B-physics anomalies: a guide to combined explanations

NASA Astrophysics Data System (ADS)

Buttazzo, Dario; Greljo, Admir; Isidori, Gino; Marzocca, David

2017-11-01

Motivated by additional experimental hints of Lepton Flavour Universality violation in B decays, both in charged- and in neutral-current processes, we analyse the ingredients necessary to provide a combined description of these phenomena. By means of an Effective Field Theory (EFT) approach, based on the hypothesis of New Physics coupled predominantly to the third generation of left-handed quarks and leptons, we show how this is possible. We demonstrate, in particular, how to solve the problems posed by electroweak precision tests and direct searches with a rather natural choice of model parameters, within the context of a U(2) q ×U(2)ℓ flavour symmetry. We further exemplify the general EFT findings by means of simplified models with explicit mediators in the TeV range: coloured scalar or vector leptoquarks and colour-less vectors. Among these, the case of an SU(2) L -singlet vector leptoquark emerges as a particularly simple and successful framework.

An accelerated training method for back propagation networks

NASA Technical Reports Server (NTRS)

Shelton, Robert O. (Inventor)

1993-01-01

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

The possibilities of improvement in the sensitivity of cancer fluorescence diagnostics by computer image processing

NASA Astrophysics Data System (ADS)

Ledwon, Aleksandra; Bieda, Robert; Kawczyk-Krupka, Aleksandra; Polanski, Andrzej; Wojciechowski, Konrad; Latos, Wojciech; Sieron-Stoltny, Karolina; Sieron, Aleksander

2008-02-01

Background: Fluorescence diagnostics uses the ability of tissues to fluoresce after exposition to a specific wavelength of light. The change in fluorescence between normal and progression to cancer allows to see early cancer and precancerous lesions often missed by white light. Aim: To improve by computer image processing the sensitivity of fluorescence images obtained during examination of skin, oral cavity, vulva and cervix lesions, during endoscopy, cystoscopy and bronchoscopy using Xillix ONCOLIFE. Methods: Function of image f(x,y):R2 --> R 3 was transformed from original color space RGB to space in which vector of 46 values refers to every point labeled by defined xy-coordinates- f(x,y):R2 --> R 46. By means of Fisher discriminator vector of attributes of concrete point analalyzed in the image was reduced according to two defined classes defined as pathologic areas (foreground) and healthy areas (background). As a result the highest four fisher's coefficients allowing the greatest separation between points of pathologic (foreground) and healthy (background) areas were chosen. In this way new function f(x,y):R2 --> R 4 was created in which point x,y corresponds with vector Y, H, a*, c II. In the second step using Gaussian Mixtures and Expectation-Maximisation appropriate classificator was constructed. This classificator enables determination of probability that the selected pixel of analyzed image is a pathologically changed point (foreground) or healthy one (background). Obtained map of probability distribution was presented by means of pseudocolors. Results: Image processing techniques improve the sensitivity, quality and sharpness of original fluorescence images. Conclusion: Computer image processing enables better visualization of suspected areas examined by means of fluorescence diagnostics.

All That Glisters Is Not Gold: Sampling-Process Uncertainty in Disease-Vector Surveys with False-Negative and False-Positive Detections

PubMed Central

Abad-Franch, Fernando; Valença-Barbosa, Carolina; Sarquis, Otília; Lima, Marli M.

2014-01-01

Background Vector-borne diseases are major public health concerns worldwide. For many of them, vector control is still key to primary prevention, with control actions planned and evaluated using vector occurrence records. Yet vectors can be difficult to detect, and vector occurrence indices will be biased whenever spurious detection/non-detection records arise during surveys. Here, we investigate the process of Chagas disease vector detection, assessing the performance of the surveillance method used in most control programs – active triatomine-bug searches by trained health agents. Methodology/Principal Findings Control agents conducted triplicate vector searches in 414 man-made ecotopes of two rural localities. Ecotope-specific ‘detection histories’ (vectors or their traces detected or not in each individual search) were analyzed using ordinary methods that disregard detection failures and multiple detection-state site-occupancy models that accommodate false-negative and false-positive detections. Mean (±SE) vector-search sensitivity was ∼0.283±0.057. Vector-detection odds increased as bug colonies grew denser, and were lower in houses than in most peridomestic structures, particularly woodpiles. False-positive detections (non-vector fecal streaks misidentified as signs of vector presence) occurred with probability ∼0.011±0.008. The model-averaged estimate of infestation (44.5±6.4%) was ∼2.4–3.9 times higher than naïve indices computed assuming perfect detection after single vector searches (11.4–18.8%); about 106–137 infestation foci went undetected during such standard searches. Conclusions/Significance We illustrate a relatively straightforward approach to addressing vector detection uncertainty under realistic field survey conditions. Standard vector searches had low sensitivity except in certain singular circumstances. Our findings suggest that many infestation foci may go undetected during routine surveys, especially when vector density is low. Undetected foci can cause control failures and induce bias in entomological indices; this may confound disease risk assessment and mislead program managers into flawed decision making. By helping correct bias in naïve indices, the approach we illustrate has potential to critically strengthen vector-borne disease control-surveillance systems. PMID:25233352

Image Coding Based on Address Vector Quantization.

NASA Astrophysics Data System (ADS)

Feng, Yushu

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Affixation in semantic space: Modeling morpheme meanings with compositional distributional semantics.

PubMed

Marelli, Marco; Baroni, Marco

2015-07-01

The present work proposes a computational model of morpheme combination at the meaning level. The model moves from the tenets of distributional semantics, and assumes that word meanings can be effectively represented by vectors recording their co-occurrence with other words in a large text corpus. Given this assumption, affixes are modeled as functions (matrices) mapping stems onto derived forms. Derived-form meanings can be thought of as the result of a combinatorial procedure that transforms the stem vector on the basis of the affix matrix (e.g., the meaning of nameless is obtained by multiplying the vector of name with the matrix of -less). We show that this architecture accounts for the remarkable human capacity of generating new words that denote novel meanings, correctly predicting semantic intuitions about novel derived forms. Moreover, the proposed compositional approach, once paired with a whole-word route, provides a new interpretative framework for semantic transparency, which is here partially explained in terms of ease of the combinatorial procedure and strength of the transformation brought about by the affix. Model-based predictions are in line with the modulation of semantic transparency on explicit intuitions about existing words, response times in lexical decision, and morphological priming. In conclusion, we introduce a computational model to account for morpheme combination at the meaning level. The model is data-driven, theoretically sound, and empirically supported, and it makes predictions that open new research avenues in the domain of semantic processing. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Assessing semantic similarity of texts - Methods and algorithms

NASA Astrophysics Data System (ADS)

Rozeva, Anna; Zerkova, Silvia

2017-12-01

Assessing the semantic similarity of texts is an important part of different text-related applications like educational systems, information retrieval, text summarization, etc. This task is performed by sophisticated analysis, which implements text-mining techniques. Text mining involves several pre-processing steps, which provide for obtaining structured representative model of the documents in a corpus by means of extracting and selecting the features, characterizing their content. Generally the model is vector-based and enables further analysis with knowledge discovery approaches. Algorithms and measures are used for assessing texts at syntactical and semantic level. An important text-mining method and similarity measure is latent semantic analysis (LSA). It provides for reducing the dimensionality of the document vector space and better capturing the text semantics. The mathematical background of LSA for deriving the meaning of the words in a given text by exploring their co-occurrence is examined. The algorithm for obtaining the vector representation of words and their corresponding latent concepts in a reduced multidimensional space as well as similarity calculation are presented.

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

NASA Technical Reports Server (NTRS)

Asbury, Scott C.

1993-01-01

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

RNA Interference in Infectious Tropical Diseases

PubMed Central

Hong, Young S.

2008-01-01

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

Human action classification using procrustes shape theory

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Oceanographic and meteorological research based on the data products of SEASAT

NASA Technical Reports Server (NTRS)

Pierson, W. J. (Principal Investigator)

1983-01-01

De-aliased SEASAT SASS vector winds obtained during the GOASEX (Gulf of Alaska SEASAT Experiment) program were processed to obtain superobservations centered on a one degree by one degree grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. Each grid point of the synoptic field provides the mean synoptic east-west and north-south wind components plus estimates of the standard deviations of these means. These superobservations winds are then processed further to obtain synoptic scale vector winds stress fiels, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations for each grid point value. The resulting fields appear to be consistant over large distances and to agree with, for example, geostationary cloud images obtained concurrently. Their quality is far superior to that of analyses based on conventional data.

Spin polarized phases in strongly interacting matter: Interplay between axial-vector and tensor mean fields

NASA Astrophysics Data System (ADS)

Maruyama, Tomoyuki; Nakano, Eiji; Yanase, Kota; Yoshinaga, Naotaka

2018-06-01

The spontaneous spin polarization of strongly interacting matter due to axial-vector- and tensor-type interactions is studied at zero temperature and high baryon-number densities. We start with the mean-field Lagrangian for the axial-vector and tensor interaction channels and find in the chiral limit that the spin polarization due to the tensor mean field (U ) takes place first as the density increases for sufficiently strong coupling constants, and then the spin polarization due to the axial-vector mean field (A ) emerges in the region of the finite tensor mean field. This can be understood as making the axial-vector mean-field finite requires a broken chiral symmetry somehow, which is achieved by the finite tensor mean field in the present case. It is also found from the symmetry argument that there appear the type I (II) Nambu-Goldstone modes with a linear (quadratic) dispersion in the spin polarized phase with U ≠0 and A =0 (U ≠0 and A ≠0 ), although these two phases exhibit the same symmetry breaking pattern.

Amplitude and dynamics of polarization-plane signaling in the central complex of the locust brain

PubMed Central

Bockhorst, Tobias

2015-01-01

The polarization pattern of skylight provides a compass cue that various insect species use for allocentric orientation. In the desert locust, Schistocerca gregaria, a network of neurons tuned to the electric field vector (E-vector) angle of polarized light is present in the central complex of the brain. Preferred E-vector angles vary along slices of neuropils in a compasslike fashion (polarotopy). We studied how the activity in this polarotopic population is modulated in ways suited to control compass-guided locomotion. To this end, we analyzed tuning profiles using measures of correlation between spike rate and E-vector angle and, furthermore, tested for adaptation to stationary angles. The results suggest that the polarotopy is stabilized by antagonistic integration across neurons with opponent tuning. Downstream to the input stage of the network, responses to stationary E-vector angles adapted quickly, which may correlate with a tendency to steer a steady course previously observed in tethered flying locusts. By contrast, rotating E-vectors corresponding to changes in heading direction under a natural sky elicited nonadapting responses. However, response amplitudes were particularly variable at the output stage, covarying with the level of ongoing activity. Moreover, the responses to rotating E-vector angles depended on the direction of rotation in an anticipatory manner. Our observations support a view of the central complex as a substrate of higher-stage processing that could assign contextual meaning to sensory input for motor control in goal-driven behaviors. Parallels to higher-stage processing of sensory information in vertebrates are discussed. PMID:25609107

Gridded Calibration of Ensemble Wind Vector Forecasts Using Ensemble Model Output Statistics

NASA Astrophysics Data System (ADS)

Lazarus, S. M.; Holman, B. P.; Splitt, M. E.

2017-12-01

A computationally efficient method is developed that performs gridded post processing of ensemble wind vector forecasts. An expansive set of idealized WRF model simulations are generated to provide physically consistent high resolution winds over a coastal domain characterized by an intricate land / water mask. Ensemble model output statistics (EMOS) is used to calibrate the ensemble wind vector forecasts at observation locations. The local EMOS predictive parameters (mean and variance) are then spread throughout the grid utilizing flow-dependent statistical relationships extracted from the downscaled WRF winds. Using data withdrawal and 28 east central Florida stations, the method is applied to one year of 24 h wind forecasts from the Global Ensemble Forecast System (GEFS). Compared to the raw GEFS, the approach improves both the deterministic and probabilistic forecast skill. Analysis of multivariate rank histograms indicate the post processed forecasts are calibrated. Two downscaling case studies are presented, a quiescent easterly flow event and a frontal passage. Strengths and weaknesses of the approach are presented and discussed.

An emergence of coordinated communication in populations of agents.

PubMed

Kvasnicka, V; Pospichal, J

1999-01-01

The purpose of this article is to demonstrate that coordinated communication spontaneously emerges in a population composed of agents that are capable of specific cognitive activities. Internal states of agents are characterized by meaning vectors. Simple neural networks composed of one layer of hidden neurons perform cognitive activities of agents. An elementary communication act consists of the following: (a) two agents are selected, where one of them is declared the speaker and the other the listener; (b) the speaker codes a selected meaning vector onto a sequence of symbols and sends it to the listener as a message; and finally, (c) the listener decodes this message into a meaning vector and adapts his or her neural network such that the differences between speaker and listener meaning vectors are decreased. A Darwinian evolution enlarged by ideas from the Baldwin effect and Dawkins' memes is simulated by a simple version of an evolutionary algorithm without crossover. The agent fitness is determined by success of the mutual pairwise communications. It is demonstrated that agents in the course of evolution gradually do a better job of decoding received messages (they are closer to meaning vectors of speakers) and all agents gradually start to use the same vocabulary for the common communication. Moreover, if agent meaning vectors contain regularities, then these regularities are manifested also in messages created by agent speakers, that is, similar parts of meaning vectors are coded by similar symbol substrings. This observation is considered a manifestation of the emergence of a grammar system in the common coordinated communication.

Modelling virus- and host-limitation in vectored plant disease epidemics.

PubMed

Jeger, M J; van den Bosch, F; Madden, L V

2011-08-01

Models of plant virus epidemics have received less attention than those caused by fungal pathogens. Intuitively, the fact that virus diseases are systemic means that the individual diseased plant can be considered as the population unit which simplifies modelling. However, the fact that a vector is required in the vast majority of cases for virus transmission, means that explicit consideration must be taken of the vector, or, the involvement of the vector in the transmission process must be considered implicitly. In the latter case it is also important that within-plant processes, such as virus multiplication and systemic movement, are taken into account. In this paper we propose an approach based on the linking of transmission at the population level with virus multiplication within plants. The resulting models are parameter-sparse and hence simplistic. However, the range of model outcomes is representative of field observations relating to the apparent limitation of epidemic development in populations of healthy susceptible plants. We propose that epidemic development can be constrained by virus limitation in the early stages of an epidemic when the availability of healthy susceptible hosts is not limiting. There is an inverse relationship between levels of transmission in the population and the mean virus titre/infected plant. In the case of competition between viruses, both virus and host limitation are likely to be important in determining whether one virus can displace another or whether both viruses can co-exist in a plant population. Lotka-Volterra type equations are derived to describe density-dependent competition between two viruses multiplying within plants, embedded within a population level epidemiological model. Explicit expressions determining displacement or co-existence of the viruses are obtained. Unlike the classical Lotka-Volterra competition equations, the co-existence requirement for the competition coefficients to be both less than 1 can be relaxed. Copyright © 2011 Elsevier B.V. All rights reserved.

Construction of siRNA/miRNA expression vectors based on a one-step PCR process

PubMed Central

Xu, Jun; Zeng, Jie Qiong; Wan, Gang; Hu, Gui Bin; Yan, Hong; Ma, Li Xin

2009-01-01

Background RNA interference (RNAi) has become a powerful means for silencing target gene expression in mammalian cells and is envisioned to be useful in therapeutic approaches to human disease. In recent years, high-throughput, genome-wide screening of siRNA/miRNA libraries has emerged as a desirable approach. Current methods for constructing siRNA/miRNA expression vectors require the synthesis of long oligonucleotides, which is costly and suffers from mutation problems. Results Here we report an ingenious method to solve traditional problems associated with construction of siRNA/miRNA expression vectors. We synthesized shorter primers (< 50 nucleotides) to generate a linear expression structure by PCR. The PCR products were directly transformed into chemically competent E. coli and converted to functional vectors in vivo via homologous recombination. The positive clones could be easily screened under UV light. Using this method we successfully constructed over 500 functional siRNA/miRNA expression vectors. Sequencing of the vectors confirmed a high accuracy rate. Conclusion This novel, convenient, low-cost and highly efficient approach may be useful for high-throughput assays of RNAi libraries. PMID:19490634

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

NASA Astrophysics Data System (ADS)

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

2003-07-01

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

Image search engine with selective filtering and feature-element-based classification

NASA Astrophysics Data System (ADS)

Li, Qing; Zhang, Yujin; Dai, Shengyang

2001-12-01

With the growth of Internet and storage capability in recent years, image has become a widespread information format in World Wide Web. However, it has become increasingly harder to search for images of interest, and effective image search engine for the WWW needs to be developed. We propose in this paper a selective filtering process and a novel approach for image classification based on feature element in the image search engine we developed for the WWW. First a selective filtering process is embedded in a general web crawler to filter out the meaningless images with GIF format. Two parameters that can be obtained easily are used in the filtering process. Our classification approach first extract feature elements from images instead of feature vectors. Compared with feature vectors, feature elements can better capture visual meanings of the image according to subjective perception of human beings. Different from traditional image classification method, our classification approach based on feature element doesn't calculate the distance between two vectors in the feature space, while trying to find associations between feature element and class attribute of the image. Experiments are presented to show the efficiency of the proposed approach.

FIVQ algorithm for interference hyper-spectral image compression

NASA Astrophysics Data System (ADS)

Wen, Jia; Ma, Caiwen; Zhao, Junsuo

2014-07-01

Based on the improved vector quantization (IVQ) algorithm [1] which was proposed in 2012, this paper proposes a further improved vector quantization (FIVQ) algorithm for LASIS (Large Aperture Static Imaging Spectrometer) interference hyper-spectral image compression. To get better image quality, IVQ algorithm takes both the mean values and the VQ indices as the encoding rules. Although IVQ algorithm can improve both the bit rate and the image quality, it still can be further improved in order to get much lower bit rate for the LASIS interference pattern with the special optical characteristics based on the pushing and sweeping in LASIS imaging principle. In the proposed algorithm FIVQ, the neighborhood of the encoding blocks of the interference pattern image, which are using the mean value rules, will be checked whether they have the same mean value as the current processing block. Experiments show the proposed algorithm FIVQ can get lower bit rate compared to that of the IVQ algorithm for the LASIS interference hyper-spectral sequences.

Efficient solution of parabolic equations by Krylov approximation methods

NASA Technical Reports Server (NTRS)

Gallopoulos, E.; Saad, Y.

1990-01-01

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

Magnetic field vector and electron density diagnostics from linear polarization measurements in 14 solar prominences

NASA Technical Reports Server (NTRS)

Bommier, V.

1986-01-01

The Hanle effect is the modification of the linear polarization parameters of a spectral line due to the effect of the magnetic field. It has been successfully applied to the magnetic field vector diagnostic in solar prominences. The magnetic field vector is determined by comparing the measured polarization to the polarization computed, taking into account all the polarizing and depolarizing processes in line formation and the depolarizing effect of the magnetic field. The method was applied to simultaneous polarization measurements in the Helium D3 line and in the hydrogen beta line in 14 prominences. Four polarization parameters are measured, which lead to the determination of the three coordinates of the magnetic field vector and the electron density, owing to the sensitivity of the hydrogen beta line to the non-negligible effect of depolarizing collisions with electrons and protons of the medium. A mean value of 1.3 x 10 to the 10th power cu. cm. is derived in 14 prominences.

Force estimation from OCT volumes using 3D CNNs.

PubMed

Gessert, Nils; Beringhoff, Jens; Otte, Christoph; Schlaefer, Alexander

2018-07-01

Estimating the interaction forces of instruments and tissue is of interest, particularly to provide haptic feedback during robot-assisted minimally invasive interventions. Different approaches based on external and integrated force sensors have been proposed. These are hampered by friction, sensor size, and sterilizability. We investigate a novel approach to estimate the force vector directly from optical coherence tomography image volumes. We introduce a novel Siamese 3D CNN architecture. The network takes an undeformed reference volume and a deformed sample volume as an input and outputs the three components of the force vector. We employ a deep residual architecture with bottlenecks for increased efficiency. We compare the Siamese approach to methods using difference volumes and two-dimensional projections. Data were generated using a robotic setup to obtain ground-truth force vectors for silicon tissue phantoms as well as porcine tissue. Our method achieves a mean average error of [Formula: see text] when estimating the force vector. Our novel Siamese 3D CNN architecture outperforms single-path methods that achieve a mean average error of [Formula: see text]. Moreover, the use of volume data leads to significantly higher performance compared to processing only surface information which achieves a mean average error of [Formula: see text]. Based on the tissue dataset, our methods shows good generalization in between different subjects. We propose a novel image-based force estimation method using optical coherence tomography. We illustrate that capturing the deformation of subsurface structures substantially improves force estimation. Our approach can provide accurate force estimates in surgical setups when using intraoperative optical coherence tomography.

Instructional Assessment Strategies for Health and Physical Education

ERIC Educational Resources Information Center

Constantinou, Phoebe

2017-01-01

Assessment is an integral part of the instructional process. It can provide valuable information to both students and teachers. Assessments can be a vector to quality corrective instruction, a second chance for struggling students to demonstrate success, and a means to provide a more complex challenge for advanced students. This article discusses…

Recent Selected Papers of Northwestern Polytechnical University in Two Parts, Part II.

DTIC Science & Technology

1981-08-28

OF CONTENTS Page Dual Properties of Elastic Structures 1 Matrix Analysis of Wings 76 On a Method for the Determination of Plane Stress Fracture...I= Ea]{(x, v,z) j l~i l’m mini The equation above means that the cisplacement function vector determines the strain function vector. (Assumption II...means that the distributed load function vector is determined by the stress function vector. In Section 1, there was an analysis of a three

Classification of tumor based on magnetic resonance (MR) brain images using wavelet energy feature and neuro-fuzzy model

NASA Astrophysics Data System (ADS)

Damayanti, A.; Werdiningsih, I.

2018-03-01

The brain is the organ that coordinates all the activities that occur in our bodies. Small abnormalities in the brain will affect body activity. Tumor of the brain is a mass formed a result of cell growth not normal and unbridled in the brain. MRI is a non-invasive medical test that is useful for doctors in diagnosing and treating medical conditions. The process of classification of brain tumor can provide the right decision and correct treatment and right on the process of treatment of brain tumor. In this study, the classification process performed to determine the type of brain tumor disease, namely Alzheimer’s, Glioma, Carcinoma and normal, using energy coefficient and ANFIS. Process stages in the classification of images of MR brain are the extraction of a feature, reduction of a feature, and process of classification. The result of feature extraction is a vector approximation of each wavelet decomposition level. The feature reduction is a process of reducing the feature by using the energy coefficients of the vector approximation. The feature reduction result for energy coefficient of 100 per feature is 1 x 52 pixels. This vector will be the input on the classification using ANFIS with Fuzzy C-Means and FLVQ clustering process and LM back-propagation. Percentage of success rate of MR brain images recognition using ANFIS-FLVQ, ANFIS, and LM back-propagation was obtained at 100%.

Vector-averaged gravity does not alter acetylcholine receptor single channel properties

NASA Technical Reports Server (NTRS)

Reitstetter, R.; Gruener, R.

1994-01-01

To examine the physiological sensitivity of membrane receptors to altered gravity, we examined the single channel properties of the acetylcholine receptor (AChR), in co-cultures of Xenopus myocytes and neurons, to vector-averaged gravity in the clinostat. This experimental paradigm produces an environment in which, from the cell's perspective, the gravitational vector is "nulled" by continuous averaging. In that respect, the clinostat simulates one aspect of space microgravity where the gravity force is greatly reduced. After clinorotation, the AChR channel mean open-time and conductance were statistically not different from control values but showed a rotation-dependent trend that suggests a process of cellular adaptation to clinorotation. These findings therefore suggest that the ACHR channel function may not be affected in the microgravity of space despite changes in the receptor's cellular organization.

Simplified process for the production of anti-CD19-CAR engineered T cells

PubMed Central

Tumaini, Barbara; Lee, Daniel W.; Lin, Tasha; Castiello, Luciano; Stroncek, David F.; Mackall, Crystal; Wayne, Alan; Sabatino, Marianna

2014-01-01

Background Adoptive Immunotherapy using chimeric antigen receptor (CAR) engineered T cells specific for CD19 has shown promising results for the treatment of B cell lymphomas and leukemia. This therapy involves the transduction of autologous T cells with a viral vector and the subsequent cell expansion. Here, we describe a new, simplified method to produce anti-CD19-CAR T cells. Methods T cells were isolated from peripheral blood mononuclear cell (PBMC) with anti-CD3/anti-CD28 paramagnetic beads. After 2 days, the T cells were added to culture bags pre-treated with RetroNectin and loaded with the retroviral anti-CD19 CAR vector. The cells, beads and vector were incubated for 24 hours and then a second transduction was performed. No spinoculation was used. Cells were then expanded for an additional 9 days. Results The method was validated using 2 PBMC products from a patient with B-CLL and one PBMC product from a healthy subject. The 2 PBMC products from the B-CLL patient contained 11.4% and 12.9% T cells. The manufacture process led to final products highly enriched in T cells with a mean CD3+ cell content of 98%, a mean expansion of 10.6 fold and a mean transduction efficiency of 68%. Similar results were obtained from the PBMCs of the first 4 ALL patients treated at our institution. Discussion We developed a simplified semi-closed system for the initial selection, activation, transduction and expansion of T cells using anti-CD3/anti-CD28 beads and bags, to produce autologous anti-CD19 CAR transduced T cells to support an ongoing clinical trial. PMID:23992830

A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

PubMed

Xie, Hong-Bo; Huang, Hu; Wu, Jianhua; Liu, Lei

2015-02-01

We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable regions in multiclass problems. We propose two fuzzy membership function-based FRVM algorithms to solve such problems, based on experiments conducted on seven healthy subjects and two amputees with six hand motions. Two feature sets, namely, AR model coefficients and room mean square value (AR-RMS), and wavelet transform (WT) features, are extracted from the recorded sEMG signals. Fuzzy support vector machine (FSVM) analysis was also conducted for wide comparison in terms of accuracy, sparsity, training and testing time, as well as the effect of training sample sizes. FRVM yielded comparable classification accuracy with dramatically fewer support vectors in comparison with FSVM. Furthermore, the processing delay of FRVM was much less than that of FSVM, whilst training time of FSVM much faster than FRVM. The results indicate that FRVM classifier trained using sufficient samples can achieve comparable generalization capability as FSVM with significant sparsity in multi-channel sEMG classification, which is more suitable for sEMG-based real-time control applications.

How representative is the 'Representative Value' of refraction provided by the Shin-Nippon NVision-K 5001 autorefractor?

PubMed

Tang, Wing Chun; Tang, Ying Yung; Lam, Carly S Y

2014-01-01

The aim of the study was to evaluate the level of agreement between the 'Representative Value' (RV) of refraction obtained from the Shin-Nippon NVision-K 5001 instrument with values calculated from individual measurement readings using standard algebraic methods. Cycloplegic autorefraction readings for 101 myopic children aged 8-13 years (10.9 ± 1.42 years) were obtained using the Shin-Nippon NVision-K 5001. Ten autorefractor measurements were taken for each eye. The spherical equivalent (SE), sphere (Sph) and cylindrical component (Cyl) power of each eye were calculated, firstly, by averaging the 10 repeated measurements (Mean SE, Mean Sph and Mean Cyl), and secondly, by the vector representation method (Vector SE, Vector Sph and Vector Cyl). These calculated values were then compared with those of RV (RV SE, RV Sph and RV Cyl) provided by the proprietary software of the NVision-K 5001 using one-way analysis of variance (anova). The agreement between the methods was also assessed. The SE of the subjects ranged from -5.37 to -0.62 D (mean ± SD, = -2.89 ± 1.01 D). The Mean SE was in exact agreement with the Vector SE. There were no significant differences between the RV readings and those calculated using non-vectorial or vectorial methods for any of the refractive powers (SE, p = 0.99; Sph, p = 0.93; Cyl, p = 0.24). The (mean ± SD) differences were: RV SE vs Mean SE (and also RV SE vs Vector SE) -0.01 ± 0.06 D; RV Sph vs Mean Sph, -0.01 ± 0.05 D; RV Sph vs Vector Sph, -0.04 ± 0.06 D; RV Cyl vs Mean Cyl, 0.01 ± 0.07 D; RV Cyl vs Vector Cyl, 0.06 ± 0.09 D. Ninety-eight percent of RV reading differed from their non-vectorial or vectorial counterparts by less than 0.25 D. The RV values showed good agreement to the results calculated using conventional methods. Although the formula used to calculate RV by the NVision-K 5001 autorefractor is proprietary, our results provide validation for the use of RV measurements in clinical practice and vision science research. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

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.

