obtained through DNA coding of the best sequence. The simulation results show that the proposed algorithm has a faster convergence speed and smaller MSE in comparison with the CMA, the MMA, and the AFS-DNA-MMA.

Epidemiological Implications of Host Biodiversity and Vector Biology: Key Insights from Simple Models.

PubMed

Dobson, Andrew D M; Auld, Stuart K J R

2016-04-01

Models used to investigate the relationship between biodiversity change and vector-borne disease risk often do not explicitly include the vector; they instead rely on a frequency-dependent transmission function to represent vector dynamics. However, differences between classes of vector (e.g., ticks and insects) can cause discrepancies in epidemiological responses to environmental change. Using a pair of disease models (mosquito- and tick-borne), we simulated substitutive and additive biodiversity change (where noncompetent hosts replaced or were added to competent hosts, respectively), while considering different relationships between vector and host densities. We found important differences between classes of vector, including an increased likelihood of amplified disease risk under additive biodiversity change in mosquito models, driven by higher vector biting rates. We also draw attention to more general phenomena, such as a negative relationship between initial infection prevalence in vectors and likelihood of dilution, and the potential for a rise in density of infected vectors to occur simultaneously with a decline in proportion of infected hosts. This has important implications; the density of infected vectors is the most valid metric for primarily zoonotic infections, while the proportion of infected hosts is more relevant for infections where humans are a primary host.

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.

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

PubMed

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

2014-07-24

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

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 .

Changes in body weight after treatment of primary hypothyroidism with levothyroxine.

PubMed

Lee, Sun Y; Braverman, Lewis E; Pearce, Elizabeth N

2014-11-01

Surprisingly few studies have examined weight change in hypothyroid patients after initiation of levothyroxine (LT4) therapy. Our study aimed to investigate weight change after initiation of LT4 treatment for primary hypothyroidism. Using electronic medical records from Boston Medical Center, Boston, Massachusetts, we performed a retrospective cohort study between January 1, 2003, and February 1, 2011. Adults ≥18 years of age with newly diagnosed primary hypothyroidism with an initial thyroid-stimulating hormone (TSH) level ≥10 mIU/L were identified. Patients with postsurgical hypothyroidism, thyroid cancer, and a history of radioactive iodine or head/neck irradiation, congestive heart failure, anorexia nervosa, end-stage renal disease, cirrhosis, pregnancy, or use of prescription weight-loss medications were excluded. TSH and weight at diagnosis and up to 24 months after LT4 initiation were collected. Weight change was assessed at the first posttreatment serum TSH level <5 mIU/L. A total of 101 patients (mean age, 48 ± 15 years; 71% women) were included. Initial median TSH was 18.3 mIU/L (range, 10.1 to 710.5 mIU/L) and initial median weight was 79.6 kg (range 41.5 to 167.5 kg). Posttreatment median TSH level was 2.3 mIU/L (range, 0.04 to 5 mIU/L), and weight change at a median of 5 months (range, 1.1 to 25.6 months) was -0.1 kg (range, -20.6 to 7.7 kg). Initial median body mass index (BMI) of 95 of the patients was 29.3 kg/m2 (range, 19.5 to 56.1 kg/m2), and the median change in BMI was -0.1 kg/m2 (range, -7.1 to 3.3 kg/m2). Only 52% of patients lost weight, with a mean weight loss of 3.8 ± 4.4 kg. Gender, race, education, insurance type, age, initial TSH level, time to normalization of TSH, and initial weight were not associated with changes in weight or BMI. Contrary to popular belief, our study of 101 patients with primary hypothyroidism showed that no significant weight change occurs after initiation of LT4 treatment.

[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.

On the electromagnetic fields, Poynting vector, and peak power radiated by lightning return strokes

NASA Technical Reports Server (NTRS)

Krider, E. P.

1992-01-01

The initial radiation fields, Poynting vector, and total electromagnetic power that a vertical return stroke radiates into the upper half space have been computed when the speed of the stroke, nu, is a significant fraction of the speed of light, c, assuming that at large distances and early times the source is an infinitesimal dipole. The initial current is also assumed to satisfy the transmission-line model with a constant nu and to be perpendicular to an infinite, perfectly conducting ground. The effect of a large nu is to increase the radiation fields by a factor of (1-beta-sq cos-sq theta) exp -1, where beta = nu/c and theta is measured from the vertical, and the Poynting vector by a factor of (1-beta-sq cos-sq theta) exp -2.

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…

Preoperative fat-free mass: a predictive factor of weight loss after gastric bypass.

PubMed

Robert, Maud; Pelascini, Elise; Disse, Emmanuel; Espalieu, Philippe; Poncet, Gilles; Laville, Martine; Gouillat, Christian

2013-04-01

Weight loss failure occurs in 8% to 40% of patients after gastric bypass (GBP). The aim of our study was to analyse the predictive factors of weight loss at 1 year so as to select the best candidates for this surgery and reduce the failures. We included 73 patients treated by laparoscopic GBP. We retrospectively analysed the predictive factors of weight loss in kilograms as well as excess weight loss in percentage (EWL%) at 1 year. The population was divided into tertiles so as to compare the sub-group with the highest weight loss with the sub-group with the least satisfactory results. The significantly predictive factors of a better weight loss in kilograms were male, higher initial weight (144 versus 118 kg, p = 0.002), a significant early weight loss and a higher preoperative percentage of fat-free mass (FFM%; p = 0.03). A higher FFM% was also associated with a better EWL% (p = 0.004). The preoperative FFM (in kilograms) was the principal factor accounting for the weight loss at 1 year regardless of age, gender, height and initial body mass index (BMI; p < 0.0001). There was a better correlation between FFM and weight loss (Spearman test, p = 0.0001) than between initial BMI and weight loss (p = 0.016). We estimated weight loss at 1 year according to initial FFM using the formula: 0.5 kg of lost weight per kilogram of initial FFM. The initial FFM appears to be a decisive factor in the success of GBP. Thus, the sarcopoenic patients would appear to be less suitable candidates for this surgery.

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

Learning with incomplete information in the committee machine.

PubMed

Bergmann, Urs M; Kühn, Reimer; Stamatescu, Ion-Olimpiu

2009-12-01

We study the problem of learning with incomplete information in a student-teacher setup for the committee machine. The learning algorithm combines unsupervised Hebbian learning of a series of associations with a delayed reinforcement step, in which the set of previously learnt associations is partly and indiscriminately unlearnt, to an extent that depends on the success rate of the student on these previously learnt associations. The relevant learning parameter lambda represents the strength of Hebbian learning. A coarse-grained analysis of the system yields a set of differential equations for overlaps of student and teacher weight vectors, whose solutions provide a complete description of the learning behavior. It reveals complicated dynamics showing that perfect generalization can be obtained if the learning parameter exceeds a threshold lambda ( c ), and if the initial value of the overlap between student and teacher weights is non-zero. In case of convergence, the generalization error exhibits a power law decay as a function of the number of examples used in training, with an exponent that depends on the parameter lambda. An investigation of the system flow in a subspace with broken permutation symmetry between hidden units reveals a bifurcation point lambda* above which perfect generalization does not depend on initial conditions. Finally, we demonstrate that cases of a complexity mismatch between student and teacher are optimally resolved in the sense that an over-complex student can emulate a less complex teacher rule, while an under-complex student reaches a state which realizes the minimal generalization error compatible with the complexity mismatch.

Improving Dengue Virus Capture Rates in Humans and Vectors in Kamphaeng Phet Province, Thailand, Using an Enhanced Spatiotemporal Surveillance Strategy

PubMed Central

Thomas, Stephen J.; Aldstadt, Jared; Jarman, Richard G.; Buddhari, Darunee; Yoon, In-Kyu; Richardson, Jason H.; Ponlawat, Alongkot; Iamsirithaworn, Sopon; Scott, Thomas W.; Rothman, Alan L.; Gibbons, Robert V.; Lambrechts, Louis; Endy, Timothy P.

2015-01-01

Dengue is of public health importance in tropical and sub-tropical regions. Dengue virus (DENV) transmission dynamics was studied in Kamphaeng Phet Province, Thailand, using an enhanced spatiotemporal surveillance of 93 hospitalized subjects with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled from 208 houses with household members with a history of fever, located within a 200-m radius of an initiate case. Of 409 associates, 86 (21%) had laboratory-confirmed DENV infection. A total of 63 (1.8%) of the 3,565 mosquitoes collected were dengue polymerase chain reaction positive (PCR+). There was a significant relationship between spatial proximity to the initiate case and likelihood of detecting DENV from associate cases and Aedes mosquitoes. The viral detection rate from human hosts and mosquito vectors in this study was higher than previously observed by the study team in the same geographic area using different methodologies. We propose that the sampling strategy used in this study could support surveillance of DENV transmission and vector interactions. PMID:25986580

Contribution of volcanic forcing to the initiation of the Black Death Epidemic

NASA Astrophysics Data System (ADS)

Fell, Henry; Baldini, James; Dodds, Ben

2017-04-01

The 14th Century plague epidemic, commonly termed the Black Death, coincided with the tumultuous climatic shift from the relative stability of the Medieval Climate Anomaly (MCA) to the initiation of the Little Ice Age (LIA). Plague is predominantly a vector borne disease that is spread through the transmission of the Yersinia pestis bacteria. This bacterium may have originated in the rodent populations of the Tibetan Plateau and later spread rapidly westward though Eurasia after vector transmission to humans. Several studies have determined that Asian rodent and vector populations are highly sensitive to climatic perturbations. The Samalas eruption of 1257 was the largest injection of aerosols in the Common Era and therefore probably had a significant climatic effect. Through a range of proxy records across Eurasia we reconstruct the climate for the period immediately preceding the outbreak of plague. This study investigates the interaction between the Samalas eruption of 1257, the climatic response to the event and the potential effect on the initiation of the Black Death epidemic which shaped population and culture across Eurasia for centuries.

Models of Disease Vector Control: When Can Aggressive Initial Intervention Lower Long-Term Cost?

PubMed

Oduro, Bismark; Grijalva, Mario J; Just, Winfried

2018-04-01

Insecticide spraying of housing units is an important control measure for vector-borne infections such as Chagas disease. As vectors may invade both from other infested houses and sylvatic areas and as the effectiveness of insecticide wears off over time, the dynamics of (re)infestations can be approximated by [Formula: see text]-type models with a reservoir, where housing units are treated as hosts, and insecticide spraying corresponds to removal of hosts. Here, we investigate three ODE-based models of this type. We describe a dual-rate effect where an initially very high spraying rate can push the system into a region of the state space with low endemic levels of infestation that can be maintained in the long run at relatively moderate cost, while in the absence of an aggressive initial intervention the same average cost would only allow a much less significant reduction in long-term infestation levels. We determine some sufficient and some necessary conditions under which this effect occurs and show that it is robust in models that incorporate some heterogeneity in the relevant properties of housing units.

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

76 FR 13619 - Disease, Disability, and Injury Prevention and Control Special Emphasis Panel (SEP): Funding...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-14

... Institute Pasteur of Madagascar and the Centers for Disease Control and Prevention on Malaria and Vector... Malaria Prevention and Control in the Republic of Uganda as Part of the President's Malaria Initiative... Institute Pasteur of Madagascar and the Centers for Disease Control and Prevention on Malaria and Vector...

Searches for transverse momentum dependent flow vector fluctuations in Pb-Pb and p-Pb collisions at the LHC

NASA Astrophysics Data System (ADS)

Acharya, S.; Adamová, D.; Adolfsson, J.; Aggarwal, M. M.; Aglieri Rinella, G.; Agnello, M.; Agrawal, N.; Ahammed, Z.; Ahmad, N.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Alam, S. N.; Alba, J. L. B.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alfaro Molina, R.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altenkamper, L.; Altsybeev, I.; Alves Garcia Prado, C.; Andrei, C.; Andreou, D.; Andrews, H. A.; Andronic, A.; Anguelov, V.; Anson, C.; Antičić, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Aphecetche, L.; Appelshäuser, H.; Arcelli, S.; Arnaldi, R.; Arnold, O. W.; Arsene, I. C.; Arslandok, M.; Audurier, B.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badalà, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baral, R. C.; Barbano, A. M.; Barbera, R.; Barile, F.; Barioglio, L.; Barnaföldi, G. G.; Barnby, L. S.; Barret, V.; Bartalini, P.; Barth, K.; Bartsch, E.; Basile, M.; Bastid, N.; Basu, S.; Bathen, B.; Batigne, G.; Batyunya, B.; Batzing, P. C.; Bearden, I. G.; Beck, H.; Bedda, C.; Behera, N. K.; Belikov, I.; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V.; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhati, A. K.; Bhattacharjee, B.; Bhom, J.; Bianchi, L.; Bianchi, N.; Bianchin, C.; Bielčík, J.; Bielčíková, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Blair, J. T.; Blau, D.; Blume, C.; Boca, G.; Bock, F.; Bogdanov, A.; Boldizsár, L.; Bombara, M.; Bonomi, G.; Bonora, M.; Book, J.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Bratrud, L.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Cabala, J.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camerini, P.; Capon, A. A.; Carena, F.; Carena, W.; Carnesecchi, F.; Castillo Castellanos, J.; Castro, A. J.; Casula, E. A. R.; Ceballos Sanchez, C.; Cerello, P.; Chandra, S.; Chang, B.; Chapeland, S.; Chartier, M.; Charvet, J. L.; Chattopadhyay, S.; Chattopadhyay, S.; Chauvin, A.; Cherney, M.; Cheshkov, C.; Cheynis, B.; Chibante Barroso, V.; Chinellato, D. D.; Cho, S.; Chochula, P.; Choi, K.; Chojnacki, M.; Choudhury, S.; Chowdhury, T.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Chung, S. U.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Concas, M.; Conesa Balbastre, G.; Conesa del Valle, Z.; Connors, M. E.; Contreras, J. G.; Cormier, T. M.; Corrales Morales, Y.; Cortés Maldonado, I.; Cortese, P.; Cosentino, M. R.; Costa, F.; Costanza, S.; Crkovská, J.; Crochet, P.; Cuautle, E.; Cunqueiro, L.; Dahms, T.; Dainese, A.; Danisch, M. C.; Danu, A.; Das, D.; Das, I.; Das, S.; Dash, A.; Dash, S.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Degenhardt, H. F.; Deisting, A.; Deloff, A.; Deplano, C.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Di Nezza, P.; Di Ruzza, B.; Diaz Corchero, M. A.; Dietel, T.; Dillenseger, P.; Divià, R.; Djuvsland, Ø.; Dobrin, A.; Domenicis Gimenez, D.; Dönigus, B.; Dordic, O.; Doremalen, L. V. V.; Drozhzhova, T.; Dubey, A. K.; Dubla, A.; Ducroux, L.; Duggal, A. K.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Endress, E.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Espagnon, B.; Esumi, S.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Fabbietti, L.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Ferencei, J.; Fernández Téllez, A.; Ferreiro, E. G.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Figueredo, M. A. S.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiore, E. M.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francescon, A.; Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Fusco Girard, M.; Gaardhøje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Gallio, M.; Galvan, C. D.; Ganoti, P.; Gao, C.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Garg, P.; Gargiulo, C.; Gasik, P.; Gauger, E. F.; Gay Ducati, M. B.; Germain, M.; Ghosh, J.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Gladysz-Dziadus, E.; Glässel, P.; Goméz Coral, D. M.; Gomez Ramirez, A.; Gonzalez, A. S.; Gonzalez, V.; González-Zamora, P.; Gorbunov, S.; Görlich, L.; Gotovac, S.; Grabski, V.; Graczykowski, L. K.; Graham, K. L.; Greiner, L.; Grelli, A.; Grigoras, C.; Grigoriev, V.; Grigoryan, A.; Grigoryan, S.; Grion, N.; Gronefeld, J. M.; Grosa, F.; Grosse-Oetringhaus, J. F.; Grosso, R.; Gruber, L.; Guber, F.; Guernane, R.; Guerzoni, B.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Guzman, I. B.; Haake, R.; Hadjidakis, C.; Hamagaki, H.; Hamar, G.; Hamon, J. C.; Haque, M. R.; Harris, J. W.; Harton, A.; Hassan, H.; Hatzifotiadou, D.; Hayashi, S.; Heckel, S. T.; Hellbär, E.; Helstrup, H.; Herghelegiu, A.; Herrera Corral, G.; Herrmann, F.; Hess, B. A.; Hetland, K. F.; Hillemanns, H.; Hills, C.; Hippolyte, B.; Hladky, J.; Hohlweger, B.; Horak, D.; Hornung, S.; Hosokawa, R.; Hristov, P.; Hughes, C.; Humanic, T. J.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Iga Buitron, S. A.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Irfan, M.; Isakov, V.; Ivanov, M.; Ivanov, V.; Izucheev, V.; Jacak, B.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jaelani, S.; Jahnke, C.; Jakubowska, M. J.; Janik, M. A.; Jayarathna, P. H. S. Y.; Jena, C.; Jena, S.; Jercic, M.; Jimenez Bustamante, R. T.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kang, J. H.; Kaplin, V.; Kar, S.; Karasu Uysal, A.; Karavichev, O.; Karavicheva, T.; Karayan, L.; Karczmarczyk, P.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keijdener, D. L. D.; Keil, M.; Ketzer, B.; Khabanova, Z.; Khan, P.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Khatun, A.; Khuntia, A.; Kielbowicz, M. M.; Kileng, B.; Kim, B.; Kim, D.; Kim, D. W.; Kim, D. J.; Kim, H.; Kim, J. S.; Kim, J.; Kim, M.; Kim, M.; Kim, S.; Kim, T.; Kirsch, S.; Kisel, I.; Kiselev, S.; Kisiel, A.; Kiss, G.; Klay, J. L.; Klein, C.; Klein, J.; Klein-Bösing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Kollegger, T.; Kolojvari, A.; Kondratiev, V.; Kondratyeva, N.; Kondratyuk, E.; Konevskikh, A.; Konyushikhin, M.; Kopcik, M.; Kour, M.; Kouzinopoulos, C.; Kovalenko, O.; Kovalenko, V.; Kowalski, M.; Koyithatta Meethaleveedu, G.; Králik, I.; Kravčáková, A.; Krivda, M.; Krizek, F.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kučera, V.; Kuhn, C.; Kuijer, P. G.; Kumar, A.; Kumar, J.; Kumar, L.; Kumar, S.; Kundu, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kuryakin, A.; Kushpil, S.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lagana Fernandes, C.; Lai, Y. S.; Lakomov, I.; Langoy, R.; Lapidus, K.; Lara, C.; Lardeux, A.; Lattuca, A.; Laudi, E.; Lavicka, R.; Lazaridis, L.; Lea, R.; Leardini, L.; Lee, S.; Lehas, F.; Lehner, S.; Lehrbach, J.; Lemmon, R. C.; Lenti, V.; Leogrande, E.; León Monzón, I.; Lévai, P.; Li, S.; Li, X.; Lien, J.; Lietava, R.; Lim, B.; Lindal, S.; Lindenstruth, V.; Lindsay, S. W.; Lippmann, C.; Lisa, M. A.; Litichevskyi, V.; Ljunggren, H. M.; Llope, W. J.; Lodato, D. F.; Loenne, P. I.; Loginov, V.; Loizides, C.; Loncar, P.; Lopez, X.; López Torres, E.; Lowe, A.; Luettig, P.; Lunardon, M.; Luparello, G.; Lupi, M.; Lutz, T. H.; Maevskaya, A.; Mager, M.; Mahajan, S.; Mahmood, S. M.; Maire, A.; Majka, R. D.; Malaev, M.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V.; Manso, F.; Manzari, V.; Mao, Y.; Marchisone, M.; Mareš, J.; Margagliotti, G. V.; Margotti, A.; Margutti, J.; Marín, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martinengo, P.; Martinez, J. A. L.; Martínez, M. I.; Martínez García, G.; Martinez Pedreira, M.; Mas, A.; Masciocchi, S.; Masera, M.; Masoni, A.; Masson, E.; Mastroserio, A.; Mathis, A. M.; Matyja, A.; Mayer, C.; Mazer, J.; Mazzilli, M.; Mazzoni, M. A.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Mercado Pérez, J.; Meres, M.; Mhlanga, S.; Miake, Y.; Mieskolainen, M. M.; Mihaylov, D.; Mihaylov, D. L.; Mikhaylov, K.; Milano, L.; Milosevic, J.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, B.; Khan, M. Mohisin; Montes, E.; Moreira De Godoy, D. A.; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Muccifora, V.; Mudnic, E.; Mühlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Münning, K.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Myers, C. J.; Myrcha, J. W.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Narayan, A.; Naru, M. U.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; Nedosekin, A.; Negrao De Oliveira, R. A.; Nellen, L.; Nesbo, S. V.; Ng, F.; Nicassio, M.; Niculescu, M.; Niedziela, J.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V.; Nobuhiro, A.; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. C.; Norman, J.; Nyanin, A.; Nystrand, J.; Oeschler, H.; Oh, S.; Ohlson, A.; Okubo, T.; Olah, L.; Oleniacz, J.; Oliveira Da Silva, A. C.; Oliver, M. H.; Onderwaater, J.; Oppedisano, C.; Orava, R.; Oravec, M.; Ortiz Velasquez, A.; Oskarsson, A.; Otwinowski, J.; Oyama, K.; Pachmayer, Y.; Pacik, V.; Pagano, D.; Pagano, P.; Paić, G.; Palni, P.; Pan, J.; Pandey, A. K.; Panebianco, S.; Papikyan, V.; Pappalardo, G. S.; Pareek, P.; Park, J.; Parmar, S.; Passfeld, A.; Pathak, S. P.; Paticchio, V.; Patra, R. N.; Paul, B.; Pei, H.; Peitzmann, T.; Peng, X.; Pereira, L. G.; Pereira Da Costa, H.; Peresunko, D.; Perez Lezama, E.; Peskov, V.; Pestov, Y.; Petráček, V.; Petrov, V.; Petrovici, M.; Petta, C.; Pezzi, R. P.; Piano, S.; Pikna, M.; Pillot, P.; Pimentel, L. O. D. L.; Pinazza, O.; Pinsky, L.; Piyarathna, D. B.; Ploskon, M.; Planinic, M.; Pliquett, F.; Pluta, J.; Pochybova, S.; Podesta-Lerma, P. L. M.; Poghosyan, M. G.; Polichtchouk, B.; Poljak, N.; Poonsawat, W.; Pop, A.; Poppenborg, H.; Porteboeuf-Houssais, S.; Porter, J.; Pozdniakov, V.; Prasad, S. K.; Preghenella, R.; Prino, F.; Pruneau, C. A.; Pshenichnov, I.; Puccio, M.; Puddu, G.; Pujahari, P.; Punin, V.; Putschke, J.; Rachevski, A.; Raha, S.; Rajput, S.; Rak, J.; Rakotozafindrabe, A.; Ramello, L.; Rami, F.; Rana, D. B.; Raniwala, R.; Raniwala, S.; Räsänen, S. S.; Rascanu, B. T.; Rathee, D.; Ratza, V.; Ravasenga, I.; Read, K. F.; Redlich, K.; Rehman, A.; Reichelt, P.; Reidt, F.; Ren, X.; Renfordt, R.; Reolon, A. R.; Reshetin, A.; Reygers, K.; Riabov, V.; Ricci, R. A.; Richert, T.; Richter, M.; Riedler, P.; Riegler, W.; Riggi, F.; Ristea, C.; Rodríguez Cahuantzi, M.; Røed, K.; Rogochaya, E.; Rohr, D.; Röhrich, D.; Rokita, P. S.; Ronchetti, F.; Rosas, E. D.; Rosnet, P.; Rossi, A.; Rotondi, A.; Roukoutakis, F.; Roy, A.; Roy, C.; Roy, P.; Rubio Montero, A. J.; Rueda, O. V.; Rui, R.; Rumyantsev, B.; Rustamov, A.; Ryabinkin, E.; Ryabov, Y.; Rybicki, A.; Saarinen, S.; Sadhu, S.; Sadovsky, S.; Šafařík, K.; Saha, S. K.; Sahlmuller, B.; Sahoo, B.; Sahoo, P.; Sahoo, R.; Sahoo, S.; Sahu, P. K.; Saini, J.; Sakai, S.; Saleh, M. A.; Salzwedel, J.; Sambyal, S.; Samsonov, V.; Sandoval, A.; Sarkar, D.; Sarkar, N.; Sarma, P.; Sas, M. H. P.; Scapparone, E.; Scarlassara, F.; Scharenberg, R. P.; Scheid, H. S.; Schiaua, C.; Schicker, R.; Schmidt, C.; Schmidt, H. R.; Schmidt, M. O.; Schmidt, M.; Schuchmann, S.; Schukraft, J.; Schutz, Y.; Schwarz, K.; Schweda, K.; Scioli, G.; Scomparin, E.; Scott, R.; Šefčík, M.; Seger, J. E.; Sekiguchi, Y.; Sekihata, D.; Selyuzhenkov, I.; Senosi, K.; Senyukov, S.; Serradilla, E.; Sett, P.; Sevcenco, A.; Shabanov, A.; Shabetai, A.; Shahoyan, R.; Shaikh, W.; Shangaraev, A.; Sharma, A.; Sharma, A.; Sharma, M.; Sharma, M.; Sharma, N.; Sheikh, A. I.; Shigaki, K.; Shou, Q.; Shtejer, K.; Sibiriak, Y.; Siddhanta, S.; Sielewicz, K. M.; Siemiarczuk, T.; Silvermyr, D.; Silvestre, C.; Simatovic, G.; Simonetti, G.; Singaraju, R.; Singh, R.; Singhal, V.; Sinha, T.; Sitar, B.; Sitta, M.; Skaali, T. B.; Slupecki, M.; Smirnov, N.; Snellings, R. J. M.; Snellman, T. W.; Song, J.; Song, M.; Soramel, F.; Sorensen, S.; Sozzi, F.; Spiriti, E.; Sputowska, I.; Srivastava, B. K.; Stachel, J.; Stan, I.; Stankus, P.; Stenlund, E.; Stocco, D.; Strmen, P.; Suaide, A. A. P.; Sugitate, T.; Suire, C.; Suleymanov, M.; Suljic, M.; Sultanov, R.; Šumbera, M.; Sumowidagdo, S.; Suzuki, K.; Swain, S.; Szabo, A.; Szarka, I.; Tabassam, U.; Takahashi, J.; Tambave, G. J.; Tanaka, N.; Tarhini, M.; Tariq, M.; Tarzila, M. G.; Tauro, A.; Tejeda Muñoz, G.; Telesca, A.; Terasaki, K.; Terrevoli, C.; Teyssier, B.; Thakur, D.; Thakur, S.; Thomas, D.; Thoresen, F.; Tieulent, R.; Tikhonov, A.; Timmins, A. R.; Toia, A.; Tripathy, S.; Trogolo, S.; Trombetta, G.; Tropp, L.; Trubnikov, V.; Trzaska, W. H.; Trzeciak, B. A.; Tsuji, T.; Tumkin, A.; Turrisi, R.; Tveter, T. S.; Ullaland, K.; Umaka, E. N.; Uras, A.; Usai, G. L.; Utrobicic, A.; Vala, M.; Van Der Maarel, J.; Van Hoorne, J. W.; van Leeuwen, M.; Vanat, T.; Vande Vyvre, P.; Varga, D.; Vargas, A.; Vargyas, M.; Varma, R.; Vasileiou, M.; Vasiliev, A.; Vauthier, A.; Vázquez Doce, O.; Vechernin, V.; Veen, A. M.; Velure, A.; Vercellin, E.; Vergara Limón, S.; Vernet, R.; Vértesi, R.; Vickovic, L.; Vigolo, S.; Viinikainen, J.; Vilakazi, Z.; Villalobos Baillie, O.; Villatoro Tello, A.; Vinogradov, A.; Vinogradov, L.; Virgili, T.; Vislavicius, V.; Vodopyanov, A.; Völkl, M. A.; Voloshin, K.; Voloshin, S. A.; Volpe, G.; von Haller, B.; Vorobyev, I.; Voscek, D.; Vranic, D.; Vrláková, J.; Wagner, B.; Wang, H.; Wang, M.; Watanabe, D.; Watanabe, Y.; Weber, M.; Weber, S. G.; Weiser, D. F.; Wenzel, S. C.; Wessels, J. P.; Westerhoff, U.; Whitehead, A. M.; Wiechula, J.; Wikne, J.; Wilk, G.; Wilkinson, J.; Willems, G. A.; Williams, M. C. S.; Willsher, E.; Windelband, B.; Witt, W. E.; Yalcin, S.; Yamakawa, K.; Yang, P.; Yano, S.; Yin, Z.; Yokoyama, H.; Yoo, I.-K.; Yoon, J. H.; Yurchenko, V.; Zaccolo, V.; Zaman, A.; Zampolli, C.; Zanoli, H. J. C.; Zardoshti, N.; Zarochentsev, A.; Závada, P.; Zaviyalov, N.; Zbroszczyk, H.; Zhalov, M.; Zhang, H.; Zhang, X.; Zhang, Y.; Zhang, C.; Zhang, Z.; Zhao, C.; Zhigareva, N.; Zhou, D.; Zhou, Y.; Zhou, Z.; Zhu, H.; Zhu, J.; Zhu, X.; Zichichi, A.; Zimmermann, A.; Zimmermann, M. B.; Zinovjev, G.; Zmeskal, J.; Zou, S.

2017-09-01

The measurement of azimuthal correlations of charged particles is presented for Pb-Pb collisions at √{s_{NN}}=2.76 TeV and p-Pb collisions at √{s_{NN}}=5.02 TeV with the ALICE detector at the CERN Large Hadron Collider. These correlations are measured for the second, third and fourth order flow vector in the pseudorapidity region | η| < 0 .8 as a function of centrality and transverse momentum p T using two observables, to search for evidence of p T-dependent flow vector fluctuations. For Pb-Pb collisions at 2.76 TeV, the measurements indicate that p T-dependent fluctuations are only present for the second order flow vector. Similar results have been found for p-Pb collisions at 5.02 TeV. These measurements are compared to hydrodynamic model calculations with event-by-event geometry fluctuations in the initial state to constrain the initial conditions and transport properties of the matter created in Pb-Pb and p-Pb collisions. [Figure not available: see fulltext.

A comparison of breeding and ensemble transform vectors for global ensemble generation

NASA Astrophysics Data System (ADS)

Deng, Guo; Tian, Hua; Li, Xiaoli; Chen, Jing; Gong, Jiandong; Jiao, Meiyan

2012-02-01

To compare the initial perturbation techniques using breeding vectors and ensemble transform vectors, three ensemble prediction systems using both initial perturbation methods but with different ensemble member sizes based on the spectral model T213/L31 are constructed at the National Meteorological Center, China Meteorological Administration (NMC/CMA). A series of ensemble verification scores such as forecast skill of the ensemble mean, ensemble resolution, and ensemble reliability are introduced to identify the most important attributes of ensemble forecast systems. The results indicate that the ensemble transform technique is superior to the breeding vector method in light of the evaluation of anomaly correlation coefficient (ACC), which is a deterministic character of the ensemble mean, the root-mean-square error (RMSE) and spread, which are of probabilistic attributes, and the continuous ranked probability score (CRPS) and its decomposition. The advantage of the ensemble transform approach is attributed to its orthogonality among ensemble perturbations as well as its consistence with the data assimilation system. Therefore, this study may serve as a reference for configuration of the best ensemble prediction system to be used in operation.

E1(-)E4(+) adenoviral gene transfer vectors function as a "pro-life" signal to promote survival of primary human endothelial cells.

PubMed

Ramalingam, R; Rafii, S; Worgall, S; Brough, D E; Crystal, R G

1999-05-01

Although endothelial cells are quiescent and long-lived in vivo, when they are removed from blood vessels and cultured in vitro they die within days to weeks. In studies of the interaction of E1(-)E4(+) replication-deficient adenovirus (Ad) vectors and human endothelium, the cells remained quiescent and were viable for prolonged periods. Evaluation of these cultures showed that E1(-)E4(+) Ad vectors provide an "antiapoptotic" signal that, in association with an increase in the ratio of Bcl2 to Bax levels, induces the endothelial cells to enter a state of "suspended animation," remaining viable for at least 30 days, even in the absence of serum and growth factors. Although the mechanisms initiating these events are unclear, the antiapoptoic signal requires the presence of E4 genes in the vector genome, suggesting that one or more E4 open reading frames of subgroup C Ad initiate a "pro-life" program that modifies cultured endothelial cells to survive for prolonged periods.

Searches for transverse momentum dependent flow vector fluctuations in Pb-Pb and p-Pb collisions at the LHC

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

Acharya, S.; Adamová, D.; Adolfsson, J.

We present the measurement of azimuthal correlations of charged particles for Pb-Pb collisions at √ s NN =2.76 TeV and p-Pb collisions at √ s NN =5.02 TeV with the ALICE detector at the CERN Large Hadron Collider. These correlations are then measured for the second, third and fourth order flow vector in the pseudorapidity region |η| < 0.8 as a function of centrality and transverse momentum p T using two observables, to search for evidence of p T -dependent flow vector fluctuations. For Pb-Pb collisions at 2.76 TeV, the measurements indicate that p T -dependent fluctuations are only presentmore » for the second order flow vector. Similar results have been found for p-Pb collisions at 5.02 TeV. Our measurements are compared to hydrodynamic model calculations with event-by-event geometry fluctuations in the initial state to constrain the initial conditions and transport properties of the matter created in Pb–Pb and p–Pb collisions.« less

Searches for transverse momentum dependent flow vector fluctuations in Pb-Pb and p-Pb collisions at the LHC

DOE PAGES

Acharya, S.; Adamová, D.; Adolfsson, J.; ...

2017-09-01

We present the measurement of azimuthal correlations of charged particles for Pb-Pb collisions at √ s NN =2.76 TeV and p-Pb collisions at √ s NN =5.02 TeV with the ALICE detector at the CERN Large Hadron Collider. These correlations are then measured for the second, third and fourth order flow vector in the pseudorapidity region |η| < 0.8 as a function of centrality and transverse momentum p T using two observables, to search for evidence of p T -dependent flow vector fluctuations. For Pb-Pb collisions at 2.76 TeV, the measurements indicate that p T -dependent fluctuations are only presentmore » for the second order flow vector. Similar results have been found for p-Pb collisions at 5.02 TeV. Our measurements are compared to hydrodynamic model calculations with event-by-event geometry fluctuations in the initial state to constrain the initial conditions and transport properties of the matter created in Pb–Pb and p–Pb collisions.« less

A Critical Assessment of Vector Control for Dengue Prevention

PubMed Central

Achee, Nicole L.; Gould, Fred; Perkins, T. Alex; Reiner, Robert C.; Morrison, Amy C.; Ritchie, Scott A.; Gubler, Duane J.; Teyssou, Remy; Scott, Thomas W.

2015-01-01

Recently, the Vaccines to Vaccinate (v2V) initiative was reconfigured into the Partnership for Dengue Control (PDC), a multi-sponsored and independent initiative. This redirection is consistent with the growing consensus among the dengue-prevention community that no single intervention will be sufficient to control dengue disease. The PDC's expectation is that when an effective dengue virus (DENV) vaccine is commercially available, the public health community will continue to rely on vector control because the two strategies complement and enhance one another. Although the concept of integrated intervention for dengue prevention is gaining increasingly broader acceptance, to date, no consensus has been reached regarding the details of how and what combination of approaches can be most effectively implemented to manage disease. To fill that gap, the PDC proposed a three step process: (1) a critical assessment of current vector control tools and those under development, (2) outlining a research agenda for determining, in a definitive way, what existing tools work best, and (3) determining how to combine the best vector control options, which have systematically been defined in this process, with DENV vaccines. To address the first step, the PDC convened a meeting of international experts during November 2013 in Washington, DC, to critically assess existing vector control interventions and tools under development. This report summarizes those deliberations. PMID:25951103

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

Vectors a Fortran 90 module for 3-dimensional vector and dyadic arithmetic

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

Brock, B.C.

1998-02-01

A major advance contained in the new Fortran 90 language standard is the ability to define new data types and the operators associated with them. Writing computer code to implement computations with real and complex three-dimensional vectors and dyadics is greatly simplified if the equations can be implemented directly, without the need to code the vector arithmetic explicitly. The Fortran 90 module described here defines new data types for real and complex 3-dimensional vectors and dyadics, along with the common operations needed to work with these objects. Routines to allow convenient initialization and output of the new types are alsomore » included. In keeping with the philosophy of data abstraction, the details of the implementation of the data types are maintained private, and the functions and operators are made generic to simplify the combining of real, complex, single- and double-precision vectors and dyadics.« less

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

PubMed

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

2010-01-01

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

Silent Aircraft Initiative Concept Risk Assessment

NASA Technical Reports Server (NTRS)

Nickol, Craig L.

2008-01-01

A risk assessment of the Silent Aircraft Initiative's SAX-40 concept design for extremely low noise has been performed. A NASA team developed a list of 27 risk items, and evaluated the level of risk for each item in terms of the likelihood that the risk would occur and the consequences of the occurrence. The following risk items were identified as high risk, meaning that the combination of likelihood and consequence put them into the top one-fourth of the risk matrix: structures and weight prediction; boundary-layer ingestion (BLI) and inlet design; variable-area exhaust and thrust vectoring; displaced-threshold and continuous descent approach (CDA) operational concepts; cost; human factors; and overall noise performance. Several advanced-technology baseline concepts were created to serve as a basis for comparison to the SAX-40 concept. These comparisons indicate that the SAX-40 would have significantly greater research, development, test, and engineering (RDT&E) and production costs than a conventional aircraft with similar technology levels. Therefore, the cost of obtaining the extremely low noise capability that has been estimated for the SAX-40 is significant. The SAX-40 concept design proved successful in focusing attention toward low noise technologies and in raising public awareness of the issue.

Eco-bio-social research on dengue in Asia: a multicountry study on ecosystem and community-based approaches for the control of dengue vectors in urban and peri-urban Asia.

PubMed

Sommerfeld, Johannes; Kroeger, Axel

2012-12-01

This article provides an overview of methods and cross-site insights of a 5-year research and capacity building initiative conducted between 2006 and 2011 in six countries of South Asia (India, Sri Lanka) and South-East Asia (Indonesia, Myanmar, Philippines, Thailand).The initiative managed an interdisciplinary investigation of ecological, biological, and social (i.e., eco-bio-social) dimensions of dengue in urban and peri-urban areas, and developed community-based interventions aimed at reducing dengue vector breeding and viral transmission. The multicountry study comprised interdisciplinary research groups from six leading Asian research institutions. The groups conducted a detailed situation analysis to identify and characterize local eco-bio-social conditions, and formed a community-of-practice for EcoHealth research where group partners disseminated results and collaboratively developed site-specific intervention tools for vector-borne diseases. In sites where water containers produced more than 70% of Aedes pupae, interventions ranged from mechanical lid covers for containers to biological control. Where small discarded containers presented the main problem, groups experimented with solid waste management, composting and recycling schemes. Many intervention tools were locally produced and all tools were implemented through community partnership strategies. All sites developed socially and culturally appropriate health education materials. The study also mobilised and empowered women's, students' and community groups and at several sites organized new volunteer groups for environmental health. The initiative's programmes showed significant impact on vector densities in some sites. Other sites showed varying effect - partially attributable to the 'contamination' of control groups - yet led to significant outcomes at the community level where local groups united around broad interests in environmental hygiene and sanitation. The programme's findings are relevant for defining efficient, effective and ecologically sound vector control interventions based on local evidence and in accordance with WHO's strategy for integrated vector management.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

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.

Horizontal vectorization of electron repulsion integrals.

PubMed

Pritchard, Benjamin P; Chow, Edmond

2016-10-30

We present an efficient implementation of the Obara-Saika algorithm for the computation of electron repulsion integrals that utilizes vector intrinsics to calculate several primitive integrals concurrently in a SIMD vector. Initial benchmarks display a 2-4 times speedup with AVX instructions over comparable scalar code, depending on the basis set. Speedup over scalar code is found to be sensitive to the level of contraction of the basis set, and is best for (lAlB|lClD) quartets when lD  = 0 or lB=lD=0, which makes such a vectorization scheme particularly suitable for density fitting. The basic Obara-Saika algorithm, how it is vectorized, and the performance bottlenecks are analyzed and discussed. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Demand-supply gaps in human resources to combat vector-borne disease in India: capacity-building measures in medical entomology.

PubMed

Pandey, Anuja; Zodpey, Sanjay; Kumar, Raj

2015-01-01

Vector-borne diseases account for a significant proportion of the global burden of infectious disease. They are one of the greatest contributors to human mortality and morbidity in tropical settings, including India. The World Health Organization declared vector-borne diseases as theme for the year 2014, and thus called for renewed commitment to their prevention and control. Human resources are critical to support public health systems, and medical entomologists play a crucial role in public health efforts to combat vector-borne diseases. This paper aims to review the capacity-building initiatives in medical entomology in India, to understand the demand and supply of medical entomologists, and to give future direction for the initiation of need-based training in the country. A systematic, predefined approach, with three parallel strategies, was used to collect and assemble the data regarding medical entomology training in India and assess the demand-supply gap in medical entomologists in the country. The findings suggest that, considering the high burden of vector-borne diseases in the country and the growing need of health manpower specialized in medical entomology, the availability of specialized training in medical entomology is insufficient in terms of number and intake capacity. The demand analysis of medical entomologists in India suggests a wide gap in demand and supply, which needs to be addressed to cater for the burden of vector-borne diseases in the country.

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.

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.

Density-dependent host choice by disease vectors: epidemiological implications of the ideal free distribution.

PubMed

Basáñez, María-Gloria; Razali, Karina; Renz, Alfons; Kelly, David

2007-03-01

The proportion of vector blood meals taken on humans (the human blood index, h) appears as a squared term in classical expressions of the basic reproduction ratio (R(0)) for vector-borne infections. Consequently, R(0) varies non-linearly with h. Estimates of h, however, constitute mere snapshots of a parameter that is predicted, from evolutionary theory, to vary with vector and host abundance. We test this prediction using a population dynamics model of river blindness assuming that, before initiation of vector control or chemotherapy, recorded measures of vector density and human infection accurately represent endemic equilibrium. We obtain values of h that satisfy the condition that the effective reproduction ratio (R(e)) must equal 1 at equilibrium. Values of h thus obtained decrease with vector density, decrease with the vector:human ratio and make R(0) respond non-linearly rather than increase linearly with vector density. We conclude that if vectors are less able to obtain human blood meals as their density increases, antivectorial measures may not lead to proportional reductions in R(0) until very low vector levels are achieved. Density dependence in the contact rate of infectious diseases transmitted by insects may be an important non-linear process with implications for their epidemiology and control.

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.

A feature-based approach to modeling protein-protein interaction hot spots.

PubMed

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-05-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to pi-related interactions, especially pi . . . pi interactions.

Extended Minus-Strand DNA as Template for R-U5-Mediated Second-Strand Transfer in Recombinational Rescue of Primer Binding Site-Modified Retroviral Vectors

PubMed Central

Mikkelsen, Jacob Giehm; Lund, Anders H.; Dybkær, Karen; Duch, Mogens; Pedersen, Finn Skou

1998-01-01

We have previously demonstrated recombinational rescue of primer binding site (PBS)-impaired Akv murine leukemia virus-based vectors involving initial priming on endogenous viral sequences and template switching during cDNA synthesis to obtain PBS complementarity in second-strand transfer of reverse transcription (Mikkelsen et al., J. Virol. 70:1439–1447, 1996). By use of the same forced recombination system, we have now found recombinant proviruses of different structures, suggesting that PBS knockout vectors may be rescued through initial priming on endogenous virus RNA, read-through of the mutated PBS during minus-strand synthesis, and subsequent second-strand transfer mediated by the R-U5 complementarity of the plus strand and the extended minus-strand DNA acceptor template. Mechanisms for R-U5-mediated second-strand transfer and its possible role in retrovirus replication and evolution are discussed. PMID:9499117

Genetic Variation of North American Triatomines (Insecta: Hemiptera: Reduviidae): Initial Divergence between Species and Populations of Chagas Disease Vector

PubMed Central

Espinoza, Bertha; Martínez-Ibarra, Jose Alejandro; Villalobos, Guiehdani; De La Torre, Patricia; Laclette, Juan Pedro; Martínez-Hernández, Fernando

2013-01-01

The triatomines vectors of Trypanosoma cruzi are principal factors in acquiring Chagas disease. For this reason, increased knowledge of domestic transmission of T. cruzi and control of its insect vectors is necessary. To contribute to genetic knowledge of North America Triatominae species, we studied genetic variations and conducted phylogenetic analysis of different triatomines species of epidemiologic importance. Our analysis showed high genetic variations between different geographic populations of Triatoma mexicana, Meccus longipennis, M. mazzottii, M. picturatus, and T. dimidiata species, suggested initial divergence, hybridation, or classifications problems. In contrast, T. gerstaeckeri, T. bolivari, and M. pallidipennis populations showed few genetics variations. Analysis using cytochrome B and internal transcribed spacer 2 gene sequences indicated that T. bolivari is closely related to the Rubrofasciata complex and not to T. dimidiata. Triatoma brailovskyi and T. gerstaeckeri showed a close relationship with Dimidiata and Phyllosoma complexes. PMID:23249692

Polarization masks: concept and initial assessment

NASA Astrophysics Data System (ADS)

Lam, Michael; Neureuther, Andrew R.

2002-07-01

Polarization from photomasks can be used as a new lever to improve lithographic performance in both binary and phase-shifting masks (PSMs). While PSMs manipulate the phase of light to control the temporal addition of electric field vectors, polarization masks manipulate the vector direction of electric field vectors to control the spatial addition of electric field components. This paper explores the theoretical possibilities of polarization masks, showing that it is possible to use bar structures within openings on the mask itself to polarize incident radiation. Rigorous electromagnetic scattering simulations using TEMPEST and imaging with SPLAT are used to give an initial assessment on the functionality of polarization masks, discussing the polarization quality and throughputs achieved with the masks. Openings between 1/8 and 1/3 of a wavelength provide both a low polarization ratio and good transmission. A final overall throughput of 33% - 40% is achievable, corresponding to a dose hit of 2.5x - 3x.

Improved wavelet packet classification algorithm for vibrational intrusions in distributed fiber-optic monitoring systems

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Pi, Shaohua; Sun, Qi; Jia, Bo

2015-05-01

An improved classification algorithm that considers multiscale wavelet packet Shannon entropy is proposed. Decomposition coefficients at all levels are obtained to build the initial Shannon entropy feature vector. After subtracting the Shannon entropy map of the background signal, components of the strongest discriminating power in the initial feature vector are picked out to rebuild the Shannon entropy feature vector, which is transferred to radial basis function (RBF) neural network for classification. Four types of man-made vibrational intrusion signals are recorded based on a modified Sagnac interferometer. The performance of the improved classification algorithm has been evaluated by the classification experiments via RBF neural network under different diffusion coefficients. An 85% classification accuracy rate is achieved, which is higher than the other common algorithms. The classification results show that this improved classification algorithm can be used to classify vibrational intrusion signals in an automatic real-time monitoring system.

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.

77 FR 5257 - Disease, Disability, and Injury Prevention and Control Special Emphasis Panel (SEP): Initial Review

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-02

... announced below concerns Detecting Emerging Vector Borne Zoonotic Pathogens in Indonesia, Funding... Pathogens in Indonesia, FOA CK12-002, initial review.'' Contact Person for More Information: Greg Anderson...

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

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.

Cost Study of Educational Media Systems and Their Equipment Components. Volume II, Technical Report. Final Report.

ERIC Educational Resources Information Center

General Learning Corp., Washington, DC.

A common instructional task and a set of educational environments are hypothesized for analysis of media cost data. The analytic structure may be conceptulized as a three-dimensional matrix: the first vector separates costs into production, distribution, and reception; the second vector delineates capital (initial) and operating (annual) costs;…

Predators indirectly control vector-borne disease: linking predator-prey and host-pathogen models.

PubMed

Moore, Sean M; Borer, Elizabeth T; Hosseini, Parviez R

2010-01-06

Pathogens transmitted by arthropod vectors are common in human populations, agricultural systems and natural communities. Transmission of these vector-borne pathogens depends on the population dynamics of the vector species as well as its interactions with other species within the community. In particular, predation may be sufficient to control pathogen prevalence indirectly via the vector. To examine the indirect effect of predators on vectored-pathogen dynamics, we developed a theoretical model that integrates predator-prey and host-pathogen theory. We used this model to determine whether predation can prevent pathogen persistence or alter the stability of host-pathogen dynamics. We found that, in the absence of predation, pathogen prevalence in the host increases with vector fecundity, whereas predation on the vector causes pathogen prevalence to decline, or even become extinct, with increasing vector fecundity. We also found that predation on a vector may drastically slow the initial spread of a pathogen. The predator can increase host abundance indirectly by reducing or eliminating infection in the host population. These results highlight the importance of studying interactions that, within the greater community, may alter our predictions when studying disease dynamics. From an applied perspective, these results also suggest situations where an introduced predator or the natural enemies of a vector may slow the rate of spread of an emerging vector-borne pathogen.

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.

Initiation of small-satellite formations via satellite ejector

NASA Astrophysics Data System (ADS)

McMullen, Matthew G

Small satellites can be constructed at a fraction of the cost of a full-size satellite. One full-size satellite can be replaced with a multitude of small satellites, offering expanded area coverage through formation flight. However, the shortcoming to the smaller size is usually a lack of thrusting capabilities. Furthermore, current designs for small satellite deployment mechanisms are only capable of love deployment velocities (on the order of meters per second). Motivated to address this shortcoming, a conceived satellite ejector would offer a significant orbit change by ejecting the satellite at higher deployment velocities (125-200 m/s). Focusing on the applications of the ejector, it is sought to bridge the gap in prior research by offering a method to initiate formation flight. As a precursor to the initiation, the desired orbit properties to initiate the formation are specified in terms of spacing and velocity change vector. From this, a systematic method is developed to find the relationship among velocity change vector, the desired orbit's orientation, and the spacing required to initiate the formation.

Control of Initialized Fractional-Order Systems. Revised

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex w-plane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex w-plane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Control of Initialized Fractional-Order Systems

NASA Technical Reports Server (NTRS)

Hartly, Tom T.; Lorenzo, Carl F.

2002-01-01

Due to the importance of historical effects in fractional-order systems, this paper presents a general fractional-order control theory that includes the time-varying initialization response. Previous studies have not properly accounted for these historical effects. The initialization response, along with the forced response, for fractional-order systems is determined. Stability properties of fractional-order systems are presented in the complex Airplane, which is a transformation of the s-plane. Time responses are discussed with respect to pole positions in the complex Airplane and frequency response behavior is included. A fractional-order vector space representation, which is a generalization of the state space concept, is presented including the initialization response. Control methods for vector representations of initialized fractional-order systems are shown. Nyquist, root-locus, and other input-output control methods are adapted to the control of fractional-order systems. Finally, the fractional-order differintegral is generalized to continuous order-distributions that have the possibility of including a continuum of fractional orders in a system element.

Improvements in Block-Krylov Ritz Vectors and the Boundary Flexibility Method of Component Synthesis

NASA Technical Reports Server (NTRS)

Carney, Kelly Scott

1997-01-01

A method of dynamic substructuring is presented which utilizes a set of static Ritz vectors as a replacement for normal eigenvectors in component mode synthesis. This set of Ritz vectors is generated in a recurrence relationship, proposed by Wilson, which has the form of a block-Krylov subspace. The initial seed to the recurrence algorithm is based upon the boundary flexibility vectors of the component. Improvements have been made in the formulation of the initial seed to the Krylov sequence, through the use of block-filtering. A method to shift the Krylov sequence to create Ritz vectors that will represent the dynamic behavior of the component at target frequencies, the target frequency being determined by the applied forcing functions, has been developed. A method to terminate the Krylov sequence has also been developed. Various orthonormalization schemes have been developed and evaluated, including the Cholesky/QR method. Several auxiliary theorems and proofs which illustrate issues in component mode synthesis and loss of orthogonality in the Krylov sequence have also been presented. The resulting methodology is applicable to both fixed and free- interface boundary components, and results in a general component model appropriate for any type of dynamic analysis. The accuracy is found to be comparable to that of component synthesis based upon normal modes, using fewer generalized coordinates. In addition, the block-Krylov recurrence algorithm is a series of static solutions and so requires significantly less computation than solving the normal eigenspace problem. The requirement for less vectors to form the component, coupled with the lower computational expense of calculating these Ritz vectors, combine to create a method more efficient than traditional component mode synthesis.

The orientating reflex: the "targeting reaction" and "searchlight of attention".

PubMed

Sokolov, E N; Nezlina, N I; Polyanskii, V B; Evtikhin, D V

2002-01-01

A concept of the orientating reflex is presented, based on the principle of vector coding of cognitive and executive processes. The orientating reflex is a complex of orientating reactions of motor, autonomic, and subjective types, accentuating new and significant stimuli. Two main systems form the orientating reflex: the "targeting reaction" and the "searchlight of attention:" In the visual system, the targeting reaction ensures that the image of the object falls onto the fovea; this is mediated by involvement of premotor neurons which are excited by saccade command neurons in the superior colliculi. The "searchlight of attention" is activated as a result of resonance within the gamma frequency range, selectively enhancing cortical detectors and involving the reticular nucleus of the thalamus. Novelty signals arise in novelty neurons of the hippocampus. The synaptic weightings of neocortical detectors for hippocampal novelty neurons is initially characterized by high efficiency, which assigns a significant level of excitation of these neurons to the new stimulus. During repeated stimulation, the synaptic weightings of all the detectors representing a given stimulus decrease, with the result that the novelty signal becomes weaker. When the stimulus changes, it acts on other detectors, whose weightings for novelty neurons remain high, which strengthens the novelty signal. Decreases in the synaptic weightings on repetition of a standard stimulus form a trace of this stimulus in the novelty neurons - this is the "neural model of the stimulus." The novelty signal is determined by the non-concordance of the new stimulus with this "neural model," which is formed under the influence of the standard stimulus. The greater the difference between the new stimulus and the previously formed neural model, the stronger the novelty signal.

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.

Hybrid diversity method utilizing adaptive diversity function for recovering unknown aberrations in an optical system

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2009-01-01

A method of recovering unknown aberrations in an optical system includes collecting intensity data produced by the optical system, generating an initial estimate of a phase of the optical system, iteratively performing a phase retrieval on the intensity data to generate a phase estimate using an initial diversity function corresponding to the intensity data, generating a phase map from the phase retrieval phase estimate, decomposing the phase map to generate a decomposition vector, generating an updated diversity function by combining the initial diversity function with the decomposition vector, generating an updated estimate of the phase of the optical system by removing the initial diversity function from the phase map. The method may further include repeating the process beginning with iteratively performing a phase retrieval on the intensity data using the updated estimate of the phase of the optical system in place of the initial estimate of the phase of the optical system, and using the updated diversity function in place of the initial diversity function, until a predetermined convergence is achieved.

Weaving Knotted Vector Fields with Tunable Helicity.

PubMed

Kedia, Hridesh; Foster, David; Dennis, Mark R; Irvine, William T M

2016-12-30

We present a general construction of divergence-free knotted vector fields from complex scalar fields, whose closed field lines encode many kinds of knots and links, including torus knots, their cables, the figure-8 knot, and its generalizations. As finite-energy physical fields, they represent initial states for fields such as the magnetic field in a plasma, or the vorticity field in a fluid. We give a systematic procedure for calculating the vector potential, starting from complex scalar functions with knotted zero filaments, thus enabling an explicit computation of the helicity of these knotted fields. The construction can be used to generate isolated knotted flux tubes, filled by knots encoded in the lines of the vector field. Lastly, we give examples of manifestly knotted vector fields with vanishing helicity. Our results provide building blocks for analytical models and simulations alike.

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.

Enrichment of human hematopoietic stem/progenitor cells facilitates transduction for stem cell gene therapy.

PubMed

Baldwin, Kismet; Urbinati, Fabrizia; Romero, Zulema; Campo-Fernandez, Beatriz; Kaufman, Michael L; Cooper, Aaron R; Masiuk, Katelyn; Hollis, Roger P; Kohn, Donald B

2015-05-01

Autologous hematopoietic stem cell (HSC) gene therapy for sickle cell disease has the potential to treat this illness without the major immunological complications associated with allogeneic transplantation. However, transduction efficiency by β-globin lentiviral vectors using CD34-enriched cell populations is suboptimal and large vector production batches may be needed for clinical trials. Transducing a cell population more enriched for HSC could greatly reduce vector needs and, potentially, increase transduction efficiency. CD34(+) /CD38(-) cells, comprising ∼1%-3% of all CD34(+) cells, were isolated from healthy cord blood CD34(+) cells by fluorescence-activated cell sorting and transduced with a lentiviral vector expressing an antisickling form of beta-globin (CCL-β(AS3) -FB). Isolated CD34(+) /CD38(-) cells were able to generate progeny over an extended period of long-term culture (LTC) compared to the CD34(+) cells and required up to 40-fold less vector for transduction compared to bulk CD34(+) preparations containing an equivalent number of CD34(+) /CD38(-) cells. Transduction of isolated CD34(+) /CD38(-) cells was comparable to CD34(+) cells measured by quantitative PCR at day 14 with reduced vector needs, and average vector copy/cell remained higher over time for LTC initiated from CD34(+) /38(-) cells. Following in vitro erythroid differentiation, HBBAS3 mRNA expression was similar in cultures derived from CD34(+) /CD38(-) cells or unfractionated CD34(+) cells. In vivo studies showed equivalent engraftment of transduced CD34(+) /CD38(-) cells when transplanted in competition with 100-fold more CD34(+) /CD38(+) cells. This work provides initial evidence for the beneficial effects from isolating human CD34(+) /CD38(-) cells to use significantly less vector and potentially improve transduction for HSC gene therapy. © 2015 AlphaMed Press.

[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.

Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.

PubMed

Aksu, Yaman; Miller, David J; Kesidis, George; Yang, Qing X

2010-05-01

Feature selection for classification in high-dimensional spaces can improve generalization, reduce classifier complexity, and identify important, discriminating feature "markers." For support vector machine (SVM) classification, a widely used technique is recursive feature elimination (RFE). We demonstrate that RFE is not consistent with margin maximization, central to the SVM learning approach. We thus propose explicit margin-based feature elimination (MFE) for SVMs and demonstrate both improved margin and improved generalization, compared with RFE. Moreover, for the case of a nonlinear kernel, we show that RFE assumes that the squared weight vector 2-norm is strictly decreasing as features are eliminated. We demonstrate this is not true for the Gaussian kernel and, consequently, RFE may give poor results in this case. MFE for nonlinear kernels gives better margin and generalization. We also present an extension which achieves further margin gains, by optimizing only two degrees of freedom--the hyperplane's intercept and its squared 2-norm--with the weight vector orientation fixed. We finally introduce an extension that allows margin slackness. We compare against several alternatives, including RFE and a linear programming method that embeds feature selection within the classifier design. On high-dimensional gene microarray data sets, University of California at Irvine (UCI) repository data sets, and Alzheimer's disease brain image data, MFE methods give promising results.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-04-01

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

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

USGS Publications Warehouse

Ginsberg, H.S.

2001-01-01

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

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.

Development of precursors recognition methods in vector signals

NASA Astrophysics Data System (ADS)

Kapralov, V. G.; Elagin, V. V.; Kaveeva, E. G.; Stankevich, L. A.; Dremin, M. M.; Krylov, S. V.; Borovov, A. E.; Harfush, H. A.; Sedov, K. S.

2017-10-01

Precursor recognition methods in vector signals of plasma diagnostics are presented. Their requirements and possible options for their development are considered. In particular, the variants of using symbolic regression for building a plasma disruption prediction system are discussed. The initial data preparation using correlation analysis and symbolic regression is discussed. Special attention is paid to the possibility of using algorithms in real time.

Ecology of West Nile Fever across four European countries: Review of weather profiles, vector population dynamics and vector control response

USDA-ARS?s Scientific Manuscript database

West Nile virus (WNV) represents a serious burden to human and animal health because of its capacity to cause large unforeseen epidemics. Until 2004, only lineage 1 and 3 WNV strains had been found in Europe. Lineage 2 strains were initially isolated in 2004 (Hungary), again in 2008 (Austria), and f...

Transverse and Quantum Effects in Superfluorescence; Pump Dynamics for Three-Level Superfluoresence; An Algorithm for Transverse, Full Transient Effects in Optical Bistability in a Fabry-Perot Cavity.

DTIC Science & Technology

1983-04-11

w - )u - v/T2’ -wKE (2) = -(w + 1)/T + vWE C3) aE + I aE 2_wnpv (4) az cat c where u,v,w are the Bloch components of the pseudo polarization vector , E...The initiation should not be inserted as a homogeneous tipping of all the individual polarization vectors phased to emit a plane wave in the forward...tipping angle. Effects of Fresnel number and of the radial dependence of initial polarization and atom density on ringing, delay, and intensity are

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

DOE PAGES

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

2015-05-22

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

Parallel-vector computation for linear structural analysis and non-linear unconstrained optimization problems

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Al-Nasra, M.; Zhang, Y.; Baddourah, M. A.; Agarwal, T. K.; Storaasli, O. O.; Carmona, E. A.