There's More to the Multimedia Effect than Meets the Eye: Is Seeing Pictures Believing?

ERIC Educational Resources Information Center

Ögren, Magnus; Nyström, Marcus; Jarodzka, Halszka

2017-01-01

Textbooks in applied mathematics often use graphs to explain the meaning of formulae, even though their benefit is still not fully explored. To test processes underlying this assumed multimedia effect we collected performance scores, eye movements, and think-aloud protocols from students solving problems in vector calculus with and without graphs.…

Vectors, Change of Basis and Matrix Representation: Onto-Semiotic Approach in the Analysis of Creating Meaning

ERIC Educational Resources Information Center

Montiel, Mariana; Wilhelmi, Miguel R.; Vidakovic, Draga; Elstak, Iwan

2012-01-01

In a previous study, the onto-semiotic approach was employed to analyse the mathematical notion of different coordinate systems, as well as some situations and university students' actions related to these coordinate systems in the context of multivariate calculus. This study approaches different coordinate systems through the process of change of…

Next Generation 3D Mixed Mode Fracture Propagation Theory Including HCF-LCF Interaction (Preprint)

DTIC Science & Technology

2010-01-01

vectors. Depending on processing symmetries, the six principal fracture resistance values may not all be unique. If they are all equal, and l m=1...detail, see [26]. Table 1. Inco 718 Crack Kink angle Data Measured Kink Angles Spec No RI RII RIII KI+ KII+ KIII+ Mean Beq Primary Secondary In Phase 1...R. Ingraffea, “Interactive Finite-Element Analyses of Fracture Processes : An Integrated Approach”, Theoretical and Applied Fracture Mechanics, Vol

Evolution of vector magnetic fields and the August 27 1990 X-3 flare

NASA Technical Reports Server (NTRS)

Wang, Haimin

1992-01-01

Vector magnetic fields in an active region of the sun are studied by means of continuous observations of magnetic-field evolution emphasizing magnetic shear build-up. The vector magnetograms are shown to measure magnetic fields correctly based on concurrent observations and a comparison of the transverse field with the H alpha fibril structure. The morphology and velocity pattern are examined, and these data and the shear build-up suggest that the active region's two major footprints are separated by a region with flows, new flux emergence, and several neutral lines. The magnetic shear appears to be caused by the collision and shear motion of two poles of opposite polarities. The transverse field is shown to turn from potential to sheared during the process of flux cancellation, and this effect can be incorporated into existing models of magnetic flux cancellation.

Environmental and social-demographic predictors of the southern house mosquito Culex quinquefasciatus in New Orleans, Louisiana.

PubMed

Moise, Imelda K; Riegel, Claudia; Muturi, Ephantus J

2018-04-17

Understanding the major predictors of disease vectors such as mosquitoes can guide the development of effective and timely strategies for mitigating vector-borne disease outbreaks. This study examined the influence of selected environmental, weather and sociodemographic factors on the spatial and temporal distribution of the southern house mosquito Culex quinquefasciatus Say in New Orleans, Louisiana, USA. Adult mosquitoes were collected over a 4-year period (2006, 2008, 2009 and 2010) using CDC gravid traps. Socio-demographic predictors were obtained from the United States Census Bureau, 2005-2009 American Community Survey and the City of New Orleans Department of Code Enforcement. Linear mixed effects models and ERDAS image processing software were used for statistical analysis and image processing. Only two of the 22 predictors examined were significant predictors of Cx. quinquefasciatus abundance. Mean temperature during the week of mosquito collection was positively associated with Cx. quinquefasciatus abundance while developed high intensity areas were negatively associated with Cx. quinquefasciatus abundance. The findings of this study illustrate the power and utility of integrating biophysical and sociodemographic data using GIS analysis to identify the biophysical and sociodemographic processes that increase the risk of vector mosquito abundance. This knowledge can inform development of accurate predictive models that ensure timely implementation of mosquito control interventions.

The two time vectors of Nachträglichkeit in the development of ego organization: significance of the concept for the symbolization of nameless traumas and anxieties.

PubMed

Dahl, Gerhard

2010-08-01

The author describes Freud 's conception of Nachträglichkeit as an active process that bridges the gap between past affective vicissitudes and the cognitive present by way of meaning. Symbolization is thereby subsequently [nachträglich] conferred on early traumatic events, which thus become susceptible to omnipotent control. The two time vectors of Nachträglichkeit are discussed: the first is a causal process operating in the forward direction of time against the background of a factual reality, while the second is a backward movement that permits an understanding of unconscious scenes and phantasies taking place at primary-process level. This twofold temporal motion was observed and described by Freud early on. However, its significance often remained hidden prior to his study of Moses. It was mostly overlooked in English and French translations, thus giving rise to a one-sided understanding of the concept in the various psychoanalytic cultures, as either deferred action or après-coup. Freud 's Moses study addresses both temporal aspects of Nachträglichkeit, seeking not only to reconstruct a past event on a causal, deterministic basis, but also to understand the subjective truth of that event in the transference along the retrograde time line. The decisive criterion for the conceptual and clinical separation of the two time vectors is the development of ego organization and the capacity for symbolization. The two vectors should not be separated on the factual level, as both aspects of Nachträglichkeit are essential to the understanding of unconscious processes, combining as they do in a relationship of circular complementarity. © 2009 Institute of Psychoanalysis.

Quantum speed limit time in a magnetic resonance

NASA Astrophysics Data System (ADS)

Ivanchenko, E. A.

2017-12-01

A visualization for dynamics of a qudit spin vector in a time-dependent magnetic field is realized by means of mapping a solution for a spin vector on the three-dimensional spherical curve (vector hodograph). The obtained results obviously display the quantum interference of precessional and nutational effects on the spin vector in the magnetic resonance. For any spin the bottom bounds of the quantum speed limit time (QSL) are found. It is shown that the bottom bound goes down when using multilevel spin systems. Under certain conditions the non-nil minimal time, which is necessary to achieve the orthogonal state from the initial one, is attained at spin S = 2. An estimation of the product of two and three standard deviations of the spin components are presented. We discuss the dynamics of the mutual uncertainty, conditional uncertainty and conditional variance in terms of spin standard deviations. The study can find practical applications in the magnetic resonance, 3D visualization of computational data and in designing of optimized information processing devices for quantum computation and communication.

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

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.

Analysis of ground-motion simulation big data

NASA Astrophysics Data System (ADS)

Maeda, T.; Fujiwara, H.

2016-12-01

We developed a parallel distributed processing system which applies a big data analysis to the large-scale ground motion simulation data. The system uses ground-motion index values and earthquake scenario parameters as input. We used peak ground velocity value and velocity response spectra as the ground-motion index. The ground-motion index values are calculated from our simulation data. We used simulated long-period ground motion waveforms at about 80,000 meshes calculated by a three dimensional finite difference method based on 369 earthquake scenarios of a great earthquake in the Nankai Trough. These scenarios were constructed by considering the uncertainty of source model parameters such as source area, rupture starting point, asperity location, rupture velocity, fmax and slip function. We used these parameters as the earthquake scenario parameter. The system firstly carries out the clustering of the earthquake scenario in each mesh by the k-means method. The number of clusters is determined in advance using a hierarchical clustering by the Ward's method. The scenario clustering results are converted to the 1-D feature vector. The dimension of the feature vector is the number of scenario combination. If two scenarios belong to the same cluster the component of the feature vector is 1, and otherwise the component is 0. The feature vector shows a `response' of mesh to the assumed earthquake scenario group. Next, the system performs the clustering of the mesh by k-means method using the feature vector of each mesh previously obtained. Here the number of clusters is arbitrarily given. The clustering of scenarios and meshes are performed by parallel distributed processing with Hadoop and Spark, respectively. In this study, we divided the meshes into 20 clusters. The meshes in each cluster are geometrically concentrated. Thus this system can extract regions, in which the meshes have similar `response', as clusters. For each cluster, it is possible to determine particular scenario parameters which characterize the cluster. In other word, by utilizing this system, we can obtain critical scenario parameters of the ground-motion simulation for each evaluation point objectively. This research was supported by CREST, JST.

Ice Shape Characterization Using Self-Organizing Maps

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Evaluation of laser cutting process with auxiliary gas pressure by soft computing approach

NASA Astrophysics Data System (ADS)

Lazov, Lyubomir; Nikolić, Vlastimir; Jovic, Srdjan; Milovančević, Miloš; Deneva, Heristina; Teirumenieka, Erika; Arsic, Nebojsa

2018-06-01

Evaluation of the optimal laser cutting parameters is very important for the high cut quality. This is highly nonlinear process with different parameters which is the main challenge in the optimization process. Data mining methodology is one of most versatile method which can be used laser cutting process optimization. Support vector regression (SVR) procedure is implemented since it is a versatile and robust technique for very nonlinear data regression. The goal in this study was to determine the optimal laser cutting parameters to ensure robust condition for minimization of average surface roughness. Three cutting parameters, the cutting speed, the laser power, and the assist gas pressure, were used in the investigation. As a laser type TruLaser 1030 technological system was used. Nitrogen as an assisted gas was used in the laser cutting process. As the data mining method, support vector regression procedure was used. Data mining prediction accuracy was very high according the coefficient (R2) of determination and root mean square error (RMSE): R2 = 0.9975 and RMSE = 0.0337. Therefore the data mining approach could be used effectively for determination of the optimal conditions of the laser cutting process.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

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.

A new automated assessment method for contrast-detail images by applying support vector machine and its robustness to nonlinear image processing.

PubMed

Takei, Takaaki; Ikeda, Mitsuru; Imai, Kuniharu; Yamauchi-Kawaura, Chiyo; Kato, Katsuhiko; Isoda, Haruo

2013-09-01

The automated contrast-detail (C-D) analysis methods developed so-far cannot be expected to work well on images processed with nonlinear methods, such as noise reduction methods. Therefore, we have devised a new automated C-D analysis method by applying support vector machine (SVM), and tested for its robustness to nonlinear image processing. We acquired the CDRAD (a commercially available C-D test object) images at a tube voltage of 120 kV and a milliampere-second product (mAs) of 0.5-5.0. A partial diffusion equation based technique was used as noise reduction method. Three radiologists and three university students participated in the observer performance study. The training data for our SVM method was the classification data scored by the one radiologist for the CDRAD images acquired at 1.6 and 3.2 mAs and their noise-reduced images. We also compared the performance of our SVM method with the CDRAD Analyser algorithm. The mean C-D diagrams (that is a plot of the mean of the smallest visible hole diameter vs. hole depth) obtained from our devised SVM method agreed well with the ones averaged across the six human observers for both original and noise-reduced CDRAD images, whereas the mean C-D diagrams from the CDRAD Analyser algorithm disagreed with the ones from the human observers for both original and noise-reduced CDRAD images. In conclusion, our proposed SVM method for C-D analysis will work well for the images processed with the non-linear noise reduction method as well as for the original radiographic images.

Relevant microclimate for determining the development rate of malaria mosquitoes and possible implications of climate change.

PubMed

Paaijmans, Krijn P; Imbahale, Susan S; Thomas, Matthew B; Takken, Willem

2010-07-09

The relationship between mosquito development and temperature is one of the keys to understanding the current and future dynamics and distribution of vector-borne diseases such as malaria. Many process-based models use mean air temperature to estimate larval development times, and hence adult vector densities and/or malaria risk. Water temperatures in three different-sized water pools, as well as the adjacent air temperature in lowland and highland sites in western Kenya were monitored. Both air and water temperatures were fed into a widely-applied temperature-dependent development model for Anopheles gambiae immatures, and subsequently their impact on predicted vector abundance was assessed. Mean water temperature in typical mosquito breeding sites was 4-6 degrees C higher than the mean temperature of the adjacent air, resulting in larval development rates, and hence population growth rates, that are much higher than predicted based on air temperature. On the other hand, due to the non-linearities in the relationship between temperature and larval development rate, together with a marginal buffering in the increase in water temperature compared with air temperature, the relative increases in larval development rates predicted due to climate change are substantially less. Existing models will tend to underestimate mosquito population growth under current conditions, and may overestimate relative increases in population growth under future climate change. These results highlight the need for better integration of biological and environmental information at the scale relevant to mosquito biology.

Spiking Neural P Systems With Rules on Synapses Working in Maximum Spiking Strategy.

PubMed

Tao Song; Linqiang Pan

2015-06-01

Spiking neural P systems (called SN P systems for short) are a class of parallel and distributed neural-like computation models inspired by the way the neurons process information and communicate with each other by means of impulses or spikes. In this work, we introduce a new variant of SN P systems, called SN P systems with rules on synapses working in maximum spiking strategy, and investigate the computation power of the systems as both number and vector generators. Specifically, we prove that i) if no limit is imposed on the number of spikes in any neuron during any computation, such systems can generate the sets of Turing computable natural numbers and the sets of vectors of positive integers computed by k-output register machine; ii) if an upper bound is imposed on the number of spikes in each neuron during any computation, such systems can characterize semi-linear sets of natural numbers as number generating devices; as vector generating devices, such systems can only characterize the family of sets of vectors computed by sequential monotonic counter machine, which is strictly included in family of semi-linear sets of vectors. This gives a positive answer to the problem formulated in Song et al., Theor. Comput. Sci., vol. 529, pp. 82-95, 2014.

Selection of optimum median-filter-based ambiguity removal algorithm parameters for NSCAT. [NASA scatterometer

NASA Technical Reports Server (NTRS)

Shaffer, Scott; Dunbar, R. Scott; Hsiao, S. Vincent; Long, David G.

1989-01-01

The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.

Viral Vectors for Use in the Development of Biodefense Vaccines

DTIC Science & Technology

2005-06-17

vaccinia virus, and Venezuelan equine encephalitis virus, as vaccine vectors has enabled researchers to develop effective means for countering the...biowarfare. The use of viruses, for example adenovirus, vaccinia virus, and Venezuelan equine encephalitis virus, as vaccine -vectors has enabled researchers to... vaccines . . . . . . . . . . . . . . . . . . . 1298 2.1.3. Vaccinia virus-vectored Venezuelan equine encephalitis vaccines

Process for computing geometric perturbations for probabilistic analysis

DOEpatents

Fitch, Simeon H. K. [Charlottesville, VA; Riha, David S [San Antonio, TX; Thacker, Ben H [San Antonio, TX

2012-04-10

A method for computing geometric perturbations for probabilistic analysis. The probabilistic analysis is based on finite element modeling, in which uncertainties in the modeled system are represented by changes in the nominal geometry of the model, referred to as "perturbations". These changes are accomplished using displacement vectors, which are computed for each node of a region of interest and are based on mean-value coordinate calculations.

Coffee, its roasted form, and their residues cause birth failure and shorten lifespan in dengue vectors.

PubMed

Dieng, Hamady; Ellias, Salbiah Binti; Satho, Tomomitsu; Ahmad, Abu Hassan; Abang, Fatimah; Ghani, Idris Abd; Noor, Sabina; Ahmad, Hamdan; Zuharah, Wan Fatma; Morales Vargas, Ronald E; Morales, Noppawan P; Hipolito, Cirilo N; Attrapadung, Siriluck; Noweg, Gabriel Tonga

2017-06-01

In dengue mosquitoes, successful embryonic development and long lifespan are key determinants for the persistence of both virus and vector. Therefore, targeting the egg stage and vector lifespan would be expected to have greater impacts than larvicides or adulticides, both strategies that have lost effectiveness due to the development of resistance. Therefore, there is now a pressing need to find novel chemical means of vector control. Coffee contains many chemicals, and its waste, which has become a growing environmental concern, is as rich in toxicants as the green coffee beans; these chemicals do not have a history of resistance in insects, but some are lost in the roasting process. We examined whether exposure to coffee during embryonic development could alter larval eclosion and lifespan of dengue vectors. A series of bioassays with different coffee forms and their residues indicated that larval eclosion responses of Aedes albopictus and Ae. aegypti were appreciably lower when embryonic maturation occurred in environments containing coffee, especially roasted coffee crude extract (RCC). In addition, the lifespan of adults derived from eggs that hatched successfully in a coffee milieu was reduced, but this effect was less pronounced with roasted and green coffee extracts (RCU and GCU, respectively). Taken together, these findings suggested that coffee and its residues have embryocidal activities with impacts that are carried over onto the adult lifespan of dengue vectors. These effects may significantly reduce the vectorial capacity of these insects. Reutilizing coffee waste in vector control may also represent a realistic solution to the issues associated with its pollution.

Multipole Vector Anomalies in the First-Year WMAP Data: A Cut-Sky Analysis

NASA Astrophysics Data System (ADS)

Bielewicz, P.; Eriksen, H. K.; Banday, A. J.; Górski, K. M.; Lilje, P. B.

2005-12-01

We apply the recently defined multipole vector framework to the frequency-specific first-year WMAP sky maps, estimating the low-l multipole coefficients from the high-latitude sky by means of a power equalization filter. While most previous analyses of this type have considered only heavily processed (and foreground-contaminated) full-sky maps, the present approach allows for greater control of residual foregrounds and therefore potentially also for cosmologically important conclusions. The low-l spherical harmonic coefficients and corresponding multipole vectors are tabulated for easy reference. Using this formalism, we reassess a set of earlier claims of both cosmological and noncosmological low-l correlations on the basis of multipole vectors. First, we show that the apparent l=3 and 8 correlation claimed by Copi and coworkers is present only in the heavily processed map produced by Tegmark and coworkers and must therefore be considered an artifact of that map. Second, the well-known quadrupole-octopole correlation is confirmed at the 99% significance level and shown to be robust with respect to frequency and sky cut. Previous claims are thus supported by our analysis. Finally, the low-l alignment with respect to the ecliptic claimed by Schwarz and coworkers is nominally confirmed in this analysis, but also shown to be very dependent on severe a posteriori choices. Indeed, we show that given the peculiar quadrupole-octopole arrangement, finding such a strong alignment with the ecliptic is not unusual.

A simple method to generate stable cell lines for the analysis of transient protein-protein interactions.

PubMed

Savage, Emilia Elizabeth; Wootten, Denise; Christopoulos, Arthur; Sexton, Patrick Michael; Furness, Sebastian George Barton

2013-04-01

Transient protein-protein interactions form the basis of signal transduction pathways in addition to many other biological processes. One tool for studying these interactions is bioluminescence resonance energy transfer (BRET). This technique has been widely applied to study signaling pathways, in particular those initiated by G protein-coupled receptors (GPCRs). These assays are routinely performed using transient transfection, a technique that has limitations in terms of assay cost and variability, overexpression of interacting proteins, vector uptake limited to cycling cells, and non-homogenous expression across cells within the assay. To address these issues, we developed bicistronic vectors for use with Life Technology's Gateway and flpIN systems. These vectors provide a means to generate isogenic cell lines for comparison of interacting proteins. They have the advantage of stable, single copy, isogenic, homogeneous expression with low inter-assay variation. We demonstrate their utility by assessing ligand-induced interactions between GPCRs and arrestin proteins.

Method for network analyzation and apparatus

DOEpatents

Bracht, Roger B.; Pasquale, Regina V.

2001-01-01

A portable network analyzer and method having multiple channel transmit and receive capability for real-time monitoring of processes which maintains phase integrity, requires low power, is adapted to provide full vector analysis, provides output frequencies of up to 62.5 MHz and provides fine sensitivity frequency resolution. The present invention includes a multi-channel means for transmitting and a multi-channel means for receiving, both in electrical communication with a software means for controlling. The means for controlling is programmed to provide a signal to a system under investigation which steps consecutively over a range of predetermined frequencies. The resulting received signal from the system provides complete time domain response information by executing a frequency transform of the magnitude and phase information acquired at each frequency step.

Mean-square state and parameter estimation for stochastic linear systems with Gaussian and Poisson noises

NASA Astrophysics Data System (ADS)

Basin, M.; Maldonado, J. J.; Zendejo, O.

2016-07-01

This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.

Method and apparatus for optimized processing of sparse matrices

DOEpatents

Taylor, Valerie E.

1993-01-01

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

A unified development of several techniques for the representation of random vectors and data sets

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1973-01-01

Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.

Optical simulation of a Popescu-Rohrlich Box

PubMed Central

Chu, Wen-Jing; Zong, Xiao-Lan; Yang, Ming; Pan, Guo-Zhu; Cao, Zhuo-Liang

2016-01-01

It is well known that the fair-sampling loophole in Bell test opened by the selection of the state to be measured can lead to post-quantum correlations. In this paper, we make the selection of the results after measurement, which opens the fair- sampling loophole too, and thus can lead to post-quantum correlations. This kind of result-selection loophole can be realized by pre- and post-selection processes within the “two-state vector formalism”, and a physical simulation of Popescu-Rohrlich (PR) box is designed in linear optical system. The probability distribution of the PR has a maximal CHSH value 4, i.e. it can maximally violate CHSH inequality. Because the “two-state vector formalism” violates the information causality, it opens the locality loophole too, which means that this kind of results selection within “two-state vector formalism” leads to both fair- sampling loophole and locality loophole, so we call it a comprehensive loophole in Bell test. The comprehensive loophole opened by the results selection within “two-state vector formalism” may be another possible explanation of why post-quantum correlations are incompatible with quantum mechanics and seem not to exist in nature. PMID:27329203

Optical simulation of a Popescu-Rohrlich Box.

PubMed

Chu, Wen-Jing; Zong, Xiao-Lan; Yang, Ming; Pan, Guo-Zhu; Cao, Zhuo-Liang

2016-06-22

It is well known that the fair-sampling loophole in Bell test opened by the selection of the state to be measured can lead to post-quantum correlations. In this paper, we make the selection of the results after measurement, which opens the fair- sampling loophole too, and thus can lead to post-quantum correlations. This kind of result-selection loophole can be realized by pre- and post-selection processes within the "two-state vector formalism", and a physical simulation of Popescu-Rohrlich (PR) box is designed in linear optical system. The probability distribution of the PR has a maximal CHSH value 4, i.e. it can maximally violate CHSH inequality. Because the "two-state vector formalism" violates the information causality, it opens the locality loophole too, which means that this kind of results selection within "two-state vector formalism" leads to both fair- sampling loophole and locality loophole, so we call it a comprehensive loophole in Bell test. The comprehensive loophole opened by the results selection within "two-state vector formalism" may be another possible explanation of why post-quantum correlations are incompatible with quantum mechanics and seem not to exist in nature.

Frozen orbit realization using LQR analogy

NASA Astrophysics Data System (ADS)

Nagarajan, N.; Rayan, H. Reno

In the case of remote sensing orbits, the Frozen Orbit concept minimizes altitude variations over a given region using passive means. This is achieved by establishing the mean eccentricity vector at the orbital poles i.e., by fixing the mean argument of perigee at 90 deg with an appropriate eccentricity to balance the perturbations due to zonal harmonics J2 and J3 of the Earth's potential. Eccentricity vector is a vector whose magnitude is the eccentricity and direction is the argument of perigee. The launcher dispersions result in an eccentricity vector which is away from the frozen orbit values. The objective is then to formulate an orbit maneuver strategy to optimize the fuel required to achieve the frozen orbit in the presence of visibility and impulse constraints. It is shown that the motion of the eccentricity vector around the frozen perigee can be approximated as a circle. Combining the circular motion of the eccentricity vector around the frozen point and the maneuver equation, the following discrete equation is obtained. X(k+1) = AX(k) + Bu(k), where X is the state (i.e. eccentricity vector components), A the state transition matrix, u the scalar control force (i.e. dV in this case) and B the control matrix which transforms dV into eccentricity vector change. Based on this, it is shown that the problem of optimizing the fuel can be treated as a Linear Quadratic Regulator (LQR) problem in which the maneuver can be solved by using control system design tools like MATLAB by deriving an analogy LQR design.

An Alternative Method for Computing Mean and Covariance Matrix of Some Multivariate Distributions

ERIC Educational Resources Information Center

Radhakrishnan, R.; Choudhury, Askar

2009-01-01

Computing the mean and covariance matrix of some multivariate distributions, in particular, multivariate normal distribution and Wishart distribution are considered in this article. It involves a matrix transformation of the normal random vector into a random vector whose components are independent normal random variables, and then integrating…

Pu239 Cross-Section Variations Based on Experimental Uncertainties and Covariances

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

Sigeti, David Edward; Williams, Brian J.; Parsons, D. Kent

2016-10-18

Algorithms and software have been developed for producing variations in plutonium-239 neutron cross sections based on experimental uncertainties and covariances. The varied cross-section sets may be produced as random samples from the multi-variate normal distribution defined by an experimental mean vector and covariance matrix, or they may be produced as Latin-Hypercube/Orthogonal-Array samples (based on the same means and covariances) for use in parametrized studies. The variations obey two classes of constraints that are obligatory for cross-section sets and which put related constraints on the mean vector and covariance matrix that detemine the sampling. Because the experimental means and covariances domore » not obey some of these constraints to sufficient precision, imposing the constraints requires modifying the experimental mean vector and covariance matrix. Modification is done with an algorithm based on linear algebra that minimizes changes to the means and covariances while insuring that the operations that impose the different constraints do not conflict with each other.« less

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

PubMed

Gu, Rui; Xu, Jinglei

2014-01-01

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

Passing in Command Line Arguments and Parallel Cluster/Multicore Batching in R with batch.

PubMed

Hoffmann, Thomas J

2011-03-01

It is often useful to rerun a command line R script with some slight change in the parameters used to run it - a new set of parameters for a simulation, a different dataset to process, etc. The R package batch provides a means to pass in multiple command line options, including vectors of values in the usual R format, easily into R. The same script can be setup to run things in parallel via different command line arguments. The R package batch also provides a means to simplify this parallel batching by allowing one to use R and an R-like syntax for arguments to spread a script across a cluster or local multicore/multiprocessor computer, with automated syntax for several popular cluster types. Finally it provides a means to aggregate the results together of multiple processes run on a cluster.

Syngeneic AAV pseudo-vectors potentiates full vector transduction

USDA-ARS?s Scientific Manuscript database

An excessive amount of empty capsids are generated during regular AAV vector production process. These pseudo-vectors often remain in final vectors used for animal studies or clinical trials. The potential effects of these pseudo-vectors on AAV transduction have been a major concern. In the current ...

Synoptic scale wind field properties from the SEASAT SASS

NASA Technical Reports Server (NTRS)

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

1984-01-01

Dealiased SEASAT SEASAT A Scatterometer System SASS vector winds obtained during the Gulf Of Alaska SEASAT Experiment GOASEX program are processed to obtain superobservations centered on a one degree by one degree grid. The grid. The results provide values for the combined effects of mesoscale variability and communication noise on the individual SASS winds. These superobservations winds are then processed further to obtain estimates of synoptic scale vector winds stress fields, the horizontal divergence of the wind, the curl of the wind stress and the vertical velocity at 200 m above the sea surface, each with appropriate standard deviations of the estimates for each grid point value. They also explain the concentration of water vapor, liquid water and precipitation found by means of the SMMR Scanning Multichannel Microwave Radiometer at fronts and occlusions in terms of strong warm, moist air advection in the warm air sector accompanied by convergence in the friction layer. Their quality is far superior to that of analyses based on conventional data, which are shown to yield many inconsistencies.