1991-01-01

Several parallel-vector computational improvements to the unconstrained optimization procedure are described which speed up the structural analysis-synthesis process. A fast parallel-vector Choleski-based equation solver, pvsolve, is incorporated into the well-known SAP-4 general-purpose finite-element code. The new code, denoted PV-SAP, is tested for static structural analysis. Initial results on a four processor CRAY 2 show that using pvsolve reduces the equation solution time by a factor of 14-16 over the original SAP-4 code. In addition, parallel-vector procedures for the Golden Block Search technique and the BFGS method are developed and tested for nonlinear unconstrained optimization. A parallel version of an iterative solver and the pvsolve direct solver are incorporated into the BFGS method. Preliminary results on nonlinear unconstrained optimization test problems, using pvsolve in the analysis, show excellent parallel-vector performance indicating that these parallel-vector algorithms can be used in a new generation of finite-element based structural design/analysis-synthesis codes.

Gene delivery with viral vectors for cerebrovascular diseases

PubMed Central

Gan, Yu; Jing, Zheng; Stetler, R. Anne; Cao, Guodong

2017-01-01

Recent achievements in the understanding of molecular events involved in the pathogenesis of central nervous system (CNS) injury have made gene transfer a promising approach for various neurological disorders, including cerebrovascular diseases. However, special obstacles, including the post-mitotic nature of neurons and the blood-brain barrier (BBB), constitute key challenges for gene delivery to the CNS. Despite the various limitations in current gene delivery systems, a spectrum of viral vectors has been successfully used to deliver genes to the CNS. Furthermore, recent advancements in vector engineering have improved the safety and delivery of viral vectors. Numerous viral vector-based clinical trials for neurological disorders have been initiated. This review will summarize the current implementation of viral gene delivery in the context of cerebrovascular diseases including ischemic stroke, hemorrhagic stroke and subarachnoid hemorrhage (SAH). In particular, we will discuss the potentially feasible ways in which viral vectors can be manipulated and exploited for use in neural delivery and therapy. PMID:23276981

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.

Development of siRNA expression vector utilizing rock bream beta-actin promoter: a potential therapeutic tool against viral infection in fish.

PubMed

Zenke, Kosuke; Nam, Yoon Kwon; Kim, Ki Hong

2010-01-01

In the present study, we have developed short interfering RNA (siRNA) expression vector utilizing rock bream beta-actin promoter and examined the possible use for the inhibition of highly pathogenic fish virus, rock bream iridovirus (RBIV), replication in vitro. Initially, in order to express siRNA effectively, we added several modifications to wild-type rock bream beta-actin promoter. Next, we succeeded in knocking down the expression of enhanced green fluorescent protein reporter gene expression in fish cells using newly developed vector more effectively than the fugu U6 promoter-driven vector we described previously. Finally, we could observe that cells transfected with modified rock bream beta-actin promoter-driven siRNA expression vector targeting major capsid protein (MCP) gene of RBIV exhibited more resistance to RBIV challenge than other control cells. Our results indicate that this novel siRNA expression vector can be used as a new tool for therapeutics in virus infection in fish species.

Progress in developing cationic vectors for non-viral systemic gene therapy against cancer.

PubMed

Morille, Marie; Passirani, Catherine; Vonarbourg, Arnaud; Clavreul, Anne; Benoit, Jean-Pierre

2008-01-01

Initially, gene therapy was viewed as an approach for treating hereditary diseases, but its potential role in the treatment of acquired diseases such as cancer is now widely recognized. The understanding of the molecular mechanisms involved in cancer and the development of nucleic acid delivery systems are two concepts that have led to this development. Systemic gene delivery systems are needed for therapeutic application to cells inaccessible by percutaneous injection and for multi-located tumor sites, i.e. metastases. Non-viral vectors based on the use of cationic lipids or polymers appear to have promising potential, given the problems of safety encountered with viral vectors. Using these non-viral vectors, the current challenge is to obtain a similarly effective transfection to viral ones. Based on the advantages and disadvantages of existing vectors and on the hurdles encountered with these carriers, the aim of this review is to describe the "perfect vector" for systemic gene therapy against cancer.

Urbanization, land tenure security and vector-borne Chagas disease.

PubMed

Levy, Michael Z; Barbu, Corentin M; Castillo-Neyra, Ricardo; Quispe-Machaca, Victor R; Ancca-Juarez, Jenny; Escalante-Mejia, Patricia; Borrini-Mayori, Katty; Niemierko, Malwina; Mabud, Tarub S; Behrman, Jere R; Naquira-Velarde, Cesar

2014-08-22

Modern cities represent one of the fastest growing ecosystems on the planet. Urbanization occurs in stages; each stage characterized by a distinct habitat that may be more or less susceptible to the establishment of disease vector populations and the transmission of vector-borne pathogens. We performed longitudinal entomological and epidemiological surveys in households along a 1900 × 125 m transect of Arequipa, Peru, a major city of nearly one million inhabitants, in which the transmission of Trypanosoma cruzi, the aetiological agent of Chagas disease, by the insect vector Triatoma infestans, is an ongoing problem. The transect spans a cline of urban development from established communities to land invasions. We find that the vector is tracking the development of the city, and the parasite, in turn, is tracking the dispersal of the vector. New urbanizations are free of vector infestation for decades. T. cruzi transmission is very recent and concentrated in more established communities. The increase in land tenure security during the course of urbanization, if not accompanied by reasonable and enforceable zoning codes, initiates an influx of construction materials, people and animals that creates fertile conditions for epidemics of some vector-borne diseases. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Retrovirus-based vectors for transient and permanent cell modification.

PubMed

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

2015-10-01

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

The lattice of trumping majorization for 4D probability vectors and 2D catalysts.

PubMed

Bosyk, Gustavo M; Freytes, Hector; Bellomo, Guido; Sergioli, Giuseppe

2018-02-27

The transformation of an initial bipartite pure state into a target one by means of local operations and classical communication and entangled-assisted by a catalyst defines a partial order between probability vectors. This partial order, so-called trumping majorization, is based on tensor products and the majorization relation. Here, we aim to study order properties of trumping majorization. We show that the trumping majorization partial order is indeed a lattice for four dimensional probability vectors and two dimensional catalysts. In addition, we show that the subadditivity and supermodularity of the Shannon entropy on the majorization lattice are inherited by the trumping majorization lattice. Finally, we provide a suitable definition of distance for four dimensional probability vectors.

Early efficacy of the ketogenic diet is not affected by initial body mass index percentile.

PubMed

Shull, Shastin; Diaz-Medina, Gloria; Wong-Kisiel, Lily; Nickels, Katherine; Eckert, Susan; Wirrell, Elaine

2014-05-01

Predictors of the ketogenic diet's success in treating pediatric intractable epilepsy are not well understood. The aim of this study was to determine whether initial body mass index and weight percentile impact early efficacy of the traditional ketogenic diet in children initiating therapy for intractable epilepsy. This retrospective study included all children initiating the ketogenic diet at Mayo Clinic, Rochester from January 2001 to December 2010 who had body mass index (children ≥2 years of age) or weight percentile (those <2 years of age) documented at diet initiation and seizure frequency recorded at diet initiation and one month. Responders were defined as achieving a >50% seizure reduction from baseline. Our cohort consisted of 48 patients (20 male) with a median age of 3.1 years. There was no significant correlation between initial body mass index or weight percentile and seizure frequency reduction at one month (P = 0.72, r = 0.26 and P = 0.91, r = 0.03). There was no significant association between body mass index or weight percentile quartile and responder rates (P = 0.21 and P = 0.57). Children considered overweight or obese at diet initiation (body mass index or weight percentile ≥85) did not have lower responder rates than those with body mass index or weight percentiles <85 (6/14 vs 19/34, respectively, P = 0.41). Greater initial body mass index and weight-for-age percentiles do not adversely affect the efficacy of the ketogenic diet. Copyright © 2014 Elsevier Inc. All rights reserved.

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

Pre-ESRD Changes in Body Weight and Survival in Nursing Home Residents Starting Dialysis

PubMed Central

Stack, Shobha; Chertow, Glenn M.; Johansen, Kirsten L.; Si, Yan

2013-01-01

Summary Background and objectives Among patients receiving maintenance dialysis, weight loss at any body mass index is associated with mortality. However, it is not known whether weight changes before dialysis initiation are associated with mortality and if so, what risks are associated with weight gain or loss. Design, setting, participants, and measurements Linking data from the US Renal Data System to a national registry of nursing home residents, this study identified 11,090 patients who started dialysis between January of 2000 and December of 2006. Patients were categorized according to weight measured between 3 and 6 months before dialysis initiation and the percentage change in body weight before dialysis initiation (divided into quintiles). The outcome was mortality within 1 year of starting dialysis. Results There were 361 patients (3.3%) who were underweight (Quételet’s [body mass] index<18.5 kg/m2) and 4046 patients (36.5%) who were obese (body mass index≥30 kg/m2) before dialysis initiation. The median percentage change in body weight before dialysis initiation was −6% (interquartile range=−13% to 1%). There were 6063 deaths (54.7%) over 1 year of follow-up. Compared with patients with minimal weight changes (−3% to 3%, quintile 4), patients with weight loss ≥15% (quintile 1) had 35% higher risk for mortality (95% confidence interval, 1.25 to 1.47), whereas those patients with weight gain≥4% (quintile 5) had a 24% higher risk for mortality (95% confidence interval, 1.14 to 1.35) adjusted for baseline body mass index and other confounders. Conclusions Among nursing home residents, changes in body weight in advance of dialysis initiation are associated with significantly higher 1-year mortality. PMID:24009221

A Translational Pathway Toward a Clinical Trial Using the Second-Generation AAV Micro-Dystrophin Vector

DTIC Science & Technology

responsible for restoring neuronal nitric oxide synthase (nNOS).Failure to restore nNOS significantly contributes to the initiation and progression...model. Our findings have provided the foundation for the recent initiation of human trials.

A Program Evaluation of a Worksite Wellness Initiative for Weight Loss

ERIC Educational Resources Information Center

Martinez, Nicholas

2017-01-01

The purpose of this study was to conduct a program evaluation of ACME's worksite weight loss initiative and collect evidence relative to the efficacy of the program. An anonymous online survey was administered to participants of the weight loss initiative. The survey was designed to gather information relative to the research questions, which…

High-order rogue waves in vector nonlinear Schrödinger equations.

PubMed

Ling, Liming; Guo, Boling; Zhao, Li-Chen

2014-04-01

We study the dynamics of high-order rogue waves (RWs) in two-component coupled nonlinear Schrödinger equations. We find that four fundamental rogue waves can emerge from second-order vector RWs in the coupled system, in contrast to the high-order ones in single-component systems. The distribution shape can be quadrilateral, triangle, and line structures by varying the proper initial excitations given by the exact analytical solutions. The distribution pattern for vector RWs is more abundant than that for scalar rogue waves. Possibilities to observe these new patterns for rogue waves are discussed for a nonlinear fiber.

Primer Vector Optimization: Survey of Theory, New Analysis and Applications

NASA Technical Reports Server (NTRS)

Guzman, J. J.; Mailhe, L. M.; Schiff, C.; Hughes, S. P.; Folta, D. C.

2002-01-01

In this paper, a summary of primer vector theory is presented. The applicability of primer vector theory is examined in an effort to understand when and why the theory can fail. For example, since the Calculus of Variations is based on "small" variations, singularities in the linearized (variational) equations of motion along the arcs must be taken into account. These singularities are a recurring problem in analyse that employ small variations. Two examples, the initialization of an orbit and a line of apsides rotation, are presented. Recommendations, future work, and the possible addition of other optimization techniques are also discussed.

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.

Advancing vector biology research: a community survey for future directions, research applications and infrastructure requirements

PubMed Central

Kohl, Alain; Pondeville, Emilie; Schnettler, Esther; Crisanti, Andrea; Supparo, Clelia; Christophides, George K.; Kersey, Paul J.; Maslen, Gareth L.; Takken, Willem; Koenraadt, Constantianus J. M.; Oliva, Clelia F.; Busquets, Núria; Abad, F. Xavier; Failloux, Anna-Bella; Levashina, Elena A.; Wilson, Anthony J.; Veronesi, Eva; Pichard, Maëlle; Arnaud Marsh, Sarah; Simard, Frédéric; Vernick, Kenneth D.

2016-01-01

Vector-borne pathogens impact public health, animal production, and animal welfare. Research on arthropod vectors such as mosquitoes, ticks, sandflies, and midges which transmit pathogens to humans and economically important animals is crucial for development of new control measures that target transmission by the vector. While insecticides are an important part of this arsenal, appearance of resistance mechanisms is increasingly common. Novel tools for genetic manipulation of vectors, use of Wolbachia endosymbiotic bacteria, and other biological control mechanisms to prevent pathogen transmission have led to promising new intervention strategies, adding to strong interest in vector biology and genetics as well as vector–pathogen interactions. Vector research is therefore at a crucial juncture, and strategic decisions on future research directions and research infrastructure investment should be informed by the research community. A survey initiated by the European Horizon 2020 INFRAVEC-2 consortium set out to canvass priorities in the vector biology research community and to determine key activities that are needed for researchers to efficiently study vectors, vector-pathogen interactions, as well as access the structures and services that allow such activities to be carried out. We summarize the most important findings of the survey which in particular reflect the priorities of researchers in European countries, and which will be of use to stakeholders that include researchers, government, and research organizations. PMID:27677378

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.

Impact of body weight on virological and immunological responses to efavirenz-containing regimens in HIV-infected, treatment-naive adults.

PubMed

Marzolini, Catia; Sabin, Caroline; Raffi, François; Siccardi, Marco; Mussini, Cristina; Launay, Odile; Burger, David; Roca, Bernardino; Fehr, Jan; Bonora, Stefano; Mocroft, Amanda; Obel, Niels; Dauchy, Frederic-Antoine; Zangerle, Robert; Gogos, Charalambos; Gianotti, Nicola; Ammassari, Adriana; Torti, Carlo; Ghosn, Jade; Chêne, Genevieve; Grarup, Jesper; Battegay, Manuel

2015-01-14

The prevalence of overweight and obesity is increasing among HIV-infected patients. Whether standard antiretroviral drug dosage is adequate in heavy individuals remains unresolved. We assessed the virological and immunological responses to initial efavirenz (EFV)-containing regimens in heavy compared to normal-weight HIV-infected patients. Observational European cohort collaboration study. Eligible patients were antiretroviral-naïve with documented weight prior to EFV start and follow-up viral loads after treatment initiation. Cox regression analyses evaluated the association between weight and time to first undetectable viral load (<50 copies/ml) after treatment initiation, and time to viral load rebound (two consecutive viral load >50 copies/ml) after initial suppression over 5 years of follow-up. Recovery of CD4 cell count was evaluated 6 and 12 months after EFV initiation. Analyses were stratified by weight (kg) group (I - <55; II - >55, <80 (reference); III - >80, <85; IV - >85, <90; V - >90, <95; VI - >95). The study included 19,968 patients, of whom 9.1, 68.3, 9.1, 5.8, 3.5, and 4.3% were in weight groups I-VI, respectively. Overall, 81.1% patients attained virological suppression, of whom 34.1% subsequently experienced viral load rebound. After multiple adjustments, no statistical difference was observed in time to undetectable viral load and virological rebound for heavier individuals compared to their normal-weight counterparts. Although heaviest individuals had significantly higher CD4 cell count at baseline, CD4 cell recovery at 6 and 12 months after EFV initiation was comparable to normal-weight individuals. Virological and immunological responses to initial EFV-containing regimens were not impaired in heavy individuals, suggesting that the standard 600 mg EFV dosage is appropriate across a wide weight range.

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.

Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics

DTIC Science & Technology

2016-09-15

Algorithm GPS Global Positioning System HOUF Higher Order Unscented Filter IC initial conditions IMM Interacting Multiple Model IMU Inertial Measurement Unit ...sources ranging from inertial measurement units to star sensors are used to construct observations for attitude estimation algorithms. The sensor...parameters. A single vector measurement will provide two independent parameters, as a unit vector constraint removes a DOF making the problem underdetermined

From oligomers to molecular giants of soybean oil in supercritical carbon dioxide medium: 1. Preparation of polymers with lower molecular weight from soybean oil.

PubMed

Liu, Zengshe; Sharma, Brajendra K; Erhan, Sevim Z

2007-01-01

Polymers with a low molecular weight derived from soybean oil have been prepared in a supercritical carbon dioxide medium by cationic polymerization. Boron trifluoride diethyl etherate was used as an initiator. Influences of polymerization temperature, amount of initiator, and carbon dioxide pressure on the molecular weight were investigated. It is shown that the higher polymerization temperature favors polymers with relatively higher molecular weights. Larger amounts of initiator also provide polymers with higher molecular weights. Higher pressure favors polymers with relatively higher molecular weights. The applications of these soy-based materials will be in the lubrication and hydraulic fluid areas.

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.

A high-accuracy two-position alignment inertial navigation system for lunar rovers aided by a star sensor with a calibration and positioning function

NASA Astrophysics Data System (ADS)

Lu, Jiazhen; Lei, Chaohua; Yang, Yanqiang; Liu, Ming

2016-12-01

An integrated inertial/celestial navigation system (INS/CNS) has wide applicability in lunar rovers as it provides accurate and autonomous navigational information. Initialization is particularly vital for a INS. This paper proposes a two-position initialization method based on a standard Kalman filter. The difference between the computed star vector and the measured star vector is measured. With the aid of a star sensor and the two positions, the attitudinal and positional errors can be greatly reduced, and the biases of three gyros and accelerometers can also be estimated. The semi-physical simulation results show that the positional and attitudinal errors converge within 0.07″ and 0.1 m, respectively, when the given initial positional error is 1 km and the attitudinal error is 10°. These good results show that the proposed method can accomplish alignment, positioning and calibration functions simultaneously. Thus the proposed two-position initialization method has the potential for application in lunar rover navigation.

Numerical simulation on the powder propellant pickup characteristics of feeding system at high pressure

NASA Astrophysics Data System (ADS)

Sun, Haijun; Hu, Chunbo; Zhu, Xiaofei

2017-10-01

A numerical study of powder propellant pickup progress at high pressure was presented in this paper by using two-fluid model with kinetic theory of granular flow in the computational fluid dynamics software package ANSYS/Fluent. Simulations were conducted to evaluate the effects of initial pressure, initial powder packing rate and mean particle diameter on the flow characteristics in terms of velocity vector distribution, granular temperature, pressure drop, particle velocity and volume. The numerical results of pressure drop were also compared with experiments to verify the TFM model. The simulated results show that the pressure drop value increases as the initial pressure increases, and the granular temperature under the conditions of different initial pressures and packing rates is almost the same in the area of throttling orifice plate. While there is an appropriate value for particle size and packing rate to form a ;core-annulus; structure in powder box, and the time-averaged velocity vector distribution of solid phase is inordinate.

Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease

PubMed Central

Daianu, Madelaine; Jahanshad, Neda; Nir, Talia M.; Leonardo, Cassandra D.; Jack, Clifford R.; Weiner, Michael W.; Bernstein, Matthew A.; Thompson, Paul M.

2015-01-01

Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. PMID:26640830

Recognizing characters of ancient manuscripts

NASA Astrophysics Data System (ADS)

Diem, Markus; Sablatnig, Robert

2010-02-01

Considering printed Latin text, the main issues of Optical Character Recognition (OCR) systems are solved. However, for degraded handwritten document images, basic preprocessing steps such as binarization, gain poor results with state-of-the-art methods. In this paper ancient Slavonic manuscripts from the 11th century are investigated. In order to minimize the consequences of false character segmentation, a binarization-free approach based on local descriptors is proposed. Additionally local information allows the recognition of partially visible or washed out characters. The proposed algorithm consists of two steps: character classification and character localization. Initially Scale Invariant Feature Transform (SIFT) features are extracted which are subsequently classified using Support Vector Machines (SVM). Afterwards, the interest points are clustered according to their spatial information. Thereby, characters are localized and finally recognized based on a weighted voting scheme of pre-classified local descriptors. Preliminary results show that the proposed system can handle highly degraded manuscript images with background clutter (e.g. stains, tears) and faded out characters.

Face recognition using tridiagonal matrix enhanced multivariance products representation

NASA Astrophysics Data System (ADS)

Ã-zay, Evrim Korkmaz

2017-01-01

This study aims to retrieve face images from a database according to a target face image. For this purpose, Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is taken into consideration. TMEMPR is a recursive algorithm based on Enhanced Multivariance Products Representation (EMPR). TMEMPR decomposes a matrix into three components which are a matrix of left support terms, a tridiagonal matrix of weight parameters for each recursion, and a matrix of right support terms, respectively. In this sense, there is an analogy between Singular Value Decomposition (SVD) and TMEMPR. However TMEMPR is a more flexible algorithm since its initial support terms (or vectors) can be chosen as desired. Low computational complexity is another advantage of TMEMPR because the algorithm has been constructed with recursions of certain arithmetic operations without requiring any iteration. The algorithm has been trained and tested with ORL face image database with 400 different grayscale images of 40 different people. TMEMPR's performance has been compared with SVD's performance as a result.

Dynamic performance of an aero-assist spacecraft - AFE

NASA Technical Reports Server (NTRS)

Chang, Ho-Pen; French, Raymond A.

1992-01-01

Dynamic performance of the Aero-assist Flight Experiment (AFE) spacecraft was investigated using a high-fidelity 6-DOF simulation model. Baseline guidance logic, control logic, and a strapdown navigation system to be used on the AFE spacecraft are also modeled in the 6-DOF simulation. During the AFE mission, uncertainties in the environment and the spacecraft are described by an error space which includes both correlated and uncorrelated error sources. The principal error sources modeled in this study include navigation errors, initial state vector errors, atmospheric variations, aerodynamic uncertainties, center-of-gravity off-sets, and weight uncertainties. The impact of the perturbations on the spacecraft performance is investigated using Monte Carlo repetitive statistical techniques. During the Solid Rocket Motor (SRM) deorbit phase, a target flight path angle of -4.76 deg at entry interface (EI) offers very high probability of avoiding SRM casing skip-out from the atmosphere. Generally speaking, the baseline designs of the guidance, navigation, and control systems satisfy most of the science and mission requirements.

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.

Guided filter-based fusion method for multiexposure images

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Qi, Feng; Zhou, Peipei

2016-11-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.

Differential Effects of IL6 and Activin A in the Development of Cancer-Associated Cachexia.

PubMed

Chen, Justin L; Walton, Kelly L; Qian, Hongwei; Colgan, Timothy D; Hagg, Adam; Watt, Matthew J; Harrison, Craig A; Gregorevic, Paul

2016-09-15

Cachexia is a life-threatening wasting syndrome lacking effective treatment, which arises in many cancer patients. Although ostensibly induced by multiple tumor-produced cytokines (tumorkines), their functional contribution to initiation and progression of this syndrome has proven difficult to determine. In this study, we used adeno-associated viral vectors to elevate circulating levels of the tumorkines IL6 and/or activin A in animals in the absence of tumors as a tactic to evaluate hypothesized roles in cachexia development. Mice with elevated levels of IL6 exhibited 8.1% weight loss after 9 weeks, whereas mice with elevated levels of activin A lost 11% of their body weight. Co-elevation of both tumorkines to levels approximating those observed in cancer cachexia models induced a more rapid and profound body weight loss of 15.4%. Analysis of body composition revealed that activin A primarily triggered loss of lean mass, whereas IL6 was a major mediator of fat loss. Histologic and transcriptional analysis of affected organs/tissues (skeletal muscle, fat, and liver) identified interactions between the activin A and IL6 signaling pathways. For example, IL6 exacerbated the detrimental effects of activin A in skeletal muscle, whereas activin A curbed the IL6-induced acute-phase response in liver. This study presents a useful model to deconstruct cachexia, opening a pathway to determining which tumorkines are best targeted to slow/reverse this devastating condition in cancer patients. Cancer Res; 76(18); 5372-82. ©2016 AACR. ©2016 American Association for Cancer Research.

A feature-based approach to modeling protein–protein interaction hot spots

PubMed Central

Cho, Kyu-il; Kim, Dongsup; Lee, Doheon

2009-01-01

Identifying features that effectively represent the energetic contribution of an individual interface residue to the interactions between proteins remains problematic. Here, we present several new features and show that they are more effective than conventional features. By combining the proposed features with conventional features, we develop a predictive model for interaction hot spots. Initially, 54 multifaceted features, composed of different levels of information including structure, sequence and molecular interaction information, are quantified. Then, to identify the best subset of features for predicting hot spots, feature selection is performed using a decision tree. Based on the selected features, a predictive model for hot spots is created using support vector machine (SVM) and tested on an independent test set. Our model shows better overall predictive accuracy than previous methods such as the alanine scanning methods Robetta and FOLDEF, and the knowledge-based method KFC. Subsequent analysis yields several findings about hot spots. As expected, hot spots have a larger relative surface area burial and are more hydrophobic than other residues. Unexpectedly, however, residue conservation displays a rather complicated tendency depending on the types of protein complexes, indicating that this feature is not good for identifying hot spots. Of the selected features, the weighted atomic packing density, relative surface area burial and weighted hydrophobicity are the top 3, with the weighted atomic packing density proving to be the most effective feature for predicting hot spots. Notably, we find that hot spots are closely related to π–related interactions, especially π · · · π interactions. PMID:19273533

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

Ecology of West Nile virus across four European countries: review of weather profiles, vector population dynamics and vector control response.

PubMed

Chaskopoulou, Alexandra; L'Ambert, Gregory; Petric, Dusan; Bellini, Romeo; Zgomba, Marija; Groen, Thomas A; Marrama, Laurence; Bicout, Dominique J

2016-09-02

West Nile virus (WNV) represents a serious burden to human and animal health because of its capacity to cause unforeseen and large epidemics. Until 2004, only lineage 1 and 3 WNV strains had been found in Europe. Lineage 2 strains were initially isolated in 2004 (Hungary) and in 2008 (Austria) and for the first time caused a major WNV epidemic in 2010 in Greece with 262 clinical human cases and 35 fatalities. Since then, WNV lineage 2 outbreaks have been reported in several European countries including Italy, Serbia and Greece. Understanding the interaction of ecological factors that affect WNV transmission is crucial for preventing or decreasing the impact of future epidemics. The synchronous co-occurrence of competent mosquito vectors, virus, bird reservoir hosts, and susceptible humans is necessary for the initiation and propagation of an epidemic. Weather is the key abiotic factor influencing the life-cycles of the mosquito vector, the virus, the reservoir hosts and the interactions between them. The purpose of this paper is to review and compare mosquito population dynamics, and weather conditions, in three ecologically different contexts (urban/semi-urban, rural/agricultural, natural) across four European countries (Italy, France, Serbia, Greece) with a history of WNV outbreaks. Local control strategies will be described as well. Improving our understanding of WNV ecology is a prerequisite step for appraising and optimizing vector control strategies in Europe with the ultimate goal to minimize the probability of WNV infection.

Visceral Leishmaniasis on the Indian Subcontinent: Modelling the Dynamic Relationship between Vector Control Schemes and Vector Life Cycles.

PubMed

Poché, David M; Grant, William E; Wang, Hsiao-Hsuan

2016-08-01

Visceral leishmaniasis (VL) is a disease caused by two known vector-borne parasite species (Leishmania donovani, L. infantum), transmitted to man by phlebotomine sand flies (species: Phlebotomus and Lutzomyia), resulting in ≈50,000 human fatalities annually, ≈67% occurring on the Indian subcontinent. Indoor residual spraying is the current method of sand fly control in India, but alternative means of vector control, such as the treatment of livestock with systemic insecticide-based drugs, are being evaluated. We describe an individual-based, stochastic, life-stage-structured model that represents a sand fly vector population within a village in India and simulates the effects of vector control via fipronil-based drugs orally administered to cattle, which target both blood-feeding adults and larvae that feed on host feces. Simulation results indicated efficacy of fipronil-based control schemes in reducing sand fly abundance depended on timing of drug applications relative to seasonality of the sand fly life cycle. Taking into account cost-effectiveness and logistical feasibility, two of the most efficacious treatment schemes reduced population peaks occurring from April through August by ≈90% (applications 3 times per year at 2-month intervals initiated in March) and >95% (applications 6 times per year at 2-month intervals initiated in January) relative to no control, with the cumulative number of sand fly days occurring April-August reduced by ≈83% and ≈97%, respectively, and more specifically during the summer months of peak human exposure (June-August) by ≈85% and ≈97%, respectively. Our model should prove useful in a priori evaluation of the efficacy of fipronil-based drugs in controlling leishmaniasis on the Indian subcontinent and beyond.

Bioengineering a non-genotoxic vector for genetic modification of mesenchymal stem cells.

PubMed

Chen, Xuguang; Nomani, Alireza; Patel, Niket; Nouri, Faranak S; Hatefi, Arash

2018-01-01

Vectors used for stem cell transfection must be non-genotoxic, in addition to possessing high efficiency, because they could potentially transform normal stem cells into cancer-initiating cells. The objective of this research was to bioengineer an efficient vector that can be used for genetic modification of stem cells without any negative somatic or genetic impact. Two types of multifunctional vectors, namely targeted and non-targeted were genetically engineered and purified from E. coli. The targeted vectors were designed to enter stem cells via overexpressed receptors. The non-targeted vectors were equipped with MPG and Pep1 cell penetrating peptides. A series of commercial synthetic non-viral vectors and an adenoviral vector were used as controls. All vectors were evaluated for their efficiency and impact on metabolic activity, cell membrane integrity, chromosomal aberrations (micronuclei formation), gene dysregulation, and differentiation ability of stem cells. The results of this study showed that the bioengineered vector utilizing VEGFR-1 receptors for cellular entry could transfect mesenchymal stem cells with high efficiency without inducing genotoxicity, negative impact on gene function, or ability to differentiate. Overall, the vectors that utilized receptors as ports for cellular entry (viral and non-viral) showed considerably better somato- and genosafety profiles in comparison to those that entered through electrostatic interaction with cellular membrane. The genetically engineered vector in this study demonstrated that it can be safely and efficiently used to genetically modify stem cells with potential applications in tissue engineering and cancer therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generalized hamming networks and applications.