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

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

USGS Publications Warehouse

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

1991-01-01

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

Limitations to mapping habitat-use areas in changing landscapes using the Mahalanobis distance statistic

USGS Publications Warehouse

Knick, Steven T.; Rotenberry, J.T.

1998-01-01

We tested the potential of a GIS mapping technique, using a resource selection model developed for black-tailed jackrabbits (Lepus californicus) and based on the Mahalanobis distance statistic, to track changes in shrubsteppe habitats in southwestern Idaho. If successful, the technique could be used to predict animal use areas, or those undergoing change, in different regions from the same selection function and variables without additional sampling. We determined the multivariate mean vector of 7 GIS variables that described habitats used by jackrabbits. We then ranked the similarity of all cells in the GIS coverage from their Mahalanobis distance to the mean habitat vector. The resulting map accurately depicted areas where we sighted jackrabbits on verification surveys. We then simulated an increase in shrublands (which are important habitats). Contrary to expectation, the new configurations were classified as lower similarity relative to the original mean habitat vector. Because the selection function is based on a unimodal mean, any deviation, even if biologically positive, creates larger Malanobis distances and lower similarity values. We recommend the Mahalanobis distance technique for mapping animal use areas when animals are distributed optimally, the landscape is well-sampled to determine the mean habitat vector, and distributions of the habitat variables does not change.

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing

PubMed Central

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery. PMID:27711246

Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

PubMed

Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

2016-01-01

Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

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

PubMed

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

2015-07-01

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

Environmental suitability for Lutzomyia (Nyssomyia) whitmani (Diptera: Psychodidae: Phlebotominae) and the occurrence of American cutaneous leishmaniasis in Brazil.

PubMed

da Costa, Simone Miranda; Cordeiro, José Luís Passos; Rangel, Elizabeth Ferreira

2018-03-07

Leishmaniasis represents an important public health problem in Brazil. The continuous process of urbanization and expansion of human activities in forest areas impacts natural habitats, modifying the ecology of some species of Leishmania, as well as its vectors and reservoirs and, consequently, changes the epidemiological pattern that contributes to the expansion of American cutaneous leishmaniasis in Brazil. Here, we discuss Lutzomyia (Nyssomyia) whitmani, the main vector of ACL, transmitting two dermotropic Leishmania species including Leishmania (Viannia) braziliensis and Leishmania (V.) shawi. We used the maximum entropy niche modelling approach (MaxEnt) to evaluate the environmental suitability of L. (N.) whitmani and the transmission of ACL in Brazil, in addition to designing models for a future scenario of climate change. MaxEnt was used under the "auto-features" mode and the default settings, with 100-fold repetition (bootstrap). The logistic output was used with higher values in the habitat suitability map, representing more favourable conditions for the occurrence of L. (N.) whitmani and human cases of ACL. Two models were developed: the Lutzomyia (N.) whitmani model (LWM) and the American cutaneous leishmaniasis model (ACLM). LWM identified the species "preferential habitat" included regions with moderate annual precipitation (AP) between 1000-1600 mm, intermediate vegetation density (NDVI) values, mean temperature of the coldest quarter (MTCQ), between 15-21 °C, and annual mean temperature (AMT), between 19-24 °C. ACLM indicates that ACL is strongly associated with areas of intermediate density vegetation, areas with AP between 800-1200 mm, MTCQ above 16 °C and AMT below 23 °C. The models generated for L. (N.) whitmani and ACL indicated a satisfactory predictive capacity. Future projections of LWM indicate an expansion of climatic suitability for L. (N.) whitmani for the northern and southern regions of Brazil. Future projections of ACL indicate the ongoing process of disease expansion in the face of the predicted climatic changes and reinforce the broad geographical expanse of this disease in Brazil. The models were able to identify that a continuous process of environmental degradation favours the establishment of L. (N.) whitmani and the occurrence of ACL by a strong association of the vector(s) and ACL to areas of intermediate vegetation cover density.

A manufacturing error measurement methodology for a rotary vector reducer cycloidal gear based on a gear measuring center

NASA Astrophysics Data System (ADS)

Li, Tianxing; Zhou, Junxiang; Deng, Xiaozhong; Li, Jubo; Xing, Chunrong; Su, Jianxin; Wang, Huiliang

2018-07-01

A manufacturing error of a cycloidal gear is the key factor affecting the transmission accuracy of a robot rotary vector (RV) reducer. A methodology is proposed to realize the digitized measurement and data processing of the cycloidal gear manufacturing error based on the gear measuring center, which can quickly and accurately measure and evaluate the manufacturing error of the cycloidal gear by using both the whole tooth profile measurement and a single tooth profile measurement. By analyzing the particularity of the cycloidal profile and its effect on the actual meshing characteristics of the RV transmission, the cycloid profile measurement strategy is planned, and the theoretical profile model and error measurement model of cycloid-pin gear transmission are established. Through the digital processing technology, the theoretical trajectory of the probe and the normal vector of the measured point are calculated. By means of precision measurement principle and error compensation theory, a mathematical model for the accurate calculation and data processing of manufacturing error is constructed, and the actual manufacturing error of the cycloidal gear is obtained by the optimization iterative solution. Finally, the measurement experiment of the cycloidal gear tooth profile is carried out on the gear measuring center and the HEXAGON coordinate measuring machine, respectively. The measurement results verify the correctness and validity of the measurement theory and method. This methodology will provide the basis for the accurate evaluation and the effective control of manufacturing precision of the cycloidal gear in a robot RV reducer.

Vectors in Use in a 3D Juggling Game Simulation

ERIC Educational Resources Information Center

Kynigos, Chronis; Latsi, Maria

2006-01-01

The new representations enabled by the educational computer game the "Juggler" can place vectors in a central role both for controlling and measuring the behaviours of objects in a virtual environment simulating motion in three-dimensional spaces. The mathematical meanings constructed by 13 year-old students in relation to vectors as…

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

USDA-ARS?s Scientific Manuscript database

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

Movements of the First Satellite-Tagged Cuvier’s and Blainville’s Beaked Whales in Hawaii

DTIC Science & Technology

2008-10-06

satellite tagging 6 Data acquisition and processing PTT transmissions are received by a series of NOAA Polar Orbiting Environmental Satellites... polar orbiting path of the satellites means that there are fewer overpasses as you get closer to the equator. In Hawai‘i in 2008 for example, the...between consecutive locations, and rate and bearings among consecutive movement vectors). The Douglas filter incorporates several user-defined variables

A Fixed-Pattern Noise Correction Method Based on Gray Value Compensation for TDI CMOS Image Sensor.

PubMed

Liu, Zhenwang; Xu, Jiangtao; Wang, Xinlei; Nie, Kaiming; Jin, Weimin

2015-09-16

In order to eliminate the fixed-pattern noise (FPN) in the output image of time-delay-integration CMOS image sensor (TDI-CIS), a FPN correction method based on gray value compensation is proposed. One hundred images are first captured under uniform illumination. Then, row FPN (RFPN) and column FPN (CFPN) are estimated based on the row-mean vector and column-mean vector of all collected images, respectively. Finally, RFPN are corrected by adding the estimated RFPN gray value to the original gray values of pixels in the corresponding row, and CFPN are corrected by subtracting the estimated CFPN gray value from the original gray values of pixels in the corresponding column. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination with the proposed method, the standard-deviation of row-mean vector decreases from 5.6798 to 0.4214 LSB, and the standard-deviation of column-mean vector decreases from 15.2080 to 13.4623 LSB. Both kinds of FPN in the real images captured by TDI-CIS are eliminated effectively with the proposed method.

Non-viral gene delivery strategies for gene therapy: a "ménage à trois" among nucleic acids, materials, and the biological environment. Stimuli-responsive gene delivery vectors

NASA Astrophysics Data System (ADS)

Pezzoli, Daniele; Candiani, Gabriele

2013-03-01

Gene delivery is the science of transferring genetic material into cells by means of a vector to alter cellular function or structure at a molecular level. In this context, a number of nucleic acid-based drugs have been proposed and experimented so far and, as they act on distinct steps along the gene transcription-translation pathway, specific delivery strategies are required to elicit the desired outcome. Cationic lipids and polymers, collectively known as non-viral delivery systems, have thus made their breakthrough in basic and medical research. Albeit they are promising alternatives to viral vectors, their therapeutic application is still rather limited as high transfection efficiencies are normally associated to adverse cytotoxic side effects. In this scenario, drawing inspiration from processes naturally occurring in vivo, major strides forward have been made in the development of more effective materials for gene delivery applications. Specifically, smart vectors sensitive to a variety of physiological stimuli such as cell enzymes, redox status, and pH are substantially changing the landscape of gene delivery by helping to overcome some of the systemic and intracellular barriers that viral vectors naturally evade. Herein, after summarizing the state-of-the-art information regarding the use of nucleic acids as drugs, we review the main bottlenecks still limiting the overall effectiveness of non-viral gene delivery systems. Finally, we provide a critical outline of emerging stimuli-responsive strategies and discuss challenges still existing on the road toward conceiving more efficient and safer multifunctional vectors.

A vector scanning processing technique for pulsed laser velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1989-01-01

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

Autonomous Environment-Monitoring Networks

NASA Technical Reports Server (NTRS)

Hand, Charles

2004-01-01

Autonomous environment-monitoring networks (AEMNs) are artificial neural networks that are specialized for recognizing familiarity and, conversely, novelty. Like a biological neural network, an AEMN receives a constant stream of inputs. For purposes of computational implementation, the inputs are vector representations of the information of interest. As long as the most recent input vector is similar to the previous input vectors, no action is taken. Action is taken only when a novel vector is encountered. Whether a given input vector is regarded as novel depends on the previous vectors; hence, the same input vector could be regarded as familiar or novel, depending on the context of previous input vectors. AEMNs have been proposed as means to enable exploratory robots on remote planets to recognize novel features that could merit closer scientific attention. AEMNs could also be useful for processing data from medical instrumentation for automated monitoring or diagnosis. The primary substructure of an AEMN is called a spindle. In its simplest form, a spindle consists of a central vector (C), a scalar (r), and algorithms for changing C and r. The vector C is constructed from all the vectors in a given continuous stream of inputs, such that it is minimally distant from those vectors. The scalar r is the distance between C and the most remote vector in the same set. The construction of a spindle involves four vital parameters: setup size, spindle-population size, and the radii of two novelty boundaries. The setup size is the number of vectors that are taken into account before computing C. The spindle-population size is the total number of input vectors used in constructing the spindle counting both those that arrive before and those that arrive after the computation of C. The novelty-boundary radii are distances from C that partition the neighborhood around C into three concentric regions (see Figure 1). During construction of the spindle, the changing spindle radius is denoted by h. It is the final value of h, reached before beginning construction on the next spindle, that is denoted by r. During construction of a spindle, if a new vector falls between C and the inner boundary, the vector is regarded as completely familiar and no action is taken. If the new vector falls into the region between the inner and outer boundaries, it is considered unusual enough to warrant the adjustment of C and r by use of the aforementioned algorithms, but not unusual enough to be considered novel. If a vector falls outside the outer boundary, it is considered novel, in which case one of several appropriate responses could be initiation of construction of a new spindle.

Approach to fitting parameters and clustering for characterising measured voltage dips based on two-dimensional polarisation ellipses

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

García-Sánchez, Tania; Gómez-Lázaro, Emilio; Muljadi, E.

An alternative approach to characterise real voltage dips is proposed and evaluated in this study. The proposed methodology is based on voltage-space vector solutions, identifying parameters for ellipses trajectories by using the least-squares algorithm applied on a sliding window along the disturbance. The most likely patterns are then estimated through a clustering process based on the k-means algorithm. The objective is to offer an efficient and easily implemented alternative to characterise faults and visualise the most likely instantaneous phase-voltage evolution during events through their corresponding voltage-space vector trajectories. This novel solution minimises the data to be stored but maintains extensivemore » information about the dips including starting and ending transients. The proposed methodology has been applied satisfactorily to real voltage dips obtained from intensive field-measurement campaigns carried out in a Spanish wind power plant up to a time period of several years. A comparison to traditional minimum root mean square-voltage and time-duration classifications is also included in this study.« less

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

EPA Science Inventory

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

Critical Analysis of the Mathematical Formalism of Theoretical Physics. II. Foundations of Vector Calculus

NASA Astrophysics Data System (ADS)

Kalanov, Temur Z.

2014-03-01

A critical analysis of the foundations of standard vector calculus is proposed. The methodological basis of the analysis is the unity of formal logic and of rational dialectics. It is proved that the vector calculus is incorrect theory because: (a) it is not based on a correct methodological basis - the unity of formal logic and of rational dialectics; (b) it does not contain the correct definitions of ``movement,'' ``direction'' and ``vector'' (c) it does not take into consideration the dimensions of physical quantities (i.e., number names, denominate numbers, concrete numbers), characterizing the concept of ''physical vector,'' and, therefore, it has no natural-scientific meaning; (d) operations on ``physical vectors'' and the vector calculus propositions relating to the ''physical vectors'' are contrary to formal logic.

Features extraction in anterior and posterior cruciate ligaments analysis.

PubMed

Zarychta, P

2015-12-01

The main aim of this research is finding the feature vectors of the anterior and posterior cruciate ligaments (ACL and PCL). These feature vectors have to clearly define the ligaments structure and make it easier to diagnose them. Extraction of feature vectors is obtained by analysis of both anterior and posterior cruciate ligaments. This procedure is performed after the extraction process of both ligaments. In the first stage in order to reduce the area of analysis a region of interest including cruciate ligaments (CL) is outlined in order to reduce the area of analysis. In this case, the fuzzy C-means algorithm with median modification helping to reduce blurred edges has been implemented. After finding the region of interest (ROI), the fuzzy connectedness procedure is performed. This procedure permits to extract the anterior and posterior cruciate ligament structures. In the last stage, on the basis of the extracted anterior and posterior cruciate ligament structures, 3-dimensional models of the anterior and posterior cruciate ligament are built and the feature vectors created. This methodology has been implemented in MATLAB and tested on clinical T1-weighted magnetic resonance imaging (MRI) slices of the knee joint. The 3D display is based on the Visualization Toolkit (VTK). Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating normal mixture parameters from the distribution of a reduced feature vector

NASA Technical Reports Server (NTRS)

Guseman, L. F.; Peters, B. C., Jr.; Swasdee, M.

1976-01-01

A FORTRAN computer program was written and tested. The measurements consisted of 1000 randomly chosen vectors representing 1, 2, 3, 7, and 10 subclasses in equal portions. In the first experiment, the vectors are computed from the input means and covariances. In the second experiment, the vectors are 16 channel measurements. The starting covariances were constructed as if there were no correlation between separate passes. The biases obtained from each run are listed.

A vector scanning processing technique for pulsed laser velocimetry

NASA Technical Reports Server (NTRS)

Wernet, Mark P.; Edwards, Robert V.

1989-01-01

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

Text analysis devices, articles of manufacture, and text analysis methods

DOEpatents

Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

2015-03-31

Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes a display configured to depict visible images, and processing circuitry coupled with the display and wherein the processing circuitry is configured to access a first vector of a text item and which comprises a plurality of components, to access a second vector of the text item and which comprises a plurality of components, to weight the components of the first vector providing a plurality of weighted values, to weight the components of the second vector providing a plurality of weighted values, and to combine the weighted values of the first vector with the weighted values of the second vector to provide a third vector.

The Alignment of the Mean Wind and Stress Vectors in the Unstable Surface Layer

NASA Astrophysics Data System (ADS)

Bernardes, M.; Dias, N. L.

2010-01-01

A significant non-alignment between the mean horizontal wind vector and the stress vector was observed for turbulence measurements both above the water surface of a large lake, and over a land surface (soybean crop). Possible causes for this discrepancy such as flow distortion, averaging times and the procedure used for extracting the turbulent fluctuations (low-pass filtering and filter widths etc.), were dismissed after a detailed analysis. Minimum averaging times always less than 30 min were established by calculating ogives, and error bounds for the turbulent stresses were derived with three different approaches, based on integral time scales (first-crossing and lag-window estimates) and on a bootstrap technique. It was found that the mean absolute value of the angle between the mean wind and stress vectors is highly related to atmospheric stability, with the non-alignment increasing distinctively with increasing instability. Given a coordinate rotation that aligns the mean wind with the x direction, this behaviour can be explained by the growth of the relative error of the u- w component with instability. As a result, under more unstable conditions the u- w and the v- w components become of the same order of magnitude, and the local stress vector gives the impression of being non-aligned with the mean wind vector. The relative error of the v- w component is large enough to make it undistinguishable from zero throughout the range of stabilities. Therefore, the standard assumptions of Monin-Obukhov similarity theory hold: it is fair to assume that the v- w stress component is actually zero, and that the non-alignment is a purely statistical effect. An analysis of the dimensionless budgets of the u- w and the v- w components confirms this interpretation, with both shear and buoyant production of u- w decreasing with increasing instability. In the v- w budget, shear production is zero by definition, while buoyancy displays very low-intensity fluctuations around zero. As local free convection is approached, the turbulence becomes effectively axisymetrical, and a practical limit seems to exist beyond which it is not possible to measure the u- w component accurately.

A multistage motion vector processing method for motion-compensated frame interpolation.

PubMed

Huang, Ai- Mei; Nguyen, Truong Q

2008-05-01

In this paper, a novel, low-complexity motion vector processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion vectors on different block sizes. Our method explicitly considers the reliability of each received motion vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion vectors. The motion vector reliability information is also used as a prior knowledge in motion vector refinement using a constrained vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.

Multiscale vector fields for image pattern recognition

NASA Technical Reports Server (NTRS)

Low, Kah-Chan; Coggins, James M.

1990-01-01

A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.

Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization.

PubMed

Karayiannis, N B; Pai, P I

1999-02-01

This paper evaluates a segmentation technique for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector quantization (FALVQ). These algorithms perform vector quantization by updating all prototypes of a competitive network through an unsupervised learning process. Segmentation of MR images is formulated as an unsupervised vector quantization process, where the local values of different relaxation parameters form the feature vectors which are represented by a relatively small set of prototypes. The experiments evaluate a variety of FALVQ algorithms in terms of their ability to identify different tissues and discriminate between normal tissues and abnormalities.

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Fluorescent tagged episomals for stoichiometric induced pluripotent stem cell reprogramming.

PubMed

Schmitt, Christopher E; Morales, Blanca M; Schmitz, Ellen M H; Hawkins, John S; Lizama, Carlos O; Zape, Joan P; Hsiao, Edward C; Zovein, Ann C

2017-06-05

Non-integrating episomal vectors have become an important tool for induced pluripotent stem cell reprogramming. The episomal vectors carrying the "Yamanaka reprogramming factors" (Oct4, Klf, Sox2, and L-Myc + Lin28) are critical tools for non-integrating reprogramming of cells to a pluripotent state. However, the reprogramming process remains highly stochastic, and is hampered by an inability to easily identify clones that carry the episomal vectors. We modified the original set of vectors to express spectrally separable fluorescent proteins to allow for enrichment of transfected cells. The vectors were then tested against the standard original vectors for reprogramming efficiency and for the ability to enrich for stoichiometric ratios of factors. The reengineered vectors allow for cell sorting based on reprogramming factor expression. We show that these vectors can assist in tracking episomal expression in individual cells and can select the reprogramming factor dosage. Together, these modified vectors are a useful tool for understanding the reprogramming process and improving induced pluripotent stem cell isolation efficiency.

Fast temporal neural learning using teacher forcing

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad (Inventor); Bahren, Jacob (Inventor)

1992-01-01

A neural network is trained to output a time dependent target vector defined over a predetermined time interval in response to a time dependent input vector defined over the same time interval by applying corresponding elements of the error vector, or difference between the target vector and the actual neuron output vector, to the inputs of corresponding output neurons of the network as corrective feedback. This feedback decreases the error and quickens the learning process, so that a much smaller number of training cycles are required to complete the learning process. A conventional gradient descent algorithm is employed to update the neural network parameters at the end of the predetermined time interval. The foregoing process is repeated in repetitive cycles until the actual output vector corresponds to the target vector. In the preferred embodiment, as the overall error of the neural network output decreasing during successive training cycles, the portion of the error fed back to the output neurons is decreased accordingly, allowing the network to learn with greater freedom from teacher forcing as the network parameters converge to their optimum values. The invention may also be used to train a neural network with stationary training and target vectors.

Fast temporal neural learning using teacher forcing

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad (Inventor); Bahren, Jacob (Inventor)

1995-01-01

A neural network is trained to output a time dependent target vector defined over a predetermined time interval in response to a time dependent input vector defined over the same time interval by applying corresponding elements of the error vector, or difference between the target vector and the actual neuron output vector, to the inputs of corresponding output neurons of the network as corrective feedback. This feedback decreases the error and quickens the learning process, so that a much smaller number of training cycles are required to complete the learning process. A conventional gradient descent algorithm is employed to update the neural network parameters at the end of the predetermined time interval. The foregoing process is repeated in repetitive cycles until the actual output vector corresponds to the target vector. In the preferred embodiment, as the overall error of the neural network output decreasing during successive training cycles, the portion of the error fed back to the output neurons is decreased accordingly, allowing the network to learn with greater freedom from teacher forcing as the network parameters converge to their optimum values. The invention may also be used to train a neural network with stationary training and target vectors.

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.

A new fundamental model of moving particle for reinterpreting Schroedinger equation

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

Umar, Muhamad Darwis

2012-06-20

The study of Schroedinger equation based on a hypothesis that every particle must move randomly in a quantum-sized volume has been done. In addition to random motion, every particle can do relative motion through the movement of its quantum-sized volume. On the other way these motions can coincide. In this proposed model, the random motion is one kind of intrinsic properties of the particle. The every change of both speed of randomly intrinsic motion and or the velocity of translational motion of a quantum-sized volume will represent a transition between two states, and the change of speed of randomly intrinsicmore » motion will generate diffusion process or Brownian motion perspectives. Diffusion process can take place in backward and forward processes and will represent a dissipative system. To derive Schroedinger equation from our hypothesis we use time operator introduced by Nelson. From a fundamental analysis, we find out that, naturally, we should view the means of Newton's Law F(vector sign) = ma(vector sign) as no an external force, but it is just to describe both the presence of intrinsic random motion and the change of the particle energy.« less

Effects of energy conservation on equilibrium properties of hot asymmetric nuclear matter

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Ko, Che Ming

2018-01-01

Based on the relativistic Vlasov-Uehling-Uhlenbeck transport model, which includes relativistic scalar and vector potentials on baryons, we consider an N -Δ -π system in a box with periodic boundary conditions to study the effects of energy conservation in particle production and absorption processes on the equilibrium properties of the system. The density and temperature of the matter in the box are taken to be similar to the hot dense matter formed in heavy ion collisions at intermediate energies. We find that to maintain the equilibrium numbers of N ,Δ , and π , which depend on the mean-field potentials of N and Δ , we must include these potentials in the energy conservation condition that determines the momenta of outgoing particles after a scattering or decay process. We further find that the baryon scalar potentials mainly affect the Δ and pion equilibrium numbers, while the baryon vector potentials have considerable effect on the effective charged pion ratio at equilibrium. Our results thus indicate that it is essential to include in the transport model the effect of potentials in the energy conservation of a scattering or decay process, which is ignored in most transport models, for studying pion production in heavy ion collisions.

Radio-guided sentinel lymph node identification by lymphoscintigraphy fused with an anatomical vector profile: clinical applications.

PubMed

Niccoli Asabella, A; Antonica, F; Renna, M A; Rubini, D; Notaristefano, A; Nicoletti, A; Rubini, G

2013-12-01

To develop a method to fuse lymphoscintigraphic images with an adaptable anatomical vector profile and to evaluate its role in the clinical practice. We used Adobe Illustrator CS6 to create different vector profiles, we fused those profiles, using Adobe Photoshop CS6, with lymphoscintigraphic images of the patient. We processed 197 lymphoscintigraphies performed in patients with cutaneous melanomas, breast cancer or delayed lymph drainage. Our models can be adapted to every patient attitude or position and contain different levels of anatomical details ranging from external body profiles to the internal anatomical structures like bones, muscles, vessels, and lymph nodes. If needed, more new anatomical details can be added and embedded in the profile without redrawing them, saving a lot of time. Details can also be easily hidden, allowing the physician to view only relevant information and structures. Fusion times are about 85 s. The diagnostic confidence of the observers increased significantly. The validation process showed a slight shift (mean 4.9 mm). We have created a new, practical, inexpensive digital technique based on commercial software for fusing lymphoscintigraphic images with built-in anatomical reference profiles. It is easily reproducible and does not alter the original scintigraphic image. Our method allows a more meaningful interpretation of lymphoscintigraphies, an easier recognition of the anatomical site and better lymph node dissection planning.

Large-scale adenovirus and poxvirus-vectored vaccine manufacturing to enable clinical trials.

PubMed

Kallel, Héla; Kamen, Amine A

2015-05-01

Efforts to make vaccines against infectious diseases and immunotherapies for cancer have evolved to utilize a variety of heterologous expression systems such as viral vectors. These vectors are often attenuated or engineered to safely deliver genes encoding antigens of different pathogens. Adenovirus and poxvirus vectors are among the viral vectors that are most frequently used to develop prophylactic vaccines against infectious diseases as well as therapeutic cancer vaccines. This mini-review describes the trends and processes in large-scale production of adenovirus and poxvirus vectors to meet the needs of clinical applications. We briefly describe the general principles for the production and purification of adenovirus and poxvirus viral vectors. Currently, adenovirus and poxvirus vector manufacturing methods rely on well-established cell culture technologies. Several improvements have been evaluated to increase the yield and to reduce the overall manufacturing cost, such as cultivation at high cell densities and continuous downstream processing. Additionally, advancements in vector characterization will greatly facilitate the development of novel vectored vaccine candidates. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An affine projection algorithm using grouping selection of input vectors

NASA Astrophysics Data System (ADS)

Shin, JaeWook; Kong, NamWoong; Park, PooGyeon

2011-10-01

This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

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

Treesearch

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

2003-01-01

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

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).

Universal Decoder for PPM of any Order

NASA Technical Reports Server (NTRS)

Moision, Bruce E.

2010-01-01

A recently developed algorithm for demodulation and decoding of a pulse-position- modulation (PPM) signal is suitable as a basis for designing a single hardware decoding apparatus to be capable of handling any PPM order. Hence, this algorithm offers advantages of greater flexibility and lower cost, in comparison with prior such algorithms, which necessitate the use of a distinct hardware implementation for each PPM order. In addition, in comparison with the prior algorithms, the present algorithm entails less complexity in decoding at large orders. An unavoidably lengthy presentation of background information, including definitions of terms, is prerequisite to a meaningful summary of this development. As an aid to understanding, the figure illustrates the relevant processes of coding, modulation, propagation, demodulation, and decoding. An M-ary PPM signal has M time slots per symbol period. A pulse (signifying 1) is transmitted during one of the time slots; no pulse (signifying 0) is transmitted during the other time slots. The information intended to be conveyed from the transmitting end to the receiving end of a radio or optical communication channel is a K-bit vector u. This vector is encoded by an (N,K) binary error-correcting code, producing an N-bit vector a. In turn, the vector a is subdivided into blocks of m = log2(M) bits and each such block is mapped to an M-ary PPM symbol. The resultant coding/modulation scheme can be regarded as equivalent to a nonlinear binary code. The binary vector of PPM symbols, x is transmitted over a Poisson channel, such that there is obtained, at the receiver, a Poisson-distributed photon count characterized by a mean background count nb during no-pulse time slots and a mean signal-plus-background count of ns+nb during a pulse time slot. In the receiver, demodulation of the signal is effected in an iterative soft decoding process that involves consideration of relationships among photon counts and conditional likelihoods of m-bit vectors of coded bits. Inasmuch as the likelihoods of all the m-bit vectors of coded bits mapping to the same PPM symbol are correlated, the best performance is obtained when the joint mbit conditional likelihoods are utilized. Unfortunately, the complexity of decoding, measured in the number of operations per bit, grows exponentially with m, and can thus become prohibitively expensive for large PPM orders. For a system required to handle multiple PPM orders, the cost is even higher because it is necessary to have separate decoding hardware for each order. This concludes the prerequisite background information. In the present algorithm, the decoding process as described above is modified by, among other things, introduction of an lbit marginalizer sub-algorithm. The term "l-bit marginalizer" signifies that instead of m-bit conditional likelihoods, the decoder computes l-bit conditional likelihoods, where l is fixed. Fixing l, regardless of the value of m, makes it possible to use a single hardware implementation for any PPM order. One could minimize the decoding complexity and obtain an especially simple design by fixing l at 1, but this would entail some loss of performance. An intermediate solution is to fix l at some value, greater than 1, that may be less than or greater than m. This solution makes it possible to obtain the desired flexibility to handle any PPM order while compromising between complexity and loss of performance.