PubMed

Koutroumbas, Konstantinos; Kalouptsidis, Nicholas

2005-09-01

In this paper the classical Hamming network is generalized in various ways. First, for the Hamming maxnet, a generalized model is proposed, which covers under its umbrella most of the existing versions of the Hamming Maxnet. The network dynamics are time varying while the commonly used ramp function may be replaced by a much more general non-linear function. Also, the weight parameters of the network are time varying. A detailed convergence analysis is provided. A bound on the number of iterations required for convergence is derived and its distribution functions are given for the cases where the initial values of the nodes of the Hamming maxnet stem from the uniform and the peak distributions. Stabilization mechanisms aiming to prevent the node(s) with the maximum initial value diverging to infinity or decaying to zero are described. Simulations demonstrate the advantages of the proposed extension. Also, a rough comparison between the proposed generalized scheme as well as the original Hamming maxnet and its variants is carried out in terms of the time required for convergence, in hardware implementations. Finally, the other two parts of the Hamming network, namely the competitors generating module and the decoding module, are briefly considered in the framework of various applications such as classification/clustering, vector quantization and function optimization.

A new Method for the Estimation of Initial Condition Uncertainty Structures in Mesoscale Models

NASA Astrophysics Data System (ADS)

Keller, J. D.; Bach, L.; Hense, A.

2012-12-01

The estimation of fast growing error modes of a system is a key interest of ensemble data assimilation when assessing uncertainty in initial conditions. Over the last two decades three methods (and variations of these methods) have evolved for global numerical weather prediction models: ensemble Kalman filter, singular vectors and breeding of growing modes (or now ensemble transform). While the former incorporates a priori model error information and observation error estimates to determine ensemble initial conditions, the latter two techniques directly address the error structures associated with Lyapunov vectors. However, in global models these structures are mainly associated with transient global wave patterns. When assessing initial condition uncertainty in mesoscale limited area models, several problems regarding the aforementioned techniques arise: (a) additional sources of uncertainty on the smaller scales contribute to the error and (b) error structures from the global scale may quickly move through the model domain (depending on the size of the domain). To address the latter problem, perturbation structures from global models are often included in the mesoscale predictions as perturbed boundary conditions. However, the initial perturbations (when used) are often generated with a variant of an ensemble Kalman filter which does not necessarily focus on the large scale error patterns. In the framework of the European regional reanalysis project of the Hans-Ertel-Center for Weather Research we use a mesoscale model with an implemented nudging data assimilation scheme which does not support ensemble data assimilation at all. In preparation of an ensemble-based regional reanalysis and for the estimation of three-dimensional atmospheric covariance structures, we implemented a new method for the assessment of fast growing error modes for mesoscale limited area models. The so-called self-breeding is development based on the breeding of growing modes technique. Initial perturbations are integrated forward for a short time period and then rescaled and added to the initial state again. Iterating this rapid breeding cycle provides estimates for the initial uncertainty structure (or local Lyapunov vectors) given a specific norm. To avoid that all ensemble perturbations converge towards the leading local Lyapunov vector we apply an ensemble transform variant to orthogonalize the perturbations in the sub-space spanned by the ensemble. By choosing different kind of norms to measure perturbation growth, this technique allows for estimating uncertainty patterns targeted at specific sources of errors (e.g. convection, turbulence). With case study experiments we show applications of the self-breeding method for different sources of uncertainty and different horizontal scales.

Evolving phage vectors for cell targeted gene delivery.

PubMed

Larocca, David; Burg, Michael A; Jensen-Pergakes, Kristen; Ravey, Edward Prenn; Gonzalez, Ana Maria; Baird, Andrew

2002-03-01

We adapted filamentous phage vectors for targeted gene delivery to mammalian cells by inserting a mammalian reporter gene expression cassette (GFP) into the vector backbone and fusing the pIII coat protein to a cell targeting ligand (i.e. FGF2, EGF). Like transfection with animal viral vectors, targeted phage gene delivery is concentration, time, and ligand dependent. Importantly, targeted phage particles are specific for the appropriate target cell surface receptor. Phage have distinct advantages over existing gene therapy vectors because they are simple, economical to produce at high titer, have no intrinsic tropism for mammalian cells, and are relatively simple to genetically modify and evolve. Initially transduction by targeted phage particles was low resulting in foreign gene expression in 1-2% of transfected cells. We increased transduction efficiency by modifying both the transfection protocol and vector design. For example, we stabilized the display of the targeting ligand to create multivalent phagemid-based vectors with transduction efficiencies of up to 45% in certain cell lines when combined with genotoxic treatment. Taken together, these studies establish that the efficiency of phage-mediated gene transfer can be significantly improved through genetic modification. We are currently evolving phage vectors with enhanced cell targeting, increased stability, reduced immunogenicity and other properties suitable for gene therapy.

Synthesis of high molecular weight PEO using non-metal initiators

DOEpatents

Yang, Jin; Sivanandan, Kulandaivelu; Pistorino, Jonathan; Eitouni, Hany Basam

2015-05-19

A new synthetic method to prepare high molecular weight poly(ethylene oxide) with a very narrow molecular weight distribution (PDI<1.5) is described. The method involves a metal free initiator system, thus avoiding dangerous, flammable organometallic compounds.

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

Simulation study of the initial crystallization processes of poly(3-hexylthiophene) in solution: ordering dynamics of main chains and side chains.

PubMed

Takizawa, Yuumi; Shimomura, Takeshi; Miura, Toshiaki

2013-05-23

We study the initial nucleation dynamics of poly(3-hexylthiophene) (P3HT) in solution, focusing on the relationship between the ordering process of main chains and that of side chains. We carried out Langevin dynamics simulation and found that the initial nucleation processes consist of three steps: the ordering of ring orientation, the ordering of main-chain vectors, and the ordering of side chains. At the start, the normal vectors of thiophene rings aligned in a very short time, followed by alignment of main-chain end-to-end vectors. The flexible side-chain ordering took almost 5 times longer than the rigid-main-chain ordering. The simulation results indicated that the ordering of side chains was induced after the formation of the regular stack structure of main chains. This slow ordering dynamics of flexible side chains is one of the factors that cause anisotropic nuclei growth, which would be closely related to the formation of nanofiber structures without external flow field. Our simulation results revealed how the combined structure of the planar and rigid-main-chain backbones and the sparse flexible side chains lead to specific ordering behaviors that are not observed in ordinary linear polymer crystallization processes.

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.

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.

Comparison of different wind data interpolation methods for a region with complex terrain in Central Asia

NASA Astrophysics Data System (ADS)

Reinhardt, Katja; Samimi, Cyrus

2018-01-01

While climatological data of high spatial resolution are largely available in most developed countries, the network of climatological stations in many other regions of the world still constitutes large gaps. Especially for those regions, interpolation methods are important tools to fill these gaps and to improve the data base indispensible for climatological research. Over the last years, new hybrid methods of machine learning and geostatistics have been developed which provide innovative prospects in spatial predictive modelling. This study will focus on evaluating the performance of 12 different interpolation methods for the wind components \\overrightarrow{u} and \\overrightarrow{v} in a mountainous region of Central Asia. Thereby, a special focus will be on applying new hybrid methods on spatial interpolation of wind data. This study is the first evaluating and comparing the performance of several of these hybrid methods. The overall aim of this study is to determine whether an optimal interpolation method exists, which can equally be applied for all pressure levels, or whether different interpolation methods have to be used for the different pressure levels. Deterministic (inverse distance weighting) and geostatistical interpolation methods (ordinary kriging) were explored, which take into account only the initial values of \\overrightarrow{u} and \\overrightarrow{v} . In addition, more complex methods (generalized additive model, support vector machine and neural networks as single methods and as hybrid methods as well as regression-kriging) that consider additional variables were applied. The analysis of the error indices revealed that regression-kriging provided the most accurate interpolation results for both wind components and all pressure heights. At 200 and 500 hPa, regression-kriging is followed by the different kinds of neural networks and support vector machines and for 850 hPa it is followed by the different types of support vector machine and ordinary kriging. Overall, explanatory variables improve the interpolation results.

A New Tropical Cyclone Dynamic Initialization Technique Using High Temporal and Spatial Density Atmospheric Motion Vectors and Airborne Field Campaign Data

NASA Technical Reports Server (NTRS)

Hendricks, Eric A.; Bell, Michael M.; Elsberry, Russell L.; Velden, Chris S.; Cecil, Dan

2016-01-01

Background: Initialization of tropical cyclones in numerical weather prediction (NWP) systems is a great challenge: Mass-wind ?eld balance; Secondary circulation and heating; Asymmetries. There can be large adjustments in structure and intensity in the ?rst 24 hours if the initial vortex is not in balance: Spurious gravity waves; Spin-up (model and physics). Existing mesoscale NWP model TC (Tropical Cyclone) initialization strategies: Bogus vortex, cold start from global analyses; 3DVAR or 4DVAR, possibly with synthetic observations; EnKF (Ensemble Kalman Filter); Dynamic initialization. Dynamic initialization allows vortex to have improved balance and physics spin-up at the initial time (e.g., Hendricks et al. 2013, 2011; Nguyen and Chen 2011; Fiorino and Warner 1981; Hoke and Anthes 1976). Himawari-8 geostationary satellite has capability of continuous imagery (10-minutes) over the full disk: New GOES-R satellites will have same capability. This will allow for unprecedented observations of tropical cyclones. However, current data assimila1on systems are not capable of ingesting such high temporal observations (Atmospheric Mo1on Vectors - AMVs). Hourly AMVs are produced, and thinned to 100-kilometer spacing in the horizontal. An entirely new data assimilation concept is required to utilize these observations.

New Insights on the Inflammatory Role of Lutzomyia longipalpis Saliva in Leishmaniasis

PubMed Central

Prates, Deboraci Brito; Araújo-Santos, Théo; Brodskyn, Cláudia; Barral-Netto, Manoel; Barral, Aldina; Borges, Valéria Matos

2012-01-01

When an haematophagous sand fly vector insect bites a vertebrate host, it introduces its mouthparts into the skin and lacerates blood vessels, forming a hemorrhagic pool which constitutes an intricate environment of cell interactions. In this scenario, the initial performance of host, parasite, and vector “authors” will heavily influence the course of Leishmania infection. Recent advances in vector-parasite-host interaction have elucidated “co-authors” and “new roles” not yet described. We review here the stimulatory role of Lutzomyia longipalpis saliva leading to inflammation and try to connect them in an early context of Leishmania infection. PMID:22506098

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.

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 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...

An experimental study of interstitial lung tissue classification in HRCT images using ANN and role of cost functions

NASA Astrophysics Data System (ADS)

Dash, Jatindra K.; Kale, Mandar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan; Prabhakar, Nidhi; Garg, Mandeep; Kalra, Naveen

2017-03-01

In this paper, we investigate the effect of the error criteria used during a training phase of the artificial neural network (ANN) on the accuracy of the classifier for classification of lung tissues affected with Interstitial Lung Diseases (ILD). Mean square error (MSE) and the cross-entropy (CE) criteria are chosen being most popular choice in state-of-the-art implementations. The classification experiment performed on the six interstitial lung disease (ILD) patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Micronodules, Fibrosis and Healthy from MedGIFT database. The texture features from an arbitrary region of interest (AROI) are extracted using Gabor filter. Two different neural networks are trained with the scaled conjugate gradient back propagation algorithm with MSE and CE error criteria function respectively for weight updation. Performance is evaluated in terms of average accuracy of these classifiers using 4 fold cross-validation. Each network is trained for five times for each fold with randomly initialized weight vectors and accuracies are computed. Significant improvement in classification accuracy is observed when ANN is trained by using CE (67.27%) as error function compared to MSE (63.60%). Moreover, standard deviation of the classification accuracy for the network trained with CE (6.69) error criteria is found less as compared to network trained with MSE (10.32) criteria.

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.

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

Small Interfering RNA Pathway Modulates Initial Viral Infection in Midgut Epithelium of Insect after Ingestion of Virus.

PubMed

Lan, Hanhong; Chen, Hongyan; Liu, Yuyan; Jiang, Chaoyang; Mao, Qianzhuo; Jia, Dongsheng; Chen, Qian; Wei, Taiyun

2016-01-15

Numerous viruses are transmitted in a persistent manner by insect vectors. Persistent viruses establish their initial infection in the midgut epithelium, from where they disseminate to the midgut visceral muscles. Although propagation of viruses in insect vectors can be controlled by the small interfering RNA (siRNA) antiviral pathway, whether the siRNA pathway can control viral dissemination from the midgut epithelium is unknown. Infection by a rice virus (Southern rice black streaked dwarf virus [SRBSDV]) of its incompetent vector (the small brown planthopper [SBPH]) is restricted to the midgut epithelium. Here, we show that the siRNA pathway is triggered by SRBSDV infection in continuously cultured cells derived from the SBPH and in the midgut of the intact insect. Knockdown of the expression of the core component Dicer-2 of the siRNA pathway by RNA interference strongly increased the ability of SRBSDV to propagate in continuously cultured SBPH cells and in the midgut epithelium, allowing viral titers in the midgut epithelium to reach the threshold (1.99 × 10(9) copies of the SRBSDV P10 gene/μg of midgut RNA) needed for viral dissemination into the SBPH midgut muscles. Our results thus represent the first elucidation of the threshold for viral dissemination from the insect midgut epithelium. Silencing of Dicer-2 further facilitated the transmission of SRBSDV into rice plants by SBPHs. Taken together, our results reveal the new finding that the siRNA pathway can control the initial infection of the insect midgut epithelium by a virus, which finally affects the competence of the virus's vector. Many viral pathogens that cause significant global health and agricultural problems are transmitted via insect vectors. The first bottleneck in viral infection, the midgut epithelium, is a principal determinant of the ability of an insect species to transmit a virus. Southern rice black streaked dwarf virus (SRBSDV) is restricted exclusively to the midgut epithelium of an incompetent vector, the small brown planthopper (SBPH). Here, we show that silencing of the core component Dicer-2 of the small interfering RNA (siRNA) pathway increases viral titers in the midgut epithelium past the threshold (1.99 × 10(9) copies of the SRBSDV P10 gene/μg of midgut RNA) for viral dissemination into the midgut muscles and then into the salivary glands, allowing the SBPH to become a competent vector of SRBSDV. This result is the first evidence that the siRNA antiviral pathway has a direct role in the control of viral dissemination from the midgut epithelium and that it affects the competence of the virus's vector. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Small Interfering RNA Pathway Modulates Initial Viral Infection in Midgut Epithelium of Insect after Ingestion of Virus

PubMed Central

Lan, Hanhong; Chen, Hongyan; Liu, Yuyan; Jiang, Chaoyang; Mao, Qianzhuo; Jia, Dongsheng; Chen, Qian

2015-01-01

ABSTRACT Numerous viruses are transmitted in a persistent manner by insect vectors. Persistent viruses establish their initial infection in the midgut epithelium, from where they disseminate to the midgut visceral muscles. Although propagation of viruses in insect vectors can be controlled by the small interfering RNA (siRNA) antiviral pathway, whether the siRNA pathway can control viral dissemination from the midgut epithelium is unknown. Infection by a rice virus (Southern rice black streaked dwarf virus [SRBSDV]) of its incompetent vector (the small brown planthopper [SBPH]) is restricted to the midgut epithelium. Here, we show that the siRNA pathway is triggered by SRBSDV infection in continuously cultured cells derived from the SBPH and in the midgut of the intact insect. Knockdown of the expression of the core component Dicer-2 of the siRNA pathway by RNA interference strongly increased the ability of SRBSDV to propagate in continuously cultured SBPH cells and in the midgut epithelium, allowing viral titers in the midgut epithelium to reach the threshold (1.99 × 109 copies of the SRBSDV P10 gene/μg of midgut RNA) needed for viral dissemination into the SBPH midgut muscles. Our results thus represent the first elucidation of the threshold for viral dissemination from the insect midgut epithelium. Silencing of Dicer-2 further facilitated the transmission of SRBSDV into rice plants by SBPHs. Taken together, our results reveal the new finding that the siRNA pathway can control the initial infection of the insect midgut epithelium by a virus, which finally affects the competence of the virus's vector. IMPORTANCE Many viral pathogens that cause significant global health and agricultural problems are transmitted via insect vectors. The first bottleneck in viral infection, the midgut epithelium, is a principal determinant of the ability of an insect species to transmit a virus. Southern rice black streaked dwarf virus (SRBSDV) is restricted exclusively to the midgut epithelium of an incompetent vector, the small brown planthopper (SBPH). Here, we show that silencing of the core component Dicer-2 of the small interfering RNA (siRNA) pathway increases viral titers in the midgut epithelium past the threshold (1.99 × 109 copies of the SRBSDV P10 gene/μg of midgut RNA) for viral dissemination into the midgut muscles and then into the salivary glands, allowing the SBPH to become a competent vector of SRBSDV. This result is the first evidence that the siRNA antiviral pathway has a direct role in the control of viral dissemination from the midgut epithelium and that it affects the competence of the virus's vector. PMID:26537672

A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations.

PubMed

Qin, Fangjun; Chang, Lubin; Jiang, Sai; Zha, Feng

2018-05-03

In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms.

A Sequential Multiplicative Extended Kalman Filter for Attitude Estimation Using Vector Observations

PubMed Central

Qin, Fangjun; Jiang, Sai; Zha, Feng

2018-01-01

In this paper, a sequential multiplicative extended Kalman filter (SMEKF) is proposed for attitude estimation using vector observations. In the proposed SMEKF, each of the vector observations is processed sequentially to update the attitude, which can make the measurement model linearization more accurate for the next vector observation. This is the main difference to Murrell’s variation of the MEKF, which does not update the attitude estimate during the sequential procedure. Meanwhile, the covariance is updated after all the vector observations have been processed, which is used to account for the special characteristics of the reset operation necessary for the attitude update. This is the main difference to the traditional sequential EKF, which updates the state covariance at each step of the sequential procedure. The numerical simulation study demonstrates that the proposed SMEKF has more consistent and accurate performance in a wide range of initial estimate errors compared to the MEKF and its traditional sequential forms. PMID:29751538

Vector Blood Meals Are an Early Indicator of the Effectiveness of the Ecohealth Approach in Halting Chagas Transmission in Guatemala

PubMed Central

Pellecer, Mariele J.; Dorn, Patricia L.; Bustamante, Dulce M.; Rodas, Antonieta; Monroy, M. Carlota

2013-01-01

A novel method using vector blood meal sources to assess the impact of control efforts on the risk of transmission of Chagas disease was tested in the village of El Tule, Jutiapa, Guatemala. Control used Ecohealth interventions, where villagers ameliorated the factors identified as most important for transmission. First, after an initial insecticide application, house walls were plastered. Later, bedroom floors were improved and domestic animals were moved outdoors. Only vector blood meal sources revealed the success of the first interventions: human blood meals declined from 38% to 3% after insecticide application and wall plastering. Following all interventions both vector blood meal sources and entomological indices revealed the reduction in transmission risk. These results indicate that vector blood meals may reveal effects of control efforts early on, effects that may not be apparent using traditional entomological indices, and provide further support for the Ecohealth approach to Chagas control in Guatemala. PMID:23382165

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.

Detection of Accelerating Targets in Clutter Using a De-Chirping Technique

DTIC Science & Technology

2014-06-01

Academy, also in Canberra, working on the the- ory and simulation of spatial optical solitons and light-induced optical switching in nonlinear...signal gain in the receiver. UNCLASSIFIED 1 DSTO–RR–0399 UNCLASSIFIED target along the velocity vector , or equivalently by radar platform. The change of...the tracker uses range rate in its track initiation logic. (2) Lateral acceleration perpendicular to the velocity vector - the target is turning and

Improving Dengue Virus Capture Rates in Humans and Vectors in Kamphaeng Phet Province, Thailand, Using an Enhanced Spatiotemporal Surveillance Strategy

DTIC Science & Technology

2015-05-18

THOMAS AND OTHERS ENHANCED SURVEILLANCE FOR DENGUE Improving Dengue Virus Capture Rates in Humans and Vectors in Kamphaeng Phet Province...of Medical Sciences, Bangkok, Thailand. Abstract. Dengue is of public health importance in tropical and sub-tropical regions. Dengue virus (DENV...with confirmed dengue (initiates) and associated cluster individuals (associates) with entomologic sampling. A total of 438 associates were enrolled

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.

Supercomputer implementation of finite element algorithms for high speed compressible flows

NASA Technical Reports Server (NTRS)

Thornton, E. A.; Ramakrishnan, R.

1986-01-01

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

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

Object motion computation for the initiation of smooth pursuit eye movements in humans.

PubMed

Wallace, Julian M; Stone, Leland S; Masson, Guillaume S

2005-04-01

Pursuing an object with smooth eye movements requires an accurate estimate of its two-dimensional (2D) trajectory. This 2D motion computation requires that different local motion measurements are extracted and combined to recover the global object-motion direction and speed. Several combination rules have been proposed such as vector averaging (VA), intersection of constraints (IOC), or 2D feature tracking (2DFT). To examine this computation, we investigated the time course of smooth pursuit eye movements driven by simple objects of different shapes. For type II diamond (where the direction of true object motion is dramatically different from the vector average of the 1-dimensional edge motions, i.e., VA not equal IOC = 2DFT), the ocular tracking is initiated in the vector average direction. Over a period of less than 300 ms, the eye-tracking direction converges on the true object motion. The reduction of the tracking error starts before the closing of the oculomotor loop. For type I diamonds (where the direction of true object motion is identical to the vector average direction, i.e., VA = IOC = 2DFT), there is no such bias. We quantified this effect by calculating the direction error between responses to types I and II and measuring its maximum value and time constant. At low contrast and high speeds, the initial bias in tracking direction is larger and takes longer to converge onto the actual object-motion direction. This effect is attenuated with the introduction of more 2D information to the extent that it was totally obliterated with a texture-filled type II diamond. These results suggest a flexible 2D computation for motion integration, which combines all available one-dimensional (edge) and 2D (feature) motion information to refine the estimate of object-motion direction over time.

Performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches in VQ codebook generation for image compression

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Chou, Ping-Yi; Chou, Jyh-Horng

2015-11-01

The aim of this study is to generate vector quantisation (VQ) codebooks by integrating principle component analysis (PCA) algorithm, Linde-Buzo-Gray (LBG) algorithm, and evolutionary algorithms (EAs). The EAs include genetic algorithm (GA), particle swarm optimisation (PSO), honey bee mating optimisation (HBMO), and firefly algorithm (FF). The study is to provide performance comparisons between PCA-EA-LBG and PCA-LBG-EA approaches. The PCA-EA-LBG approaches contain PCA-GA-LBG, PCA-PSO-LBG, PCA-HBMO-LBG, and PCA-FF-LBG, while the PCA-LBG-EA approaches contain PCA-LBG, PCA-LBG-GA, PCA-LBG-PSO, PCA-LBG-HBMO, and PCA-LBG-FF. All training vectors of test images are grouped according to PCA. The PCA-EA-LBG used the vectors grouped by PCA as initial individuals, and the best solution gained by the EAs was given for LBG to discover a codebook. The PCA-LBG approach is to use the PCA to select vectors as initial individuals for LBG to find a codebook. The PCA-LBG-EA used the final result of PCA-LBG as an initial individual for EAs to find a codebook. The search schemes in PCA-EA-LBG first used global search and then applied local search skill, while in PCA-LBG-EA first used local search and then employed global search skill. The results verify that the PCA-EA-LBG indeed gain superior results compared to the PCA-LBG-EA, because the PCA-EA-LBG explores a global area to find a solution, and then exploits a better one from the local area of the solution. Furthermore the proposed PCA-EA-LBG approaches in designing VQ codebooks outperform existing approaches shown in the literature.

The upstream enhancer elements of the G6PC promoter are critical for optimal G6PC expression in murine glycogen storage disease type Ia.

PubMed

Lee, Young Mok; Pan, Chi-Jiunn; Koeberl, Dwight D; Mansfield, Brian C; Chou, Janice Y

2013-11-01

Glycogen storage disease type-Ia (GSD-Ia) patients deficient in glucose-6-phosphatase-α (G6Pase-α or G6PC) manifest impaired glucose homeostasis characterized by fasting hypoglycemia, growth retardation, hepatomegaly, nephromegaly, hyperlipidemia, hyperuricemia, and lactic acidemia. Two efficacious recombinant adeno-associated virus pseudotype 2/8 (rAAV8) vectors expressing human G6Pase-α have been independently developed. One is a single-stranded vector containing a 2864-bp of the G6PC promoter/enhancer (rAAV8-GPE) and the other is a double-stranded vector containing a shorter 382-bp minimal G6PC promoter/enhancer (rAAV8-miGPE). To identify the best construct, a direct comparison of the rAAV8-GPE and the rAAV8-miGPE vectors was initiated to determine the best vector to take forward into clinical trials. We show that the rAAV8-GPE vector directed significantly higher levels of hepatic G6Pase-α expression, achieved greater reduction in hepatic glycogen accumulation, and led to a better toleration of fasting in GSD-Ia mice than the rAAV8-miGPE vector. Our results indicated that additional control elements in the rAAV8-GPE vector outweigh the gains from the double-stranded rAAV8-miGPE transduction efficiency, and that the rAAV8-GPE vector is the current choice for clinical translation in human GSD-Ia. © 2013.

Influence of sequence and size of DNA on packaging efficiency of parvovirus MVM-based vectors.

PubMed

Brandenburger, A; Coessens, E; El Bakkouri, K; Velu, T

1999-05-01

We have derived a vector from the autonomous parvovirus MVM(p), which expresses human IL-2 specifically in transformed cells (Russell et al., J. Virol 1992;66:2821-2828). Testing the therapeutic potential of these vectors in vivo requires high-titer stocks. Stocks with a titer of 10(9) can be obtained after concentration and purification (Avalosse et al., J. Virol. Methods 1996;62:179-183), but this method requires large culture volumes and cannot easily be scaled up. We wanted to increase the production of recombinant virus at the initial transfection step. Poor vector titers could be due to inadequate genome amplification or to inefficient packaging. Here we show that intracellular amplification of MVM vector genomes is not the limiting factor for vector production. Several vector genomes of different size and/or structure were amplified to an equal extent. Their amplification was also equivalent to that of a cotransfected wild-type genome. We did not observe any interference between vector and wild-type genomes at the level of DNA amplification. Despite equivalent genome amplification, vector titers varied greatly between the different genomes, presumably owing to differences in packaging efficiency. Genomes with a size close to 100% that of wild type were packaged most efficiently with loss of efficiency at lower and higher sizes. However, certain genomes of identical size showed different packaging efficiencies, illustrating the importance of the DNA sequence, and probably its structure.

Adenoviral vector tethering to metal surfaces via hydrolysable cross-linkers for the modulation of vector release and transduction

PubMed Central

Fishbein, Ilia; Forbes, Scott P.; Chorny, Michael; Connolly, Jeanne M.; Adamo, Richard F.; Corrales, Ricardo; Alferiev, Ivan S.; Levy, Robert J.

2013-01-01

The use of arterial stents and other medical implants as a delivery platform for surface immobilized gene vectors allows for safe and efficient localized expression of therapeutic transgenes. In this study we investigate the use of hydrolysable cross-linkers with distinct kinetics of hydrolysis for delivery of gene vectors from polyallylamine bisphosphonate-modified metal surfaces. Three cross-linkers with the estimated t1/2 of ester bonds hydrolysis of 5, 12 and 50 days demonstrated a cumulative 20%, 39% and 45% vector release, respectively, after 30 days exposure to physiological buffer at 37°C. Transgene expression in endothelial and smooth muscles cells transduced with substrate immobilized adenovirus resulted in significantly different expression profiles for each individual cross-linker. Furthermore, immobilization of adenoviral vectors effectively extended their transduction effectiveness beyond the initial phase of release. Transgene expression driven by adenovirus-tethered stents in rat carotid arteries demonstrated that a faster rate of cross-linker hydrolysis resulted in higher expression levels at day 1, which declined by day 8 after stent implantation, while inversely, slower hydrolysis was associated with increased arterial expression at day 8 in comparison with day 1. In conclusion, adjustable release of transduction-competent adenoviral vectors from metallic surfaces can be achieved, both in vitro and in vivo, through surface immobilization of adenoviral vectors using hydrolysable cross-linkers with structure-specific release kinetics. PMID:23777912

Geminivirus vectors for high-level expression of foreign proteins in plant cells.

PubMed

Mor, Tsafrir S; Moon, Yong-Sun; Palmer, Kenneth E; Mason, Hugh S

2003-02-20

Bean yellow dwarf virus (BeYDV) is a monopartite geminivirus that can infect dicotyledonous plants. We have developed a high-level expression system that utilizes elements of the replication machinery of this single-stranded DNA virus. The replication initiator protein (Rep) mediates release and replication of a replicon from a DNA construct ("LSL vector") that contains an expression cassette for a gene of interest flanked by cis-acting elements of the virus. We used tobacco NT1 cells and biolistic delivery of plasmid DNA for evaluation of replication and expression of reporter genes contained within an LSL vector. By codelivery of a GUS reporter-LSL vector and a Rep-supplying vector, we obtained up to 40-fold increase in expression levels compared to delivery of the reporter-LSL vectors alone. High-copy replication of the LSL vector was correlated with enhanced expression of GUS. Rep expression using a whole BeYDV clone, a cauliflower mosaic virus 35S promoter driving either genomic rep or an intron-deleted rep gene, or 35S-rep contained in the LSL vector all achieved efficient replication and enhancement of GUS expression. We anticipate that this system can be adapted for use in transgenic plants or plant cell cultures with appropriately regulated expression of Rep, with the potential to greatly increase yield of recombinant proteins. Copyright 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 81: 430-437, 2003.

Virus altered rice attractiveness to planthoppers is mediated by volatiles and related to virus titre and expression of defence and volatile-biosynthesis genes.

PubMed

Lu, Guanghua; Zhang, Tong; He, Yuange; Zhou, Guohui

2016-12-07

Viruses may induce changes in plant hosts and vectors to enhance their transmission. The white-backed planthopper (WBPH) and brown planthopper (BPH) are vectors of Southern rice black-streaked dwarf virus (SRBSDV) and Rice ragged stunt virus (RRSV), respectively, which cause serious rice diseases. We herein describe the effects of SRBSDV and RRSV infections on host-selection behaviour of vector and non-vector planthoppers at different disease stages. The Y-tube olfactometer choice and free-choice tests indicated that SRBSDV and RRSV infections altered the attractiveness of rice plants to vector and non-vector planthoppers. The attractiveness was mainly mediated by rice volatiles, and varied with disease progression. The attractiveness of the SRBSDV- or RRSV-infected rice plants to the virus-free WBPHs or BPHs initially decreased, then increased, and finally decreased again. For the viruliferous WBPHs and BPHs, SRBSDV or RRSV infection increased the attractiveness of plants more for the non-vector than for the vector planthoppers. Furthermore, we observed that the attractiveness of infected plants to planthoppers was positively correlated with the virus titres. The titre effects were greater for virus-free than for viruliferous planthoppers. Down-regulated defence genes OsAOS1, OsICS, and OsACS2 and up-regulated volatile-biosynthesis genes OsLIS, OsCAS, and OsHPL3 expression in infected plants may influence their attractiveness.

Eating behaviors and weight over time in a prospective study: the Healthy Twin Study.

PubMed

Song, Yun-Mi; Lee, Kayoung; Sung, Joohon

2014-01-01

We examined the relationships of combined initial restrained and external/emotional eating with initial BMI and change in weight and these subscales over time. BMI and the Dutch Eating Behavior Questionnaire were twicemeasured in 1361 Korean twins and families (482 men, 879 women) over a period of 2.7±0.9 years. Subjects were classified by combination of initial sex-specific restrained and external (or emotional) eating tertiles. Linear mixed models were performed after adjusting for confounders at baseline (household, sibling relations, sex, age, education level, smoking, alcohol use, energy intake, physical activity, and medical history). In adjusted models, initial BMI increased with increasing tertiles of initial restrained eating across initial external/emotional eating tertiles. Weight was less likely to increase over time with increasing tertiles of initial restrained eating in the lowest external eating tertile and middle tertile of emotional eating at baseline. Subscale scores decreased over time with increasing tertiles of corresponding subscales at baseline. These findings suggest that high dietary restraint and external/emotional eating may indicate concurrent high BMI and attenuated weight gain and decreases in corresponding subscales over time.

Constraining primordial vector mode from B-mode polarization

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

Saga, Shohei; Ichiki, Kiyotomo; Shiraishi, Maresuke, E-mail: saga.shohei@nagoya-u.jp, E-mail: maresuke.shiraishi@pd.infn.it, E-mail: ichiki@a.phys.nagoya-u.ac.jp

The B-mode polarization spectrum of the Cosmic Microwave Background (CMB) may be the smoking gun of not only the primordial tensor mode but also of the primordial vector mode. If there exist nonzero vector-mode metric perturbations in the early Universe, they are known to be supported by anisotropic stress fluctuations of free-streaming particles such as neutrinos, and to create characteristic signatures on both the CMB temperature, E-mode, and B-mode polarization anisotropies. We place constraints on the properties of the primordial vector mode characterized by the vector-to-scalar ratio r{sub v} and the spectral index n{sub v} of the vector-shear power spectrum,more » from the Planck and BICEP2 B-mode data. We find that, for scale-invariant initial spectra, the ΛCDM model including the vector mode fits the data better than the model including the tensor mode. The difference in χ{sup 2} between the vector and tensor models is Δχ{sup 2} = 3.294, because, on large scales the vector mode generates smaller temperature fluctuations than the tensor mode, which is preferred for the data. In contrast, the tensor mode can fit the data set equally well if we allow a significantly blue-tilted spectrum. We find that the best-fitting tensor mode has a large blue tilt and leads to an indistinct reionization bump on larger angular scales. The slightly red-tilted vector mode supported by the current data set can also create O(10{sup -22})-Gauss magnetic fields at cosmological recombination. Our constraints should motivate research that considers models of the early Universe that involve the vector mode.« less

The significance of vector magnetic field measurements

NASA Technical Reports Server (NTRS)

Hagyard, M. J.

1990-01-01

Observations of four flaring solar active regions, obtained during 1980-1986 with the NASA Marshall vector magnetograph (Hagyard et al., 1982 and 1985), are presented graphically and characterized in detail, with reference to nearly simultaneous Big Bear Solar Observatory and USAF ASW H-alpha images. It is shown that the flares occurred where local photospheric magnetic fields differed most from the potential field, with initial brightening on either side of a magnetic-neutral line near the point of maximum angular shear (rather than that of maximum magnetic-field strength, typically 1 kG or greater). Particular emphasis is placed on the fact that these significant nonpotential features were detected only by measuring all three components of the vector magnetic field.

Investigation on partially coherent vector beams and their propagation and focusing properties.

PubMed

Hu, Kelei; Chen, Ziyang; Pu, Jixiong

2012-11-01

The propagation and focusing properties of partially coherent vector beams including radially polarized and azimuthally polarized (AP) beams are theoretically and experimentally investigated. The beam profile of a partially coherent radially or AP beam can be shaped by adjusting the initial spatial coherence length. The dark hollow, flat-topped, and Gaussian beam spots can be obtained, which will be useful in trapping particles. The experimental observations are consistent with the theoretical results.

Magnetometer-only attitude and angular velocity filtering estimation for attitude changing spacecraft

NASA Astrophysics Data System (ADS)

Ma, Hongliang; Xu, Shijie

2014-09-01

This paper presents an improved real-time sequential filter (IRTSF) for magnetometer-only attitude and angular velocity estimation of spacecraft during its attitude changing (including fast and large angular attitude maneuver, rapidly spinning or uncontrolled tumble). In this new magnetometer-only attitude determination technique, both attitude dynamics equation and first time derivative of measured magnetic field vector are directly leaded into filtering equations based on the traditional single vector attitude determination method of gyroless and real-time sequential filter (RTSF) of magnetometer-only attitude estimation. The process noise model of IRTSF includes attitude kinematics and dynamics equations, and its measurement model consists of magnetic field vector and its first time derivative. The observability of IRTSF for small or large angular velocity changing spacecraft is evaluated by an improved Lie-Differentiation, and the degrees of observability of IRTSF for different initial estimation errors are analyzed by the condition number and a solved covariance matrix. Numerical simulation results indicate that: (1) the attitude and angular velocity of spacecraft can be estimated with sufficient accuracy using IRTSF from magnetometer-only data; (2) compared with that of RTSF, the estimation accuracies and observability degrees of attitude and angular velocity using IRTSF from magnetometer-only data are both improved; and (3) universality: the IRTSF of magnetometer-only attitude and angular velocity estimation is observable for any different initial state estimation error vector.

Effects of Changing Body Weight Distribution on Mediolateral Stability Control during Gait Initiation

PubMed Central

Caderby, Teddy; Yiou, Eric; Peyrot, Nicolas; de Viviés, Xavier; Bonazzi, Bruno; Dalleau, Georges

2017-01-01

During gait initiation, anticipatory postural adjustments (APA) precede the execution of the first step. It is generally acknowledged that these APA contribute to forward progression but also serve to stabilize the whole body in the mediolateral direction during step execution. Although previous studies have shown that changes in the distribution of body weight between both legs influence motor performance during gait initiation, it is not known whether and how such changes affect a person’s postural stability during this task. The aim of this study was to investigate the effects of changing initial body weight distribution between legs on mediolateral postural stability during gait initiation. Changes in body weight distribution were induced under experimental conditions by modifying the frontal plane distribution of an external load located at the participants’ waists. Fifteen healthy adults performed a gait initiation series at a similar speed under three conditions: with the overload evenly distributed over both legs; with the overload strictly distributed over the swing-limb side; and with the overload strictly distributed over the stance-leg side. Our results showed that the mediolateral location of center-of-mass (CoM) during the initial upright posture differed between the experimental conditions, indicating modifications in the initial distribution of body weight between the legs according to the load distribution. While the parameters related to the forward progression remained unchanged, the alterations in body weight distribution elicited adaptive changes in the amplitude of APA in the mediolateral direction (i.e., maximal mediolateral shift of the center of pressure (CoP)), without variation in their duration. Specifically, it was observed that the amplitude of APA was modulated in such a way that mediolateral dynamic stability at swing foot-contact, quantified by the margin of stability (i.e., the distance between the base of support boundary and the extrapolated CoM position), did not vary between the conditions. These findings suggest that APA seem to be scaled as a function of the initial body weight distribution between both legs so as to maintain optimal conditions of stability during gait initiation. PMID:28396629

Lorcaserin plus lifestyle modification for weight loss maintenance: Rationale and design for a randomized controlled trial.

PubMed

Tronieri, Jena Shaw; Alfaris, Nasreen; Chao, Ariana M; Pearl, Rebecca L; Alamuddin, Naji; Bakizada, Zayna M; Berkowitz, Robert I; Wadden, Thomas A

2017-08-01

Few studies have examined the efficacy of recently approved medications for chronic weight management in facilitating the maintenance of lost weight. This paper provides an overview of the design and rationale for a trial investigating whether lorcaserin, when combined with behavioral weight loss maintenance sessions (WLM), will facilitate the maintenance of losses of ≥5% of initial weight. In this two-phase trial, participants with obesity will enroll in a 14-week run-in diet program consisting of weekly group lifestyle modification sessions and a 1000-1200kcal/d meal replacement diet. Participants who complete this weight induction phase and lose at least 5% of initial weight will then be randomized to 52weeks of WLM plus lorcaserin or WLM plus placebo. We hypothesize that at 52weeks post randomization, participants assigned to WLM plus lorcaserin will achieve significantly better maintenance of the prior 5% weight loss. We will recruit 182 adults with obesity to participate in the diet run-in, 136 of whom (75%) are expected to become eligible for the randomized controlled trial. Co-primary outcomes include the percentage of participants who maintain a loss of at least 5% of initial weight at week 52 and change in weight (kg) from randomization to week 52. This two-phase design will allow us to determine the potential efficacy of chronic weight management using lorcaserin for maintaining initial losses of at least 5% body weight, induced by the use of a structured meal-replacement diet. This combined approach holds promise of achieving larger long-term weight losses. NCT02388568 on ClinicalTrials.gov. Copyright © 2017 Elsevier Inc. All rights reserved.

Edge Detection and Geometric Methods in Computer Vision,

DTIC Science & Technology

1985-02-01

enlightening discussion) Derivations or Eqs. 3.29, 3.31, 3.32 (some statistics) Experimental results (pictures)-- not very informative, extensive or useful. lie... neurophysiology and hardware design. If one views 9 the state space as a free vector space on the labels over the field of weights (which we take to be R), then

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…

Accurate Initial State Estimation in a Monocular Visual–Inertial SLAM System

PubMed Central

Chen, Jing; Zhou, Zixiang; Leng, Zhen; Fan, Lei

2018-01-01

The fusion of monocular visual and inertial cues has become popular in robotics, unmanned vehicles and augmented reality fields. Recent results have shown that optimization-based fusion strategies outperform filtering strategies. Robust state estimation is the core capability for optimization-based visual–inertial Simultaneous Localization and Mapping (SLAM) systems. As a result of the nonlinearity of visual–inertial systems, the performance heavily relies on the accuracy of initial values (visual scale, gravity, velocity and Inertial Measurement Unit (IMU) biases). Therefore, this paper aims to propose a more accurate initial state estimation method. On the basis of the known gravity magnitude, we propose an approach to refine the estimated gravity vector by optimizing the two-dimensional (2D) error state on its tangent space, then estimate the accelerometer bias separately, which is difficult to be distinguished under small rotation. Additionally, we propose an automatic termination criterion to determine when the initialization is successful. Once the initial state estimation converges, the initial estimated values are used to launch the nonlinear tightly coupled visual–inertial SLAM system. We have tested our approaches with the public EuRoC dataset. Experimental results show that the proposed methods can achieve good initial state estimation, the gravity refinement approach is able to efficiently speed up the convergence process of the estimated gravity vector, and the termination criterion performs well. PMID:29419751

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.

Predictability of tropical cyclone events on intraseasonal timescales with the ECMWF monthly forecast model

NASA Astrophysics Data System (ADS)

Elsberry, Russell L.; Jordan, Mary S.; Vitart, Frederic

2010-05-01

The objective of this study is to provide evidence of predictability on intraseasonal time scales (10-30 days) for western North Pacific tropical cyclone formation and subsequent tracks using the 51-member ECMWF 32-day forecasts made once a week from 5 June through 25 December 2008. Ensemble storms are defined by grouping ensemble member vortices whose positions are within a specified separation distance that is equal to 180 n mi at the initial forecast time t and increases linearly to 420 n mi at Day 14 and then is constant. The 12-h track segments are calculated with a Weighted-Mean Vector Motion technique in which the weighting factor is inversely proportional to the distance from the endpoint of the previous 12-h motion vector. Seventy-six percent of the ensemble storms had five or fewer member vortices. On average, the ensemble storms begin 2.5 days before the first entry of the Joint Typhoon Warning Center (JTWC) best-track file, tend to translate too slowly in the deep tropics, and persist for longer periods over land. A strict objective matching technique with the JTWC storms is combined with a second subjective procedure that is then applied to identify nearby ensemble storms that would indicate a greater likelihood of a tropical cyclone developing in that region with that track orientation. The ensemble storms identified in the ECMWF 32-day forecasts provided guidance on intraseasonal timescales of the formations and tracks of the three strongest typhoons and two other typhoons, but not for two early season typhoons and the late season Dolphin. Four strong tropical storms were predicted consistently over Week-1 through Week-4, as was one weak tropical storm. Two other weak tropical storms, three tropical cyclones that developed from precursor baroclinic systems, and three other tropical depressions were not predicted on intraseasonal timescales. At least for the strongest tropical cyclones during the peak season, the ECMWF 32-day ensemble provides guidance of formation and tracks on 10-30 day timescales.

Zika virus infection-the next wave after dengue?

PubMed

Wong, Samson Sai-Yin; Poon, Rosana Wing-Shan; Wong, Sally Cheuk-Ying

2016-04-01

Zika virus was initially discovered in east Africa about 70 years ago and remained a neglected arboviral disease in Africa and Southeast Asia. The virus first came into the limelight in 2007 when it caused an outbreak in Micronesia. In the ensuing decade, it spread widely in other Pacific islands, after which its incursion into Brazil in 2015 led to a widespread epidemic in Latin America. In most infected patients the disease is relatively benign. Serious complications include Guillain-Barré syndrome and congenital infection which may lead to microcephaly and maculopathy. Aedes mosquitoes are the main vectors, in particular, Ae. aegypti. Ae. albopictus is another potential vector. Since the competent mosquito vectors are highly prevalent in most tropical and subtropical countries, introduction of the virus to these areas could readily result in endemic transmission of the disease. The priorities of control include reinforcing education of travellers to and residents of endemic areas, preventing further local transmission by vectors, and an integrated vector management programme. The container habitats of Ae. aegypti and Ae. albopictus means engagement of the community and citizens is of utmost importance to the success of vector control. Copyright © 2016. Published by Elsevier B.V.

Eco-bio-social determinants for house infestation by non-domiciliated Triatoma dimidiata in the Yucatan Peninsula, Mexico.

PubMed

Dumonteil, Eric; Nouvellet, Pierre; Rosecrans, Kathryn; Ramirez-Sierra, Maria Jesus; Gamboa-León, Rubi; Cruz-Chan, Vladimir; Rosado-Vallado, Miguel; Gourbière, Sébastien

2013-01-01

Chagas disease is a vector-borne disease of major importance in the Americas. Disease prevention is mostly limited to vector control. Integrated interventions targeting ecological, biological and social determinants of vector-borne diseases are increasingly used for improved control. We investigated key factors associated with transient house infestation by T. dimidiata in rural villages in Yucatan, Mexico, using a mixed modeling approach based on initial null-hypothesis testing followed by multimodel inference and averaging on data from 308 houses from three villages. We found that the presence of dogs, chickens and potential refuges, such as rock piles, in the peridomicile as well as the proximity of houses to vegetation at the periphery of the village and to public light sources are major risk factors for infestation. These factors explain most of the intra-village variations in infestation. These results underline a process of infestation distinct from that of domiciliated triatomines and may be used for risk stratification of houses for both vector surveillance and control. Combined integrated vector interventions, informed by an Ecohealth perspective, should aim at targeting several of these factors to effectively reduce infestation and provide sustainable vector control.

User's Guide for Monthly Vector Wind Profile Model

NASA Technical Reports Server (NTRS)

Adelfang, S. I.

1999-01-01

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

Improved Escherichia coli Bactofection and Cytotoxicity by Heterologous Expression of Bacteriophage ΦX174 Lysis Gene E.

PubMed

Chung, Tai-Chun; Jones, Charles H; Gollakota, Akhila; Kamal Ahmadi, Mahmoud; Rane, Snehal; Zhang, Guojian; Pfeifer, Blaine A

2015-05-04

Bactofection offers a gene delivery option particularly useful in the context of immune modulation. The bacterial host naturally attracts recognition and cellular uptake by antigen presenting cells (APCs) as the initial step in triggering an immune response. Moreover, depending on the bacterial vector, molecular biology tools are available to influence and/or overcome additional steps and barriers to effective antigen presentation. In this work, molecular engineering was applied using Escherichia coli as a bactofection vector. In particular, the bacteriophage ΦX174 lysis E (LyE) gene was designed for variable expression across strains containing different levels of lysteriolysin O (LLO). The objective was to generate a bacterial vector with improved attenuation and delivery characteristics. The resulting strains exhibited enhanced gene and protein release and inducible cellular death. In addition, the new vectors demonstrated improved gene delivery and cytotoxicity profiles to RAW264.7 macrophage APCs.

Design and evaluation of thrust vectored nozzles using a multicomponent thrust stand

NASA Technical Reports Server (NTRS)

Carpenter, Thomas W.; Blattner, Ernest W.; Stagner, Robert E.; Contreras, Juanita; Lencioni, Dennis; Mcintosh, Greg

1990-01-01

Future aircraft with the capability of short takeoff and landing, and improved maneuverability especially in the post-stall flight regime will incorporate exhaust nozzles which can be thrust vectored. In order to conduct thrust vector research in the Mechanical Engineering Department at Cal Poly, a program was planned with two objectives; design and construct a multicomponent thrust stand for the specific purpose of measuring nozzle thrust vectors; and to provide quality low moisture air to the thrust stand for cold flow nozzle tests. The design and fabrication of the six-component thrust stand was completed. Detailed evaluation tests of the thrust stand will continue upon the receipt of one signal conditioning option (-702) for the Fluke Data Acquisition System. Preliminary design of thrust nozzles with air supply plenums were completed. The air supply was analyzed with regard to head loss. Initial flow visualization tests were conducted using dual water jets.

Interruption of vector transmission by native vectors and “the art of the possible”

PubMed Central

Salvatella, Roberto; Irabedra, Pilar; Castellanos, Luis G

2013-01-01

In a recent article in the Reader’s Opinion, advantages and disadvantages of the certification processes of interrupted Chagas disease transmission (American trypanosomiasis) by native vector were discussed. Such concept, accepted by those authors for the case of endemic situations with introduced vectors, has been built on a long and laborious process by endemic countries and Subregional Initiatives for Prevention, Control and Treatment of Chagas, with Technical Secretariat of the Pan American Health Organization/World Health Organization, to create a horizon target and goal to concentrate priorities and resource allocation and actions. With varying degrees of sucess, which are not replaceable for a certificate of good practice, has allowed during 23 years to safeguard the effective control of transmission of Trypanosoma cruzi not to hundreds of thousands, but millions of people at risk conditions, truly “the art of the possible.” PMID:24626310

A parametric study of the behavior of the angular momentum vector during spin rate changes of rigid body spacecraft

NASA Technical Reports Server (NTRS)

Longuski, J. M.

1982-01-01

During a spin-up or spin-down maneuver of a spinning spacecraft, it is usual to have not only a constant body-fixed torque about the desired spin axis, but also small undesired constant torques about the transverse axes. This causes the orientation of the angular momentum vector to change in inertial space. Since an analytic solution is available for the angular momentum vector as a function of time, this behavior can be studied for large variations of the dynamic parameters, such as the initial spin rate, the inertial properties and the torques. As an example, the spin-up and spin-down maneuvers of the Galileo spacecraft was studied and as a result, very simple heuristic solutions were discovered which provide very good approximations to the parametric behavior of the angular momentum vector orientation.

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.

A fosmid cloning strategy for detecting the widest possible spectrum of microbes from the international space station drinking water system.

PubMed

Choi, Sangdun; Chang, Mi Sook; Stuecker, Tara; Chung, Christine; Newcombe, David A; Venkateswaran, Kasthuri

2012-12-01

In this study, fosmid cloning strategies were used to assess the microbial populations in water from the International Space Station (ISS) drinking water system (henceforth referred to as Prebiocide and Tank A water samples). The goals of this study were: to compare the sensitivity of the fosmid cloning strategy with that of traditional culture-based and 16S rRNA-based approaches and to detect the widest possible spectrum of microbial populations during the water purification process. Initially, microbes could not be cultivated, and conventional PCR failed to amplify 16S rDNA fragments from these low biomass samples. Therefore, randomly primed rolling-circle amplification was used to amplify any DNA that might be present in the samples, followed by size selection by using pulsed-field gel electrophoresis. The amplified high-molecular-weight DNA from both samples was cloned into fosmid vectors. Several hundred clones were randomly selected for sequencing, followed by Blastn/Blastx searches. Sequences encoding specific genes from Burkholderia, a species abundant in the soil and groundwater, were found in both samples. Bradyrhizobium and Mesorhizobium, which belong to rhizobia, a large community of nitrogen fixers often found in association with plant roots, were present in the Prebiocide samples. Ralstonia, which is prevalent in soils with a high heavy metal content, was detected in the Tank A samples. The detection of many unidentified sequences suggests the presence of potentially novel microbial fingerprints. The bacterial diversity detected in this pilot study using a fosmid vector approach was higher than that detected by conventional 16S rRNA gene sequencing.

Determinants of weight evolution among HIV-positive patients initiating antiretroviral treatment in low resource settings

PubMed Central

Huis in ‘t Veld, D.; Balestre, E.; Buyze, J; Menten, J.; Jaquet, A.; Cooper, D.A.; Dabis, F.; Yiannoutsos, C. T.; Diero, L.; Mutevedzi, P.; Fox, M.P.; Messou, E.; Hoffmann, C.J.; Prozesky, H.W.; Egger, M.; Hemingway-Foday, J.J.; Colebunders, R.

2015-01-01

Background In resource limited settings clinical parameters, including body weight changes, are used to monitor clinical response. Therefore we studied body weight changes in patients on antiretroviral treatment (ART) in different regions of the world. Methods Data were extracted from the “International Epidemiologic Databases to Evaluate AIDS”, a network of ART programmes that prospectively collects routine clinical data. Adults on ART from the Southern-, East-, West- and Central African and the Asia-Pacific regions were selected from the database if baseline data on body weight, gender, ART regimen and CD4 count were available. Body weight change over the first two years and the probability of body weight loss in the second year were modelled using linear mixed models and logistic regression respectively. Results Data from 205,571 patients were analysed. Mean adjusted body weight change in the first 12 months was higher in patients started on tenofovir and/or efavirenz; in patients from Central, West and East Africa, in men, and in patients with a poorer clinical status. In the second year of ART it was greater in patients initiated on tenofovir and/or nevirapine, and for patients not on stavudine, in women, in Southern Africa and in patients with a better clinical status at initiation. Stavudine in the initial regimen was associated with a lower mean adjusted body weight change and with weight loss in the second treatment year. Conclusion Different ART regimens have different effects on body weight change. Body weight loss after one year of treatment in patients on stavudine might be associated with lipoatrophy. PMID:26375465

Efficacy of a "small-changes" workplace weight loss initiative on weight and productivity outcomes.

PubMed

Zinn, Caryn; Schofield, Grant M; Hopkins, Will G

2012-10-01

The effect of weight reduction on workplace productivity is unknown. We have investigated a "small-changes" workplace weight loss intervention on weight and productivity outcomes. Overweight/obese employees at two New Zealand worksites (n = 102) received the 12-week intervention. One site received an extra 9-month weight-maintenance component. Magnitudes of effects on weight and productivity were assessed via standardization. Both groups reduced weight at 12 weeks and maintained lost weight at 12 months. There were small possible improvements in productivity at one worksite and trivial reductions at the other by 12 weeks, with little subsequent change during maintenance in either group. At an individual level, weight change was associated with at most only small improvements or small reductions in productivity. Workplace weight loss initiatives may need to be more intensive or multidimensional to enhance productivity.

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.

Weight-based determination of fluid overload status and mortality in pediatric intensive care unit patients requiring continuous renal replacement therapy

PubMed Central

Selewski, David T.; Cornell, Timothy T.; Lombel, Rebecca M.; Blatt, Neal B.; Han, Yong Y.; Mottes, Theresa; Kommareddi, Mallika; Kershaw, David B.; Shanley, Thomas P.; Heung, Michael

2012-01-01

Purpose In pediatric intensive care unit (PICU) patients, fluid overload (FO) at initiation of continuous renal replacement therapy (CRRT) has been reported to be an independent risk factor for mortality. Previous studies have calculated FO based on daily fluid balance during ICU admission, which is labor intensive and error prone. We hypothesized that a weight-based definition of FO at CRRT initiation would correlate with the fluid balance method and prove predictive of outcome. Methods This is a retrospective single-center review of PICU patients requiring CRRT from July 2006 through February 2010 (n = 113). We compared the degree of FO at CRRT initiation using the standard fluid balance method versus methods based on patient weight changes assessed by both univariate and multivariate analyses. Results The degree of fluid overload at CRRT initiation was significantly greater in nonsurvivors, irrespective of which method was used. The univariate odds ratio for PICU mortality per 1% increase in FO was 1.056 [95% confidence interval (CI) 1.025, 1.087] by the fluid balance method, 1.044 (95% CI 1.019, 1.069) by the weight-based method using PICU admission weight, and 1.045 (95% CI 1.022, 1.07) by the weight-based method using hospital admission weight. On multivariate analyses, all three methods approached significance in predicting PICU survival. Conclusions Our findings suggest that weight-based definitions of FO are useful in defining FO at CRRT initiation and are associated with increased mortality in a broad PICU patient population. This study provides evidence for a more practical weight-based definition of FO that can be used at the bedside. PMID:21533569

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.

Disentangling Vector-Borne Transmission Networks: A Universal DNA Barcoding Method to Identify Vertebrate Hosts from Arthropod Bloodmeals

PubMed Central

Alcaide, Miguel; Rico, Ciro; Ruiz, Santiago; Soriguer, Ramón; Muñoz, Joaquín; Figuerola, Jordi

2009-01-01

Emerging infectious diseases represent a challenge for global economies and public health. About one fourth of the last pandemics have been originated by the spread of vector-borne pathogens. In this sense, the advent of modern molecular techniques has enhanced our capabilities to understand vector-host interactions and disease ecology. However, host identification protocols have poorly profited of international DNA barcoding initiatives and/or have focused exclusively on a limited array of vector species. Therefore, ascertaining the potential afforded by DNA barcoding tools in other vector-host systems of human and veterinary importance would represent a major advance in tracking pathogen life cycles and hosts. Here, we show the applicability of a novel and efficient molecular method for the identification of the vertebrate host's DNA contained in the midgut of blood-feeding arthropods. To this end, we designed a eukaryote-universal forward primer and a vertebrate-specific reverse primer to selectively amplify 758 base pairs (bp) of the vertebrate mitochondrial Cytochrome c Oxidase Subunit I (COI) gene. Our method was validated using both extensive sequence surveys from the public domain and Polymerase Chain Reaction (PCR) experiments carried out over specimens from different Classes of vertebrates (Mammalia, Aves, Reptilia and Amphibia) and invertebrate ectoparasites (Arachnida and Insecta). The analysis of mosquito, culicoid, phlebotomie, sucking bugs, and tick bloodmeals revealed up to 40 vertebrate hosts, including 23 avian, 16 mammalian and one reptilian species. Importantly, the inspection and analysis of direct sequencing electropherograms also assisted the resolving of mixed bloodmeals. We therefore provide a universal and high-throughput diagnostic tool for the study of the ecology of haematophagous invertebrates in relation to their vertebrate hosts. Such information is crucial to support the efficient management of initiatives aimed at reducing epidemiologic risks of arthropod vector-borne pathogens, a priority for public health. PMID:19768113

Eco-bio-social research on dengue in Asia: a multicountry study on ecosystem and community-based approaches for the control of dengue vectors in urban and peri-urban Asia

PubMed Central

Sommerfeld, Johannes; Kroeger, Axel

2012-01-01

This article provides an overview of methods and cross-site insights of a 5-year research and capacity building initiative conducted between 2006 and 2011 in six countries of South Asia (India, Sri Lanka) and South-East Asia (Indonesia, Myanmar, Philippines, Thailand).The initiative managed an interdisciplinary investigation of ecological, biological, and social (i.e., eco-bio-social) dimensions of dengue in urban and peri-urban areas, and developed community-based interventions aimed at reducing dengue vector breeding and viral transmission. The multicountry study comprised interdisciplinary research groups from six leading Asian research institutions. The groups conducted a detailed situation analysis to identify and characterize local eco-bio-social conditions, and formed a community-of-practice for EcoHealth research where group partners disseminated results and collaboratively developed site-specific intervention tools for vector-borne diseases. In sites where water containers produced more than 70% of Aedes pupae, interventions ranged from mechanical lid covers for containers to biological control. Where small discarded containers presented the main problem, groups experimented with solid waste management, composting and recycling schemes. Many intervention tools were locally produced and all tools were implemented through community partnership strategies. All sites developed socially and culturally appropriate health education materials. The study also mobilised and empowered women’s, students’ and community groups and at several sites organized new volunteer groups for environmental health. The initiative’s programmes showed significant impact on vector densities in some sites. Other sites showed varying effect — partially attributable to the ‘contamination’ of control groups — yet led to significant outcomes at the community level where local groups united around broad interests in environmental hygiene and sanitation. The programme’s findings are relevant for defining efficient, effective and ecologically sound vector control interventions based on local evidence and in accordance with WHO’s strategy for integrated vector management. PMID:23318234

Randomized Controlled Trial for Behavioral Smoking and Weight Control Treatment: Effect of Concurrent versus Sequential Intervention

PubMed Central

Spring, Bonnie; Doran, Neal; Pagoto, Sherry; Schneider, Kristin; Pingitore, Regina; Hedeker, Don

2014-01-01

Prospects for changing multiple health behaviors conjointly remain controversial. We compared effects on tobacco abstinence and weight gain of adding diet and exercise concurrently or after smoking treatment. Female regular smokers (n=315) randomized to 3 conditions received 16 weeks of behavioral smoking treatment, quit at week 5, and were followed for 9 months after the quit date. Weight management was added to the first 8 weeks for Early Diet (ED), the final 8 weeks for Late Diet (LD), and omitted for Control. Both Diet groups tended to show greater bio-verified abstinence than Control although differences were nonsignificant. Compared to Control, ED initially suppressed weight gain but lost that effect over time, whereas LD initially lacked but gradually acquired a weight suppression effect that stabilized [p = .004]. Behavioral weight control did not undermine smoking cessation and slowed the rate of weight gain when initiated after the smoking quit date, supporting a sequential approach to multiple behavior change. PMID:15482037

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.