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

PubMed

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

2017-02-01

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

Production of lentiviral vectors

PubMed Central

Merten, Otto-Wilhelm; Hebben, Matthias; Bovolenta, Chiara

2016-01-01

Lentiviral vectors (LV) have seen considerably increase in use as gene therapy vectors for the treatment of acquired and inherited diseases. This review presents the state of the art of the production of these vectors with particular emphasis on their large-scale production for clinical purposes. In contrast to oncoretroviral vectors, which are produced using stable producer cell lines, clinical-grade LV are in most of the cases produced by transient transfection of 293 or 293T cells grown in cell factories. However, more recent developments, also, tend to use hollow fiber reactor, suspension culture processes, and the implementation of stable producer cell lines. As is customary for the biotech industry, rather sophisticated downstream processing protocols have been established to remove any undesirable process-derived contaminant, such as plasmid or host cell DNA or host cell proteins. This review compares published large-scale production and purification processes of LV and presents their process performances. Furthermore, developments in the domain of stable cell lines and their way to the use of production vehicles of clinical material will be presented. PMID:27110581

Rabies Virus Envelope Glycoprotein Targets Lentiviral Vectors to the Axonal Retrograde Pathway in Motor Neurons*

PubMed Central

Hislop, James N.; Islam, Tarin A.; Eleftheriadou, Ioanna; Carpentier, David C. J.; Trabalza, Antonio; Parkinson, Michael; Schiavo, Giampietro; Mazarakis, Nicholas D.

2014-01-01

Rabies pseudotyped lentiviral vectors have great potential in gene therapy, not least because of their ability to transduce neurons following their distal axonal application. However, very little is known about the molecular processes that underlie their retrograde transport and cell transduction. Using multiple labeling techniques and confocal microscopy, we demonstrated that pseudotyping with rabies virus envelope glycoprotein (RV-G) enabled the axonal retrograde transport of two distinct subtypes of lentiviral vector in motor neuron cultures. Analysis of this process revealed that these vectors trafficked through Rab5-positive endosomes and accumulated within a non-acidic Rab7 compartment. RV-G pseudotyped vectors were co-transported with both the tetanus neurotoxin-binding fragment and the membrane proteins thought to mediate rabies virus endocytosis (neural cell adhesion molecule, nicotinic acetylcholine receptor, and p75 neurotrophin receptor), thus demonstrating that pseudotyping with RV-G targets lentiviral vectors for transport along the same pathway exploited by several toxins and viruses. Using motor neurons cultured in compartmentalized chambers, we demonstrated that axonal retrograde transport of these vectors was rapid and efficient; however, it was not able to transduce the targeted neurons efficiently, suggesting that impairment in processes occurring after arrival of the viral vector in the soma is responsible for the low transduction efficiency seen in vivo, which suggests a novel area for improvement of gene therapy vectors. PMID:24753246

Turbulent fluid motion 2: Scalars, vectors, and tensors

NASA Technical Reports Server (NTRS)

Deissler, Robert G.

1991-01-01

The author shows that the sum or difference of two vectors is a vector. Similarly the sum of any two tensors of the same order is a tensor of that order. No meaning is attached to the sum of tensors of different orders, say u(sub i) + u(sub ij); that is not a tensor. In general, an equation containing tensors has meaning only if all the terms in the equation are tensors of the same order, and if the same unrepeated subscripts appear in all the terms. These facts will be used in obtaining appropriate equations for fluid turbulence. With the foregoing background, the derivation of appropriate continuum equations for turbulence should be straightforward.

Study of the correlation parameters of the surface structure of disordered semiconductors by the two-dimensional DFA and average mutual information methods

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

Alpatov, A. V.; Vikhrov, S. P.; Rybina, N. V., E-mail: pgnv@mail.ru

The processes of self-organization of the surface structure of hydrogenated amorphous silicon are studied by the methods of fluctuation analysis and average mutual information on the basis of atomic-force-microscopy images of the surface. It is found that all of the structures can be characterized by a correlation vector and represented as a superposition of harmonic components and noise. It is shown that, under variations in the technological parameters of the production of a-Si:H films, the correlation properties of their structure vary as well. As the substrate temperature is increased, the formation of structural irregularities becomes less efficient; in this case,more » the length of the correlation vector and the degree of structural ordering increase. It is shown that the procedure based on the method of fluctuation analysis in combination with the method of average mutual information provides a means for studying the self-organization processes in any structures on different length scales.« less

Hydroclimatic Assessment of West Nile Virus Occurrence Across Continental US

NASA Astrophysics Data System (ADS)

Billian, H. E.; Jutla, A.; Colwell, R. R.

2014-12-01

West Nile virus (WNV) is the most widely infections from arbovirus in mid-latitudes, having reached the Western Hemisphere in 1999. As a vector-borne disease, WNV is primarily spread by mosquitoes; the disease is predominantly found in tropical and temperate regions of the world, and is now considered an endemic pathogen in the United States, Africa, Asia, Australia, the Middle East, and Europe. Environmental processes play a vital role in the trigger of WNV. Here, using logistical regression models, we quantified relationships between hydroclimatic processes and mosquito abundance for WNV across the continental USA using precipitation and temperature at different spatial and temporal scales. It will be shown that reported cases of this disease are more prevalent during spring and summer months in the entire country, when there is more precipitation and higher surface air temperatures for 2003 to 2013. The key impacts of this research are those related to the improvement of human health, and a means to predict mosquito breeding patterns long term as they relate to the prevalence of vector-borne illnesses.

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Visualization and Analysis of Geology Word Vectors for Efficient Information Extraction

NASA Astrophysics Data System (ADS)

Floyd, J. S.

2016-12-01

When a scientist begins studying a new geographic region of the Earth, they frequently begin by gathering relevant scientific literature in order to understand what is known, for example, about the region's geologic setting, structure, stratigraphy, and tectonic and environmental history. Experienced scientists typically know what keywords to seek and understand that if a document contains one important keyword, then other words in the document may be important as well. Word relationships in a document give rise to what is known in linguistics as the context-dependent nature of meaning. For example, the meaning of the word `strike' in geology, as in the strike of a fault, is quite different from its popular meaning in baseball. In addition, word order, such as in the phrase `Cretaceous-Tertiary boundary,' often corresponds to the order of sequences in time or space. The context of words and the relevance of words to each other can be derived quantitatively by machine learning vector representations of words. Here we show the results of training a neural network to create word vectors from scientific research papers from selected rift basins and mid-ocean ridges: the Woodlark Basin of Papua New Guinea, the Hess Deep rift, and the Gulf of Mexico basin. The word vectors are statistically defined by surrounding words within a given window, limited by the length of each sentence. The word vectors are analyzed by their cosine distance to related words (e.g., `axial' and `magma'), classified by high dimensional clustering, and visualized by reducing the vector dimensions and plotting the vectors on a two- or three-dimensional graph. Similarity analysis of `Triassic' and `Cretaceous' returns `Jurassic' as the nearest word vector, suggesting that the model is capable of learning the geologic time scale. Similarity analysis of `basalt' and `minerals' automatically returns mineral names such as `chlorite', `plagioclase,' and `olivine.' Word vector analysis and visualization allow one to extract information from hundreds of papers or more and find relationships in less time than it would take to read all of the papers. As machine learning tools become more commonly available, more and more scientists will be able to use and refine these tools for their individual needs.

Vector processing efficiency of plasma MHD codes by use of the FACOM 230-75 APU

NASA Astrophysics Data System (ADS)

Matsuura, T.; Tanaka, Y.; Naraoka, K.; Takizuka, T.; Tsunematsu, T.; Tokuda, S.; Azumi, M.; Kurita, G.; Takeda, T.

1982-06-01

In the framework of pipelined vector architecture, the efficiency of vector processing is assessed with respect to plasma MHD codes in nuclear fusion research. By using a vector processor, the FACOM 230-75 APU, the limit of the enhancement factor due to parallelism of current vector machines is examined for three numerical codes based on a fluid model. Reasonable speed-up factors of approximately 6,6 and 4 times faster than the highly optimized scalar version are obtained for ERATO (linear stability code), AEOLUS-R1 (nonlinear stability code) and APOLLO (1-1/2D transport code), respectively. Problems of the pipelined vector processors are discussed from the viewpoint of restructuring, optimization and choice of algorithms. In conclusion, the important concept of "concurrency within pipelined parallelism" is emphasized.

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 .

Chagas disease vector control and Taylor's law

PubMed Central

Rodríguez-Planes, Lucía I.; Gaspe, María S.; Cecere, María C.; Cardinal, Marta V.

2017-01-01

Background Large spatial and temporal fluctuations in the population density of living organisms have profound consequences for biodiversity conservation, food production, pest control and disease control, especially vector-borne disease control. Chagas disease vector control based on insecticide spraying could benefit from improved concepts and methods to deal with spatial variations in vector population density. Methodology/Principal findings We show that Taylor's law (TL) of fluctuation scaling describes accurately the mean and variance over space of relative abundance, by habitat, of four insect vectors of Chagas disease (Triatoma infestans, Triatoma guasayana, Triatoma garciabesi and Triatoma sordida) in 33,908 searches of people's dwellings and associated habitats in 79 field surveys in four districts in the Argentine Chaco region, before and after insecticide spraying. As TL predicts, the logarithm of the sample variance of bug relative abundance closely approximates a linear function of the logarithm of the sample mean of abundance in different habitats. Slopes of TL indicate spatial aggregation or variation in habitat suitability. Predictions of new mathematical models of the effect of vector control measures on TL agree overall with field data before and after community-wide spraying of insecticide. Conclusions/Significance A spatial Taylor's law identifies key habitats with high average infestation and spatially highly variable infestation, providing a new instrument for the control and elimination of the vectors of a major human disease. PMID:29190728

Confidence regions of planar cardiac vectors

NASA Technical Reports Server (NTRS)

Dubin, S.; Herr, A.; Hunt, P.

1980-01-01

A method for plotting the confidence regions of vectorial data obtained in electrocardiology is presented. The 90%, 95% and 99% confidence regions of cardiac vectors represented in a plane are obtained in the form of an ellipse centered at coordinates corresponding to the means of a sample selected at random from a bivariate normal distribution. An example of such a plot for the frontal plane QRS mean electrical axis for 80 horses is also presented.

Adaptive marginal median filter for colour images.

PubMed

Morillas, Samuel; Gregori, Valentín; Sapena, Almanzor

2011-01-01

This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter.

Relative efficacy of repellent-treated wristbands against three major mosquito (Diptera: Culicidae) vectors of disease, under laboratory conditions.

PubMed

Karunamoorthi, Kaliyaperumal; Sabesan, Shanmugavelu

2009-12-01

A laboratory study was carried out to evaluate the relative efficacy of N-N-diethyl-m-toluamide (DEET)- and N,N-diethyl phenylacetamide (DEPA)-treated wristbands against three major vector mosquitoes viz., Anopheles stephensi Liston, Culex quinquefasciatus Say and Aedes aegypti (L.), at two different concentrations viz., 1.5 and 2.0 mg/cm(2). Overall, both DEET and DEPA have shown various degrees of repellency impact against all three vector mosquitoes. DEET offered the highest 317.0 min mean complete protection against An. stephensi and DEPA provided 275.6 min complete protection to Cx. quinquefasciatus at 2.0 mg/cm(2). However, DEPA-treated wristbands did not show any significant differences in terms of reduction of human landing rate and mean complete protection time against An. stephensi and Ae. aegypti between 1.5 and 2.0 mg/cm(2). DEET demonstrated relatively higher repellency impact to vector mosquitoes than DEPA. However, χ(2) analysis revealed that there was no statistically significant difference found in repellent efficiency between DEET and DEPA (P = 0.924). The present study result suggests that repellent-treated wristbands could serve as a means of potential personal protection expedient to avoid insect's annoyance and reduce vector-borne disease transmission. They are extremely valuable whenever and wherever other kinds of personal protection measures are unfeasible.

Climate change and altitudinal structuring of malaria vectors in south-western Cameroon: their relation to malaria transmission.

PubMed

Tanga, M C; Ngundu, W I; Judith, N; Mbuh, J; Tendongfor, N; Simard, Frédéric; Wanji, S

2010-07-01

An entomological survey was conducted in Cameroon between October 2004 and September 2005, in nine localities targeted for malaria vector control based on adult productivity and variability. Mosquitoes were collected by human-landing catches (HLCs) and pyrethrum spray catches. A total of 12 500 anophelines were collected and dissected: Anopheles gambiae s.l. (56.86%), An. funestus s.l. (32.57%), An. hancocki (9.38%), and An. nili (1.18%). Applying PCR revealed that specimens of the An. funestus group were An. funestus s.s. and An. gambiae complex were mostly An. melas and An. gambiae s.s. of the M and S molecular forms with the M forms being the most predominant. The natural distribution patterns of Anopheles species were largely determined by altitude with some species having unique environmental tolerance limits. A human blood index (HBI) of 99.05% was recorded. Mean probability of daily survival of the malaria vectors was 0.92, with annual mean life expectancy of 21.9 days and the expectation of infective life was long with a mean of 7.4 days. The high survival rates suggest a high vector potential for the species. This information enhances the development of a more focused and informed vector control intervention. Copyright 2010 Royal Society of Tropical Medicine and Hygiene. Published by Elsevier Ltd. All rights reserved.

Incoherent averaging of phase singularities in speckle-shearing interferometry.

PubMed

Mantel, Klaus; Nercissian, Vanusch; Lindlein, Norbert

2014-08-01

Interferometric speckle techniques are plagued by the omnipresence of phase singularities, impairing the phase unwrapping process. To reduce the number of phase singularities by physical means, an incoherent averaging of multiple speckle fields may be applied. It turns out, however, that the results may strongly deviate from the expected √N behavior. Using speckle-shearing interferometry as an example, we investigate the mechanism behind the reduction of phase singularities, both by calculations and by computer simulations. Key to an understanding of the reduction mechanism during incoherent averaging is the representation of the physical averaging process in terms of certain vector fields associated with each speckle field.

Cross-coherent vector sensor processing for spatially distributed glider networks.

PubMed

Nichols, Brendan; Sabra, Karim G

2015-09-01

Autonomous underwater gliders fitted with vector sensors can be used as a spatially distributed sensor array to passively locate underwater sources. However, to date, the positional accuracy required for robust array processing (especially coherent processing) is not achievable using dead-reckoning while the gliders remain submerged. To obtain such accuracy, the gliders can be temporarily surfaced to allow for global positioning system contact, but the acoustically active sea surface introduces locally additional sensor noise. This letter demonstrates that cross-coherent array processing, which inherently mitigates the effects of local noise, outperforms traditional incoherent processing source localization methods for this spatially distributed vector sensor network.

[4D-CT-based plan target volume (PTV) definition compared with conventional PTV definition using general margin in radiotherapy for lung cancer].

PubMed

Ju, Xiao; Li, Minghui; Zhou, Zongmei; Zhang, Ke; Han, Wei; Fu, Guishan; Cao, Ying; Wang, Lyuhua

2014-01-01

To investigate the dosimetric benefit of 4D-CT in the planning target volume (PTV) definition process compared with conventional PTV definition using general margin in radiotherapy of lung cancer. A set of 4D-CT images and multiphase helical CT scans were obtained in 10 patients with lung cancer. The radiotherapeutic plans based on PTV determined by 4D-CT and in addition of general margin were performed, respectively. The 3D motion of the centroid of GTV and the 3D spatial motion vectors were calculated. The differences of the two kinds of PTVs, mean lung dose (MLD), V5,V10,V15,V20 of total lung, mean heart dose (MHD), V30 and V40 of heart, D99 and D95 were compared, and the correlation between them and the 3D spatial motion vector was analyzed. The PTV4D in eight patients were smaller than PTVconv, with a mean reduction of (13.0 ± 8.0)% (P = 0.018). In other two patients, whose respiration motion was great, PTV4D was larger than PTVconv. The mean 3D spatial motion vector of GTV centroid was (0.78 ± 0.72)cm. By using 4D-CT, the mean reduction of MLD was (8.6 ± 9.9)% (P = 0.037). V5, V10, V15, V20 of total lung were decreased averagely by (7.2 ± 10.5)%, (5.5 ± 8.9)%, (6.5 ± 8.4)% and (5.7 ± 7.4)%, respectively (P < 0.05 for all). There was a significant positive correlation between PTV4D/PTVconv and the 3D spatial motion vector of the GTV centroid (P = 0.008). A significant inverse correlation was found between D994D/D99conv and the 3D spatial motion vector of the GTV centroid (P = 0.002). D994D/D99conv, (MLDconv-MLD4D) /MLDconv, total lung (V5conv-V54D)/V5conv, total lung (V10conv-V104D)/V10conv, (MHDconv-MHD4D)/MHDconv, heart (V30conv-V304D)/V30conv were inversely correlated with PTV4D/PTVconv (P < 0.05 for all). 4D-CT can be used to evaluate the respiration motion of lung tumor accurately. The 4D-CT-based PTV definition and radiotherapeutic planing can reduce the volume of PTV in patients with small respiration motion, increase the intra-target dose, and decrease the dose of normal tissue sequentially. For patients with large respiration motion, especially those more than 1.5-2 cm, this method can avoid target miss, meanwhile, not increase the dose of normal tissue significantly.

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

PubMed

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

2018-02-05

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

Estimation of attitude sensor timetag biases

NASA Technical Reports Server (NTRS)

Sedlak, J.

1995-01-01

This paper presents an extended Kalman filter for estimating attitude sensor timing errors. Spacecraft attitude is determined by finding the mean rotation from a set of reference vectors in inertial space to the corresponding observed vectors in the body frame. Any timing errors in the observations can lead to attitude errors if either the spacecraft is rotating or the reference vectors themselves vary with time. The state vector here consists of the attitude quaternion, timetag biases, and, optionally, gyro drift rate biases. The filter models the timetags as random walk processes: their expectation values propagate as constants and white noise contributes to their covariance. Thus, this filter is applicable to cases where the true timing errors are constant or slowly varying. The observability of the state vector is studied first through an examination of the algebraic observability condition and then through several examples with simulated star tracker timing errors. The examples use both simulated and actual flight data from the Extreme Ultraviolet Explorer (EUVE). The flight data come from times when EUVE had a constant rotation rate, while the simulated data feature large angle attitude maneuvers. The tests include cases with timetag errors on one or two sensors, both constant and time-varying, and with and without gyro bias errors. Due to EUVE's sensor geometry, the observability of the state vector is severely limited when the spacecraft rotation rate is constant. In the absence of attitude maneuvers, the state elements are highly correlated, and the state estimate is unreliable. The estimates are particularly sensitive to filter mistuning in this case. The EUVE geometry, though, is a degenerate case having coplanar sensors and rotation vector. Observability is much improved and the filter performs well when the rate is either varying or noncoplanar with the sensors, as during a slew. Even with bad geometry and constant rates, if gyro biases are independently known, the timetag error for a single sensor can be accurately estimated as long as its boresight is not too close to the spacecraft rotation axis.

Vertebrate Development in Space: Gravity Is a Drag (and Has Been for Eons and Eons)

NASA Technical Reports Server (NTRS)

Keefe, J. R.

1985-01-01

Brief sketches of developmental biology studies during spaceflight presented are intended to be complete in scope and to provide the reader with an overview of the present status of such studies. Means of evaluating both the direct role of gravity on all processes of mammalian reproduction and development as well as defining the means of assessing indirect transplacemental aspects are considered. The potential present in the development of a spaceflight system/program specifically designed to provide chronic exposure of a representative variety of mammalian species with periodic sampling for multiple generations to fully assess the potential impact of an altered gravitational vector on general mammalian development is also considered.

Monte-Carlo Method Application for Precising Meteor Velocity from TV Observations

NASA Astrophysics Data System (ADS)

Kozak, P.

2014-12-01

Monte-Carlo method (method of statistical trials) as an application for meteor observations processing was developed in author's Ph.D. thesis in 2005 and first used in his works in 2008. The idea of using the method consists in that if we generate random values of input data - equatorial coordinates of the meteor head in a sequence of TV frames - in accordance with their statistical distributions we get a possibility to plot the probability density distributions for all its kinematical parameters, and to obtain their mean values and dispersions. At that the theoretical possibility appears to precise the most important parameter - geocentric velocity of a meteor - which has the highest influence onto precision of meteor heliocentric orbit elements calculation. In classical approach the velocity vector was calculated in two stages: first we calculate the vector direction as a vector multiplication of vectors of poles of meteor trajectory big circles, calculated from two observational points. Then we calculated the absolute value of velocity independently from each observational point selecting any of them from some reasons as a final parameter. In the given method we propose to obtain a statistical distribution of velocity absolute value as an intersection of two distributions corresponding to velocity values obtained from different points. We suppose that such an approach has to substantially increase the precision of meteor velocity calculation and remove any subjective inaccuracies.

Design and cloning strategies for constructing shRNA expression vectors

PubMed Central

McIntyre, Glen J; Fanning, Gregory C

2006-01-01

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

National malaria vector control policy: an analysis of the decision to scale-up larviciding in Nigeria.

PubMed

Tesfazghi, Kemi; Hill, Jenny; Jones, Caroline; Ranson, Hilary; Worrall, Eve

2016-02-01

New vector control tools are needed to combat insecticide resistance and reduce malaria transmission. The World Health Organization (WHO) endorses larviciding as a supplementary vector control intervention using larvicides recommended by the WHO Pesticides Evaluation Scheme (WHOPES). The decision to scale-up larviciding in Nigeria provided an opportunity to investigate the factors influencing policy adoption and assess the role that actors and evidence play in the policymaking process, in order to draw lessons that help accelerate the uptake of new methods for vector control. A retrospective policy analysis was carried out using in-depth interviews with national level policy stakeholders to establish normative national vector control policy or strategy decision-making processes and compare these with the process that led to the decision to scale-up larviciding. The interviews were transcribed, then coded and analyzed using NVivo10. Data were coded according to pre-defined themes from an analytical policy framework developed a priori. Stakeholders reported that the larviciding decision-making process deviated from the normative vector control decision-making process. National malaria policy is normally strongly influenced by WHO recommendations, but the potential of larviciding to contribute to national economic development objectives through larvicide production in Nigeria was cited as a key factor shaping the decision. The larviciding decision involved a restricted range of policy actors, and notably excluded actors that usually play advisory, consultative and evidence generation roles. Powerful actors limited the access of some actors to the policy processes and content. This may have limited the influence of scientific evidence in this policy decision. This study demonstrates that national vector control policy change can be facilitated by linking malaria control objectives to wider socioeconomic considerations and through engaging powerful policy champions to drive policy change and thereby accelerate access to new vector control tools. © The Author 2015. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Image stitching and image reconstruction of intestines captured using radial imaging capsule endoscope

NASA Astrophysics Data System (ADS)

Ou-Yang, Mang; Jeng, Wei-De; Wu, Yin-Yi; Dung, Lan-Rong; Wu, Hsien-Ming; Weng, Ping-Kuo; Huang, Ker-Jer; Chiu, Luan-Jiau

2012-05-01

This study investigates image processing using the radial imaging capsule endoscope (RICE) system. First, an experimental environment is established in which a simulated object has a shape that is similar to a cylinder, such that a triaxial platform can be used to push the RICE into the sample and capture radial images. Then four algorithms (mean absolute error, mean square error, Pearson correlation coefficient, and deformation processing) are used to stitch the images together. The Pearson correlation coefficient method is the most effective algorithm because it yields the highest peak signal-to-noise ratio, higher than 80.69 compared to the original image. Furthermore, a living animal experiment is carried out. Finally, the Pearson correlation coefficient method and vector deformation processing are used to stitch the images that were captured in the living animal experiment. This method is very attractive because unlike the other methods, in which two lenses are required to reconstruct the geometrical image, RICE uses only one lens and one mirror.

Unbiased mean direction of paleomagnetic data and better estimate of paleolatitude

NASA Astrophysics Data System (ADS)

Hatakeyama, T.; Shibuya, H.

2010-12-01

In paleomagnetism, when we obtain only paleodirection data without paleointensities we calculate Fisher-mean directions (I, D) and Fisher-mean VGP positions as the description of the mean field. However, Kono (1997) and Hatakeyama and Kono (2001) indicated that these averaged directions does not show the unbiased estimated mean directions derived from the time-averaged field (TAF). Hatakeyama and Kono (2002) calculated the TAF and paleosecular variation (PSV) models for the past 5My with considering the biases due to the averaging of the nonlinear functions such as the summation of the unit vectors in the Fisher statistics process. Here we will show a zonal TAF model based on the Hatakeyama and Kono TAF model. Moreover, we will introduce the biased angles due to the PSV in the mean direction and a method for determining true paleolatitudes, which represents the TAF, from paleodirections. This method will helps tectonics studies, especially in the estimation of the accurate paleolatitude in the middle latitude regions.

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.

Spin Filtering Studies at COSY and AD

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

Nass, Alexander

2009-08-04

The high physics potential of experiments with stored high-energy polarized antiprotons led to the proposal of PAX (Polarized Antiproton eXperiment) for the High Energy Storage Ring (HESR) of the FAIR at GSI (Darmstadt/Germany). It is proposed to polarize a stored antiproton beam by means of spin filtering with a polarized H (D) gas target. The feasibility of spin filtering has been demonstrated in the FILTEX experiment. The current interpretation foresees a self-cancellation of the electron contribution to the filtering process and only the hadronic contribution is effective. Several experimental studies with protons (at COSY/Juelich) as well as antiprotons (at AD/CERN)more » will be carried out to test the principle and measure p-barp-vector and p-bard-vector cross sections. A polarized internal gas target (PIT) with surrounding Silicon detectors immersed into a low-beta section has to be set up.« less

Real-time characterization of motion of motile microorganisms by means of a hybrid laser Doppler velocimeter technique

NASA Astrophysics Data System (ADS)

Zheng, Bin; Pleass, Charles M.; Ih, Charles S.

1993-11-01

A hybrid three-axis laser Doppler velocimeter system has been demonstrated in our laboratory. The system can monitor the motion of microorganisms in an unconstrained environment. During measurement, a computer system collects and processes time series data from the transit of a microorganism through the measurement volume. The fast Fourier transform of this data contains the motion signature of this microorganism. Because individual microorganisms can be selected from the field, ambiguity caused by multiscattering among two or more microorganisms can be avoided. Using this new system, we can obtain a feature vector that relates to features of the microorganism, such as its size, average translational velocity, rotation or wobbling, and its flagellum beat frequency. Such a vector appears to be a useful criterion for distinguishing the species using statistical pattern recognition. Successful experiments demonstrate that the new system and technique has some unique advantages.