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.

Weight changes and their associations with demographic and clinical characteristics in risperidone maintenance treatment for schizophrenia.

PubMed

Xiang, Y-T; Wang, C-Y; Ungvari, G S; Kreyenbuhl, J A; Chiu, H F K; Lai, K Y C; Lee, E H M; Bo, Q-J; Dixon, L B

2011-06-01

This study aimed to characterize weight changes in schizophrenia patients taking risperidone as part of a randomized, controlled, open-label clinical trial. A total of 374 patients with schizophrenia who had been clinically stabilized following an acute episode were randomly assigned to a 'no-dose-reduction' group (initial optimal therapeutic doses continued throughout the study), a '4-week group' (initial optimal therapeutic doses continued for 4 weeks followed by a half dose reduction that was maintained until the end of the study) or a '26-week group' (initial optimal therapeutic doses continued for 26 weeks followed by a half dose reduction until the end of the study). Participants were assessed monthly using standardized assessment instruments during the first 6 months, and then every 2 months until the last recruited patient completed the 1-year follow-up. Weight gain was defined as gaining at least 7% of initial body weight, weight loss as losing at least 7% of initial body weight. A BMI <18.5 kg m⁻² was defined as underweight, 18.5-24.9 kg m⁻² as normal range, and ≥ 25 kg m⁻² as overweight or obese. At the end of follow-up, of the patients who started within the underweight range (n=22), 77.3% gained weight, whereas 4.5% lost weight. The corresponding figures were 39.6% and 4.8% in patients who started at normal weight (n=273), respectively, and 17.7% and 17.7% in patients who started at overweight (n=79), respectively. At the same time, 59.1% of the patients who started at underweight range went into the normal weight and 13.6% into the overweight/obese range, respectively, while 24.5% of those who started at normal weight went into the overweight/obese range, and 1.1% into underweight range, respectively; 20.3% of those who started at overweight range went into normal weight at the end of the follow-up. Multiple logistic regression analyses revealed that being underweight or normal weight at study entry predicted weight gain compared to being overweight, whereas being overweight at entry was associated with a higher likelihood of weight loss compared to being normal weight. No correlation was found between weight change and dose reduction. Weight change is a common, long-term, but heterogeneous side effect in risperidone maintenance treatment for stable schizophrenia patients. Special attention should be paid to fluctuations in weight that may occur throughout the course of treatment with risperidone. © Georg Thieme Verlag KG Stuttgart · New York.

Why don't families initiate treatment? A qualitative multicentre study investigating parents' reasons for declining paediatric weight management.

PubMed

Perez, Arnaldo; Holt, Nicholas; Gokiert, Rebecca; Chanoine, Jean-Pierre; Legault, Laurent; Morrison, Katherine; Sharma, Arya; Ball, Geoff

2015-05-01

Many families referred to specialized health services for managing paediatric obesity do not initiate treatment; however, reasons for noninitiation are poorly understood. To understand parents' reasons for declining tertiary-level health services for paediatric weight management. Interviews were conducted with 18 parents of children (10 to 17 years of age; body mass index ≥85th percentile) who were referred for weight management, but did not initiate treatment at one of three Canadian multidisciplinary weight management clinics. A semi-structured interview guide was used to elicit parents' responses about reasons for noninitiation. Interviews were audio-recorded and transcribed verbatim. Data were managed using NVivo 9 (QSR International, Australia) and analyzed thematically. Most parents (mean age 44.1 years; range 34 to 55 years) were female (n=16 [89%]), obese (n=12 [66%]) and had a university degree (n=13 [71%]). Parents' reasons for not initiating health services were grouped into five themes: no perceived need for paediatric weight management (eg, perceived children did not have a weight or health problem); no perceived need for further actions (eg, perceived children already had a healthy lifestyle); no intention to initiate recommended care (eg, perceived clinical program was not efficacious); participation barriers (eg, children's lack of motivation); and situational factors (eg, weather). Physicians should not only discuss the need for and value of specialized care for managing paediatric obesity, but also explore parents' intention to initiate treatment and address reasons for noninitiation that are within their control.

A Comparison of Nonlinear Filters for Orbit Determination and Estimation

DTIC Science & Technology

1986-06-01

Com- mand uses a nonlinear least squares filter for element set maintenance for all objects orbiting the Earth (3). These objects, including active...initial state vector is the singularly averaged classical orbital element set provided by SPACECOM/DOA. The state vector in this research consists of...GSF (G) - - 26.0 36.7 GSF(A) 32.1 77.4 38.8 59.6 The Air Force Space Command is responsible for main- taining current orbital element sets for about

Brain Biology Machine Initiative: Developing Innovative Novel Methods to Improve Neuro-Rehabilitation for Amputees and Treatment for Patients at Remote Sites with Acute Brain Injury

DTIC Science & Technology

2010-10-01

bode well for the future. The paper we submitted to the Journal of Neuroscience detailing the TVAG rabies tracer system was accepted with revisions...of brain electrical activity. Stas Kounitsky successfully completed the port of the new vector-additive implicit (VAI) method for the anisotropic ...Alternating Difference 14 Implicit (ADI) for isotropic head models, and the Vector Additive Implicit (VAI) for anisotropic head models. The ADI method

Nonlinear Adjustment with or without Constraints, Applicable to Geodetic Models

DTIC Science & Technology

1989-03-01

corrections are neglected, resulting in the familiar (linearized) observation equations. In matrix notation, the latter are expressed by V = A X + I...where A is the design matrix, x=X -x is the column-vector of parametric corrections , VzLa-L b is the column-vector of residuals, and L=L -Lb is the...X0 . corresponds to the set ua of model-surface 0 coordinates describing the initial point P. The final set of parametric corrections , X, then

Optimal impulsive manoeuvres and aerodynamic braking

NASA Technical Reports Server (NTRS)

Jezewski, D. J.

1985-01-01

A method developed for obtaining solutions to the aerodynamic braking problem, using impulses in the exoatmospheric phases is discussed. The solution combines primer vector theory and the results of a suboptimal atmospheric guidance program. For a specified initial and final orbit, the solution determines: (1) the minimum impulsive cost using a maximum of four impulses, (2) the optimal atmospheric entry and exit-state vectors subject to equality and inequality constraints, and (3) the optimal coast times. Numerical solutions which illustrate the characteristics of the solution are presented.

An Evaluation of an Algorithm for Linear Inequalities and Its Applications

NASA Technical Reports Server (NTRS)

Jurgensen, J.

1973-01-01

An algorithm is presented for obtaining a solution alpha to a set of inequalities (A alpha) 0 where A is an N x m-matrix and alpha is an m-vector. If the set of inequalities is consistant, then the algorithm is guaranteed to arrive at a solution in a finite number of steps. Also, if in the iteration, a negative vector is obtained, then the initial set of inequalities is inconsistant, and the iteration is terminated.

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

NASA Technical Reports Server (NTRS)

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

1978-01-01

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

Gene therapy for cardiovascular disease: advances in vector development, targeting, and delivery for clinical translation.

PubMed

Rincon, Melvin Y; VandenDriessche, Thierry; Chuah, Marinee K

2015-10-01

Gene therapy is a promising modality for the treatment of inherited and acquired cardiovascular diseases. The identification of the molecular pathways involved in the pathophysiology of heart failure and other associated cardiac diseases led to encouraging preclinical gene therapy studies in small and large animal models. However, the initial clinical results yielded only modest or no improvement in clinical endpoints. The presence of neutralizing antibodies and cellular immune responses directed against the viral vector and/or the gene-modified cells, the insufficient gene expression levels, and the limited gene transduction efficiencies accounted for the overall limited clinical improvements. Nevertheless, further improvements of the gene delivery technology and a better understanding of the underlying biology fostered renewed interest in gene therapy for heart failure. In particular, improved vectors based on emerging cardiotropic serotypes of the adeno-associated viral vector (AAV) are particularly well suited to coax expression of therapeutic genes in the heart. This led to new clinical trials based on the delivery of the sarcoplasmic reticulum Ca(2+)-ATPase protein (SERCA2a). Though the first clinical results were encouraging, a recent Phase IIb trial did not confirm the beneficial clinical outcomes that were initially reported. New approaches based on S100A1 and adenylate cyclase 6 are also being considered for clinical applications. Emerging paradigms based on the use of miRNA regulation or CRISPR/Cas9-based genome engineering open new therapeutic perspectives for treating cardiovascular diseases by gene therapy. Nevertheless, the continuous improvement of cardiac gene delivery is needed to allow the use of safer and more effective vector doses, ultimately bringing gene therapy for heart failure one step closer to reality. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Cardiology.

The relationship between three-dimensional knee MRI bone shape and total knee replacement—a case control study: data from the Osteoarthritis Initiative

PubMed Central

Barr, Andrew J.; Dube, Bright; Hensor, Elizabeth M. A.; Kingsbury, Sarah R.; Peat, George; Bowes, Mike A.; Sharples, Linda D.

2016-01-01

Objective. There is growing understanding of the importance of bone in OA. Our aim was to determine the relationship between 3D MRI bone shape and total knee replacement (TKR). Methods. A nested case-control study within the Osteoarthritis Initiative cohort identified case knees with confirmed TKR for OA and controls that were matched using propensity scores. Active appearance modelling quantification of the bone shape of all knee bones identified vectors between knees having or not having OA. Vectors were scaled such that −1 and +1 represented the mean non-OA and mean OA shapes. Results. Compared to controls (n = 310), TKR cases (n = 310) had a more positive mean baseline 3D bone shape vector, indicating more advanced structural OA, for the femur [mean 0.98 vs −0.11; difference (95% CI) 1.10 (0.88, 1.31)], tibia [mean 0.86 vs −0.07; difference (95% CI) 0.94 (0.72, 1.16)] and patella [mean 0.95 vs 0.03; difference (95% CI) 0.92 (0.65, 1.20)]. Odds ratios (95% CI) for TKR per normalized unit of 3D bone shape vector for the femur, tibia and patella were: 1.85 (1.59, 2.16), 1.64 (1.42, 1.89) and 1.36 (1.22, 1.50), respectively, all P < 0.001. After including Kellgren–Lawrence grade in a multivariable analysis, only the femur 3D shape vector remained significantly associated with TKR [odds ratio 1.24 (1.02, 1.51)]. Conclusion. 3D bone shape was associated with the endpoint of this study, TKR, with femoral shape being most associated. This study contributes to the validation of quantitative MRI bone biomarkers for OA structure-modification trials. PMID:27185958

A Hierarchical Network Approach for Modeling Rift Valley Fever Epidemics with Applications in North America

PubMed Central

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

2013-01-01

Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread. PMID:23667453

A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America.

PubMed

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

2013-01-01

Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread.

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

PubMed

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

2009-03-02

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

Adenovirus-Mediated Gene Delivery: Potential Applications for Gene and Cell-Based Therapies in the New Era of Personalized Medicine

PubMed Central

Lee, Cody S.; Bishop, Elliot S.; Zhang, Ruyi; Yu, Xinyi; Farina, Evan M.; Yan, Shujuan; Zhao, Chen; Zheng, Zongyue; Shu, Yi; Wu, Xingye; Lei, Jiayan; Li, Yasha; Zhang, Wenwen; Yang, Chao; Wu, Ke; Wu, Ying; Ho, Sherwin; Athiviraham, Aravind; Lee, Michael J.; Wolf, Jennifer Moriatis; Reid, Russell R.; He, Tong-Chuan

2017-01-01

With rapid advances in understanding molecular pathogenesis of human diseases in the era of genome sciences and systems biology, it is anticipated that increasing numbers of therapeutic genes or targets will become available for targeted therapies. Despite numerous setbacks, efficacious gene and/or cell-based therapies still hold the great promise to revolutionize the clinical management of human diseases. It is wildly recognized that poor gene delivery is the limiting factor for most in vivo gene therapies. There has been a long-lasting interest in using viral vectors, especially adenoviral vectors, to deliver therapeutic genes for the past two decades. Among all currently available viral vectors, adenovirus is the most efficient gene delivery system in a broad range of cell and tissue types. The applications of adenoviral vectors in gene delivery have greatly increased in number and efficiency since their initial development. In fact, among over 2,000 gene therapy clinical trials approved worldwide since 1989, a significant portion of the trials have utilized adenoviral vectors. This review aims to provide a comprehensive overview on the characteristics of adenoviral vectors, including adenoviral biology, approaches to engineering adenoviral vectors, and their applications in clinical and pre-clinical studies with an emphasis in the areas of cancer treatment, vaccination and regenerative medicine. Current challenges and future directions regarding the use of adenoviral vectors are also discussed. It is expected that the continued improvements in adenoviral vectors should provide great opportunities for cell and gene therapies to live up to its enormous potential in personalized medicine. PMID:28944281

Antibody-mediated targeting of replication-competent retroviral vectors.

PubMed

Tai, Chien-Kuo; Logg, Christopher R; Park, Jinha M; Anderson, W French; Press, Michael F; Kasahara, Noriyuki

2003-05-20

Replication-competent murine leukemia virus (MLV) vectors can be engineered to achieve high efficiency gene transfer to solid tumors in vivo and tumor-restricted replication, however their safety can be further enhanced by redirecting tropism of the virus envelope. We have therefore tested the targeting capability and replicative stability of ecotropic and amphotropic replication-competent retrovirus (RCR) vectors containing two tandem repeats from the immunoglobulin G-binding domain of Staphylococcal protein A inserted into the proline-rich "hinge" region of the envelope, which enables modular use of antibodies of various specificities for vector targeting. The modified envelopes were efficiently expressed and incorporated into virions, were capable of capturing monoclonal anti-HER2 antibodies, and mediated efficient binding of the virus-antibody complex to HER2-positive target cells. While infectivity was markedly reduced by pseudotyping with targeted envelopes alone, coexpression of wild-type envelope rescued efficient cellular entry. Both ecotropic and amphotropic RCR vector/anti-HER2 antibody complexes achieved significant enhancement of transduction on murine target cells overexpressing HER2, which could be competed by preincubation with excess free antibodies. Interestingly, HER2-expressing human breast cancer cells did not show enhancement of transduction despite efficient antibody-mediated cell surface binding, suggesting that target cell-specific parameters markedly affect the efficiency of post-binding entry processes. Serial replication of targeted vectors resulted in selection of Z domain deletion variants, but reduction of the overall size of the vector genome enhanced its stability. Application of antibody-mediated targeting to the initial localization of replication-competent virus vectors to tumor sites will thus require optimized target selection and vector design.

Development of an adenoviral vector with robust expression driven by p53

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

Bajgelman, Marcio C.; Biotechnology Program, Biomedical Sciences Institute, University of Sao Paulo; Millennium Institute-Gene Therapy Network, Ministry of Science and Technology

2008-02-05

Here we introduce a new adenoviral vector where transgene expression is driven by p53. We first developed a synthetic promoter, referred to as PGTx{beta}, containing a p53-responsive element, a minimal promoter and the first intron of the rabbit {beta}-globin gene. Initial assays using plasmid-based vectors indicated that expression was tightly controlled by p53 and was 5-fold stronger than the constitutive CMV immediate early promoter/enhancer. The adenoviral vector, AdPG, was also shown to offer p53-responsive expression in prostate carcinoma cells LNCaP (wt p53), DU-145 (temperature sensitive mutant of p53) and PC3 (p53-null, but engineered to express temperature-sensitive p53 mutants). AdPG servedmore » as a sensor of p53 activity in LNCaP cells treated with chemotherapeutic agents. Since p53 can be induced by radiotherapy and chemotherapy, this new vector could be further developed for use in combination with conventional therapies to bring about cooperation between the genetic and pharmacologic treatment modalities.« less

Structured caustic vector vortex optical field: manipulating optical angular momentum flux and polarization rotation.

PubMed

Chen, Rui-Pin; Chen, Zhaozhong; Chew, Khian-Hooi; Li, Pei-Gang; Yu, Zhongliang; Ding, Jianping; He, Sailing

2015-05-29

A caustic vector vortex optical field is experimentally generated and demonstrated by a caustic-based approach. The desired caustic with arbitrary acceleration trajectories, as well as the structured states of polarization (SoP) and vortex orders located in different positions in the field cross-section, is generated by imposing the corresponding spatial phase function in a vector vortex optical field. Our study reveals that different spin and orbital angular momentum flux distributions (including opposite directions) in different positions in the cross-section of a caustic vector vortex optical field can be dynamically managed during propagation by intentionally choosing the initial polarization and vortex topological charges, as a result of the modulation of the caustic phase. We find that the SoP in the field cross-section rotates during propagation due to the existence of the vortex. The unique structured feature of the caustic vector vortex optical field opens the possibility of multi-manipulation of optical angular momentum fluxes and SoP, leading to more complex manipulation of the optical field scenarios. Thus this approach further expands the functionality of an optical system.

Current Status of Gene Therapy for Inherited Lung Diseases

PubMed Central

Driskell, Ryan R.; Engelhardt, John F.

2007-01-01

Gene therapy as a treatment modality for pulmonary disorders has attracted significant interest over the past decade. Since the initiation of the first clinical trials for cystic fibrosis lung disease using recombinant adenovirus in the early 1990s, the field has encountered numerous obstacles including vector inflammation, inefficient delivery, and vector production. Despite these obstacles, enthusiasm for lung gene therapy remains high. In part, this enthusiasm is fueled through the diligence of numerous researchers whose studies continue to reveal great potential of new gene transfer vectors that demonstrate increased tropism for airway epithelia. Several newly identified serotypes of adeno-associated virus have demonstrated substantial promise in animal models and will likely surface soon in clinical trials. Furthermore, an increased understanding of vector biology has also led to the development of new technologies to enhance the efficiency and selectivity of gene delivery to the lung. Although the promise of gene therapy to the lung has yet to be realized, the recent concentrated efforts in the field that focus on the basic virology of vector development will undoubtedly reap great rewards over the next decade in treating lung diseases. PMID:12524461

Horror Image Recognition Based on Context-Aware Multi-Instance Learning.

PubMed

Li, Bing; Xiong, Weihua; Wu, Ou; Hu, Weiming; Maybank, Stephen; Yan, Shuicheng

2015-12-01

Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme emotions. In this paper, we present a novel context-aware multi-instance learning (CMIL) algorithm for horror image recognition. The CMIL algorithm identifies horror images and picks out the regions that cause the sensation of horror in these horror images. It obtains contextual cues among adjacent regions in an image using a random walk on a contextual graph. Borrowing the strength of the fuzzy support vector machine (FSVM), we define a heuristic optimization procedure based on the FSVM to search for the optimal classifier for the CMIL. To improve the initialization of the CMIL, we propose a novel visual saliency model based on the tensor analysis. The average saliency value of each segmented region is set as its initial fuzzy membership in the CMIL. The advantage of the tensor-based visual saliency model is that it not only adaptively selects features, but also dynamically determines fusion weights for saliency value combination from different feature subspaces. The effectiveness of the proposed CMIL model is demonstrated by its use in horror image recognition on two large-scale image sets collected from the Internet.

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.

The Influence of the Orbital Evolution of Main Belt Asteroids on Their Spin Vectors

NASA Astrophysics Data System (ADS)

Skoglöv, E.; Erikson, A.

2002-11-01

It was found that certain features in the observed spin vector distribution of main belt asteroids can be explained by the differences in the dynamical spin vector evolution between objects with high and low orbital inclinations. In particular, the deficiency of high-inclination objects whose spin vectors are close to the ecliptic plane can be accounted for. The present spin vector distribution of main belt asteroids is due to several factors connected with their collisional and dynamical evolution. In this paper, the influence of the orbital evolution on the spin axis of asteroids is examined in the case of 25 objects with typical main belt orbital evolution and 125 synthetic objects, during an integration over a time period of 1 Myr. This investigation produced the following general results: • The difference between maximum and minimum obliquity increases in an approximately linear fashion with increasing orbital inclination of the studied objects. • The inclination is the major factor influencing the magnitude of the obliquity variation. This variation is generally larger for asteroids with their initial spin vectors located close to the orbital plane. • In general, the regular obliquity differences are relatively insensitive to differences in the shape, composition, and spin rate of the asteroids. The result is compared with the properties of the observed spin vectors for 73 main belt asteroids and good agreement is found between the above results and the existing spin vector distribution.

Two novel motion-based algorithms for surveillance video analysis on embedded platforms

NASA Astrophysics Data System (ADS)

Vijverberg, Julien A.; Loomans, Marijn J. H.; Koeleman, Cornelis J.; de With, Peter H. N.

2010-05-01

This paper proposes two novel motion-vector based techniques for target detection and target tracking in surveillance videos. The algorithms are designed to operate on a resource-constrained device, such as a surveillance camera, and to reuse the motion vectors generated by the video encoder. The first novel algorithm for target detection uses motion vectors to construct a consistent motion mask, which is combined with a simple background segmentation technique to obtain a segmentation mask. The second proposed algorithm aims at multi-target tracking and uses motion vectors to assign blocks to targets employing five features. The weights of these features are adapted based on the interaction between targets. These algorithms are combined in one complete analysis application. The performance of this application for target detection has been evaluated for the i-LIDS sterile zone dataset and achieves an F1-score of 0.40-0.69. The performance of the analysis algorithm for multi-target tracking has been evaluated using the CAVIAR dataset and achieves an MOTP of around 9.7 and MOTA of 0.17-0.25. On a selection of targets in videos from other datasets, the achieved MOTP and MOTA are 8.8-10.5 and 0.32-0.49 respectively. The execution time on a PC-based platform is 36 ms. This includes the 20 ms for generating motion vectors, which are also required by the video encoder.

Generalized wave operators, weighted Killing fields, and perturbations of higher dimensional spacetimes

NASA Astrophysics Data System (ADS)

Araneda, Bernardo

2018-04-01

We present weighted covariant derivatives and wave operators for perturbations of certain algebraically special Einstein spacetimes in arbitrary dimensions, under which the Teukolsky and related equations become weighted wave equations. We show that the higher dimensional generalization of the principal null directions are weighted conformal Killing vectors with respect to the modified covariant derivative. We also introduce a modified Laplace–de Rham-like operator acting on tensor-valued differential forms, and show that the wave-like equations are, at the linear level, appropriate projections off shell of this operator acting on the curvature tensor; the projection tensors being made out of weighted conformal Killing–Yano tensors. We give off shell operator identities that map the Einstein and Maxwell equations into weighted scalar equations, and using adjoint operators we construct solutions of the original field equations in a compact form from solutions of the wave-like equations. We study the extreme and zero boost weight cases; extreme boost corresponding to perturbations of Kundt spacetimes (which includes near horizon geometries of extreme black holes), and zero boost to static black holes in arbitrary dimensions. In 4D our results apply to Einstein spacetimes of Petrov type D and make use of weighted Killing spinors.

Effect of temperature of extrinsic incubation on the vector competence of Culex tarsalis for western equine encephalomyelitis virus.

PubMed

Kramer, L D; Hardy, J L; Presser, S B

1983-09-01

Culex tarsalis was a less competent vector of western equine encephalomyelitis (WEE) virus after 2-3 weeks' extrinsic incubation at 32 degrees C than after incubation at 18 degrees or 25 degrees C. The high temperature itself was not directly detrimental to mosquito infection as all mosquitoes were initially infected, but subsequently some females were able to limit viral multiplication and/or dissemination. Elevated maintenance temperatures enhanced the expression of modulation, and elevated larval rearing temperatures selected for those females with this trait. This is the first report of an inverse relationship between temperature of extrinsic incubation within the range of 25 degrees-32 degrees C and vector competence of a mosquito for an arbovirus.

Spectral analysis of difference and differential operators in weighted spaces

NASA Astrophysics Data System (ADS)

Bichegkuev, M. S.

2013-11-01

This paper is concerned with describing the spectrum of the difference operator \\displaystyle \\mathscr{K}\\colon l_\\alpha^p( Z,X)\\to l_\\alpha^p( Z......athscr{K}x)(n)=Bx(n-1), \\ \\ n\\in{Z}, \\ \\ x\\in l_\\alpha^p( Z,X), with a constant operator coefficient B, which is a bounded linear operator in a Banach space X. It is assumed that \\mathscr{K} acts in the weighted space l_\\alpha^p( Z,X), 1\\leq p\\leq \\infty, of two-sided sequences of vectors from X. The main results are obtained in terms of the spectrum \\sigma(B) of the operator coefficient B and properties of the weight function. Applications to the study of the spectrum of a differential operator with an unbounded operator coefficient (the generator of a strongly continuous semigroup of operators) in weighted function spaces are given. Bibliography: 23 titles.

The proper weighting function for retrieving temperatures from satellite measured radiances

NASA Technical Reports Server (NTRS)

Arking, A.

1976-01-01

One class of methods for converting satellite measured radiances into atmospheric temperature profiles, involves a linearization of the radiative transfer equation: delta r = the sum of (W sub i) (delta T sub i) where (i=1...s) and where delta T sub i is the deviation of the temperature in layer i from that of a reference atmosphere, delta R is the difference in the radiance at satellite altitude from the corresponding radiance for the reference atmosphere, and W sub i is the discrete (or vector) form of the T-weighting (i.e., temperature weighting) function W(P), where P is pressure. The top layer of the atmosphere corresponds to i = 1, the bottom layer to i = s - 1, and i = s refers to the surface. Linearization in temperature (or some function of temperature) is at the heart of all linear or matrix methods. The weighting function that should be used is developed.

Comparison of the inertial properties and forces required to initiate movement for three gait trainers.

PubMed

Paleg, Ginny; Huang, Morris; Vasquez Gabela, Stephanie C; Sprigle, Stephen; Livingstone, Roslyn

2016-01-01

The purpose of this study was to evaluate the inertial properties and forces required to initiate movement on two different surfaces in a sample of three commonly prescribed gait trainers. Tests were conducted in a laboratory setting to compare the Prime Engineering KidWalk, Rifton Pacer, and Snug Seat Mustang with and without a weighted anthropometric test dummy configured to the weight and proportions of a 4-year-old child. The Pacer was the lightest and the KidWalk the heaviest while footprints of the three gait trainers were similar. Weight was borne fairly evenly on the four casters of the Pacer and Mustang while 85% of the weight was borne on the large wheels of the mid-wheel drive KidWalk. These differences in frame style, wheel, and caster style and overall mass impact inertial properties and forces required to initiate movement. Test results suggest that initiation forces on tile were equivalent for the Pacer and KidWalk while the Mustang had the highest initiation force. Initiation forces on carpet were lowest for the KidWalk and highest for the Mustang. This initial study of inertia and movement initiation forces may provide added information for clinicians to consider when selecting a gait trainer for their clients.

Neural-network-based online HJB solution for optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems.

PubMed

Liu, Derong; Wang, Ding; Wang, Fei-Yue; Li, Hongliang; Yang, Xiong

2014-12-01

In this paper, the infinite horizon optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems is investigated using neural-network-based online solution of Hamilton-Jacobi-Bellman (HJB) equation. By establishing an appropriate bounded function and defining a modified cost function, the optimal robust guaranteed cost control problem is transformed into an optimal control problem. It can be observed that the optimal cost function of the nominal system is nothing but the optimal guaranteed cost of the original uncertain system. A critic neural network is constructed to facilitate the solution of the modified HJB equation corresponding to the nominal system. More importantly, an additional stabilizing term is introduced for helping to verify the stability, which reinforces the updating process of the weight vector and reduces the requirement of an initial stabilizing control. The uniform ultimate boundedness of the closed-loop system is analyzed by using the Lyapunov approach as well. Two simulation examples are provided to verify the effectiveness of the present control approach.

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

Hantaan virus surveillance targeting small mammals at Dagmar North Training Area, Gyeonggi Province, Republic of Korea, 2001-2005.

PubMed

Klein, Terry A; Kang, Hae Ji; Gu, Se Hun; Moon, Sungsil; Shim, So-Hee; Park, Yon Mi; Lee, Sook-Young; Kim, Heung-Chul; Chong, Sung-Tae; O'Guinn, Monica; Lee, John S; Turell, Michael J; Song, Jin-Won

2011-12-01

In response to a hemorrhagic fever with renal syndrome case in November 2000, a seasonal rodent-borne disease surveillance program was initiated at Dagmar North Training Area (DNTA), Gyeonggi Province, Republic of Korea. From April 2001-December 2005, 1,848 small mammals were captured. Apodemus agrarius accounted for 92.5%, followed by Mus musculus (3.6%), Crocidura lasiura (2.1%), and Microtus fortis (1.1%). Three species of rodents were found to be antibody-positive (Ab+) for Hantaan virus (HTNV): A. agrarius (22.3%), M. musculus (9.1%), and M. fortis (5.0%). Ab+ rates for A. agrarius increased with increasing weight (age), except for those weighing <10 g. The peak HTNV transmission period in Korea coincided with the peak reproductive potential of A. agrarius during the fall (August/September) surveys. HTNV strains from DNTA were distinct from HTNV strains from the People's Republic of China. From these studies, more accurate risk assessments can be developed to better protect personnel from rodent-borne diseases. © 2011 The Society for Vector Ecology.

Development of a two-dimensional dual pendulum thrust stand for Hall thrusters.

PubMed

Nagao, N; Yokota, S; Komurasaki, K; Arakawa, Y

2007-11-01

A two-dimensional dual pendulum thrust stand was developed to measure thrust vectors [axial and horizontal (transverse) direction thrusts] of a Hall thruster. A thruster with a steering mechanism is mounted on the inner pendulum, and thrust is measured from the displacement between inner and outer pendulums, by which a thermal drift effect is canceled out. Two crossover knife-edges support each pendulum arm: one is set on the other at a right angle. They enable the pendulums to swing in two directions. Thrust calibration using a pulley and weight system showed that the measurement errors were less than 0.25 mN (1.4%) in the main thrust direction and 0.09 mN (1.4%) in its transverse direction. The thrust angle of the thrust vector was measured with the stand using the thruster. Consequently, a vector deviation from the main thrust direction of +/-2.3 degrees was measured with the error of +/-0.2 degrees under the typical operating conditions for the thruster.

Automatic sleep staging using multi-dimensional feature extraction and multi-kernel fuzzy support vector machine.