Semantically enabled image similarity search

NASA Astrophysics Data System (ADS)

Casterline, May V.; Emerick, Timothy; Sadeghi, Kolia; Gosse, C. A.; Bartlett, Brent; Casey, Jason

2015-05-01

Georeferenced data of various modalities are increasingly available for intelligence and commercial use, however effectively exploiting these sources demands a unified data space capable of capturing the unique contribution of each input. This work presents a suite of software tools for representing geospatial vector data and overhead imagery in a shared high-dimension vector or embedding" space that supports fused learning and similarity search across dissimilar modalities. While the approach is suitable for fusing arbitrary input types, including free text, the present work exploits the obvious but computationally difficult relationship between GIS and overhead imagery. GIS is comprised of temporally-smoothed but information-limited content of a GIS, while overhead imagery provides an information-rich but temporally-limited perspective. This processing framework includes some important extensions of concepts in literature but, more critically, presents a means to accomplish them as a unified framework at scale on commodity cloud architectures.

A hybrid dynamic harmony search algorithm for identical parallel machines scheduling

NASA Astrophysics Data System (ADS)

Chen, Jing; Pan, Quan-Ke; Wang, Ling; Li, Jun-Qing

2012-02-01

In this article, a dynamic harmony search (DHS) algorithm is proposed for the identical parallel machines scheduling problem with the objective to minimize makespan. First, an encoding scheme based on a list scheduling rule is developed to convert the continuous harmony vectors to discrete job assignments. Second, the whole harmony memory (HM) is divided into multiple small-sized sub-HMs, and each sub-HM performs evolution independently and exchanges information with others periodically by using a regrouping schedule. Third, a novel improvisation process is applied to generate a new harmony by making use of the information of harmony vectors in each sub-HM. Moreover, a local search strategy is presented and incorporated into the DHS algorithm to find promising solutions. Simulation results show that the hybrid DHS (DHS_LS) is very competitive in comparison to its competitors in terms of mean performance and average computational time.

Focusing behavior of the fractal vector optical fields designed by fractal lattice growth model.

PubMed

Gao, Xu-Zhen; Pan, Yue; Zhao, Meng-Dan; Zhang, Guan-Lin; Zhang, Yu; Tu, Chenghou; Li, Yongnan; Wang, Hui-Tian

2018-01-22

We introduce a general fractal lattice growth model, significantly expanding the application scope of the fractal in the realm of optics. This model can be applied to construct various kinds of fractal "lattices" and then to achieve the design of a great diversity of fractal vector optical fields (F-VOFs) combinating with various "bases". We also experimentally generate the F-VOFs and explore their universal focusing behaviors. Multiple focal spots can be flexibly enginnered, and the optical tweezers experiment validates the simulated tight focusing fields, which means that this model allows the diversity of the focal patterns to flexibly trap and manipulate micrometer-sized particles. Furthermore, the recovery performance of the F-VOFs is also studied when the input fields and spatial frequency spectrum are obstructed, and the results confirm the robustness of the F-VOFs in both focusing and imaging processes, which is very useful in information transmission.

Memory persistency and nonlinearity in daily mean dew point across India

NASA Astrophysics Data System (ADS)

Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik; Bhattacharjee, Anup Kumar

2016-04-01

Enterprising endeavour has been taken in this work to realize and estimate the persistence in memory of the daily mean dew point time series obtained from seven different weather stations viz. Kolkata, Chennai (Madras), New Delhi, Mumbai (Bombay), Bhopal, Agartala and Ahmedabad representing different geographical zones in India. Hurst exponent values reveal an anti-persistent behaviour of these dew point series. To affirm the Hurst exponent values, five different scaling methods have been used and the corresponding results are compared to synthesize a finer and reliable conclusion out of it. The present analysis also bespeaks that the variation in daily mean dew point is governed by a non-stationary process with stationary increments. The delay vector variance (DVV) method has been exploited to investigate nonlinearity, and the present calculation confirms the presence of deterministic nonlinear profile in the daily mean dew point time series of the seven stations.

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.

Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

PubMed

Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

2017-09-01

In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

Localization of heart vectors produced by epicardial burns and ectopic stimuli; validation of a dipole ranging method.

PubMed

Ideker, R E; Bandura, J P; Larsen, R A; Cox, J W; Keller, F W; Brody, D A

1975-01-01

Location of the equivalent cardiac dipole has been estimated but not fully verified in several laboratories. To test the accuracy of such a procedure, injury vectors were produced in 14 isolated, perfused rabbit hearts by epicardial searing. Strongly dipolar excitation fronts were produced in 6 additional hearts by left ventricular pacing. Twenty computer-processed signals, derived from surface electrodes on a spherical electrolyte-filled tank containing the test preparation, were optimally fitted with a locatable cardiac dipole that accounted for over 99% of the root-mean-square surface potential. For the 14 burns (mean radius 5.0 mm), the S-T injury dipole was located 3.4 plus or minus 0.7 (SD) mm from the burn center. For the 6 paced hearts, the dipole early in the ectopic beat was located 3.7 mm (range 2.6 to 4.6 mm) from the stimulating electrode. Phase inhomogeneities within the chamber appeared to have a small but predictable effect on dipole site determination. The study demonstrates that equivalent dipole location can be determined with acceptable accuracy from potential measurements of the external cardiac field.

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

PubMed Central

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M.

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. PMID:27438600

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks.

PubMed

Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M

2016-01-01

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover.

Rabies virus envelope glycoprotein targets lentiviral vectors to the axonal retrograde pathway in motor neurons.

PubMed

Hislop, James N; Islam, Tarin A; Eleftheriadou, Ioanna; Carpentier, David C J; Trabalza, Antonio; Parkinson, Michael; Schiavo, Giampietro; Mazarakis, Nicholas D

2014-06-06

Rabies pseudotyped lentiviral vectors have great potential in gene therapy, not least because of their ability to transduce neurons following their distal axonal application. However, very little is known about the molecular processes that underlie their retrograde transport and cell transduction. Using multiple labeling techniques and confocal microscopy, we demonstrated that pseudotyping with rabies virus envelope glycoprotein (RV-G) enabled the axonal retrograde transport of two distinct subtypes of lentiviral vector in motor neuron cultures. Analysis of this process revealed that these vectors trafficked through Rab5-positive endosomes and accumulated within a non-acidic Rab7 compartment. RV-G pseudotyped vectors were co-transported with both the tetanus neurotoxin-binding fragment and the membrane proteins thought to mediate rabies virus endocytosis (neural cell adhesion molecule, nicotinic acetylcholine receptor, and p75 neurotrophin receptor), thus demonstrating that pseudotyping with RV-G targets lentiviral vectors for transport along the same pathway exploited by several toxins and viruses. Using motor neurons cultured in compartmentalized chambers, we demonstrated that axonal retrograde transport of these vectors was rapid and efficient; however, it was not able to transduce the targeted neurons efficiently, suggesting that impairment in processes occurring after arrival of the viral vector in the soma is responsible for the low transduction efficiency seen in vivo, which suggests a novel area for improvement of gene therapy vectors. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Pixel-By Estimation of Scene Motion in Video

NASA Astrophysics Data System (ADS)

Tashlinskii, A. G.; Smirnov, P. V.; Tsaryov, M. G.

2017-05-01

The paper considers the effectiveness of motion estimation in video using pixel-by-pixel recurrent algorithms. The algorithms use stochastic gradient decent to find inter-frame shifts of all pixels of a frame. These vectors form shift vectors' field. As estimated parameters of the vectors the paper studies their projections and polar parameters. It considers two methods for estimating shift vectors' field. The first method uses stochastic gradient descent algorithm to sequentially process all nodes of the image row-by-row. It processes each row bidirectionally i.e. from the left to the right and from the right to the left. Subsequent joint processing of the results allows compensating inertia of the recursive estimation. The second method uses correlation between rows to increase processing efficiency. It processes rows one after the other with the change in direction after each row and uses obtained values to form resulting estimate. The paper studies two criteria of its formation: gradient estimation minimum and correlation coefficient maximum. The paper gives examples of experimental results of pixel-by-pixel estimation for a video with a moving object and estimation of a moving object trajectory using shift vectors' field.

Gaussian statistics for palaeomagnetic vectors

USGS Publications Warehouse

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

2003-01-01

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

Gaussian statistics for palaeomagnetic vectors

NASA Astrophysics Data System (ADS)

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

2003-03-01

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

Students' difficulties with vector calculus in electrodynamics

NASA Astrophysics Data System (ADS)

Bollen, Laurens; van Kampen, Paul; De Cock, Mieke

2015-12-01

Understanding Maxwell's equations in differential form is of great importance when studying the electrodynamic phenomena discussed in advanced electromagnetism courses. It is therefore necessary that students master the use of vector calculus in physical situations. In this light we investigated the difficulties second year students at KU Leuven encounter with the divergence and curl of a vector field in mathematical and physical contexts. We have found that they are quite skilled at doing calculations, but struggle with interpreting graphical representations of vector fields and applying vector calculus to physical situations. We have found strong indications that traditional instruction is not sufficient for our students to fully understand the meaning and power of Maxwell's equations in electrodynamics.

Parents' perceptions of their adolescent sons' recovery in a therapeutic community for addicted clients.

PubMed

Chen, Gila; Elisha, Ety; Timor, Uri; Ronel, Natti

2013-11-01

A qualitative phenomenological study of parents of addicted male adolescents who were residents of a Jewish therapeutic community (TC) describes and interprets the parents' perceptions of the recovery process. Deep, semistructured interviews with 14 parents provided the data. The parents' perceptions were clustered into three main themes of meaning: (a) the process of change, (b) the experiences of family members in the course of the son's recovery process, and (c) the parents' perception of the treatment at Retorno. According to the parents, the admission of their sons into the TC brought notable relief to the family life, which enabled the whole family to begin a recovery process. The findings support the positive criminology perspective that emphasizes the disintegration-integration vector as significant in the recovery process. Recommendations for intervention planning are provided.

The impact of dissociation on transposon-mediated disease control strategies.

PubMed

Marshall, John M

2008-03-01

Vector-borne diseases such as malaria and dengue fever continue to be a major health concern through much of the world. The emergence of chloroquine-resistant strains of malaria and insecticide-resistant mosquitoes emphasize the need for novel methods of disease control. Recently, there has been much interest in the use of transposable elements to drive resistance genes into vector populations as a means of disease control. One concern that must be addressed before a release is performed is the potential loss of linkage between a transposable element and a resistance gene. Transposable elements such as P and hobo have been shown to produce internal deletion derivatives at a significant rate, and there is concern that a similar process could lead to loss of the resistance gene from the drive system following a transgenic release. Additionally, transposable elements such as Himar1 have been shown to transpose significantly more frequently when free of exogenous DNA. Here, we show that any transposon-mediated gene drive strategy must have an exceptionally low rate of dissociation if it is to be effective. Additionally, the resistance gene must confer a large selective advantage to the vector to surmount the effects of a moderate dissociation rate and transpositional handicap.

An imaging vector magnetograph for the next solar maximum

NASA Technical Reports Server (NTRS)

Mickey, D. L.; Labonte, B. J.; Canfield, R. C.

1989-01-01

Researchers describe the conceptual design of a new imaging vector magnetograph currently being constructed at the University of Hawaii. The instrument combines a modest solar telescope with a rotating quarter-wave plate, an acousto-optical tunable prefilter as a blocker for a servo-controlled Fabry-Perot etalon, CCD cameras, and on-line digital image processing. Its high spatial resolution (1/2 arcsec pixel size) over a large field of view (5 by 5 arcmin) will be sufficient to significantly measure, for the first time, the magnetic energy dissipated in major solar flares. Its millisecond tunability and wide spectral range (5000 to 7000 A) enable nearly simultaneous vector magnetic field measurements in the gas-pressure-dominated photosphere and magnetically-dominated chromosphere, as well as effective co-alignment with Solar-A's X ray images. Researchers expect to have the instrument in operation at Mees Solar Observatory (Haleakala) in early 1991. They have chosen to use tunable filters as wavelength-selection elements in order to emphasize the spatial relationships between magnetic field elements, and to permit construction of a compact, efficient instrument. This means that spectral information must be obtained from sequences of images, which can cause line profile distortions due to effects of atmospheric seeing.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

PubMed

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

A selective-update affine projection algorithm with selective input vectors

NASA Astrophysics Data System (ADS)

Kong, NamWoong; Shin, JaeWook; Park, PooGyeon

2011-10-01

This paper proposes an affine projection algorithm (APA) with selective input vectors, which based on the concept of selective-update in order to reduce estimation errors and computations. The algorithm consists of two procedures: input- vector-selection and state-decision. The input-vector-selection procedure determines the number of input vectors by checking with mean square error (MSE) whether the input vectors have enough information for update. The state-decision procedure determines the current state of the adaptive filter by using the state-decision criterion. As the adaptive filter is in transient state, the algorithm updates the filter coefficients with the selected input vectors. On the other hand, as soon as the adaptive filter reaches the steady state, the update procedure is not performed. Through these two procedures, the proposed algorithm achieves small steady-state estimation errors, low computational complexity and low update complexity for colored input signals.

Pre-existing immunity against vaccine vectors – friend or foe?

PubMed Central

Saxena, Manvendra; Van, Thi Thu Hao; Baird, Fiona J.; Coloe, Peter J.

2013-01-01

Over the last century, the successful attenuation of multiple bacterial and viral pathogens has led to an effective, robust and safe form of vaccination. Recently, these vaccines have been evaluated as delivery vectors for heterologous antigens, as a means of simultaneous vaccination against two pathogens. The general consensus from published studies is that these vaccine vectors have the potential to be both safe and efficacious. However, some of the commonly employed vectors, for example Salmonella and adenovirus, often have pre-existing immune responses in the host and this has the potential to modify the subsequent immune response to a vectored antigen. This review examines the literature on this topic, and concludes that for bacterial vectors there can in fact, in some cases, be an enhancement in immunogenicity, typically humoral, while for viral vectors pre-existing immunity is a hindrance for subsequent induction of cell-mediated responses. PMID:23175507

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.

Large Electroweak Corrections to Vector-Boson Scattering at the Large Hadron Collider.

PubMed

Biedermann, Benedikt; Denner, Ansgar; Pellen, Mathieu

2017-06-30

For the first time full next-to-leading-order electroweak corrections to off-shell vector-boson scattering are presented. The computation features the complete matrix elements, including all nonresonant and off-shell contributions, to the electroweak process pp→μ^{+}ν_{μ}e^{+}ν_{e}jj and is fully differential. We find surprisingly large corrections, reaching -16% for the fiducial cross section, as an intrinsic feature of the vector-boson-scattering processes. We elucidate the origin of these large electroweak corrections upon using the double-pole approximation and the effective vector-boson approximation along with leading-logarithmic corrections.

Normal mode-guided transition pathway generation in proteins

PubMed Central

Lee, Byung Ho; Seo, Sangjae; Kim, Min Hyeok; Kim, Youngjin; Jo, Soojin; Choi, Moon-ki; Lee, Hoomin; Choi, Jae Boong

2017-01-01

The biological function of proteins is closely related to its structural motion. For instance, structurally misfolded proteins do not function properly. Although we are able to experimentally obtain structural information on proteins, it is still challenging to capture their dynamics, such as transition processes. Therefore, we need a simulation method to predict the transition pathways of a protein in order to understand and study large functional deformations. Here, we present a new simulation method called normal mode-guided elastic network interpolation (NGENI) that performs normal modes analysis iteratively to predict transition pathways of proteins. To be more specific, NGENI obtains displacement vectors that determine intermediate structures by interpolating the distance between two end-point conformations, similar to a morphing method called elastic network interpolation. However, the displacement vector is regarded as a linear combination of the normal mode vectors of each intermediate structure, in order to enhance the physical sense of the proposed pathways. As a result, we can generate more reasonable transition pathways geometrically and thermodynamically. By using not only all normal modes, but also in part using only the lowest normal modes, NGENI can still generate reasonable pathways for large deformations in proteins. This study shows that global protein transitions are dominated by collective motion, which means that a few lowest normal modes play an important role in this process. NGENI has considerable merit in terms of computational cost because it is possible to generate transition pathways by partial degrees of freedom, while conventional methods are not capable of this. PMID:29020017

Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.

2013-12-01

The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

Genetic differentiation of the pine wilt disease vector Monochamus alternatus (Coleoptera: Cerambycidae) over a mountain range - revealed from microsatellite DNA markers.

PubMed

Shoda-Kagaya, E

2007-04-01

To study the dispersal process of the pine sawyer Monochamus alternatus (Hope) in frontier populations, a microsatellite marker-based genetic analysis was performed on expanding populations at the northern limit of its range in Japan. In Asian countries, M. alternatus is the main vector of pine wilt disease, the most serious forest disease in Japan. Sawyers were collected from nine sites near the frontier of the pine wilt disease damage area. A mountain range divides the population into western and eastern sides. Five microsatellite loci were examined and a total of 188 individuals was genotyped from each locus with the number of alleles ranged from two to nine. The mean observed heterozygosity for all loci varied from 0.282 to 0.480 in the nine sites, with an overall mean of 0.364. None of the populations have experienced a significant bottleneck. Significant differentiation was found across the mountain range, but the genetic composition was similar amongst populations of each side. It is believed that the mountain range acts as a geographical barrier to dispersal and that gene flow without a geographical barrier is high. On the west side of the mountain range, a pattern of isolation by distance was detected. This was likely to be caused by secondary contact of different colonizing routes on a small spatial scale. Based on these data, a process linking genetic structure at local (kilometres) and regional spatial scales (hundreds of kilometres) was proposed.

Estimate of accuracy of determining the orientation of the star sensor system according to the experimental data

NASA Astrophysics Data System (ADS)

Avanesov, G. A.; Bessonov, R. V.; Kurkina, A. N.; Nikitin, A. V.; Sazonov, V. V.

2018-01-01

The BOKZ-M60 star sensor (Unit for Measuring Star Coordinates) is intended for determining the parameters of the orientation of the axes of the intrinsic coordinate system relative to the axes of the inertial system by observations of the regions of the stellar sky. It is convenient to characterize an error of the single determination of the orientation of the intrinsic coordinate system of the sensor by the vector of an infinitesimal turn of this system relative to its found position. Full-scale ground-based tests have shown that, for a resting sensor the root-mean-square values of the components of this vector along the axes of the intrinsic coordinate system lying in the plane of the sensor CCD matrix are less than 2″ and the component along the axis perpendicular to the matrix plane is characterized by the root-mean-square value of 15″. The joint processing of one-stage readings of several sensors installed on the same platform allows us to improve the indicated accuracy characteristics. In this paper, estimates of the accuracy of systems from BOKZ-M60 with two and four sensors performed from measurements carried out during the normal operation of these sensors on the Resurs-P satellite are given. Processing the measurements of the sensor system allowed us to increase the accuracy of determining the each of their orientations and to study random and systematic errors in these measurements.

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

PubMed Central

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

2012-01-01

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

Rapid Detection of Volatile Oil in Mentha haplocalyx by Near-Infrared Spectroscopy and Chemometrics.

PubMed

Yan, Hui; Guo, Cheng; Shao, Yang; Ouyang, Zhen

2017-01-01

Near-infrared spectroscopy combined with partial least squares regression (PLSR) and support vector machine (SVM) was applied for the rapid determination of chemical component of volatile oil content in Mentha haplocalyx . The effects of data pre-processing methods on the accuracy of the PLSR calibration models were investigated. The performance of the final model was evaluated according to the correlation coefficient ( R ) and root mean square error of prediction (RMSEP). For PLSR model, the best preprocessing method combination was first-order derivative, standard normal variate transformation (SNV), and mean centering, which had of 0.8805, of 0.8719, RMSEC of 0.091, and RMSEP of 0.097, respectively. The wave number variables linking to volatile oil are from 5500 to 4000 cm-1 by analyzing the loading weights and variable importance in projection (VIP) scores. For SVM model, six LVs (less than seven LVs in PLSR model) were adopted in model, and the result was better than PLSR model. The and were 0.9232 and 0.9202, respectively, with RMSEC and RMSEP of 0.084 and 0.082, respectively, which indicated that the predicted values were accurate and reliable. This work demonstrated that near infrared reflectance spectroscopy with chemometrics could be used to rapidly detect the main content volatile oil in M. haplocalyx . The quality of medicine directly links to clinical efficacy, thus, it is important to control the quality of Mentha haplocalyx . Near-infrared spectroscopy combined with partial least squares regression (PLSR) and support vector machine (SVM) was applied for the rapid determination of chemical component of volatile oil content in Mentha haplocalyx . For SVM model, 6 LVs (less than 7 LVs in PLSR model) were adopted in model, and the result was better than PLSR model. It demonstrated that near infrared reflectance spectroscopy with chemometrics could be used to rapidly detect the main content volatile oil in Mentha haplocalyx . Abbreviations used: 1 st der: First-order derivative; 2 nd der: Second-order derivative; LOO: Leave-one-out; LVs: Latent variables; MC: Mean centering, NIR: Near-infrared; NIRS: Near infrared spectroscopy; PCR: Principal component regression, PLSR: Partial least squares regression; RBF: Radial basis function; RMSEC: Root mean square error of cross validation, RMSEC: Root mean square error of calibration; RMSEP: Root mean square error of prediction; SNV: Standard normal variate transformation; SVM: Support vector machine; VIP: Variable Importance in projection.

The Prediction of Broadband Shock-Associated Noise Including Propagation Effects

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2011-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock- associated noise (BBSAN) that directly incorporates the vector Green's function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) as the mean flow. The vector Green's function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation. An adjoint vector Green's function solver is implemented to determine the vector Green's function based on a locally parallel mean flow at streamwise locations of the SRANS solution. However, the developed acoustic analogy could easily be based on any adjoint vector Green's function solver, such as one that makes no assumptions about the mean flow. The newly developed acoustic analogy can be simplified to one that uses the Green's function associated with the Helmholtz equation, which is consistent with the formulation of Morris and Miller (AIAAJ 2010). A large number of predictions are generated using three different nozzles over a wide range of fully expanded Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise labs. In addition, two models for the so-called 'fine-scale' mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include the propagation effects, especially in the upstream direction of the jet.

Development of a hybrid image processing algorithm for automatic evaluation of intramuscular fat content in beef M. longissimus dorsi.

PubMed

Du, Cheng-Jin; Sun, Da-Wen; Jackman, Patrick; Allen, Paul

2008-12-01

An automatic method for estimating the content of intramuscular fat (IMF) in beef M. longissimus dorsi (LD) was developed using a sequence of image processing algorithm. To extract IMF particles within the LD muscle from structural features of intermuscular fat surrounding the muscle, three steps of image processing algorithm were developed, i.e. bilateral filter for noise removal, kernel fuzzy c-means clustering (KFCM) for segmentation, and vector confidence connected and flood fill for IMF extraction. The technique of bilateral filtering was firstly applied to reduce the noise and enhance the contrast of the beef image. KFCM was then used to segment the filtered beef image into lean, fat, and background. The IMF was finally extracted from the original beef image by using the techniques of vector confidence connected and flood filling. The performance of the algorithm developed was verified by correlation analysis between the IMF characteristics and the percentage of chemically extractable IMF content (P<0.05). Five IMF features are very significantly correlated with the fat content (P<0.001), including count densities of middle (CDMiddle) and large (CDLarge) fat particles, area densities of middle and large fat particles, and total fat area per unit LD area. The highest coefficient is 0.852 for CDLarge.

Simple cloning strategy using GFPuv gene as positive/negative indicator.

PubMed

Miura, Hiromi; Inoko, Hidetoshi; Inoue, Ituro; Tanaka, Masafumi; Sato, Masahiro; Ohtsuka, Masato

2011-09-15

Because construction of expression vectors is the first requisite in the functional analysis of genes, development of simple cloning systems is a major requirement during the postgenomic era. In the current study, we developed cloning vectors for gain- or loss-of-function studies by using the GFPuv gene as a positive/negative indicator of cloning. These vectors allow us to easily detect correct clones and obtain expression vectors from a simple procedure by means of the combined use of the GFPuv gene and a type IIS restriction enzyme. Copyright © 2011 Elsevier Inc. All rights reserved.

HOSVD-Based 3D Active Appearance Model: Segmentation of Lung Fields in CT Images.

PubMed

Wang, Qingzhu; Kang, Wanjun; Hu, Haihui; Wang, Bin

2016-07-01

An Active Appearance Model (AAM) is a computer vision model which can be used to effectively segment lung fields in CT images. However, the fitting result is often inadequate when the lungs are affected by high-density pathologies. To overcome this problem, we propose a Higher-order Singular Value Decomposition (HOSVD)-based Three-dimensional (3D) AAM. An evaluation was performed on 310 diseased lungs form the Lung Image Database Consortium Image Collection. Other contemporary AAMs operate directly on patterns represented by vectors, i.e., before applying the AAM to a 3D lung volume,it has to be vectorized first into a vector pattern by some technique like concatenation. However, some implicit structural or local contextual information may be lost in this transformation. According to the nature of the 3D lung volume, HOSVD is introduced to represent and process the lung in tensor space. Our method can not only directly operate on the original 3D tensor patterns, but also efficiently reduce the computer memory usage. The evaluation resulted in an average Dice coefficient of 97.0 % ± 0.59 %, a mean absolute surface distance error of 1.0403 ± 0.5716 mm, a mean border positioning errors of 0.9187 ± 0.5381 pixel, and a Hausdorff Distance of 20.4064 ± 4.3855, respectively. Experimental results showed that our methods delivered significant and better segmentation results, compared with the three other model-based lung segmentation approaches, namely 3D Snake, 3D ASM and 3D AAM.

Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator.

PubMed

Khazendar, S; Sayasneh, A; Al-Assam, H; Du, H; Kaijser, J; Ferrara, L; Timmerman, D; Jassim, S; Bourne, T

2015-01-01

Preoperative characterisation of ovarian masses into benign or malignant is of paramount importance to optimise patient management. In this study, we developed and validated a computerised model to characterise ovarian masses as benign or malignant. Transvaginal 2D B mode static ultrasound images of 187 ovarian masses with known histological diagnosis were included. Images were first pre-processed and enhanced, and Local Binary Pattern Histograms were then extracted from 2 × 2 blocks of each image. A Support Vector Machine (SVM) was trained using stratified cross validation with randomised sampling. The process was repeated 15 times and in each round 100 images were randomly selected. The SVM classified the original non-treated static images as benign or malignant masses with an average accuracy of 0.62 (95% CI: 0.59-0.65). This performance significantly improved to an average accuracy of 0.77 (95% CI: 0.75-0.79) when images were pre-processed, enhanced and treated with a Local Binary Pattern operator (mean difference 0.15: 95% 0.11-0.19, p < 0.0001, two-tailed t test). We have shown that an SVM can classify static 2D B mode ultrasound images of ovarian masses into benign and malignant categories. The accuracy improves if texture related LBP features extracted from the images are considered.

Principal fiber bundle description of number scaling for scalars and vectors: application to gauge theory

NASA Astrophysics Data System (ADS)

Benioff, Paul

2015-05-01

The purpose of this paper is to put the description of number scaling and its effects on physics and geometry on a firmer foundation, and to make it more understandable. A main point is that two different concepts, number and number value are combined in the usual representations of number structures. This is valid as long as just one structure of each number type is being considered. It is not valid when different structures of each number type are being considered. Elements of base sets of number structures, considered by themselves, have no meaning. They acquire meaning or value as elements of a number structure. Fiber bundles over a space or space time manifold, M, are described. The fiber consists of a collection of many real or complex number structures and vector space structures. The structures are parameterized by a real or complex scaling factor, s. A vector space at a fiber level, s, has, as scalars, real or complex number structures at the same level. Connections are described that relate scalar and vector space structures at both neighbor M locations and at neighbor scaling levels. Scalar and vector structure valued fields are described and covariant derivatives of these fields are obtained. Two complex vector fields, each with one real and one imaginary field, appear, with one complex field associated with positions in M and the other with position dependent scaling factors. A derivation of the covariant derivative for scalar and vector valued fields gives the same vector fields. The derivation shows that the complex vector field associated with scaling fiber levels is the gradient of a complex scalar field. Use of these results in gauge theory shows that the imaginary part of the vector field associated with M positions acts like the electromagnetic field. The physical relevance of the other three fields, if any, is not known.

Thermodynamic integration of the free energy along a reaction coordinate in Cartesian coordinates

NASA Astrophysics Data System (ADS)

den Otter, W. K.

2000-05-01

A generalized formulation of the thermodynamic integration (TI) method for calculating the free energy along a reaction coordinate is derived. Molecular dynamics simulations with a constrained reaction coordinate are used to sample conformations. These are then projected onto conformations with a higher value of the reaction coordinate by means of a vector field. The accompanying change in potential energy plus the divergence of the vector field constitute the derivative of the free energy. Any vector field meeting some simple requirements can be used as the basis of this TI expression. Two classes of vector fields are of particular interest here. The first recovers the conventional TI expression, with its cumbersome dependence on a full set of generalized coordinates. As the free energy is a function of the reaction coordinate only, it should in principle be possible to derive an expression depending exclusively on the definition of the reaction coordinate. This objective is met by the second class of vector fields to be discussed. The potential of mean constraint force (PMCF) method, after averaging over the unconstrained momenta, falls in this second class. The new method is illustrated by calculations on the isomerization of n-butane, and is compared with existing methods.

[Orthogonal Vector Projection Algorithm for Spectral Unmixing].

PubMed

Song, Mei-ping; Xu, Xing-wei; Chang, Chein-I; An, Ju-bai; Yao, Li

2015-12-01

Spectrum unmixing is an important part of hyperspectral technologies, which is essential for material quantity analysis in hyperspectral imagery. Most linear unmixing algorithms require computations of matrix multiplication and matrix inversion or matrix determination. These are difficult for programming, especially hard for realization on hardware. At the same time, the computation costs of the algorithms increase significantly as the number of endmembers grows. Here, based on the traditional algorithm Orthogonal Subspace Projection, a new method called. Orthogonal Vector Projection is prompted using orthogonal principle. It simplifies this process by avoiding matrix multiplication and inversion. It firstly computes the final orthogonal vector via Gram-Schmidt process for each endmember spectrum. And then, these orthogonal vectors are used as projection vector for the pixel signature. The unconstrained abundance can be obtained directly by projecting the signature to the projection vectors, and computing the ratio of projected vector length and orthogonal vector length. Compared to the Orthogonal Subspace Projection and Least Squares Error algorithms, this method does not need matrix inversion, which is much computation costing and hard to implement on hardware. It just completes the orthogonalization process by repeated vector operations, easy for application on both parallel computation and hardware. The reasonability of the algorithm is proved by its relationship with Orthogonal Sub-space Projection and Least Squares Error algorithms. And its computational complexity is also compared with the other two algorithms', which is the lowest one. At last, the experimental results on synthetic image and real image are also provided, giving another evidence for effectiveness of the method.

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

PubMed

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

2009-11-01

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

Optical computing and image processing using photorefractive gallium arsenide

NASA Technical Reports Server (NTRS)

Cheng, Li-Jen; Liu, Duncan T. H.

1990-01-01

Recent experimental results on matrix-vector multiplication and multiple four-wave mixing using GaAs are presented. Attention is given to a simple concept of using two overlapping holograms in GaAs to do two matrix-vector multiplication processes operating in parallel with a common input vector. This concept can be used to construct high-speed, high-capacity, reconfigurable interconnection and multiplexing modules, important for optical computing and neural-network applications.

Agate Beach BOBr Processed Breaking Wave Data

DOE Data Explorer

Adam C Brown

2013-10-31

This data was recorded of the coast of Newport, OR at Agate Beach in the surf zone. The data was recorded by a 9dof inertial measurement unit and consists of a timestamp, quaternion orientation, acceleration vector, rotation vector, and magnetic vector. The acceleration, rotation, and magnetic vectors have all been corrected back to a North East Down reference frame.

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.

Remote sensing of earth terrain

NASA Technical Reports Server (NTRS)

Kong, J. A.

1988-01-01

Two monographs and 85 journal and conference papers on remote sensing of earth terrain have been published, sponsored by NASA Contract NAG5-270. A multivariate K-distribution is proposed to model the statistics of fully polarimetric data from earth terrain with polarizations HH, HV, VH, and VV. In this approach, correlated polarizations of radar signals, as characterized by a covariance matrix, are treated as the sum of N n-dimensional random vectors; N obeys the negative binomial distribution with a parameter alpha and mean bar N. Subsequently, and n-dimensional K-distribution, with either zero or non-zero mean, is developed in the limit of infinite bar N or illuminated area. The probability density function (PDF) of the K-distributed vector normalized by its Euclidean norm is independent of the parameter alpha and is the same as that derived from a zero-mean Gaussian-distributed random vector. The above model is well supported by experimental data provided by MIT Lincoln Laboratory and the Jet Propulsion Laboratory in the form of polarimetric measurements.

The potential of latent semantic analysis for machine grading of clinical case summaries.

PubMed

Kintsch, Walter

2002-02-01

This paper introduces latent semantic analysis (LSA), a machine learning method for representing the meaning of words, sentences, and texts. LSA induces a high-dimensional semantic space from reading a very large amount of texts. The meaning of words and texts can be represented as vectors in this space and hence can be compared automatically and objectively. A generative theory of the mental lexicon based on LSA is described. The word vectors LSA constructs are context free, and each word, irrespective of how many meanings or senses it has, is represented by a single vector. However, when a word is used in different contexts, context appropriate word senses emerge. Several applications of LSA to educational software are described, involving the ability of LSA to quickly compare the content of texts, such as an essay written by a student and a target essay. An LSA-based software tool is sketched for machine grading of clinical case summaries written by medical students.

The use of computer-generated color graphic images for transient thermal analysis. [for hypersonic aircraft

NASA Technical Reports Server (NTRS)

Edwards, C. L. W.; Meissner, F. T.; Hall, J. B.

1979-01-01

Color computer graphics techniques were investigated as a means of rapidly scanning and interpreting large sets of transient heating data. The data presented were generated to support the conceptual design of a heat-sink thermal protection system (TPS) for a hypersonic research airplane. Color-coded vector and raster displays of the numerical geometry used in the heating calculations were employed to analyze skin thicknesses and surface temperatures of the heat-sink TPS under a variety of trajectory flight profiles. Both vector and raster displays proved to be effective means for rapidly identifying heat-sink mass concentrations, regions of high heating, and potentially adverse thermal gradients. The color-coded (raster) surface displays are a very efficient means for displaying surface-temperature and heating histories, and thereby the more stringent design requirements can quickly be identified. The related hardware and software developments required to implement both the vector and the raster displays for this application are also discussed.

Definition of Contravariant Velocity Components

NASA Technical Reports Server (NTRS)

Hung, Ching-moa; Kwak, Dochan (Technical Monitor)

2002-01-01

In this paper we have reviewed the basics of tensor analysis in an attempt to clarify some misconceptions regarding contravariant and covariant vector components as used in fluid dynamics. We have indicated that contravariant components are components of a given vector expressed as a unique combination of the covariant base vector system and, vice versa, that the covariant components are components of a vector expressed with the contravariant base vector system. Mathematically, expressing a vector with a combination of base vector is a decomposition process for a specific base vector system. Hence, the contravariant velocity components are decomposed components of velocity vector along the directions of coordinate lines, with respect to the covariant base vector system. However, the contravariant (and covariant) components are not physical quantities. Their magnitudes and dimensions are controlled by their corresponding covariant (and contravariant) base vectors.

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

NASA Technical Reports Server (NTRS)

Chen, Hsin-Chu; He, Ai-Fang

1993-01-01

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

2016-05-01

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

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.

Dark forces coupled to nonconserved currents

NASA Astrophysics Data System (ADS)

Dror, Jeff A.; Lasenby, Robert; Pospelov, Maxim

2017-10-01

New light vectors with dimension-4 couplings to Standard Model states have (energy/vectormass)2-enhanced production rates unless the current they couple to is conserved. These processes allow us to derive new constraints on the couplings of such vectors, that are significantly stronger than the previous literature for a wide variety of models. Examples include vectors with axial couplings to quarks and vectors coupled to currents (such as baryon number) that are only broken by the chiral anomaly. Our new limits arise from a range of processes, including rare Z decays and flavor-changing meson decays, and rule out a number of phenomenologically motivated proposals.

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

NASA Technical Reports Server (NTRS)

Rutishauser, David

2006-01-01

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Simultaneous Inference Procedures for Means.

ERIC Educational Resources Information Center

Krishnaiah, P. R.

Some aspects of simultaneous tests for means are reviewed. Specifically, the comparison of univariate or multivariate normal populations based on the values of the means or mean vectors when the variances or covariance matrices are equal is discussed. Tukey's and Dunnett's tests for multiple comparisons of means, Scheffe's method of examining…

40 CFR 240.206 - Vectors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 24 2010-07-01 2010-07-01 false Vectors. 240.206 Section 240.206 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) SOLID WASTES GUIDELINES FOR THE THERMAL PROCESSING OF SOLID WASTES Requirements and Recommended Procedures § 240.206 Vectors. ...

Transcriptome of the adult female malaria mosquito vector Anopheles albimanus.

PubMed

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

2012-05-30

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

Benchmarking GPU and CPU codes for Heisenberg spin glass over-relaxation

NASA Astrophysics Data System (ADS)

Bernaschi, M.; Parisi, G.; Parisi, L.

2011-06-01

We present a set of possible implementations for Graphics Processing Units (GPU) of the Over-relaxation technique applied to the 3D Heisenberg spin glass model. The results show that a carefully tuned code can achieve more than 100 GFlops/s of sustained performance and update a single spin in about 0.6 nanoseconds. A multi-hit technique that exploits the GPU shared memory further reduces this time. Such results are compared with those obtained by means of a highly-tuned vector-parallel code on latest generation multi-core CPUs.

Data Mining Methods for Recommender Systems

NASA Astrophysics Data System (ADS)

Amatriain, Xavier; Jaimes*, Alejandro; Oliver, Nuria; Pujol, Josep M.

In this chapter, we give an overview of the main Data Mining techniques used in the context of Recommender Systems. We first describe common preprocessing methods such as sampling or dimensionality reduction. Next, we review the most important classification techniques, including Bayesian Networks and Support Vector Machines. We describe the k-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

V+jets Background and Systematic Uncertainties in Top Quark Analyses

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

Adomeit, Stefanie; Peters, Reinhild Yvonne

2014-12-01

Vector boson production in association with jets is an important process to test perturbative quantum chromodynamics and also a background process in top quark analyses. Measurements on vector boson production in association with light and heavy flavour jets are presented, performed by the D0 and CDF collaborations at the Tevatron as well as the ATLAS and CMS experiments at LHC. Techniques applied in top quark analyses to estimate the vector boson+jets background are also discussed.

The magnetic field investigation on Cluster

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

GaAs Supercomputing: Architecture, Language, And Algorithms For Image Processing

NASA Astrophysics Data System (ADS)

Johl, John T.; Baker, Nick C.

1988-10-01

The application of high-speed GaAs processors in a parallel system matches the demanding computational requirements of image processing. The architecture of the McDonnell Douglas Astronautics Company (MDAC) vector processor is described along with the algorithms and language translator. Most image and signal processing algorithms can utilize parallel processing and show a significant performance improvement over sequential versions. The parallelization performed by this system is within each vector instruction. Since each vector has many elements, each requiring some computation, useful concurrent arithmetic operations can easily be performed. Balancing the memory bandwidth with the computation rate of the processors is an important design consideration for high efficiency and utilization. The architecture features a bus-based execution unit consisting of four to eight 32-bit GaAs RISC microprocessors running at a 200 MHz clock rate for a peak performance of 1.6 BOPS. The execution unit is connected to a vector memory with three buses capable of transferring two input words and one output word every 10 nsec. The address generators inside the vector memory perform different vector addressing modes and feed the data to the execution unit. The functions discussed in this paper include basic MATRIX OPERATIONS, 2-D SPATIAL CONVOLUTION, HISTOGRAM, and FFT. For each of these algorithms, assembly language programs were run on a behavioral model of the system to obtain performance figures.

Estimation of the daily global solar radiation based on the Gaussian process regression methodology in the Saharan climate

NASA Astrophysics Data System (ADS)

Guermoui, Mawloud; Gairaa, Kacem; Rabehi, Abdelaziz; Djafer, Djelloul; Benkaciali, Said

2018-06-01

Accurate estimation of solar radiation is the major concern in renewable energy applications. Over the past few years, a lot of machine learning paradigms have been proposed in order to improve the estimation performances, mostly based on artificial neural networks, fuzzy logic, support vector machine and adaptive neuro-fuzzy inference system. The aim of this work is the prediction of the daily global solar radiation, received on a horizontal surface through the Gaussian process regression (GPR) methodology. A case study of Ghardaïa region (Algeria) has been used in order to validate the above methodology. In fact, several combinations have been tested; it was found that, GPR-model based on sunshine duration, minimum air temperature and relative humidity gives the best results in term of mean absolute bias error (MBE), root mean square error (RMSE), relative mean square error (rRMSE), and correlation coefficient ( r) . The obtained values of these indicators are 0.67 MJ/m2, 1.15 MJ/m2, 5.2%, and 98.42%, respectively.

Divide and Recombine for Large Complex Data

DTIC Science & Technology

2017-12-01

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

Response to Blood Meal in the Fat Body of Anopheles stephensi Using Quantitative Proteomics: Toward New Vector Control Strategies Against Malaria.

PubMed

Kumar, Manish; Mohanty, Ajeet Kumar; Sreenivasamurthy, Sreelakshmi K; Dey, Gourav; Advani, Jayshree; Pinto, Sneha M; Kumar, Ashwani; Prasad, Thottethodi Subrahmanya Keshava

2017-09-01

Malaria remains a grand challenge for disruptive innovation in global health therapeutics and diagnostics. Anopheles stephensi is one of the major vectors of malaria in Asia. Vector and transmission control are key focus areas in the fight against malaria, a field of postgenomics research where proteomics can play a substantive role. Moreover, to identify novel strategies to control the vector population, it is necessary to understand the vector life processes at a global and molecular scale. In this context, fat body is a vital organ required for vitellogenesis, vector immunity, vector physiology, and vector-parasite interaction. Given its central role in energy metabolism, vitellogenesis, and immune function, the proteome profile of the fat body and the impact of blood meal (BM) ingestion on the protein abundances of this vital organ have not been investigated so far. Therefore, using a proteomics approach, we identified the proteins expressed in the fat body of An. stephensi and their differential expression in response to BM ingestion. In all, we identified 3,218 proteins in the fat body using high-resolution mass spectrometry, of which 483 were found to be differentially expressed in response to the BM ingestion. Bioinformatics analysis of these proteins underscored their role in amino acid metabolism, vitellogenesis, lipid transport, signal peptide processing, mosquito immunity, and oxidation-reduction processes. Interestingly, we identified five novel genes, which were found to be differentially expressed upon BM ingestion. Proteins that exhibited altered expression in the present study are potential targets for vector control strategies and development of transmission blocking vaccines in the fight against malaria.

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

PubMed

Campos, Samuel K; Barry, Michael A

2004-11-01

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

Deterministic binary vectors for efficient automated indexing of MEDLINE/PubMed abstracts.

PubMed

Wahle, Manuel; Widdows, Dominic; Herskovic, Jorge R; Bernstam, Elmer V; Cohen, Trevor

2012-01-01

The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI.

Deterministic Binary Vectors for Efficient Automated Indexing of MEDLINE/PubMed Abstracts

PubMed Central

Wahle, Manuel; Widdows, Dominic; Herskovic, Jorge R.; Bernstam, Elmer V.; Cohen, Trevor

2012-01-01

The need to maintain accessibility of the biomedical literature has led to development of methods to assist human indexers by recommending index terms for newly encountered articles. Given the rapid expansion of this literature, it is essential that these methods be scalable. Document vector representations are commonly used for automated indexing, and Random Indexing (RI) provides the means to generate them efficiently. However, RI is difficult to implement in real-world indexing systems, as (1) efficient nearest-neighbor search requires retaining all document vectors in RAM, and (2) it is necessary to maintain a store of randomly generated term vectors to index future documents. Motivated by these concerns, this paper documents the development and evaluation of a deterministic binary variant of RI. The increased capacity demonstrated by binary vectors has implications for information retrieval, and the elimination of the need to retain term vectors facilitates distributed implementations, enhancing the scalability of RI. PMID:23304369

Manipulation of dielectric Rayleigh particles using highly focused elliptically polarized vector fields.

PubMed

Gu, Bing; Xu, Danfeng; Rui, Guanghao; Lian, Meng; Cui, Yiping; Zhan, Qiwen

2015-09-20

Generation of vectorial optical fields with arbitrary polarization distribution is of great interest in areas where exotic optical fields are desired. In this work, we experimentally demonstrate the versatile generation of linearly polarized vector fields, elliptically polarized vector fields, and circularly polarized vortex beams through introducing attenuators in a common-path interferometer. By means of Richards-Wolf vectorial diffraction method, the characteristics of the highly focused elliptically polarized vector fields are studied. The optical force and torque on a dielectric Rayleigh particle produced by these tightly focused vector fields are calculated and exploited for the stable trapping of dielectric Rayleigh particles. It is shown that the additional degree of freedom provided by the elliptically polarized vector field allows one to control the spatial structure of polarization, to engineer the focusing field, and to tailor the optical force and torque on a dielectric Rayleigh particle.

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

PubMed Central

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

2009-01-01

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

Optical implementation of systolic array processing

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Backward and forward Monte Carlo method for vector radiative transfer in a two-dimensional graded index medium

NASA Astrophysics Data System (ADS)

Qian, Lin-Feng; Shi, Guo-Dong; Huang, Yong; Xing, Yu-Ming

2017-10-01

In vector radiative transfer, backward ray tracing is seldom used. We present a backward and forward Monte Carlo method to simulate vector radiative transfer in a two-dimensional graded index medium, which is new and different from the conventional Monte Carlo method. The backward and forward Monte Carlo method involves dividing the ray tracing into two processes backward tracing and forward tracing. In multidimensional graded index media, the trajectory of a ray is usually a three-dimensional curve. During the transport of a polarization ellipse, the curved ray trajectory will induce geometrical effects and cause Stokes parameters to continuously change. The solution processes for a non-scattering medium and an anisotropic scattering medium are analysed. We also analyse some parameters that influence the Stokes vector in two-dimensional graded index media. The research shows that the Q component of the Stokes vector cannot be ignored. However, the U and V components of the Stokes vector are very small.

Numerical simulation of air distribution in a room with a sidewall jet under benchmark test conditions

NASA Astrophysics Data System (ADS)

Zasimova, Marina; Ivanov, Nikolay

2018-05-01

The goal of the study is to validate Large Eddy Simulation (LES) data on mixing ventilation in an isothermal room at conditions of benchmark experiments by Hurnik et al. (2015). The focus is on the accuracy of the mean and rms velocity fields prediction in the quasi-free jet zone of the room with 3D jet supplied from a sidewall rectangular diffuser. Calculations were carried out using the ANSYS Fluent 16.2 software with an algebraic wall-modeled LES subgrid-scale model. CFD results on the mean velocity vector are compared with the Laser Doppler Anemometry data. The difference between the mean velocity vector and the mean air speed in the jet zone, both LES-computed, is presented and discussed.

A model for predicting field-directed particle transport in the magnetofection process.

PubMed

Furlani, Edward P; Xue, Xiaozheng

2012-05-01

To analyze the magnetofection process in which magnetic carrier particles with surface-bound gene vectors are attracted to target cells for transfection using an external magnetic field and to obtain a fundamental understanding of the impact of key factors such as particle size and field strength on the gene delivery process. A numerical model is used to study the field-directed transport of the carrier particle-gene vector complex to target cells in a conventional multiwell culture plate system. The model predicts the transport dynamics and the distribution of particle accumulation at the target cells. The impact of several factors that strongly influence gene vector delivery is assessed including the properties of the carrier particles, the strength of the field source, and its extent and proximity relative to the target cells. The study demonstrates that modeling can be used to predict and optimize gene vector delivery in the magnetofection process for novel and conventional in vitro systems.

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).

Mathematical modeling of Chikungunya fever control

NASA Astrophysics Data System (ADS)

Hincapié-Palacio, Doracelly; Ospina, Juan

2015-05-01

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

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.

Optical implementation of inner product neural associative memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor)

1995-01-01

An optical implementation of an inner-product neural associative memory is realized with a first spatial light modulator for entering an initial two-dimensional N-tuple vector and for entering a thresholded output vector image after each iteration until convergence is reached, and a second spatial light modulator for entering M weighted vectors of inner-product scalars multiplied with each of the M stored vectors, where the inner-product scalars are produced by multiplication of the initial input vector in the first iterative cycle (and thresholded vectors in subsequent iterative cycles) with each of the M stored vectors, and the weighted vectors are produced by multiplication of the scalars with corresponding ones of the stored vectors. A Hughes liquid crystal light valve is used for the dual function of summing the weighted vectors and thresholding the sum vector. The thresholded vector is then entered through the first spatial light modulator for reiteration of the process cycle until convergence is reached.

Photodynamic diagnosis of bladder cancer in ex vivo urine cytology

NASA Astrophysics Data System (ADS)

Fu, C. Y.; Ng, B. K.; Razul, S. Gulam; Olivo, Malini C.; Lau, Weber K. O.; Tan, P. H.; Chin, William

2006-02-01

Bladder cancer is the fourth common malignant disease worldwide, accounting for 4% of all cancer cases. In Singapore, it is the ninth most common form of cancer. The high mortality rate can be reduced by early treatment following precancerous screening. Currently, the gold standard for screening bladder tumors is histological examination of biopsy specimen, which is both invasive and time-consuming. In this study ex vivo urine fluorescence cytology is investigated to offer a timely and biopsy-free means for detecting bladder cancers. Sediments in patients' urine samples were extracted and incubated with a novel photosensitizer, hypericin. Laser confocal microscopy was used to capture the fluorescence images at an excitation wavelength of 488 nm. Images were subsequently processed to single out the exfoliated bladder cells from the other cells based on the cellular size. Intensity histogram of each targeted cell was plotted and feature vectors, derived from the histogram moments, were used to represent each sample. A difference in the distribution of the feature vectors of normal and low-grade cancerous bladder cells was observed. Diagnostic algorithm for discriminating between normal and low-grade cancerous cells is elucidated in this paper. This study suggests that the fluorescence intensity profiles of hypericin in bladder cells can potentially provide an automated quantitative means of early bladder cancer diagnosis.

Simple satellite orbit propagator

NASA Astrophysics Data System (ADS)

Gurfil, P.

2008-06-01

An increasing number of space missions require on-board autonomous orbit determination. The purpose of this paper is to develop a simple orbit propagator (SOP) for such missions. Since most satellites are limited by the available processing power, it is important to develop an orbit propagator that will use limited computational and memory resources. In this work, we show how to choose state variables for propagation using the simplest numerical integration scheme available-the explicit Euler integrator. The new state variables are derived by the following rationale: Apply a variation-of-parameters not on the gravity-affected orbit, but rather on the gravity-free orbit, and teart the gravity as a generalized force. This ultimately leads to a state vector comprising the inertial velocity and a modified position vector, wherein the product of velocity and time is subtracted from the inertial position. It is shown that the explicit Euler integrator, applied on the new state variables, becomes a symplectic integrator, preserving the Hamiltonian and the angular momentum (or a component thereof in the case of oblateness perturbations). The main application of the proposed propagator is estimation of mean orbital elements. It is shown that the SOP is capable of estimating the mean elements with an accuracy that is comparable to a high-order integrator that consumes an order-of-magnitude more computational time than the SOP.

Proteome-wide analysis of Anopheles culicifacies mosquito midgut: new insights into the mechanism of refractoriness.

PubMed

Vijay, Sonam; Rawal, Ritu; Kadian, Kavita; Singh, Jagbir; Adak, Tridibesh; Sharma, Arun

2018-05-08

Midgut invasion, a major bottleneck for malaria parasites transmission is considered as a potential target for vector-parasite interaction studies. New intervention strategies are required to explore the midgut proteins and their potential role in refractoriness for malaria control in Anopheles mosquitoes. To better understand the midgut functional proteins of An. culicifacies susceptible and refractory species, proteomic approaches coupled with bioinformatics analysis is an effective means in order to understand the mechanism of refractoriness. In the present study, an integrated in solution- in gel trypsin digestion approach, along with Isobaric tag for relative and absolute quantitation (iTRAQ)-Liquid chromatography/Mass spectrometry (LC/MS/MS) and data mining were performed to identify the proteomic profile and differentially expressed proteins in Anopheles culicifacies susceptible species A and refractory species B. Shot gun proteomics approaches led to the identification of 80 proteins in An. culicifacies susceptible species A and 92 in refractory species B and catalogue was prepared. iTRAQ based proteomic analysis identified 48 differentially expressed proteins from total 130 proteins. Of these, 41 were downregulated and 7 were upregulated in refractory species B in comparison to susceptible species A. We report that the altered midgut proteins identified in naturally refractory mosquitoes are involved in oxidative phosphorylation, antioxidant and proteolysis process that may suggest their role in parasite growth inhibition. Furthermore, real time polymerase chain reaction (PCR) analysis of few proteins indicated higher expression of iTRAQ upregulated protein in refractory species than susceptible species. This study elucidates the first proteome of the midguts of An. culicifacies sibling species that attempts to analyze unique proteogenomic interactions to provide insights for better understanding of the mechanism of refractoriness. Functional implications of these upregulated proteins in refractory species may reflect the phenotypic characteristics of the mosquitoes and will improve our understandings of blood meal digestion process, parasite vector interactions and proteomes of other vectors of human diseases for development of novel vector control strategies.

Optoelectronic Inner-Product Neural Associative Memory

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1993-01-01

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

Wind speed vector restoration algorithm

NASA Astrophysics Data System (ADS)

Baranov, Nikolay; Petrov, Gleb; Shiriaev, Ilia

2018-04-01

Impulse wind lidar (IWL) signal processing software developed by JSC «BANS» recovers full wind speed vector by radial projections and provides wind parameters information up to 2 km distance. Increasing accuracy and speed of wind parameters calculation signal processing technics have been studied in this research. Measurements results of IWL and continuous scanning lidar were compared. Also, IWL data processing modeling results have been analyzed.

Agreement of Power Measures between Garmin Vector and SRM Cycle Power Meters

ERIC Educational Resources Information Center

Novak, Andrew R.; Dascombe, Benjamin J.

2016-01-01

This study aimed to determine if the Garmin Vector (Schaffhausen, Switzerland) power meter produced acceptable measures when compared with the Schoberer Rad Messetechnik (SRM; Julich, Germany) power meter across a range of high-intensity efforts. Twenty-one well-trained cyclists completed power profiles (seven maximal mean efforts between 5 and…

A GaAs vector processor based on parallel RISC microprocessors

NASA Astrophysics Data System (ADS)

Misko, Tim A.; Rasset, Terry L.

A vector processor architecture based on the development of a 32-bit microprocessor using gallium arsenide (GaAs) technology has been developed. The McDonnell Douglas vector processor (MVP) will be fabricated completely from GaAs digital integrated circuits. The MVP architecture includes a vector memory of 1 megabyte, a parallel bus architecture with eight processing elements connected in parallel, and a control processor. The processing elements consist of a reduced instruction set CPU (RISC) with four floating-point coprocessor units and necessary memory interface functions. This architecture has been simulated for several benchmark programs including complex fast Fourier transform (FFT), complex inner product, trigonometric functions, and sort-merge routine. The results of this study indicate that the MVP can process a 1024-point complex FFT at a speed of 112 microsec (389 megaflops) while consuming approximately 618 W of power in a volume of approximately 0.1 ft-cubed.