PubMed

Zhang, Yanjun; Zhang, Xiangmin; Liu, Wenhui; Luo, Yuxi; Yu, Enjia; Zou, Keju; Liu, Xiaoliang

2014-01-01

This paper employed the clinical Polysomnographic (PSG) data, mainly including all-night Electroencephalogram (EEG), Electrooculogram (EOG) and Electromyogram (EMG) signals of subjects, and adopted the American Academy of Sleep Medicine (AASM) clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM) were learned and the multi-kernel FSVM (MK-FSVM) was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

Noninvasive assessment of extracellular and intracellular dehydration in healthy humans using the resistance-reactance-score graph method.

PubMed

Heavens, Kristen R; Charkoudian, Nisha; O'Brien, Catherine; Kenefick, Robert W; Cheuvront, Samuel N

2016-03-01

Few dehydration assessment measures provide accurate information; most are based on reference change values and very few are diagnostically accurate from a single observation or measure. Bioelectrical impedance may lack the precision to detect common forms of dehydration in healthy individuals. Limitations in bioimpedance may be addressed by a unique resistance-reactance (RXc)-score graph method, which transforms vector components into z scores for use with any impedance analyzer in any population. We tested whether the RXc-score graph method provides accurate single or serial assessments of dehydration when compared with gold-standard measures of total body water by using stable isotope dilution (deuterium oxide) combined with body-weight changes. We retrospectively analyzed data from a previous study in which 9 healthy young men participated in 3 trials: euhydration (EUH), extracellular dehydration (ED; via a diuretic), and intracellular dehydration (ID; via exercise in the heat). Participants lost 4-5% of their body weight during the dehydration trials; volume loss was similar between trials (ID compared with ED group: 3.5 ± 0.8 compared with 3.0 ± 0.6 L; P > 0.05). Despite significant losses of body water, most RXc vector scores for ED and ID groups were classified as "normal" (within the 75% population tolerance ellipse). However, directional displacement of vectors was consistent with loss of volume in both ED and ID conditions compared with the EUH condition and tended to be longer in ED than in ID conditions (P = 0.054). We conclude that, whereas individual RXc-score graph values do not provide accurate detection of dehydration from single measurements, directional changes in vector values from serial measurements are consistent with fluid loss for both ED and ID conditions. The RXc-score graph method may therefore alert clinicians to changes in hydration state, which may bolster the interpretation of other recognized change measures of hydration. © 2016 American Society for Nutrition.

Characterization of a midgut mucin-like glycoconjugate of Lutzomyia longipalpis with a potential role in Leishmania attachment.

PubMed

Myšková, Jitka; Dostálová, Anna; Pěničková, Lucie; Halada, Petr; Bates, Paul A; Volf, Petr

2016-07-25

Leishmania parasites are transmitted by phlebotomine sand flies and a crucial step in their life-cycle is the binding to the sand fly midgut. Laboratory studies on sand fly competence to Leishmania parasites suggest that the sand flies fall into two groups: several species are termed "specific/restricted" vectors that support the development of one Leishmania species only, while the others belong to so-called "permissive" vectors susceptible to a wide range of Leishmania species. In a previous study we revealed a correlation between specificity vs permissivity of the vector and glycosylation of its midgut proteins. Lutzomyia longipalpis and other four permissive species tested possessed O-linked glycoproteins whereas none were detected in three specific vectors examined. We used a combination of biochemical, molecular and parasitological approaches to characterize biochemical and biological properties of O-linked glycoprotein of Lu. longipalpis. Lectin blotting and mass spectrometry revealed that this molecule with an apparent molecular weight about 45-50 kDa corresponds to a putative 19 kDa protein with unknown function detected in a midgut cDNA library of Lu. longipalpis. We produced a recombinant glycoprotein rLuloG with molecular weight around 45 kDa. Anti-rLuloG antibodies localize the native glycoprotein on epithelial midgut surface of Lu. longipalpis. Although we could not prove involvement of LuloG in Leishmania attachment by blocking the native protein with anti-rLuloG during sand fly infections, we demonstrated strong binding of rLuloG to whole surface of Leishmania promastigotes. We characterized a novel O-glycoprotein from sand fly Lutzomyia longipalpis. It has mucin-like properties and is localized on the luminal side of the midgut epithelium. Recombinant form of the protein binds to Leishmania parasites in vitro. We propose a role of this molecule in Leishmania attachment to sand fly midgut.

SU-E-T-422: Fast Analytical Beamlet Optimization for Volumetric Intensity-Modulated Arc Therapy

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

Chan, Kenny S K; Lee, Louis K Y; Xing, L

2015-06-15

Purpose: To implement a fast optimization algorithm on CPU/GPU heterogeneous computing platform and to obtain an optimal fluence for a given target dose distribution from the pre-calculated beamlets in an analytical approach. Methods: The 2D target dose distribution was modeled as an n-dimensional vector and estimated by a linear combination of independent basis vectors. The basis set was composed of the pre-calculated beamlet dose distributions at every 6 degrees of gantry angle and the cost function was set as the magnitude square of the vector difference between the target and the estimated dose distribution. The optimal weighting of the basis,more » which corresponds to the optimal fluence, was obtained analytically by the least square method. Those basis vectors with a positive weighting were selected for entering into the next level of optimization. Totally, 7 levels of optimization were implemented in the study.Ten head-and-neck and ten prostate carcinoma cases were selected for the study and mapped to a round water phantom with a diameter of 20cm. The Matlab computation was performed in a heterogeneous programming environment with Intel i7 CPU and NVIDIA Geforce 840M GPU. Results: In all selected cases, the estimated dose distribution was in a good agreement with the given target dose distribution and their correlation coefficients were found to be in the range of 0.9992 to 0.9997. Their root-mean-square error was monotonically decreasing and converging after 7 cycles of optimization. The computation took only about 10 seconds and the optimal fluence maps at each gantry angle throughout an arc were quickly obtained. Conclusion: An analytical approach is derived for finding the optimal fluence for a given target dose distribution and a fast optimization algorithm implemented on the CPU/GPU heterogeneous computing environment greatly reduces the optimization time.« less

High-level rapid production of full-size monoclonal antibodies in plants by a single-vector DNA replicon system

PubMed Central

Huang, Zhong; Phoolcharoen, Waranyoo; Lai, Huafang; Piensook, Khanrat; Cardineau, Guy; Zeitlin, Larry; Whaley, Kevin J.; Arntzen, Charles J.

2010-01-01

Plant viral vectors have great potential in rapid production of important pharmaceutical proteins. However, high-yield production of heterooligomeric proteins that require the expression and assembly of two or more protein subunits often suffers problems due to the “competing” nature of viral vectors derived from the same virus. Previously we reported that a bean yellow dwarf virus (BeYDV)-derived, three-component DNA replicon system allows rapid production of single recombinant proteins in plants (Huang et al. 2009). In this article, we report further development of this expression system for its application in high-yield production of oligomeric protein complexes including monoclonal antibodies (mAbs) in plants. We showed that the BeYDV replicon system permits simultaneous efficient replication of two DNA replicons and thus, high-level accumulation of two recombinant proteins in the same plant cell. We also demonstrated that a single vector that contains multiple replicon cassettes was as efficient as the three-component system in driving the expression of two distinct proteins. Using either the non-competing, three-vector system or the multi-replicon single vector, we produced both the heavy and light chain subunits of a protective IgG mAb 6D8 against Ebola virus GP1 (Wilson et al. 2000) at 0.5 mg of mAb per gram leaf fresh weight within 4 days post infiltration of Nicotiana benthamiana leaves. We further demonstrated that full-size tetrameric IgG complex containing two heavy and two light chains was efficiently assembled and readily purified, and retained its functionality in specific binding to inactivated Ebola virus. Thus, our single-vector replicon system provides high-yield production capacity for heterooligomeric proteins, yet eliminates the difficult task of identifying non-competing virus and the need for co-infection of multiple expression modules. The multi-replicon vector represents a significant advance in transient expression technology for antibody production in plants. PMID:20047189

Altered control strategy between leading and trailing leg increases knee adduction moment in the elderly while descending stairs.

PubMed

Karamanidis, Kiros; Arampatzis, Adamantios

2011-02-24

The aim of the study was to examine the external knee adduction moments in a group of older and younger adults while descending stairs and thus the possibility of an increased risk of knee osteoarthritis due to altered knee joint loading in the elderly. Twenty-seven older and 16 younger adults descended a purpose-built staircase. A motion capture system and a force plate were used to determine the subjects' 3D kinematics and ground reaction forces (GRF) during locomotion. Calculation of the leg kinematics and kinetics was done by means of a rigid, three-segment, 3D leg model. In the initial portion of the support phase, older adults showed a more medio-posterior GRF vector relative to the ankle joint, leading to lower ankle joint moments (P<0.05). At the knee, the older adults demonstrated a more medio-posterior directed GRF vector, increasing in knee flexion and adduction in the second part of the single support phase (P<0.05). Further, GRF magnitude was lower in the initial and higher in the mid-portions of the support phase for the elderly (P<0.05). The results show that older adults descend stairs by using the trailing leg before the initiation of the double support phase more compared to the younger ones. The consequence of this altered control strategy while stepping down is a more medially directed GRF vector increasing the magnitude of external knee adduction moment in the elderly. The observed changes between leading and trailing leg in the elderly may cause a redistribution of the mechanical load at the tibiofemoral joint, affecting the initiation and progression of knee osteoarthritis in the elderly. Copyright © 2010 Elsevier Ltd. All rights reserved.

Study design and protocol for a theory-based behavioral intervention focusing on maintenance of weight loss: the Maintenance After Initiation of Nutrition TrAINing (MAINTAIN) study.

PubMed

Voils, Corrine I; Gierisch, Jennifer M; Olsen, Maren K; Maciejewski, Matthew L; Grubber, Janet; McVay, Megan A; Strauss, Jennifer L; Bolton, Jamiyla; Gaillard, Leslie; Strawbridge, Elizabeth; Yancy, William S

2014-09-01

Obesity is a significant public health problem. Although various lifestyle approaches are effective for inducing significant weight loss, few effective behavioral weight maintenance strategies have been identified. It has been proposed that behavior maintenance is a distinct state that involves different psychological processes and behavioral skills than initial behavior change. Previously, we created a conceptual model that distinguishes behavior initiation from maintenance. This model was used to generate Maintenance After Initiation of Nutrition TrAINing (MAINTAIN), an intervention to enhance weight loss maintenance following initiation. The effectiveness of MAINTAIN is being evaluated in an ongoing trial, the rationale and procedures of which are reported herein. Veterans aged ≤ 75 with body mass index ≥ 30 kg/m(2) participate in a 16-week, group-based weight loss program. Participants who lose ≥ 4 kg by the end of 16 weeks (target n = 230) are randomized 1:1 to receive (a) usual care for 56 weeks or (b) MAINTAIN, a theoretically-informed weight loss maintenance intervention for 40 weeks, followed by 16 weeks of no intervention contact. MAINTAIN involves 3 in-person group visits that transition to 8 individualized telephone calls with decreasing contact frequency. MAINTAIN focuses on satisfaction with outcomes, weight self-monitoring, relapse prevention, and social support. We hypothesize that, compared to usual care, MAINTAIN will result in at least 3.5 kg less regain and better relative levels of caloric intake and physical activity over 56 weeks, and that it will be cost-effective. If effective, MAINTAIN could serve as a model for redesigning existing weight loss programs. NCT01357551. Published by Elsevier Inc.

Footwear and Foam Surface Alter Gait Initiation of Typical Subjects

PubMed Central

Vieira, Marcus Fraga; Sacco, Isabel de Camargo Neves; Nora, Fernanda Grazielle da Silva Azevedo; Rosenbaum, Dieter; Lobo da Costa, Paula Hentschel

2015-01-01

Gait initiation is the task commonly used to investigate the anticipatory postural adjustments necessary to begin a new gait cycle from the standing position. In this study, we analyzed whether and how foot-floor interface characteristics influence the gait initiation process. For this purpose, 25 undergraduate students were evaluated while performing a gait initiation task in three experimental conditions: barefoot on a hard surface (barefoot condition), barefoot on a soft surface (foam condition), and shod on a hard surface (shod condition). Two force plates were used to acquire ground reaction forces and moments for each foot separately. A statistical parametric mapping (SPM) analysis was performed in COP time series. We compared the anterior-posterior (AP) and medial-lateral (ML) resultant center of pressure (COP) paths and average velocities, the force peaks under the right and left foot, and the COP integral x force impulse for three different phases: the anticipatory postural adjustment (APA) phase (Phase 1), the swing-foot unloading phase (Phase 2), and the support-foot unloading phase (Phase 3). In Phase 1, significantly smaller ML COP paths and velocities were found for the shod condition compared to the barefoot and foam conditions. Significantly smaller ML COP paths were also found in Phase 2 for the shod condition compared to the barefoot and foam conditions. In Phase 3, increased AP COP velocities were found for the shod condition compared to the barefoot and foam conditions. SPM analysis revealed significant differences for vector COP time series in the shod condition compared to the barefoot and foam conditions. The foam condition limited the impulse-generating capacity of COP shift and produced smaller ML force peaks, resulting in limitations to body-weight transfer from the swing to the support foot. The results suggest that footwear and a soft surface affect COP and impose certain features of gait initiation, especially in the ML direction of Phase 1. PMID:26270323

Human gene therapy: a brief overview of the genetic revolution.

PubMed

Misra, Sanjukta

2013-02-01

Advances in biotechnology have brought gene therapy to the forefront of medical research. The prelude to successful gene therapy i.e. the efficient transfer and expression of a variety of human gene into target cells has already been accomplished in several systems. Safe methods have been devised to do this, using several viral and no-viral vectors. Two main approaches emerged: in vivo modification and ex vivo modification. Retrovirus, adenovirus, adeno-associated virus are suitable for gene therapeutic approaches which are based on permanent expression of the therapeutic gene. Non-viral vectors are far less efficient than viral vectors, but they have advantages due to their low immunogenicity and their large capacity for therapeutic DNA. To improve the function of non-viral vectors, the addition of viral functions such as receptor mediated uptake and nuclear translocation of DNA may finally lead to the development of an artificial virus. Gene transfer protocols have been approved for human use in inherited diseases, cancers and acquired disorders. In 1990, the first successful clinical trial of gene therapy was initiated for adenosine deaminase deficiency. Since then, the number of clinical protocols initiated worldwide has increased exponentially. Although preliminary results of these trials are somewhat disappointing, but human gene therapy dreams of treating diseases by replacing or supplementing the product of defective or introducing novel therapeutic genes. So definitely human gene therapy is an effective addition to the arsenal of approaches to many human therapies in the 21st century.

HBx drives alpha fetoprotein expression to promote initiation of liver cancer stem cells through activating PI3K/AKT signal pathway.

PubMed

Zhu, Mingyue; Li, Wei; Lu, Yan; Dong, Xu; Lin, Bo; Chen, Yi; Zhang, Xueer; Guo, Junli; Li, Mengsen

2017-03-15

Hepatitis B virus (HBV)-X protein (HBx) plays critical role in inducing the malignant transformation of liver cells. Alpha fetoprotein (AFP) expression is closely related to hepatocarcinogenesis. We report that Oct4, Klf4, Sox2 and c-myc expression positively associated with AFP(+)/HBV(+) hepatocellular carcinoma(HCC) tissues, and the expression of the stemness markers CD44, CD133 and EpCAM was significantly higher in AFP(+)/HBV(+) HCC tissues compared to normal liver tissues or AFP (-)/HBV(-) HCC tissues. AFP expression turned on prior to expression of Oct4, Klf4, Sox2 and c-myc, and the stemness markers CD44, CD133 and EpCAM in the normal human liver L-02 cell line or CHL cell lines upon transfection with MCV-HBx vectors. Stem-like cells generated more tumour colonies compared to primary cells, and xenografts induced tumourigenesis in nude mice. Expression of reprogramming-related proteins was significantly enhanced in HLE cells while transfected with pcDNA3.1-afp vectors. The specific PI3K inhibitor Ly294002 inhibited the effects of pcDNA3.1-afp vectors. AFP-siRNA vectors were able to inhibit tumour colony formation and reprogramming-related gene expression. Altogether, HBx stimulates AFP expression to induce natural reprogramming of liver cells, and AFP plays a critical role in promoting the initiation of HCC progenitor/stem cells. AFP may be a potential novel biotarget for combating HBV-induced hepatocarcinogenesis. © 2016 UICC.

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

NASA Astrophysics Data System (ADS)

Secmen, Mustafa

2011-10-01

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

Altered orientation and flight paths of pigeons reared on gravity anomalies: a GPS tracking study.

PubMed

Blaser, Nicole; Guskov, Sergei I; Meskenaite, Virginia; Kanevskyi, Valerii A; Lipp, Hans-Peter

2013-01-01

The mechanisms of pigeon homing are still not understood, in particular how they determine their position at unfamiliar locations. The "gravity vector" theory holds that pigeons memorize the gravity vector at their home loft and deduct home direction and distance from the angular difference between memorized and actual gravity vector. However, the gravity vector is tilted by different densities in the earth crust leading to gravity anomalies. We predicted that pigeons reared on different gravity anomalies would show different initial orientation and also show changes in their flight path when crossing a gravity anomaly. We reared one group of pigeons in a strong gravity anomaly with a north-to-south gravity gradient, and the other group of pigeons in a normal area but on a spot with a strong local anomaly with a west-to-east gravity gradient. After training over shorter distances, pigeons were released from a gravitationally and geomagnetically normal site 50 km north in the same direction for both home lofts. As expected by the theory, the two groups of pigeons showed divergent initial orientation. In addition, some of the GPS-tracked pigeons also showed changes in their flight paths when crossing gravity anomalies. We conclude that even small local gravity anomalies at the birth place of pigeons may have the potential to bias the map sense of pigeons, while reactivity to gravity gradients during flight was variable and appeared to depend on individual navigational strategies and frequency of position updates.

A general framework for regularized, similarity-based image restoration.

PubMed

Kheradmand, Amin; Milanfar, Peyman

2014-12-01

Any image can be represented as a function defined on a weighted graph, in which the underlying structure of the image is encoded in kernel similarity and associated Laplacian matrices. In this paper, we develop an iterative graph-based framework for image restoration based on a new definition of the normalized graph Laplacian. We propose a cost function, which consists of a new data fidelity term and regularization term derived from the specific definition of the normalized graph Laplacian. The normalizing coefficients used in the definition of the Laplacian and associated regularization term are obtained using fast symmetry preserving matrix balancing. This results in some desired spectral properties for the normalized Laplacian such as being symmetric, positive semidefinite, and returning zero vector when applied to a constant image. Our algorithm comprises of outer and inner iterations, where in each outer iteration, the similarity weights are recomputed using the previous estimate and the updated objective function is minimized using inner conjugate gradient iterations. This procedure improves the performance of the algorithm for image deblurring, where we do not have access to a good initial estimate of the underlying image. In addition, the specific form of the cost function allows us to render the spectral analysis for the solutions of the corresponding linear equations. In addition, the proposed approach is general in the sense that we have shown its effectiveness for different restoration problems, including deblurring, denoising, and sharpening. Experimental results verify the effectiveness of the proposed algorithm on both synthetic and real examples.

Lentiviral Vector Induced Insertional Haploinsufficiency of Ebf1 Causes Murine Leukemia

PubMed Central

Heckl, Dirk; Schwarzer, Adrian; Haemmerle, Reinhard; Steinemann, Doris; Rudolph, Cornelia; Skawran, Britta; Knoess, Sabine; Krause, Johanna; Li, Zhixiong; Schlegelberger, Brigitte; Baum, Christopher; Modlich, Ute

2012-01-01

Integrating vectors developed on the basis of various retroviruses have demonstrated therapeutic potential following genetic modification of long-lived hematopoietic stem and progenitor cells. Lentiviral vectors (LV) are assumed to circumvent genotoxic events previously observed with γ-retroviral vectors, due to their integration bias to transcription units in comparison to the γ-retroviral preference for promoter regions and CpG islands. However, recently several studies have revealed the potential for gene activation by LV insertions. Here, we report a murine acute B-lymphoblastic leukemia (B-ALL) triggered by insertional gene inactivation. LV integration occurred into the 8th intron of Ebf1, a major regulator of B-lymphopoiesis. Various aberrant splice variants could be detected that involved splice donor and acceptor sites of the lentiviral construct, inducing downregulation of Ebf1 full-length message. The transcriptome signature was compatible with loss of this major determinant of B-cell differentiation, with partial acquisition of myeloid markers, including Csf1r (macrophage colony-stimulating factor (M-CSF) receptor). This was accompanied by receptor phosphorylation and STAT5 activation, both most likely contributing to leukemic progression. Our results highlight the risk of intragenic vector integration to initiate leukemia by inducing haploinsufficiency of a tumor suppressor gene. We propose to address this risk in future vector design. PMID:22472950

Xylella fastidiosa Afimbrial Adhesins Mediate Cell Transmission to Plants by Leafhopper Vectors▿

PubMed Central

Killiny, Nabil; Almeida, Rodrigo P. P.

2009-01-01

The interactions between the economically important plant-pathogenic bacterium Xylella fastidiosa and its leafhopper vectors are poorly characterized. We used different approaches to determine how X. fastidiosa cells interact with the cuticular surface of the foreguts of vectors. We demonstrate that X. fastidiosa binds to different polysaccharides with various affinities and that these interactions are mediated by cell surface carbohydrate-binding proteins. In addition, competition assays showed that N-acetylglucosamine inhibits bacterial adhesion to vector foregut extracts and intact wings, demonstrating that attachment to leafhopper surfaces is affected in the presence of specific polysaccharides. In vitro experiments with several X. fastidiosa knockout mutants indicated that hemagglutinin-like proteins are associated with cell adhesion to polysaccharides. These results were confirmed with biological experiments in which hemagglutinin-like protein mutants were transmitted to plants by vectors at lower rates than that of the wild type. Furthermore, although these mutants were defective in adhesion to the cuticle of vectors, their growth rate once attached to leafhoppers was similar to that of the wild type, suggesting that these proteins are important for initial adhesion of X. fastidiosa to leafhoppers. We propose that X. fastidiosa colonization of leafhopper vectors is a complex, stepwise process similar to the formation of biofilms on surfaces. PMID:19011051

Eco-Bio-Social Determinants for House Infestation by Non-domiciliated Triatoma dimidiata in the Yucatan Peninsula, Mexico

PubMed Central

Dumonteil, Eric; Nouvellet, Pierre; Rosecrans, Kathryn; Ramirez-Sierra, Maria Jesus; Gamboa-León, Rubi; Cruz-Chan, Vladimir; Rosado-Vallado, Miguel; Gourbière, Sébastien

2013-01-01

Background Chagas disease is a vector-borne disease of major importance in the Americas. Disease prevention is mostly limited to vector control. Integrated interventions targeting ecological, biological and social determinants of vector-borne diseases are increasingly used for improved control. Methodology/principal findings We investigated key factors associated with transient house infestation by T. dimidiata in rural villages in Yucatan, Mexico, using a mixed modeling approach based on initial null-hypothesis testing followed by multimodel inference and averaging on data from 308 houses from three villages. We found that the presence of dogs, chickens and potential refuges, such as rock piles, in the peridomicile as well as the proximity of houses to vegetation at the periphery of the village and to public light sources are major risk factors for infestation. These factors explain most of the intra-village variations in infestation. Conclusions/significance These results underline a process of infestation distinct from that of domiciliated triatomines and may be used for risk stratification of houses for both vector surveillance and control. Combined integrated vector interventions, informed by an Ecohealth perspective, should aim at targeting several of these factors to effectively reduce infestation and provide sustainable vector control. PMID:24086790

Production of high levels of poly-3-hydroxybutyrate in plastids of Camelina sativa seeds.

PubMed

Malik, Meghna R; Yang, Wenyu; Patterson, Nii; Tang, Jihong; Wellinghoff, Rachel L; Preuss, Mary L; Burkitt, Claire; Sharma, Nirmala; Ji, Yuanyuan; Jez, Joseph M; Peoples, Oliver P; Jaworski, Jan G; Cahoon, Edgar B; Snell, Kristi D

2015-06-01

Poly-3-hydroxybutyrate (PHB) production in plastids of Camelina sativa seeds was investigated by comparing levels of polymer produced upon transformation of plants with five different binary vectors containing combinations of five seed-specific promoters for expression of transgenes. Genes encoding PHB biosynthetic enzymes were modified at the N-terminus to encode a plastid targeting signal. PHB levels of up to 15% of the mature seed weight were measured in single sacrificed T1 seeds with a genetic construct containing the oleosin and glycinin promoters. A more detailed analysis of the PHB production potential of two of the best performing binary vectors in a Camelina line bred for larger seed size yielded lines containing up to 15% polymer in mature T2 seeds. Transmission electron microscopy showed the presence of distinct granules of PHB in the seeds. PHB production had varying effects on germination, emergence and survival of seedlings. Once true leaves formed, plants grew normally and were able to set seeds. PHB synthesis lowered the total oil but not the protein content of engineered seeds. A change in the oil fatty acid profile was also observed. High molecular weight polymer was produced with weight-averaged molecular weights varying between 600 000 and 1 500 000, depending on the line. Select lines were advanced to later generations yielding a line with 13.7% PHB in T4 seeds. The levels of polymer produced in this study are the highest reported to date in a seed and are an important step forward for commercializing an oilseed-based platform for PHB production. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Mechanisms of inhibition of growth of human pancreatic carcinoma implanted in nude mice by somatostatin receptor subtype 2.

PubMed

Kumar, Manoj; Liu, Zheng-Ren; Thapa, Laxmi; Wang, Da-Yu; Tian, Rui; Qin, Ren-Yi

2004-08-01

Several studies reported that somatostatin receptor subtypes, especially subtype 2 (SSTR2), exerted their cytostatic and/or cytotoxic effects on various types of tumors. The aim of this study was to investigate the antitumor effect of SSTR2 gene transfer to the pancreatic cancer cell line PC-3 and the mechanisms involved in this effect. The full-length human SSTR2 cDNA was introduced into pancreatic cancer cell line PC-3 by lipofectamine-mediated transfection; positive clones were screened by G418, and stable expression of SSTR2 was detected by the immunohistochemical SABC method and RT-PCR. Athymic mice were separately xenografted with SSTR2-expressing cells (experimental group), vector control, and mock control cells. TUNEL assay was used to determine the apoptotic index (AI) in the tumors of these groups. The immunohistochemical SP method was used to determine expression of apoptosis-regulating genes Bcl-2 and Bax and re-expression of SSTR2 and to assess intratumoral microvessel density (MVD). Moreover, tumor volume and weight were compared among these 3 groups. Restoration of SSTR2 was observed in the experimental group both in vitro and in vivo. The AI was significantly higher in the experimental group (3.39 +/- 0.84%) compared with that in the vector control (0.69 +/- 0.08%) and mock control (0.68 +/- 0.09%) (P < 0.05). MVD was significantly lower in the experimental group (6.30 +/- 1.71) than that in the vector control (12.64 +/- 1.69) and mock control (13.50 +/- 1.86) (P < 0.05). Furthermore, a significant decrease in Bcl-2 and increase in Bax protein expression were detected in the experimental group compared with the vector control and mock control (P < 0.05). A significant negative correlation of protein expression between Bcl-2/Bax ratio and SSTR2 was observed in these tumors (P < 0.05). Tumor volume and weight were significantly decreased in the experimental group compared with the vector control and mock control (P < 0.05) groups. However, no significant differences were observed between the vector control and mock control (P > 0.05). Re-expression of the SSTR2 gene, the expression of which is frequently lost in human pancreatic adenocarcinoma, induces apoptosis, which may be mediated via down-regulation of Bcl-2 and up-regulation of Bax (alteration of Bcl-2/Bax ratio) and inhibits tumor angiogenesis in pancreatic carcinoma, resulting in inhibition of tumor growth.

Impact of vectorborne parasitic neglected tropical diseases on child health.

PubMed

Barry, Meagan A; Murray, Kristy O; Hotez, Peter J; Jones, Kathryn M

2016-07-01

Chagas disease, leishmaniasis, onchocerciasis and lymphatic filariasis are all vectorborne neglected tropical diseases (NTDs) that are responsible for significant disease burden in impoverished children and adults worldwide. As vectorborne parasitic diseases, they can all be targeted for elimination through vector control strategies. Examples of successful vector control programmes for these diseases over the past two decades have included the Southern Cone Initiative against Chagas disease, the Kala-azar Control Scheme against leishmaniasis, the Onchocerciasis Control Programme and the lymphatic filariasis control programme in The Gambia. A common vector control component in all of these programmes is the use of adulticides including dichlorodiphenyltrichloroethane and newer synthetic pyrethroid insecticides against the insect vectors of disease. Household spraying has been used against Chagas disease and leishmaniasis, and insecticide-treated bed nets have helped prevent leishmaniasis and lymphatic filariasis. Recent trends in vector control focus on collaborations between programmes and sectors to achieve integrated vector management that addresses the holistic vector control needs of a community rather than approaching it on a disease-by-disease basis, with the goals of increased efficacy, sustainability and cost-effectiveness. As evidence of vector resistance to currently used insecticide regimens emerges, research to develop new and improved insecticides and novel control strategies will be critical in reducing disease burden. In the quest to eliminate these vectorborne NTDs, efforts need to be made to continue existing control programmes, further implement integrated vector control strategies and stimulate research into new insecticides and control methods. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

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

PubMed Central

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

2015-01-01

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

Weight Changes in Patients with Differentiated Thyroid Carcinoma during Postoperative Long-Term Follow-up under Thyroid Stimulating Hormone Suppression

PubMed Central

Sohn, Seo Young; Joung, Ji Young; Cho, Yoon Young; Park, Sun Mi; Jin, Sang Man; Chung, Jae Hoon

2015-01-01

Background There are limited data about whether patients who receive initial treatment for differentiated thyroid cancer (DTC) gain or lose weight during long-term follow-up under thyroid stimulating hormone (TSH) suppression. This study was aimed to evaluate whether DTC patients under TSH suppression experience long-term weight gain after initial treatment. We also examined the impact of the radioactive iodine ablation therapy (RAIT) preparation method on changes of weight, comparing thyroid hormone withdrawal (THW) and recombinant human TSH (rhTSH). Methods We retrospectively reviewed 700 DTC patients who underwent a total thyroidectomy followed by either RAIT and levothyroxine (T4) replacement or T4 replacement alone. The control group included 350 age-matched patients with benign thyroid nodules followed during same period. Anthropometric data were measured at baseline, 1 to 2 years, and 3 to 4 years after thyroidectomy. Comparisons were made between weight and body mass index (BMI) at baseline and follow-up. Results Significant gains in weight and BMI were observed 3 to 4 years after initial treatment for female DTC but not in male patients. These gains among female DTC patients were also significant compared to age-matched control. Women in the THW group gained a significant amount of weight and BMI compared to baseline, while there was no increase in weight or BMI in the rhTSH group. There were no changes in weight and BMI in men according to RAIT preparation methods. Conclusion Female DTC patients showed significant gains in weight and BMI during long-term follow-up after initial treatment. These changes were seen only in patients who underwent THW for RAIT. PMID:26248858

One-year weight losses in the Tianjin Gestational Diabetes Mellitus Prevention Programme: A randomized clinical trial.