An Algorithm for Converting Static Earth Sensor Measurements into Earth Observation Vectors

NASA Technical Reports Server (NTRS)

Harman, R.; Hashmall, Joseph A.; Sedlak, Joseph

2004-01-01

An algorithm has been developed that converts penetration angles reported by Static Earth Sensors (SESs) into Earth observation vectors. This algorithm allows compensation for variation in the horizon height including that caused by Earth oblateness. It also allows pitch and roll to be computed using any number (greater than 1) of simultaneous sensor penetration angles simplifying processing during periods of Sun and Moon interference. The algorithm computes body frame unit vectors through each SES cluster. It also computes GCI vectors from the spacecraft to the position on the Earth's limb where each cluster detects the Earth's limb. These body frame vectors are used as sensor observation vectors and the GCI vectors are used as reference vectors in an attitude solution. The attitude, with the unobservable yaw discarded, is iteratively refined to provide the Earth observation vector solution.

Clinical applications of retinal gene therapy.

PubMed

Lipinski, Daniel M; Thake, Miriam; MacLaren, Robert E

2013-01-01

Many currently incurable forms of blindness affecting the retina have a genetic etiology and several others, such as those resulting from retinal vascular disturbances, respond to repeated, potentially indefinite administration of molecular based treatments. The recent clinical advances in retinal gene therapy have shown that viral vectors can deliver genes safely to the retina and the promising initial results from a number of clinical trials suggest that certain diseases may potentially be treatable. Gene therapy provides a means of expressing proteins within directly transduced cells with far greater efficacy than might be achieved by traditional systemic pharmacological approaches. Recent developments have demonstrated how vector gene expression may be regulated and further improvements to vector design have limited side effects and improved safety profiles. These recent steps have been most significant in bringing gene therapy into the mainstream of ophthalmology. Nevertheless translating retinal gene therapy from animal research into clinical trials is still a lengthy process, including complexities in human retinal diseases that have been difficult to model in the laboratory. The focus of this review is to summarize the genetic background of the most common retinal diseases, highlight current concepts of gene delivery technology, and relate those technologies to pre-clinical and clinical gene therapy studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identification of Migratory Insects from their Physical Features using a Decision-Tree Support Vector Machine and its Application to Radar Entomology.

PubMed

Hu, Cheng; Kong, Shaoyang; Wang, Rui; Long, Teng; Fu, Xiaowei

2018-04-03

Migration is a key process in the population dynamics of numerous insect species, including many that are pests or vectors of disease. Identification of insect migrants is critically important to studies of insect migration. Radar is an effective means of monitoring nocturnal insect migrants. However, species identification of migrating insects is often unachievable with current radar technology. Special-purpose entomological radar can measure radar cross-sections (RCSs) from which the insect mass, wingbeat frequency and body length-to-width ratio (a measure of morphological form) can be estimated. These features may be valuable for species identification. This paper explores the identification of insect migrants based on the mass, wingbeat frequency and length-to-width ratio, and body length is also introduced to assess the benefit of adding another variable. A total of 23 species of migratory insects captured by a searchlight trap are used to develop a classification model based on decision-tree support vector machine method. The results reveal that the identification accuracy exceeds 80% for all species if the mass, wingbeat frequency and length-to-width ratio are utilized, and the addition of body length is shown to further increase accuracy. It is also shown that improving the precision of the measurements leads to increased identification accuracy.

On scalar and vector fields coupled to the energy-momentum tensor

NASA Astrophysics Data System (ADS)

Jiménez, Jose Beltrán; Cembranos, Jose A. R.; Sánchez Velázquez, Jose M.

2018-05-01

We consider theories for scalar and vector fields coupled to the energy-momentum tensor. Since these fields also carry a non-trivial energy-momentum tensor, the coupling prescription generates self-interactions. In analogy with gravity theories, we build the action by means of an iterative process that leads to an infinite series, which can be resumed as the solution of a set of differential equations. We show that, in some particular cases, the equations become algebraic and that is also possible to find solutions in the form of polynomials. We briefly review the case of the scalar field that has already been studied in the literature and extend the analysis to the case of derivative (disformal) couplings. We then explore theories with vector fields, distinguishing between gauge-and non-gauge-invariant couplings. Interactions with matter are also considered, taking a scalar field as a proxy for the matter sector. We also discuss the ambiguity introduced by superpotential (boundary) terms in the definition of the energy-momentum tensor and use them to show that it is also possible to generate Galileon-like interactions with this procedure. We finally use collider and astrophysical observations to set constraints on the dimensionful coupling which characterises the phenomenology of these models.

A comparative study of DIGNET, average, complete, single hierarchical and k-means clustering algorithms in 2D face image recognition

NASA Astrophysics Data System (ADS)

Thanos, Konstantinos-Georgios; Thomopoulos, Stelios C. A.

2014-06-01

The study in this paper belongs to a more general research of discovering facial sub-clusters in different ethnicity face databases. These new sub-clusters along with other metadata (such as race, sex, etc.) lead to a vector for each face in the database where each vector component represents the likelihood of participation of a given face to each cluster. This vector is then used as a feature vector in a human identification and tracking system based on face and other biometrics. The first stage in this system involves a clustering method which evaluates and compares the clustering results of five different clustering algorithms (average, complete, single hierarchical algorithm, k-means and DIGNET), and selects the best strategy for each data collection. In this paper we present the comparative performance of clustering results of DIGNET and four clustering algorithms (average, complete, single hierarchical and k-means) on fabricated 2D and 3D samples, and on actual face images from various databases, using four different standard metrics. These metrics are the silhouette figure, the mean silhouette coefficient, the Hubert test Γ coefficient, and the classification accuracy for each clustering result. The results showed that, in general, DIGNET gives more trustworthy results than the other algorithms when the metrics values are above a specific acceptance threshold. However when the evaluation results metrics have values lower than the acceptance threshold but not too low (too low corresponds to ambiguous results or false results), then it is necessary for the clustering results to be verified by the other algorithms.

Is there a role for symbiotic bacteria in plant virus transmission?

USDA-ARS?s Scientific Manuscript database

During the process of circulative plant virus transmission by insect vectors, viruses interact with different insect vector tissues prior to transmission to a new host plant. An area of intense debate in the field is whether bacterial symbionts of insect vectors are involved in the virus transmissi...

A comprehensive data processing plan for crop calendar MSS signature development from satellite imagery: Crop identification using vegetation phenology

NASA Technical Reports Server (NTRS)

Hlavka, C. A. (Principal Investigator); Carlyle, S. M.; Haralick, R. M.; Yokoyama, R.

1978-01-01

The author has identified the following significant results. The phenological method of crop identification involves the creation of crop signatures which characterize multispectral observations as phenological growth states. The phenological signature models spectral reflectance explicitly as a function of crop maturity rather than as a function of date. A correspondence of time to growth state is established which minimizes the smallest difference between the given multispectral multitemporal vector and a category mean vector. The application of the method to the identification of winter wheat and corn shows (1) the method is capable of discriminating crop type with about the same degree of accuracy as more traditional classifiers; (2) the use of LANDSAT observations on two or more dates yields better results than the use of a single observation; and (3) some potential is demonstrated for labeling the degree of maturity of the crop, as well as the crop type.

A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer.

PubMed

Khan, Adil Mehmood; Lee, Young-Koo; Lee, Sungyoung Y; Kim, Tae-Seong

2010-09-01

Physical-activity recognition via wearable sensors can provide valuable information regarding an individual's degree of functional ability and lifestyle. In this paper, we present an accelerometer sensor-based approach for human-activity recognition. Our proposed recognition method uses a hierarchical scheme. At the lower level, the state to which an activity belongs, i.e., static, transition, or dynamic, is recognized by means of statistical signal features and artificial-neural nets (ANNs). The upper level recognition uses the autoregressive (AR) modeling of the acceleration signals, thus, incorporating the derived AR-coefficients along with the signal-magnitude area and tilt angle to form an augmented-feature vector. The resulting feature vector is further processed by the linear-discriminant analysis and ANNs to recognize a particular human activity. Our proposed activity-recognition method recognizes three states and 15 activities with an average accuracy of 97.9% using only a single triaxial accelerometer attached to the subject's chest.

CRITICAL EVALUATION OF THE EFFECTIVENESS OF SEWAGE SLUDGE DISINFECTION AND VECTOR ATTRACTION REDUCTION PROCESSES

EPA Science Inventory

What is the current state of management practices for biosolids production and application, and how can those be made more effective? How effective are Class B disinfection and vector attraction processes, and public access and harvesting restrictions at reducing the public's exp...

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

PubMed

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

2018-02-01

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

Automated characterisation of ultrasound images of ovarian tumours: the diagnostic accuracy of a support vector machine and image processing with a local binary pattern operator

PubMed Central

Khazendar, S.; Sayasneh, A.; Al-Assam, H.; Du, H.; Kaijser, J.; Ferrara, L.; Timmerman, D.; Jassim, S.; Bourne, T.

2015-01-01

Introduction: Preoperative characterisation of ovarian masses into benign or malignant is of paramount importance to optimise patient management. Objectives: In this study, we developed and validated a computerised model to characterise ovarian masses as benign or malignant. Materials and methods: Transvaginal 2D B mode static ultrasound images of 187 ovarian masses with known histological diagnosis were included. Images were first pre-processed and enhanced, and Local Binary Pattern Histograms were then extracted from 2 × 2 blocks of each image. A Support Vector Machine (SVM) was trained using stratified cross validation with randomised sampling. The process was repeated 15 times and in each round 100 images were randomly selected. Results: The SVM classified the original non-treated static images as benign or malignant masses with an average accuracy of 0.62 (95% CI: 0.59-0.65). This performance significantly improved to an average accuracy of 0.77 (95% CI: 0.75-0.79) when images were pre-processed, enhanced and treated with a Local Binary Pattern operator (mean difference 0.15: 95% 0.11-0.19, p < 0.0001, two-tailed t test). Conclusion: We have shown that an SVM can classify static 2D B mode ultrasound images of ovarian masses into benign and malignant categories. The accuracy improves if texture related LBP features extracted from the images are considered. PMID:25897367

Discrimination of raw and processed Dipsacus asperoides by near infrared spectroscopy combined with least squares-support vector machine and random forests

NASA Astrophysics Data System (ADS)

Xin, Ni; Gu, Xiao-Feng; Wu, Hao; Hu, Yu-Zhu; Yang, Zhong-Lin

2012-04-01

Most herbal medicines could be processed to fulfill the different requirements of therapy. The purpose of this study was to discriminate between raw and processed Dipsacus asperoides, a common traditional Chinese medicine, based on their near infrared (NIR) spectra. Least squares-support vector machine (LS-SVM) and random forests (RF) were employed for full-spectrum classification. Three types of kernels, including linear kernel, polynomial kernel and radial basis function kernel (RBF), were checked for optimization of LS-SVM model. For comparison, a linear discriminant analysis (LDA) model was performed for classification, and the successive projections algorithm (SPA) was executed prior to building an LDA model to choose an appropriate subset of wavelengths. The three methods were applied to a dataset containing 40 raw herbs and 40 corresponding processed herbs. We ran 50 runs of 10-fold cross validation to evaluate the model's efficiency. The performance of the LS-SVM with RBF kernel (RBF LS-SVM) was better than the other two kernels. The RF, RBF LS-SVM and SPA-LDA successfully classified all test samples. The mean error rates for the 50 runs of 10-fold cross validation were 1.35% for RBF LS-SVM, 2.87% for RF, and 2.50% for SPA-LDA. The best classification results were obtained by using LS-SVM with RBF kernel, while RF was fast in the training and making predictions.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

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

Stroke localization and classification using microwave tomography with k-means clustering and support vector machine.

PubMed

Guo, Lei; Abbosh, Amin

2018-05-01

For any chance for stroke patients to survive, the stroke type should be classified to enable giving medication within a few hours of the onset of symptoms. In this paper, a microwave-based stroke localization and classification framework is proposed. It is based on microwave tomography, k-means clustering, and a support vector machine (SVM) method. The dielectric profile of the brain is first calculated using the Born iterative method, whereas the amplitude of the dielectric profile is then taken as the input to k-means clustering. The cluster is selected as the feature vector for constructing and testing the SVM. A database of MRI-derived realistic head phantoms at different signal-to-noise ratios is used in the classification procedure. The performance of the proposed framework is evaluated using the receiver operating characteristic (ROC) curve. The results based on a two-dimensional framework show that 88% classification accuracy, with a sensitivity of 91% and a specificity of 87%, can be achieved. Bioelectromagnetics. 39:312-324, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

A Subdivision-Based Representation for Vector Image Editing.

PubMed

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

2012-11-01

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

The 1D Richards' equation in two layered soils: a Filippov approach to treat discontinuities

NASA Astrophysics Data System (ADS)

Berardi, Marco; Difonzo, Fabio; Vurro, Michele; Lopez, Luciano

2018-05-01

The infiltration process into the soil is generally modeled by the Richards' partial differential equation (PDE). In this paper a new approach for modeling the infiltration process through the interface of two different soils is proposed, where the interface is seen as a discontinuity surface defined by suitable state variables. Thus, the original 1D Richards' PDE, enriched by a particular choice of the boundary conditions, is first approximated by means of a time semidiscretization, that is by means of the transversal method of lines (TMOL). In such a way a sequence of discontinuous initial value problems, described by a sequence of second order differential systems in the space variable, is derived. Then, Filippov theory on discontinuous dynamical systems may be applied in order to study the relevant dynamics of the problem. The numerical integration of the semidiscretized differential system will be performed by using a one-step method, which employs an event driven procedure to locate the discontinuity surface and to adequately change the vector field.

Phytoplankton Enumeration and Evaluation Experiments

DTIC Science & Technology

2009-05-01

deballasted in another. The entrained organisms are generally discharged along with the ballast water. This process has been identified as a vector...ballasted in one port and deballasted in another. This process has been identified as a vector for the translocation of non- indigenous species (NIS...the probability that variable rates of cell survival from the irradiation process impacted NRLKW s ability to prepare samples with accurate numbers

[Periodontitis treatment by "vector" system].

PubMed

Vadachkoriia, N R; Mandzhavidze, N A; Gumberidze, N Sh

2008-11-01

Periodontal therapy by means of Vector device directly effects an environment of the tooth. It allows removing sub gingival dental plaque destroying pathogenic microorganisms and their toxins, washing out periodontal pockets carefully and polishing teeth roots. During treatment the hard tissues are not injured and the gum is not injured as well. Efficiency of a new ultrasonic technique in the complex treatment of periodontal diseases was declared. Periodontal therapy with the ultrasonic device leads to clinical improvements. It was found that Vector treatment was effective in the treatment of patients suffering from periodontitis.

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

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

Nesterenko, A. V.

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

Higher-order vector beams produced by photonic-crystal lasers.

PubMed

Iwahashi, Seita; Kurosaka, Yoshitaka; Sakai, Kyosuke; Kitamura, Kyoko; Takayama, Naoki; Noda, Susumu

2011-06-20

We have successfully generated vector beams with higher-order polarization states using photonic-crystal lasers. We have analyzed and designed lattice structures that provide cavity modes with different symmetries. Fabricated devices based on these lattice structures produced doughnut-shaped vector beams, with symmetries corresponding to the cavity modes. Our study enables the systematic analysis of vector beams, which we expect will lead to applications such as high-resolution microscopy, laser processing, and optical trapping.

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2008-04-15

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

Features in the speckle correlations of light scattered from volume-disordered dielectric media

NASA Astrophysics Data System (ADS)

Malyshkin, V.; McGurn, A. R.; Maradudin, A. A.

1999-03-01

A diagrammatic perturbation theory approach, based on a scalar wave treatment, is used to study the scattering of light of frequency ω from a volume disordered dielectric medium. The dielectric medium is described by a position-dependent dielectric constant of the form ɛ(r-->)=ɛ(ω)+δɛ(r-->), where ɛ(ω) does not depend on r-->, and δɛ(r-->) is a zero-mean Gaussian random process defined by <δɛ(r-->)δɛ(r-->')>=σ2 exp(-\\|r-->-r-->'\\|2/a2), where the angle brackets denote an average over the ensemble of realizations of δɛ(r-->), a is the correlation length of the disorder, and σ is the root mean square deviation of the dielectric constant from its average value ɛ(ω). The speckle correlation function C(q-->,k-->\\|q-->',k-->')=<[I(q-->\\|k-->)-\\|k-->)>][I(q-->'\\|k-->')-'\\|k-->')]> where I(q-->\\|k-->) is proportional to the differential-scattering coefficient for the scattering of light of incident wave vector k--> into light of wave vector q--> is computed. In these calculations the contributions associated with both ladder and maximally crossed diagrams are summed in a Feynman diagram treatment of the speckle correlator, in the approximation that only s-wave-scattering terms are retained. Results are presented for the differential-scattering coefficient of light scattered from the disordered medium, which displays the phenomenon of enhanced backscattering, and for the correlator C in the approximation where C=C(1)+C(10)+C(1.5). The contribution C(1) is proportional to δ(q-->-k-->-q-->'+k-->') and describes the memory and time-reversed memory effects. C(10) is proportional to δ(q-->-k-->+q-->'-k-->'), while C(1.5) is unrestricted in its dependence on q-->,k-->,q-->',k-->'. The latter two contributions have recently been treated in the scattering of light from randomly rough surfaces, but have not been previously treated in the scattering of light by volume disordered media. A number of peaks associated with resonant processes are observed in C(1.5) considered as a function of the wave vectors of the incident and scattered light.

Vector Potential, Electromagnetic Induction and "Physical Meaning"

ERIC Educational Resources Information Center

Giuliani, G.

2010-01-01

A forgotten experiment by Andre Blondel (1914) proves, as held on the basis of theoretical arguments in a previous paper, that the time variation of the magnetic flux is not the cause of the induced emf; the physical agent is instead the vector potential through the term [equation omitted] (when the induced circuit is at rest). The "good…

Computation of Surface Integrals of Curl Vector Fields

ERIC Educational Resources Information Center

Hu, Chenglie

2007-01-01

This article presents a way of computing a surface integral when the vector field of the integrand is a curl field. Presented in some advanced calculus textbooks such as [1], the technique, as the author experienced, is simple and applicable. The computation is based on Stokes' theorem in 3-space calculus, and thus provides not only a means to…

Preloadable vector sensitive latch

NASA Technical Reports Server (NTRS)

Acres, William R. (Inventor)

1987-01-01

A preloadable vector-sensitive latch which automatically releases when the force vector from a latch memebr reaches a specified release angle is presented. In addition, it contains means to remove clearance between the latched members and to preload the latch to prevent separation at angles less than the specified release angle. The latch comprises a triangular main link, a free link connected between a first corner of the main link and a yoke member, a housing, and an actuator connected between the yoke member and the housing. A return spring bias means connects the main link to a portion of the housing. A second corner of the main link is slidably and pivotally connected to the housing via a slot in a web portion of the housing. The latch housing has a rigid docking ring alignable with a mating locking ring which is engageable by a locking roller journalled on the third corner of the triangular main link.

Ectoparasites and other epifaunistic arthropods of sympatric cotton mice and golden mice: comparisons and implications for vector-borne zoonotic diseases.

PubMed

Durden, Lance A; Polur, Ram N; Nims, Todd; Banks, Craig W; Oliver, James H

2004-12-01

Ectoparasite and epifaunistic arthropod biodiversity and infestation parameters were compared between 2 sympatric small rodent species, the cotton mouse (Peromyscus gossypinus (Le Conte)) and golden mouse (Ochrotomys nuttalli (Harlan)), in southern Georgia from 1992 to 2003. Because the cotton mouse is known to be a reservoir of more vector-borne zoonotic pathogens than the golden mouse, we hypothesized that it would be parasitized by more ectoparasites that are known to be vectors of these pathogens. Cotton mice (n = 202) were parasitized by 19 species of arthropods, whereas golden mice (n = 46) were parasitized by 12 species. Eleven species of arthropods were recovered from both host species, whereas 7 were recorded only from cotton mice, and 1 species only from golden mice. Infestation prevalences (percent of mice parasitized) were significantly higher for 1 species of arthropod (the tropical rat mite Ornithonyssus bacoti (Hirst)) infesting cotton mice and for 4 species (the flea Peromyscopsylla scotti Fox and the mites Glycyphagus hypudaei Koch, Androlaelaps casalis (Berlese), and Androlaelaps fahrenholzi (Berlese)) infesting golden mice. Mean intensities (mean per infested mouse) were significantly higher for 2 species (the flea Orchopeas leucopus (Baker) and the blacklegged tick Ixodes scapularis Say) infesting cotton mice and for 2 species (G. hypudaei and A. fahrenholzi) infesting golden mice. Ectoparasites that are known to be vectors of zoonotic pathogens were significantly more common on cotton mice than on golden mice. These ectoparasites included the rhopalopsyllid flea Polygenis gwyni (Fox), a vector of the agent of murine typhus; I. scapularis, the principal vector of the agents of Lyme borreliosis, human granulocytic ehrlichiosis, and human babesiosis; and O. bacoti, a laboratory vector of several zoonotic pathogens. However, 2 species of ixodid ticks that can transmit zoonotic pathogens were recovered from both host species. These were the American dog tick Dermacentor variabilis (Say), the principal vector of the agent of Rocky Mountain spotted fever in eastern North America, and Ixodes minor Neumann, an enzootic vector of the agent of Lyme borreliosis. Overall, the cotton mouse was parasitized by significantly more ectoparasites that are known to be vectors of zoonotic pathogens than was the golden mouse. These data support the hypothesis that the cotton mouse has greater epidemiological importance for zoonotic vector-borne pathogen transmission than does the golden mouse.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

A Connectionist Simulation of Attention and Vector Comparison: The Need for Serial Processing in Parallel Hardware

DTIC Science & Technology

1991-01-01

visual and three-layer connectionist network, in that the input layer of memory processing is serial, and is likely to represent each module is... Selective attention gates visual University Press. processing in the extrastnate cortex. Science, 229:782-784. Treasman, A.M. (1985). Preartentive...AD-A242 225 A CONNECTIONIST SIMULATION OF ATTENTION AND VECTOR COMPARISON: THE NEED FOR SERIAL PROCESSING IN PARALLEL HARDWARE Technical Report AlP

What is the 'true' effect of Trypanosoma rangeli on its triatomine bug vector?

PubMed

Peterson, Jennifer K; Graham, Andrea L

2016-06-01

The phrase, "T. rangeli is pathogenic to its insect vector," is commonly found in peer-reviewed publications on the matter, such that it has become the orthodox view of this interaction. In a literature survey, we identified over 20 papers with almost the exact phrase and several others alluding to it. The idea is of particular importance in triatomine population dynamics and the study of vector-borne T. cruzi transmission, as it could mean that triatomines infected with T. rangeli have lower fitness than uninfected insects. Trypanosoma rangeli pathogenicity was first observed in a series of studies carried out over fifty years ago using the triatomine species Rhodnius prolixus. However, there are few studies of the effect of T. rangeli on its other vector species, and several of the studies were carried out with R. prolixus under non-physiological conditions. Here, we re-evaluate the published studies that led to the conclusion that T. rangeli is pathogenic to its vector, to determine whether or not this indeed is the "true" effect of T. rangeli on its triatomine vector. © 2016 The Society for Vector Ecology.

Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

PubMed

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India

PubMed Central

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Background Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. Method We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. Results For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. Conclusion The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. PMID:24971510

Rapid high-yield expression of full-size IgG antibodies in plants coinfected with noncompeting viral vectors

PubMed Central

Giritch, Anatoli; Marillonnet, Sylvestre; Engler, Carola; van Eldik, Gerben; Botterman, Johan; Klimyuk, Victor; Gleba, Yuri

2006-01-01

Plant viral vectors allow expression of heterologous proteins at high yields, but so far, they have been unable to express heterooligomeric proteins efficiently. We describe here a rapid and indefinitely scalable process for high-level expression of functional full-size mAbs of the IgG class in plants. The process relies on synchronous coinfection and coreplication of two viral vectors, each expressing a separate antibody chain. The two vectors are derived from two different plant viruses that were found to be noncompeting. Unlike vectors derived from the same virus, noncompeting vectors effectively coexpress the heavy and light chains in the same cell throughout the plant body, resulting in yields of up to 0.5 g of assembled mAbs per kg of fresh-leaf biomass. This technology allows production of gram quantities of mAbs for research purposes in just several days, and the same protocol can be used on an industrial scale in situations requiring rapid response, such as pandemic or terrorism events. PMID:16973752

Search for heavy vector-like quarks coupling to light quarks in proton–proton collisions at s = 7   TeV with the ATLAS detector

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2012-05-01

This Letter presents a search for singly produced vector-like quarks, Q, coupling to light quarks, q. The search is sensitive to both charged current (CC) and neutral current (NC) processes, pp→Qq→Wqq' and pp→Qq→Zqq' with a leptonic decay of the vector gauge boson. In 1.04fb -1 of data taken in 2011 by the ATLAS experiment at a center-of-mass energy √s=7TeV, no evidence of such heavy vector-like quarks is observed above the expected Standard Model background. Limits on the heavy vector-like quark production cross section times branching ratio as a function of mass m Q are obtained. For a coupling κ qQ=v/mmore » Q, where v is the Higgs vacuum expectation value, 95% C.L. lower limits on the mass of a vector-like quark are set at 900 GeV and 760 GeV from CC and NC processes, respectively.« less

Selection vector filter framework

NASA Astrophysics Data System (ADS)

Lukac, Rastislav; Plataniotis, Konstantinos N.; Smolka, Bogdan; Venetsanopoulos, Anastasios N.

2003-10-01

We provide a unified framework of nonlinear vector techniques outputting the lowest ranked vector. The proposed framework constitutes a generalized filter class for multichannel signal processing. A new class of nonlinear selection filters are based on the robust order-statistic theory and the minimization of the weighted distance function to other input samples. The proposed method can be designed to perform a variety of filtering operations including previously developed filtering techniques such as vector median, basic vector directional filter, directional distance filter, weighted vector median filters and weighted directional filters. A wide range of filtering operations is guaranteed by the filter structure with two independent weight vectors for angular and distance domains of the vector space. In order to adapt the filter parameters to varying signal and noise statistics, we provide also the generalized optimization algorithms taking the advantage of the weighted median filters and the relationship between standard median filter and vector median filter. Thus, we can deal with both statistical and deterministic aspects of the filter design process. It will be shown that the proposed method holds the required properties such as the capability of modelling the underlying system in the application at hand, the robustness with respect to errors in the model of underlying system, the availability of the training procedure and finally, the simplicity of filter representation, analysis, design and implementation. Simulation studies also indicate that the new filters are computationally attractive and have excellent performance in environments corrupted by bit errors and impulsive noise.

Distribution of black-tailed jackrabbit habitat determined by GIS in southwestern Idaho

USGS Publications Warehouse

Knick, Steven T.; Dyer, D.L.

1997-01-01

We developed a multivariate description of black-tailed jackrabbit (Lepus californicus) habitat associations from Geographical Information Systems (GIS) signatures surrounding known jackrabbit locations in the Snake River Birds of Prey National Conservation Area (NCA), in southwestern Idaho. Habitat associations were determined for characteristics within a 1-km radius (approx home range size) of jackrabbits sighted on night spotlight surveys conducted from 1987 through 1995. Predictive habitat variables were number of shrub, agriculture, and hydrography cells, mean and standard deviation of shrub patch size, habitat richness, and a measure of spatial heterogeneity. In winter, jackrabbits used smaller and less variable sizes of shrub patches and areas of higher spatial heterogeneity when compared to summer observations (P 0.05), differed significantly between high and low population phase. We used the Mahalanobis distance statistic to rank all 50-m cells in a 440,000-ha region relative to the multivariate mean habitat vector. On verification surveys to test predicted models, we sighted jackrabbits in areas ranked close to the mean habitat vector. Areas burned by large-scale fires between 1980 and 1992 or in an area repeatedly burned by military training activities had greater Mahalanobis distances from the mean habitat vector than unburned areas and were less likely to contain habitats used by jackrabbits.