PubMed

Liu, Huikun; Wang, Leishen; Zhang, Shuang; Leng, Junhong; Li, Nan; Li, Weiqin; Wang, Jing; Tian, Huiguang; Qi, Lu; Yang, Xilin; Yu, Zhijie; Tuomilehto, Jaakko; Hu, Gang

2018-05-01

To report the weight loss findings after the first year of a lifestyle intervention trial among women with gestational diabetes mellitus (GDM). A total of 1180 women with GDM were randomly assigned (1:1) to receive a 4-year lifestyle intervention (intervention group, n = 586) or standard care (control group, n = 594) between August 2009 and July 2011. Major elements of the intervention included 6 face-to-face sessions with study dieticians and two telephone calls in the first year, and two individual sessions and two telephone calls in each subsequent year. Among 79% of participants who completed the year 1 trial, mean weight loss was 0.82 kg (1.12% of initial weight) in the intervention group and 0.09 kg (0.03% of initial weight) in the control group (P = .001). In a prespecified subgroup analysis of people who completed the trial, weight loss was more pronounced in women who were overweight (body mass index ≥24 kg/m 2 ) at baseline: mean weight loss 2.01 kg (2.87% of initial weight) in the intervention group and 0.44 kg (0.52% of initial weight) in the control group (P < .001). Compared with those in the control group, women in the intervention group had a greater decrease in waist circumference (1.76 cm vs 0.73 cm; P = .003) and body fat (0.50% vs 0.05% increase; P = .001). The 1-year lifestyle intervention led to significant weight losses after delivery in women who had GDM, and the effect was more pronounced in women who were overweight at baseline. © 2018 John Wiley & Sons Ltd.

In vitro and in vivo gene therapy with CMV vector-mediated presumed dog beta-nerve growth factor in pyridoxine-induced neuropathy dogs.

PubMed

Chung, Jin Young; Choi, Jung Hoon; Shin, Il Seob; Choi, Eun Wha; Hwang, Cheol Yong; Lee, Sang Koo; Youn, Hwa Young

2008-12-01

Due to the therapeutic potential of gene therapy for neuronal injury, many studies of neurotrophic factors, vectors, and animal models have been performed. The presumed dog beta-nerve growth factor (pdbeta-NGF) was generated and cloned and its expression was confirmed in CHO cells. The recombinant pdbeta-NGF protein reacted with a human beta-NGF antibody and showed bioactivity in PC12 cells. The pdbeta-NGF was shown to have similar bioactivity to the dog beta-NGF. The recombinant pdbeta-NGF plasmid was administrated into the intrathecal space in the gene therapy group. Twenty-four hours after the vector inoculation, the gene therapy group and the positive control group were intoxicated with excess pyridoxine for seven days. Each morning throughout the test period, the dogs' body weight was taken and postural reaction assessments were made. Electrophysiological recordings were performed twice, once before the experiment and once after the test period. After the experimental period, histological analysis was performed. Dogs in the gene therapy group had no weight change and were normal in postural reaction assessments. Electrophysiological recordings were also normal for the gene therapy group. Histological analysis showed that neither the axons nor the myelin of the dorsal funiculus of L4 were severely damaged in the gene therapy group. In addition, the dorsal root ganglia of L4 and the peripheral nerves (sciatic nerve) did not experience severe degenerative changes in the gene therapy group. This study is the first to show the protective effect of NGF gene therapy in a dog model.

FGF2 High Molecular Weight Isoforms Contribute to Osteoarthropathy in Male Mice

PubMed Central

Meo Burt, Patience; Xiao, Liping; Dealy, Caroline; Fisher, Melanie C.

2016-01-01

Humans with X-linked hypophosphatemia (XLH) and Hyp mice, the murine homolog of the disease, develop severe osteoarthropathy and the precise factors that contribute to this joint degeneration remain largely unknown. Fibroblast growth factor 2 (FGF2) is a key regulatory growth factor in osteoarthritis. Although there are multiple FGF2 isoforms the potential involvement of specific FGF2 isoforms in joint degradation has not been investigated. Mice that overexpress the high molecular weight FGF2 isoforms in bone (HMWTg mice) phenocopy Hyp mice and XLH subjects and Hyp mice overexpress the HMWFGF2 isoforms in osteoblasts and osteocytes. Given that Hyp mice and XLH subjects develop osteoarthropathies we examined whether HMWTg mice also develop knee joint degeneration at 2, 8, and 18 mo compared with VectorTg (control) mice. HMWTg mice developed spontaneous osteoarthropathy as early as age 2 mo with thinning of subchondral bone, osteophyte formation, decreased articular cartilage thickness, abnormal mineralization within the joint, increased cartilage degradative enzymes, hypertrophic markers, and angiogenesis. FGF receptors 1 and 3 and fibroblast growth factor 23 were significantly altered compared with VectorTg mice. In addition, gene expression of growth factors and cytokines including bone morphogenetic proteins, Insulin like growth factor 1, Interleukin 1 beta, as well as transcription factors Sex determining region Y box 9, hypoxia inducible factor 1, and nuclear factor kappa B subunit 1 were differentially modulated in HMWTg compared with VectorTg. This study demonstrates that overexpression of the HMW isoforms of FGF2 in bone results in catabolic activity in joint cartilage and bone that leads to osteoarthropathy. PMID:27732085

Classification of Alzheimer's disease patients with hippocampal shape wrapper-based feature selection and support vector machine

NASA Astrophysics Data System (ADS)

Young, Jonathan; Ridgway, Gerard; Leung, Kelvin; Ourselin, Sebastien

2012-02-01

It is well known that hippocampal atrophy is a marker of the onset of Alzheimer's disease (AD) and as a result hippocampal volumetry has been used in a number of studies to provide early diagnosis of AD and predict conversion of mild cognitive impairment patients to AD. However, rates of atrophy are not uniform across the hippocampus making shape analysis a potentially more accurate biomarker. This study studies the hippocampi from 226 healthy controls, 148 AD patients and 330 MCI patients obtained from T1 weighted structural MRI images from the ADNI database. The hippocampi are anatomically segmented using the MAPS multi-atlas segmentation method, and the resulting binary images are then processed with SPHARM software to decompose their shapes as a weighted sum of spherical harmonic basis functions. The resulting parameterizations are then used as feature vectors in Support Vector Machine (SVM) classification. A wrapper based feature selection method was used as this considers the utility of features in discriminating classes in combination, fully exploiting the multivariate nature of the data and optimizing the selected set of features for the type of classifier that is used. The leave-one-out cross validated accuracy obtained on training data is 88.6% for classifying AD vs controls and 74% for classifying MCI-converters vs MCI-stable with very compact feature sets, showing that this is a highly promising method. There is currently a considerable fall in accuracy on unseen data indicating that the feature selection is sensitive to the data used, however feature ensemble methods may overcome this.

Bayesian analogy with relational transformations.

PubMed

Lu, Hongjing; Chen, Dawn; Holyoak, Keith J

2012-07-01

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. Copyright 2012 APA, all rights reserved.

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

PubMed

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

2011-01-01

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

Bayesian anomaly detection in monitoring data applying relevance vector machine

NASA Astrophysics Data System (ADS)

Saito, Tomoo

2011-04-01

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

Multilayer perceptron, fuzzy sets, and classification

NASA Technical Reports Server (NTRS)

Pal, Sankar K.; Mitra, Sushmita

1992-01-01

A fuzzy neural network model based on the multilayer perceptron, using the back-propagation algorithm, and capable of fuzzy classification of patterns is described. The input vector consists of membership values to linguistic properties while the output vector is defined in terms of fuzzy class membership values. This allows efficient modeling of fuzzy or uncertain patterns with appropriate weights being assigned to the backpropagated errors depending upon the membership values at the corresponding outputs. During training, the learning rate is gradually decreased in discrete steps until the network converges to a minimum error solution. The effectiveness of the algorithm is demonstrated on a speech recognition problem. The results are compared with those of the conventional MLP, the Bayes classifier, and the other related models.

THE ROLE OF SELF-MONITORING IN THE MAINTENANCE OF WEIGHT LOSS SUCCESS

PubMed Central

Minski, Samantha A.; Perri, Michael G.

2016-01-01

Introduction Self-monitoring has been shown to be a crucial part of initial weight loss success in behavioral interventions. However, little is known about the impact of self-monitoring during the period following initial treatment. Methods The current study examined the role of self-monitoring on weight loss during an initial 6-month intervention period (Phase1) and a 12-month extended care period (Phase 2) in a group of 167 obese women (M±SD: BMI = 37.0±5.1 kg/m2, age = 59.9±6.2 years) enrolled in a behavioral weight loss program. Results Cluster analysis identified three groups of participants with low, moderate, and high rates of weight loss success during Phase 1 and Phase 2. A one-way ANOVA revealed no significant differences in self-monitoring frequency between groups during Phase 1 (p = .645), but significant differences between all three groups during Phase 2 (p = .001). High success participants completed the most self-monitoring records, followed by the moderate group. The low success group completed the least number of records. Furthermore, self-monitoring during Phase 2 significantly mediated the relationship between extended-care session attendance and percent weight change during that time (95% CI [−.004, −.001], p < .001). Conclusion These results highlight the importance of continuing self-monitoring after the initial phase of treatment to maintain lost weight. PMID:26974582

Ineffectiveness of commercial weight-loss programs for achieving modest but meaningful weight loss: Systematic review and meta-analysis.

PubMed

McEvedy, Samantha M; Sullivan-Mort, Gillian; McLean, Siân A; Pascoe, Michaela C; Paxton, Susan J

2017-10-01

This study collates existing evidence regarding weight loss among overweight but otherwise healthy adults who use commercial weight-loss programs. Systematic search of 3 databases identified 11 randomized controlled trials and 14 observational studies of commercial meal-replacement, calorie-counting, or pre-packaged meal programs which met inclusion criteria. In meta-analysis using intention-to-treat data, 57 percent of individuals who commenced a commercial weight program lost less than 5 percent of their initial body weight. One in two (49%) studies reported attrition ≥30 percent. A second meta-analysis found that 37 percent of program completers lost less than 5 percent of initial body weight. We conclude that commercial weight-loss programs frequently fail to produce modest but clinically meaningful weight loss with high rates of attrition suggesting that many consumers find dietary changes required by these programs unsustainable.

DietBet: A Web-Based Program that Uses Social Gaming and Financial Incentives to Promote Weight Loss

PubMed Central

Rosen, Jamie

2014-01-01

Background Web-based commercial weight loss programs are increasing in popularity. Despite their significant public health potential, there is limited research on the effectiveness of such programs. Objective The objective of our study was to examine weight losses produced by DietBet and explore whether baseline and engagement variables predict weight outcomes. Methods DietBet is a social gaming website that uses financial incentives and social influence to promote weight loss. Players bet money and join a game. All players have 4 weeks to lose 4% of their initial body weight. At enrollment, players can choose to share their participation on Facebook. During the game, players interact with one another and report their weight loss on the DietBet platform. At week 4, all players within each game who lose at least 4% of initial body weight are declared winners and split the pool of money bet at the start of the game. Official weigh-in procedures are used to verify weights at the start of the game and at the end. Results From December 2012 to July 2013, 39,387 players (84.04% female, 33,101/39,387; mean weight 87.8kg, SD 22.6kg) competed in 1934 games. The average amount bet was US $27 (SD US $22). A total of 65.63% (25,849/39,387) provided a verified weight at the end of the 4-week competition. The average intention-to-treat weight loss was 2.6% (SD 2.3%). Winners (n=17,171) won an average of US $59 (SD US $35) and lost 4.9% (SD 1.0%) of initial body weight, with 30.68% (5268/17,171) losing 5% or more of their initial weight. Betting more money at game entry, sharing on Facebook, completing more weigh-ins, and having more social interactions during the game predicted greater weight loss and greater likelihood of winning (Ps<.001). In addition, weight loss clustered within games (P<.001), suggesting that players influenced each others’ weight outcomes. Conclusions DietBet, a social gaming website, reached nearly 40,000 individuals in just 7 months and produced excellent 4-week weight loss results. Given its reach and potential public health impact, future research may consider examining whether a longer program promotes additional weight loss. PMID:25658966

Reducing vector-borne disease by empowering farmers in integrated vector management.

PubMed

van den Berg, Henk; von Hildebrand, Alexander; Ragunathan, Vaithilingam; Das, Pradeep K

2007-07-01

Irrigated agriculture exposes rural people to health risks associated with vector-borne diseases and pesticides used in agriculture and for public health protection. Most developing countries lack collaboration between the agricultural and health sectors to jointly address these problems. We present an evaluation of a project that uses the "farmer field school" method to teach farmers how to manage vector-borne diseases and how to improve rice yields. Teaching farmers about these two concepts together is known as "integrated pest and vector management". An intersectoral project targeting rice irrigation systems in Sri Lanka. Project partners developed a new curriculum for the field school that included a component on vector-borne diseases. Rice farmers in intervention villages who graduated from the field school took vector-control actions as well as improving environmental sanitation and their personal protection measures against disease transmission. They also reduced their use of agricultural pesticides, especially insecticides. The intervention motivated and enabled rural people to take part in vector-management activities and to reduce several environmental health risks. There is scope for expanding the curriculum to include information on the harmful effects of pesticides on human health and to address other public health concerns. Benefits of this approach for community-based health programmes have not yet been optimally assessed. Also, the institutional basis of the integrated management approach needs to be broadened so that people from a wider range of organizations take part. A monitoring and evaluation system needs to be established to measure the performance of integrated management initiatives.

Phase measurement for driven spin oscillations in a storage ring

NASA Astrophysics Data System (ADS)

Hempelmann, N.; Hejny, V.; Pretz, J.; Soltner, H.; Augustyniak, W.; Bagdasarian, Z.; Bai, M.; Barion, L.; Berz, M.; Chekmenev, S.; Ciullo, G.; Dymov, S.; Eversmann, D.; Gaisser, M.; Gebel, R.; Grigoryev, K.; Grzonka, D.; Guidoboni, G.; Heberling, D.; Hetzel, J.; Hinder, F.; Kacharava, A.; Kamerdzhiev, V.; Keshelashvili, I.; Koop, I.; Kulikov, A.; Lehrach, A.; Lenisa, P.; Lomidze, N.; Lorentz, B.; Maanen, P.; Macharashvili, G.; Magiera, A.; Mchedlishvili, D.; Mey, S.; Müller, F.; Nass, A.; Nikolaev, N. N.; Nioradze, M.; Pesce, A.; Prasuhn, D.; Rathmann, F.; Rosenthal, M.; Saleev, A.; Schmidt, V.; Semertzidis, Y.; Senichev, Y.; Shmakova, V.; Silenko, A.; Slim, J.; Stahl, A.; Stassen, R.; Stephenson, E.; Stockhorst, H.; Ströher, H.; Tabidze, M.; Tagliente, G.; Talman, R.; Thörngren Engblom, P.; Trinkel, F.; Uzikov, Yu.; Valdau, Yu.; Valetov, E.; Vassiliev, A.; Weidemann, C.; Wrońska, A.; Wüstner, P.; Zuprański, P.; Żurek, M.; JEDI Collaboration

2018-04-01

This paper reports the first simultaneous measurement of the horizontal and vertical components of the polarization vector in a storage ring under the influence of a radio frequency (rf) solenoid. The experiments were performed at the Cooler Synchrotron COSY in Jülich using a vector polarized, bunched 0.97 GeV /c deuteron beam. Using the new spin feedback system, we set the initial phase difference between the solenoid field and the precession of the polarization vector to a predefined value. The feedback system was then switched off, allowing the phase difference to change over time, and the solenoid was switched on to rotate the polarization vector. We observed an oscillation of the vertical polarization component and the phase difference. The oscillations can be described using an analytical model. The results of this experiment also apply to other rf devices with horizontal magnetic fields, such as Wien filters. The precise manipulation of particle spins in storage rings is a prerequisite for measuring the electric dipole moment (EDM) of charged particles.

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

NASA Astrophysics Data System (ADS)

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

1999-12-01

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

Cubic-panorama image dataset analysis for storage and transmission

NASA Astrophysics Data System (ADS)

Salehi, Saeed; Dubois, Eric

2013-02-01

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

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model.

PubMed

Selvaraj, Lokesh; Ganesan, Balakrishnan

2014-01-01

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

Zoom in at African country level: potential climate induced changes in areas of suitability for survival of malaria vectors.

PubMed

Tonnang, Henri E Z; Tchouassi, David P; Juarez, Henry S; Igweta, Lilian K; Djouaka, Rousseau F

2014-05-07

Predicting anopheles vectors' population densities and boundary shifts is crucial in preparing for malaria risks and unanticipated outbreaks. Although shifts in the distribution and boundaries of the major malaria vectors (Anopheles gambiae s.s. and An. arabiensis) across Africa have been predicted, quantified areas of absolute change in zone of suitability for their survival have not been defined. In this study, we have quantified areas of absolute change conducive for the establishment and survival of these vectors, per African country, under two climate change scenarios and based on our findings, highlight practical measures for effective malaria control in the face of changing climatic patterns. We developed a model using CLIMEX simulation platform to estimate the potential geographical distribution and seasonal abundance of these malaria vectors in relation to climatic factors (temperature, rainfall and relative humidity). The model yielded an eco-climatic index (EI) describing the total favourable geographical locations for the species. The EI values were classified and exported to a GIS package. Using ArcGIS, the EI shape points were clipped to the extent of Africa and then converted to a raster layer using Inverse Distance Weighted (IDW) interpolation method. Generated maps were then transformed into polygon-based geo-referenced data set and their areas computed and expressed in square kilometers (km(2)). Five classes of EI were derived indicating the level of survivorship of these malaria vectors. The proportion of areas increasing or decreasing in level of survival of these malaria vectors will be more pronounced in eastern and southern African countries than those in western Africa. Angola, Ethiopia, Kenya, Mozambique, Tanzania, South Africa and Zambia appear most likely to be affected in terms of absolute change of malaria vectors suitability zones under the selected climate change scenarios. The potential shifts of these malaria vectors have implications for human exposure to malaria, as recrudescence of the disease is likely to be recorded in several new areas and regions. Therefore, the need to develop, compile and share malaria preventive measures, which can be adapted to different climatic scenarios, remains crucial.

Financial incentive strategies for maintenance of weight loss: results from an internet-based randomized controlled trial.

PubMed

Yancy, William S; Shaw, Pamela A; Wesby, Lisa; Hilbert, Victoria; Yang, Lin; Zhu, Jingsan; Troxel, Andrea; Huffman, David; Foster, Gary D; Wojtanowski, Alexis C; Volpp, Kevin G

2018-05-25

Financial incentives can improve initial weight loss; we examined whether financial incentives can improve weight loss maintenance. Participants aged 30-80 years who lost at least 5 kg during the first 4-6 months in a nationally available commercial weight loss program were recruited via the internet into a three-arm randomized trial of two types of financial incentives versus active control during months 1-6 (Phase I) followed by passive monitoring during months 7-12 (Phase II). Interventions were daily self-weighing and text messaging feedback alone (control) or combined with a lottery-based incentive or a direct incentive. The primary outcome was weight change 6 months after initial weight loss. Secondary outcomes included weight change 12 months after initial weight loss (6 months after cessation of maintenance intervention), and self-reported physical activity and eating behaviors. Of 191 participants randomized, the mean age was 49.0 (SD = 10.5) years and weight loss prior to randomization was 11.4 (4.7) kg; 92% were women and 89% were White. Mean weight changes during the next 6 months (Phase I) were: lottery -3.0 (5.8) kg; direct -2.8 (5.8) kg; and control -1.4 (5.8) kg (all pairwise comparisons p > 0.1). Weight changes through the end of 12 months post-weight loss (Phase II) were: lottery -1.8 (10.5) kg; direct -0.7 (10.7) kg; and control -0.3 (9.4) kg (all pairwise comparisons p > 0.1). The percentages of participants who maintained their weight loss (defined as gaining ≤1.36 kg) were: lottery 79%, direct 76%, and control 67% at 6 months and lottery 66%, direct 62%, and control 59% at 12 months (all pairwise comparisons p > 0.1). At 6 and 12 months after initial weight loss, changes in self-reported physical activity or eating behaviors did not differ across arms. Compared with the active control of daily texting based on daily home weighing, lottery-based and direct monetary incentives provided no additional benefit for weight loss maintenance.

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

PubMed

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

2015-12-02

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

Numerical simulations of fast-axis instability of vector solitons in mode-locked fiber lasers.

PubMed

Du, Yueqing; Shu, Xuewen; Cheng, Peiyun

2017-01-23

We demonstrate the fast-axis instability in mode-locked fiber lasers numerically for the first time. We find that the energy of the fast mode will be transferred to the slow mode when the strong pump strength makes the soliton period short. A nearly linearly polarized vector soliton along the slow-axis could be generated under certain cavity parameters. The final polarization of the vector soliton is related to the initial polarization of the seed pulse. Two regimes of energy exchanging between the slow mode and the fast mode are explored and the direction of the energy flow between two modes depends on the phase difference. The dip-type sidebands are found to be intrinsic characteristics of the mode-locked fiber lasers under high pulse energy.

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.

Life Cycle, Feeding, and Defecation Patterns of Panstrongylus chinai (Hemiptera: Reduviidae: Triatominae) Under Laboratory Conditions.

PubMed

Mosquera, Katherine D; Villacís, Anita G; Grijalva, Mario J

2016-07-01

Chagas disease is caused by the protozoan Trypanosoma cruzi Panstrongylus chinai (Del Ponte) is highly domiciliated in the Peruvian and Ecuadorian Andes and has been found naturally infected with T. cruzi The objective of this study was to describe the life cycle, feeding, and defecation patterns of P. chinai in the Loja province within southern Ecuador. To characterize its life cycle, a cohort of 70 individuals was followed from egg to adult. At each stage of development, prefeeding time, feeding time, weight of ingested meal, proportional weight increase, and the time to the first defecation were recorded. Panstrongylus chinai completed its development in 371.4 ± 22.3 d, (95% CI 355.4-387.4), which means that it is likely a univoltine species. Prefeeding time, feeding time, and weight of ingested meal increased as individuals developed through nymphal stages. Moreover, time to first defecation was shortest in the early nymphal stages, suggesting higher vector potential in the early developmental stages. Data obtained in this study represent an important advance in our knowledge of the biology of P. chinai, which should be considered as a secondary Chagas disease vector species in the Andean valleys of Loja (Ecuador) and in the north of Peru, and included in entomological surveillance programs. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Numerical limitations in application of vector autoregressive modeling and Granger causality to analysis of EEG time series

NASA Astrophysics Data System (ADS)

Kammerdiner, Alla; Xanthopoulos, Petros; Pardalos, Panos M.

2007-11-01

In this chapter a potential problem with application of the Granger-causality based on the simple vector autoregressive (VAR) modeling to EEG data is investigated. Although some initial studies tested whether the data support the stationarity assumption of VAR, the stability of the estimated model is rarely (if ever) been verified. In fact, in cases when the stability condition is violated the process may exhibit a random walk like behavior or even be explosive. The problem is illustrated by an example.

Biostable insect kinin analogs reduce blood meal and disrupt ecdysis in the blood-gorging Chagas’ disease vector, Rhodnius prolixus

USDA-ARS?s Scientific Manuscript database

Rhodnius prolixus is a blood-gorging hemipteran that takes blood meals that are approximately 10 times its body weight. This blood meal is crucial for growth and development and is needed to ensure a successful molt into the next instar. Kinins are a multifunctional family of neuropeptides which hav...

BDDC algorithms with deluxe scaling and adaptive selection of primal constraints for Raviart-Thomas vector fields

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

Oh, Duk -Soon; Widlund, Olof B.; Zampini, Stefano

Here, a BDDC domain decomposition preconditioner is defined by a coarse component, expressed in terms of primal constraints, a weighted average across the interface between the subdomains, and local components given in terms of solvers of local subdomain problems. BDDC methods for vector field problems discretized with Raviart-Thomas finite elements are introduced. The methods are based on a new type of weighted average an adaptive selection of primal constraints developed to deal with coefficients with high contrast even inside individual subdomains. For problems with very many subdomains, a third level of the preconditioner is introduced. Assuming that the subdomains aremore » all built from elements of a coarse triangulation of the given domain, and that in each subdomain the material parameters are consistent, one obtains a bound for the preconditioned linear system's condition number which is independent of the values and jumps of these parameters across the subdomains' interface. Numerical experiments, using the PETSc library, are also presented which support the theory and show the algorithms' effectiveness even for problems not covered by the theory. Also included are experiments with Brezzi-Douglas-Marini finite-element approximations.« less

Action Direction of Muscle Synergies in Three-Dimensional Force Space

PubMed Central

Hagio, Shota; Kouzaki, Motoki

2015-01-01

Redundancy in the musculoskeletal system was supposed to be simplified by muscle synergies, which modularly organize muscles. To clarify the underlying mechanisms of motor control using muscle synergies, it is important to examine the spatiotemporal contribution of muscle synergies in the task space. In this study, we quantified the mechanical contribution of muscle synergies as considering spatiotemporal correlation between the activation of muscle synergies and endpoint force fluctuations. Subjects performed isometric force generation in the three-dimensional force space. The muscle-weighting vectors of muscle synergies and their activation traces across different trials were extracted from electromyogram data using decomposing technique. We then estimated mechanical contribution of muscle synergies across each trial based on cross-correlation analysis. The contributing vectors were averaged for all trials, and the averaging was defined as action direction (AD) of muscle synergies. As a result, we extracted approximately five muscle synergies. The ADs of muscle synergies mainly depended on the anatomical functions of their weighting muscles. Furthermore, the AD of each muscle indicated the synchronous activation of muscles, which composed of the same muscle synergy. These results provide the spatiotemporal characteristics of muscle synergies as neural basis. PMID:26618156

Action Direction of Muscle Synergies in Three-Dimensional Force Space.

PubMed

Hagio, Shota; Kouzaki, Motoki

2015-01-01

Redundancy in the musculoskeletal system was supposed to be simplified by muscle synergies, which modularly organize muscles. To clarify the underlying mechanisms of motor control using muscle synergies, it is important to examine the spatiotemporal contribution of muscle synergies in the task space. In this study, we quantified the mechanical contribution of muscle synergies as considering spatiotemporal correlation between the activation of muscle synergies and endpoint force fluctuations. Subjects performed isometric force generation in the three-dimensional force space. The muscle-weighting vectors of muscle synergies and their activation traces across different trials were extracted from electromyogram data using decomposing technique. We then estimated mechanical contribution of muscle synergies across each trial based on cross-correlation analysis. The contributing vectors were averaged for all trials, and the averaging was defined as action direction (AD) of muscle synergies. As a result, we extracted approximately five muscle synergies. The ADs of muscle synergies mainly depended on the anatomical functions of their weighting muscles. Furthermore, the AD of each muscle indicated the synchronous activation of muscles, which composed of the same muscle synergy. These results provide the spatiotemporal characteristics of muscle synergies as neural basis.

A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier.

PubMed

Zhou, Shenghan; Qian, Silin; Chang, Wenbing; Xiao, Yiyong; Cheng, Yang

2018-06-14

Timely and accurate state detection and fault diagnosis of rolling element bearings are very critical to ensuring the reliability of rotating machinery. This paper proposes a novel method of rolling bearing fault diagnosis based on a combination of ensemble empirical mode decomposition (EEMD), weighted permutation entropy (WPE) and an improved support vector machine (SVM) ensemble classifier. A hybrid voting (HV) strategy that combines SVM-based classifiers and cloud similarity measurement (CSM) was employed to improve the classification accuracy. First, the WPE value of the bearing vibration signal was calculated to detect the fault. Secondly, if a bearing fault occurred, the vibration signal was decomposed into a set of intrinsic mode functions (IMFs) by EEMD. The WPE values of the first several IMFs were calculated to form the fault feature vectors. Then, the SVM ensemble classifier was composed of binary SVM and the HV strategy to identify the bearing multi-fault types. Finally, the proposed model was fully evaluated by experiments and comparative studies. The results demonstrate that the proposed method can effectively detect bearing faults and maintain a high accuracy rate of fault recognition when a small number of training samples are available.

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Space-Time Earthquake Prediction: The Error Diagrams

NASA Astrophysics Data System (ADS)

Molchan, G.

2010-08-01

The quality of earthquake prediction is usually characterized by a two-dimensional diagram n versus τ, where n is the rate of failures-to-predict and τ is a characteristic of space-time alarm. Unlike the time prediction case, the quantity τ is not defined uniquely. We start from the case in which τ is a vector with components related to the local alarm times and find a simple structure of the space-time diagram in terms of local time diagrams. This key result is used to analyze the usual 2-d error sets { n, τ w } in which τ w is a weighted mean of the τ components and w is the weight vector. We suggest a simple algorithm to find the ( n, τ w ) representation of all random guess strategies, the set D, and prove that there exists the unique case of w when D degenerates to the diagonal n + τ w = 1. We find also a confidence zone of D on the ( n, τ w ) plane when the local target rates are known roughly. These facts are important for correct interpretation of ( n, τ w ) diagrams when we discuss the prediction capability of the data or prediction methods.

Inferring the Functions of Proteins from the Interrelationships between Functional Categories.

PubMed

Taha, Kamal

2018-01-01

This study proposes a new method to determine the functions of an unannotated protein. The proteins and amino acid residues mentioned in biomedical texts associated with an unannotated protein can be considered as characteristics terms for , which are highly predictive of the potential functions of . Similarly, proteins and amino acid residues mentioned in biomedical texts associated with proteins annotated with a functional category can be considered as characteristics terms of . We introduce in this paper an information extraction system called IFP_IFC that predicts the functions of an unannotated protein by representing and each functional category by a vector of weights. Each weight reflects the degree of association between a characteristic term and (or a characteristic term and ). First, IFP_IFC constructs a network, whose nodes represent the different functional categories, and its edges the interrelationships between the nodes. Then, it determines the functions of by employing random walks with restarts on the mentioned network. The walker is the vector of . Finally, is assigned to the functional categories of the nodes in the network that are visited most by the walker. We evaluated the quality of IFP_IFC by comparing it experimentally with two other systems. Results showed marked improvement.