Application of Krylov exponential propagation to fluid dynamics equations

NASA Technical Reports Server (NTRS)

Saad, Youcef; Semeraro, David

1991-01-01

An application of matrix exponentiation via Krylov subspace projection to the solution of fluid dynamics problems is presented. The main idea is to approximate the operation exp(A)v by means of a projection-like process onto a krylov subspace. This results in a computation of an exponential matrix vector product similar to the one above but of a much smaller size. Time integration schemes can then be devised to exploit this basic computational kernel. The motivation of this approach is to provide time-integration schemes that are essentially of an explicit nature but which have good stability properties.

Currency crisis indication by using ensembles of support vector machine classifiers

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Photon and vector meson exchanges in the production of light meson pairs and elementary atoms

NASA Astrophysics Data System (ADS)

Gevorkyan, S. R.; Kuraev, E. A.; Volkov, M. K.

2013-01-01

The production of pseudoscalar and scalar meson pairs ππ, ηη, η‧η‧, σσ as well as bound states in high energy γγ collisions are considered. The exchange by a vector particle in the binary process γ + γ → ha + hb with hadronic states ha, hb in fragmentation regions of the initial particle leads to nondecreasing cross sections with increasing energy, that is a priority of peripheral kinematics. Unlike the photon exchange the vector meson exchange needs a reggeization leading to fall with energy growth. Nevertheless, due to the peripheral kinematics beyond very forward production angles the vector meson exchanges dominate over all possible exchanges. The proposed approach allows one to express the matrix elements of the considered processes through impacting factors, which can be calculated in perturbation models like chiral perturbation theory (ChPT) or the Nambu-Jona-Lasinio (NJL) model. In particular cases the impact factors can be determined from relevant γγ sub-processes or the vector meson radiative decay width. The pionium atom production in the collisions of high energy electrons and pions with protons is considered and the relevant cross sections have been estimated.

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

PubMed

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

2010-01-28

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

Fast software-based volume rendering using multimedia instructions on PC platforms and its application to virtual endoscopy

NASA Astrophysics Data System (ADS)

Mori, Kensaku; Suenaga, Yasuhito; Toriwaki, Jun-ichiro

2003-05-01

This paper describes a software-based fast volume rendering (VolR) method on a PC platform by using multimedia instructions, such as SIMD instructions, which are currently available in PCs' CPUs. This method achieves fast rendering speed through highly optimizing software rather than an improved rendering algorithm. In volume rendering using a ray casting method, the system requires fast execution of the following processes: (a) interpolation of voxel or color values at sample points, (b) computation of normal vectors (gray-level gradient vectors), (c) calculation of shaded values obtained by dot-products of normal vectors and light source direction vectors, (d) memory access to a huge area, and (e) efficient ray skipping at translucent regions. The proposed software implements these fundamental processes in volume rending by using special instruction sets for multimedia processing. The proposed software can generate virtual endoscopic images of a 3-D volume of 512x512x489 voxel size by volume rendering with perspective projection, specular reflection, and on-the-fly normal vector computation on a conventional PC without any special hardware at thirteen frames per second. Semi-translucent display is also possible.

Application of a VLSI vector quantization processor to real-time speech coding

NASA Technical Reports Server (NTRS)

Davidson, G.; Gersho, A.

1986-01-01

Attention is given to a working vector quantization processor for speech coding that is based on a first-generation VLSI chip which efficiently performs the pattern-matching operation needed for the codebook search process (CPS). Using this chip, the CPS architecture has been successfully incorporated into a compact, single-board Vector PCM implementation operating at 7-18 kbits/sec. A real time Adaptive Vector Predictive Coder system using the CPS has also been implemented.

Feasibility of Bioelectrical Impedance Spectroscopy Measurement before and after Thoracentesis

PubMed Central

Weyer, Sören; Pauly, Karolin; Napp, Andreas; Dreher, Michael; Leonhardt, Steffen; Marx, Nikolaus; Schauerte, Patrick; Mischke, Karl

2015-01-01

Background. Bioelectrical impedance spectroscopy is applied to measure changes in tissue composition. The aim of this study was to evaluate its feasibility in measuring the fluid shift after thoracentesis in patients with pleural effusion. Methods. 45 participants (21 with pleural effusion and 24 healthy subjects) were included. Bioelectrical impedance was analyzed for “Transthoracic,” “Foot to Foot,” “Foot to Hand,” and “Hand to Hand” vectors in low and high frequency domain before and after thoracentesis. Healthy subjects were measured at a single time point. Results. The mean volume of removed pleural effusion was 1169 ± 513 mL. The “Foot to Foot,” “Hand to Hand,” and “Foot to Hand” vector indicated a trend for increased bioelectrical impedance after thoracentesis. Values for the low frequency domain in the “Transthoracic” vector increased significantly (P < 0.001). A moderate correlation was observed between the amount of removed fluid and impedance change in the low frequency domain using the “Foot to Hand” vector (r = −0.7). Conclusion. Bioelectrical impedance changes in correlation with the thoracic fluid level. It was feasible to monitor significant fluid shifts and loss after thoracentesis in the “Transthoracic” vector by means of bioelectrical impedance spectroscopy. The trial is registered with Registration Numbers IRB EK206/11 and NCT01778270. PMID:25861647

Fluctuations in diffusion processes in microgravity.

PubMed

Mazzoni, Stefano; Cerbino, Roberto; Vailati, Alberto; Giglio, Marzio

2006-09-01

It has been shown recently that diffusion processes exhibit giant nonequilibrium fluctuations (NEFs). That is, the diffusing fronts display corrugations whose length scale ranges from the molecular to the macroscopic one. The amplitude of the NEF diverges following a power law behavior proportional to q(-4) (where q is the wave vector). However, fluctuations of wave number smaller than a critical "rolloff" wave vector are quenched by the presence of gravity. It is therefore expected that in microgravity conditions, the amplitude of the NEF should be boosted by the absence of the buoyancy-driven restoring force. This may affect any diffusion process performed in microgravity, such as the crystallization of a protein solution induced by the diffusion of a salt buffer. The aim of GRADFLEX (GRAdient-Driven FLuctuation EXperiment), a joint project of ESA and NASA, is to investigate the presence of NEFs arising in a diffusion process under microgravity conditions. The project consists of two experiments. One is carried out by UNIMI (University of Milan) and INFM (Istituto Nazionale per la Fisica della Materia) and is focused on NEF in a concentration diffusion process. The other experiment is performed by UCSB (University of California at Santa Barbara) concerning temperature NEF in a simple fluid. In the UNIMI part of the GRADFLEX experimental setup, NEFs are induced in a binary mixture by means of the Soret effect. The diagnostic method is an all-optical quantitative shadowgraph technique. The power spectrum of the induced NEFs is obtained by the processing of the shadowgraph images. A detailed description of the experimental apparatus as well as the ground-based experimental results is presented here for the UNIMI-INFM experiment. The GRADFLEX payload is scheduled to fly on the FOTON M3 capsule in April 2007.

An Alternative Lunar Ephemeris Model for On-Board Flight Software Use

NASA Technical Reports Server (NTRS)

Simpson, David G.

1998-01-01

In calculating the position vector of the Moon in on-board flight software, one often begins by using a series expansion to calculate the ecliptic latitude and longitude of the Moon, referred to the mean ecliptic and equinox of date. One then performs a reduction for precession, followed by a rotation of the position vector from the ecliptic plane to the equator, and a transformation from spherical to Cartesian coordinates before finally arriving at the desired result: equatorial J2000 Cartesian components of the lunar position vector. An alternative method is developed here in which the equatorial J2000 Cartesian components of the lunar position vector are calculated directly by a series expansion, saving valuable on-board computer resources.

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.

Design of a mixer for the thrust-vectoring system on the high-alpha research vehicle

NASA Technical Reports Server (NTRS)

Pahle, Joseph W.; Bundick, W. Thomas; Yeager, Jessie C.; Beissner, Fred L., Jr.

1996-01-01

One of the advanced control concepts being investigated on the High-Alpha Research Vehicle (HARV) is multi-axis thrust vectoring using an experimental thrust-vectoring (TV) system consisting of three hydraulically actuated vanes per engine. A mixer is used to translate the pitch-, roll-, and yaw-TV commands into the appropriate TV-vane commands for distribution to the vane actuators. A computer-aided optimization process was developed to perform the inversion of the thrust-vectoring effectiveness data for use by the mixer in performing this command translation. Using this process a new mixer was designed for the HARV and evaluated in simulation and flight. An important element of the Mixer is the priority logic, which determines priority among the pitch-, roll-, and yaw-TV commands.

The Ins and Outs of Meaning: Behavioral and Neuroanatomical Dissociation of Semantically-Driven Word Retrieval and Multimodal Semantic Recognition in Aphasia

PubMed Central

Mirman, Daniel; Zhang, Yongsheng; Wang, Ze; Coslett, H. Branch; Schwartz, Myrna F.

2015-01-01

Theories about the architecture of language processing differ with regard to whether verbal and nonverbal comprehension share a functional and neural substrate and how meaning extraction in comprehension relates to the ability to use meaning to drive verbal production. We (re-)evaluate data from 17 cognitive-linguistic performance measures of 99 participants with chronic aphasia using factor analysis to establish functional components and support vector regression-based lesion-symptom mapping to determine the neural correlates of deficits on these functional components. The results are highly consistent with our previous findings: production of semantic errors is behaviorally and neuroanatomically distinct from verbal and nonverbal comprehension. Semantic errors were most strongly associated with left ATL damage whereas deficits on tests of verbal and non-verbal semantic recognition were most strongly associated with damage to deep white matter underlying the frontal lobe at the confluence of multiple tracts, including the inferior fronto-occipital fasciculus, the uncinate fasciculus, and the anterior thalamic radiations. These results suggest that traditional views based on grey matter hub(s) for semantic processing are incomplete and that the role of white matter in semantic cognition has been underappreciated. PMID:25681739

Manufacture of Third-Generation Lentivirus for Preclinical Use, with Process Development Considerations for Translation to Good Manufacturing Practice.

PubMed

Gándara, Carolina; Affleck, Valerie; Stoll, Elizabeth Ann

2018-02-01

Lentiviral vectors are used in laboratories around the world for in vivo and ex vivo delivery of gene therapies, and increasingly clinical investigation as well as preclinical applications. The third-generation lentiviral vector system has many advantages, including high packaging capacity, stable gene expression in both dividing and post-mitotic cells, and low immunogenicity in the recipient organism. Yet, the manufacture of these vectors is challenging, especially at high titers required for direct use in vivo, and further challenges are presented by the process of translating preclinical gene therapies toward manufacture of products for clinical investigation. The goals of this paper are to report the protocol for manufacturing high-titer third-generation lentivirus for preclinical testing and to provide detailed information on considerations for translating preclinical viral vector manufacture toward scaled-up platforms and processes in order to make gene therapies under Good Manufacturing Practice that are suitable for clinical trials.

Manufacture of Third-Generation Lentivirus for Preclinical Use, with Process Development Considerations for Translation to Good Manufacturing Practice

PubMed Central

Gándara, Carolina; Affleck, Valerie; Stoll, Elizabeth Ann

2018-01-01

Lentiviral vectors are used in laboratories around the world for in vivo and ex vivo delivery of gene therapies, and increasingly clinical investigation as well as preclinical applications. The third-generation lentiviral vector system has many advantages, including high packaging capacity, stable gene expression in both dividing and post-mitotic cells, and low immunogenicity in the recipient organism. Yet, the manufacture of these vectors is challenging, especially at high titers required for direct use in vivo, and further challenges are presented by the process of translating preclinical gene therapies toward manufacture of products for clinical investigation. The goals of this paper are to report the protocol for manufacturing high-titer third-generation lentivirus for preclinical testing and to provide detailed information on considerations for translating preclinical viral vector manufacture toward scaled-up platforms and processes in order to make gene therapies under Good Manufacturing Practice that are suitable for clinical trials. PMID:29212357

Training Extract, AFSC 113X0B, Flight Engineer, Helicopter Qualified.

DTIC Science & Technology

1982-12-01

TRAINING .................................................................. 1I0 SE. GENERAL rLIGHT RULES A 9 C t | 7. PeRFORM INSPECIIOIS 12 7A... TRAINING .................................................................. lIC 6E. GENERAL FLIGHT RULES A a C...ME"BERS PERFORMING I-A I PROGRAM GENERATED VECTOR IMEMBERS/ NO TYPE VECTOR MEAN - SC DESCRIPTION I TN. SEP J.6 2.J TRAINING EMPHASIS RATINSS I IIOS

Beauty vector meson decay constants from QCD sum rules

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

Lucha, Wolfgang; Melikhov, Dmitri; D. V. Skobeltsyn Institute of Nuclear Physics, M. V. Lomonosov Moscow State University, 119991, Moscow

We present the outcomes of a very recent investigation of the decay constants of nonstrange and strange heavy-light beauty vector mesons, with special emphasis on the ratio of any such decay constant to the decay constant of the corresponding pseudoscalar meson, by means of Borel-transformed QCD sum rules. Our results suggest that both these ratios are below unity.

The Identification of Hunger Behaviour of Lates Calcarifer through the Integration of Image Processing Technique and Support Vector Machine

NASA Astrophysics Data System (ADS)

Taha, Z.; Razman, M. A. M.; Adnan, F. A.; Ghani, A. S. Abdul; Majeed, A. P. P. Abdul; Musa, R. M.; Sallehudin, M. F.; Mukai, Y.

2018-03-01

Fish Hunger behaviour is one of the important element in determining the fish feeding routine, especially for farmed fishes. Inaccurate feeding routines (under-feeding or over-feeding) lead the fishes to die and thus, reduces the total production of fishes. The excessive food which is not eaten by fish will be dissolved in the water and thus, reduce the water quality (oxygen quantity in the water will be reduced). The reduction of oxygen (water quality) leads the fish to die and in some cases, may lead to fish diseases. This study correlates Barramundi fish-school behaviour with hunger condition through the hybrid data integration of image processing technique. The behaviour is clustered with respect to the position of the centre of gravity of the school of fish prior feeding, during feeding and after feeding. The clustered fish behaviour is then classified by means of a machine learning technique namely Support vector machine (SVM). It has been shown from the study that the Fine Gaussian variation of SVM is able to provide a reasonably accurate classification of fish feeding behaviour with a classification accuracy of 79.7%. The proposed integration technique may increase the usefulness of the captured data and thus better differentiates the various behaviour of farmed fishes.

Probing dark matter at the LHC using vector boson fusion processes.

PubMed

Delannoy, Andres G; Dutta, Bhaskar; Gurrola, Alfredo; Johns, Will; Kamon, Teruki; Luiggi, Eduardo; Melo, Andrew; Sheldon, Paul; Sinha, Kuver; Wang, Kechen; Wu, Sean

2013-08-09

Vector boson fusion processes at the Large Hadron Collider (LHC) provide a unique opportunity to search for new physics with electroweak couplings. A feasibility study for the search of supersymmetric dark matter in the final state of two vector boson fusion jets and large missing transverse energy is presented at 14 TeV. Prospects for determining the dark matter relic density are studied for the cases of wino and bino-Higgsino dark matter. The LHC could probe wino dark matter with mass up to approximately 600 GeV with a luminosity of 1000  fb(-1).

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.

New vector-like fermions and flavor physics

DOE PAGES

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

2015-10-06

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

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 optical fields with bipolar symmetry of linear polarization.

PubMed

Pan, Yue; Li, Yongnan; Li, Si-Min; Ren, Zhi-Cheng; Si, Yu; Tu, Chenghou; Wang, Hui-Tian

2013-09-15

We focus on a new kind of vector optical field with bipolar symmetry of linear polarization instead of cylindrical and elliptical symmetries, enriching members of family of vector optical fields. We design theoretically and generate experimentally the demanded vector optical fields and then explore some novel tightly focusing properties. The geometric configurations of states of polarization provide additional degrees of freedom assisting in engineering the field distribution at the focus to the specific applications such as lithography, optical trapping, and material processing.

An efficient system for reliably transmitting image and video data over low bit rate noisy channels

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.; Huang, Y. F.; Stevenson, Robert L.

1994-01-01

This research project is intended to develop an efficient system for reliably transmitting image and video data over low bit rate noisy channels. The basic ideas behind the proposed approach are the following: employ statistical-based image modeling to facilitate pre- and post-processing and error detection, use spare redundancy that the source compression did not remove to add robustness, and implement coded modulation to improve bandwidth efficiency and noise rejection. Over the last six months, progress has been made on various aspects of the project. Through our studies of the integrated system, a list-based iterative Trellis decoder has been developed. The decoder accepts feedback from a post-processor which can detect channel errors in the reconstructed image. The error detection is based on the Huber Markov random field image model for the compressed image. The compression scheme used here is that of JPEG (Joint Photographic Experts Group). Experiments were performed and the results are quite encouraging. The principal ideas here are extendable to other compression techniques. In addition, research was also performed on unequal error protection channel coding, subband vector quantization as a means of source coding, and post processing for reducing coding artifacts. Our studies on unequal error protection (UEP) coding for image transmission focused on examining the properties of the UEP capabilities of convolutional codes. The investigation of subband vector quantization employed a wavelet transform with special emphasis on exploiting interband redundancy. The outcome of this investigation included the development of three algorithms for subband vector quantization. The reduction of transform coding artifacts was studied with the aid of a non-Gaussian Markov random field model. This results in improved image decompression. These studies are summarized and the technical papers included in the appendices.

On the Runge-Lenz-Pauli vector operator as an aid to the calculation of atomic processes in laboratory and astrophysical plasmas

NASA Astrophysics Data System (ADS)

Hey, J. D.

2015-09-01

On the basis of the original definition and analysis of the vector operator by Pauli (1926 Z. Phys. 36 336-63), and further developments by Flamand (1966 J. Math. Phys. 7 1924-31), and by Becker and Bleuler (1976 Z. Naturforsch. 31a 517-23), we consider the action of the operator on both spherical polar and parabolic basis state wave functions, both with and without direct use of Pauli’s identity (Valent 2003 Am. J. Phys. 71 171-75). Comparison of the results, with the aid of two earlier papers (Hey 2006 J. Phys. B: At. Mol. Opt. Phys. 39 2641-64, Hey 2007 J. Phys. B: At. Mol. Opt. Phys. 40 4077-96), yields a convenient ladder technique in the form of a recurrence relation for calculating the transformation coefficients between the two sets of basis states, without explicit use of generalized hypergeometric functions. This result is therefore very useful for application to Stark effect and impact broadening calculations applied to high-n radio recombination lines from tenuous space plasmas. We also demonstrate the versatility of the Runge-Lenz-Pauli vector operator as a means of obtaining recurrence relations between expectation values of successive powers of quantum mechanical operators, by using it to provide, as an example, a derivation of the Kramers-Pasternack relation. It is suggested that this operator, whose potential use in Stark- and Zeeman-effect calculations for magnetically confined fusion edge plasmas (Rosato, Marandet and Stamm 2014 J. Phys. B: At. Mol. Opt. Phys. 47 105702) and tenuous space plasmas ( H II regions) has not been fully explored and exploited, may yet be found to yield a number of valuable results for applications to plasma diagnostic techniques based upon rate calculations of atomic processes.

A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents

PubMed Central

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control—enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates. PMID:28446872

A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents.

PubMed

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

Despite their small size, insect brains are able to produce robust and efficient navigation in complex environments. Specifically in social insects, such as ants and bees, these navigational capabilities are guided by orientation directing vectors generated by a process called path integration. During this process, they integrate compass and odometric cues to estimate their current location as a vector, called the home vector for guiding them back home on a straight path. They further acquire and retrieve path integration-based vector memories globally to the nest or based on visual landmarks. Although existing computational models reproduced similar behaviors, a neurocomputational model of vector navigation including the acquisition of vector representations has not been described before. Here we present a model of neural mechanisms in a modular closed-loop control-enabling vector navigation in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns in circular arrays. A reward-modulated learning rule enables the acquisition of vector memories by associating the local food reward with the path integration state. A motor output is computed based on the combination of vector memories and random exploration. In simulation, we show that the neural mechanisms enable robust homing and localization, even in the presence of external sensory noise. The proposed learning rules lead to goal-directed navigation and route formation performed under realistic conditions. Consequently, we provide a novel approach for vector learning and navigation in a simulated, situated agent linking behavioral observations to their possible underlying neural substrates.

Mosquito biting activity on humans & detection of Plasmodium falciparum infection in Anopheles stephensi in Goa, India.

PubMed

Korgaonkar, Nandini S; Kumar, Ashwani; Yadav, Rajpal S; Kabadi, Dipak; Dash, Aditya P

2012-01-01

Knowledge of the bionomics of mosquitoes, especially of disease vectors, is essential to plan appropriate vector avoidance and control strategies. Information on biting activity of vectors during the night hours in different seasons is important for choosing personal protection measures. This study was carried out to find out the composition of mosquito fauna biting on humans and seasonal biting trends in Goa, India. Biting activities of all mosquitoes including vectors were studied from 1800 to 0600 h during 85 nights using human volunteers in 14 different localities of three distinct ecotypes in Goa. Seasonal biting trends of vector species were analysed and compared. Seasonal biting periodicity during different phases of night was also studied using William's mean. A total of 4,191 mosquitoes of five genera and 23 species were collected. Ten species belonged to Anopheles, eight to Culex, three to Aedes and one each to Mansonia and Armigeres. Eleven vector species had human hosts, including malaria vectors Anopheles stephensi (1.3%), An. fluviatilis (1.8%), and An. culicifacies (0.76%); filariasis vectors Culex quinquefasciatus (40.8%) and Mansonia uniformis (1.8%); Japanese encephalitis vectors Cx. tritaeniorhynchus (17.4%), Cx. vishnui (7.7%), Cx. pseudovishnui (0.1%), and Cx. gelidus (2.4%); and dengue and chikungunya vectors Aedes albopictus (0.9%) and Ae. aegypti (0.6%). Two An. stephensi of the total 831 female anophelines, were found positive for P. falciparum sporozoites. The entomological inoculation rate (EIR) of P. falciparum was 18.1 and 2.35 for Panaji city and Goa, respectively. Most of the mosquito vector species were collected in all seasons and throughout the scotophase. Biting rates of different vector species differed during different phases of night and seasons. Personal protection methods could be used to stop vector-host contact.

Vectors and transmission dynamics for Setaria tundra (Filarioidea; Onchocercidae), a parasite of reindeer in Finland

PubMed Central

Laaksonen, Sauli; Solismaa, Milla; Kortet, Raine; Kuusela, Jussi; Oksanen, Antti

2009-01-01

Background Recent studies have revealed expansion by an array of Filarioid nematodes' into the northern boreal region of Finland. The vector-borne nematode, Setaria tundra, caused a serious disease outbreak in the Finnish reindeer population in 2003–05. The main aim of this study was to understand the outbreak dynamics and the rapid expansion of S. tundra in the sub arctic. We describe the vectors of S. tundra, and its development in vectors, for the first time. Finally we discuss the results in the context of the host-parasite ecology of S. tundra in Finland Results Development of S. tundra to the infective stage occurs in mosquitoes, (genera Aedes and Anopheles). We consider Aedes spp. the most important vectors. The prevalence of S. tundra naturally infected mosquitoes from Finland varied from 0.5 to 2.5%. The rate of development in mosquitoes was temperature-dependent. Infective larvae were present approximately 14 days after a blood meal in mosquitoes maintained at room temperature (mean 21 C), but did not develop in mosquitoes maintained outside for 22 days at a mean temperature of 14.1 C. The third-stage (infective) larvae were elongated (mean length 1411 μm (SD 207), and width 28 μm (SD 2)). The anterior end was blunt, and bore two liplike structures, the posterior end slight tapering with a prominent terminal papilla. Infective larvae were distributed anteriorly in the insect's body, the highest abundance being 70 larvae in one mosquito. A questionnaire survey revealed that the peak activity of Culicidae in the reindeer herding areas of Finland was from the middle of June to the end of July and that warm summer weather was associated with reindeer flocking behaviour on mosquito-rich wetlands. Conclusion In the present work, S. tundra vectors and larval development were identified and described for the first time. Aedes spp. mosquitoes likely serve as the most important and competent vectors for S. tundra in Finland. Warm summers apparently promote transmission and genesis of disease outbreaks by favouring the development of S. tundra in its mosquito vectors, by improving the development and longevity of mosquitoes, and finally by forcing the reindeer to flock on mosquito rich wetlands. Thus we predict that global climate change has the potential to promote the further emergence of Filarioid nematodes and the disease caused by them in subarctic regions. PMID:19126197

Increase of efficiency of finishing-cleaning and hardening processing of details based on rotor-screw technological systems

NASA Astrophysics Data System (ADS)

Lebedev, V. A.; Serga, G. V.; Khandozhko, A. V.

2018-03-01

The article proposes technical solutions for increasing the efficiency of finishing-cleaning and hardening processing of parts on the basis of rotor-screw technological systems. The essence, design features and technological capabilities of the rotor-screw technological system with a rotating container are disclosed, which allows one to expand the range of the resulting displacement vectors, granules of the abrasive medium and processed parts. Ways of intensification of the processing on their basis by means of vibration activation of the process providing a combined effect on the mass of loading of large and small amplitude low-frequency oscillations are proposed. The results of the experimental studies of the movement of bulk materials in a screw container are presented, which showed that Kv = 0.5-0.6 can be considered the optimal value of the container filling factor. The estimation of screw containers application efficiency proceeding from their design features is given.

Prevention of Salmonella cross-contamination in an oilmeal manufacturing plant.

PubMed

Morita, T; Kitazawa, H; Iida, T; Kamata, S

2006-08-01

The mechanisms of Salmonella contamination in an oilmeal plant were investigated and the basic data were collected in order to achieve control of Salmonella in oilmeal. Salmonella was detected in all contamination vectors and environmental factors investigated, namely: operators, processing floor, dust in the air and rodents. In particular, high concentrations of Salmonella were detected on the processing floor of the manufacturing area, which has high oil content. Steam was the most effective disinfection method used for the processing floor, as the effects of heat sterilization and disinfection may work in tandem. In addition, restricting the movement of operators of the production chain remarkably reduced Salmonella contamination, even in areas of otherwise high contamination. Within the oilmeal plant, high Salmonella contamination rates for the processing floor represent the greatest risk of contamination of oilmeal via operators, dust in the air and rodents. Therefore, control of the processing floor is the most important means for reducing the oilmeal contamination rate. Specific Salmonella control methods for oilmeal plants have been established.

Accounting for phase drifts in SSVEP-based BCIs by means of biphasic stimulation.

PubMed

Wu, Hung-Yi; Lee, Po-Lei; Chang, Hsiang-Chih; Hsieh, Jen-Chuen

2011-05-01

This study proposes a novel biphasic stimulation technique to solve the issue of phase drifts in steady-state visual evoked potential (SSVEPs) in phase-tagged systems. Phase calibration was embedded in stimulus sequences using a biphasic flicker, which is driven by a sequence with alternating reference and phase-shift states. Nine subjects were recruited to participate in off-line and online tests. Signals were bandpass filtered and segmented by trigger signals into reference and phase-shift epochs. Frequency components of SSVEP in the reference and phase-shift epochs were extracted using the Fourier method with a 50% overlapped sliding window. The real and imaginary parts of the SSVEP frequency components were organized into complex vectors in each epoch. Hotelling's t-square test was used to determine the significances of nonzero mean vectors. The rejection of noisy data segments and the validation of gaze detections were made based on p values. The phase difference between the valid mean vectors of reference and phase-shift epochs was used to identify user's gazed targets in this system. Data showed an average information transfer rate of 44.55 and 38.21 bits/min in off-line and online tests, respectively. © 2011 IEEE

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

The effect of leg preference on postural stability in healthy athletes.

PubMed

Huurnink, Arnold; Fransz, Duncan P; Kingma, Idsart; Hupperets, Maarten D W; van Dieën, Jaap H

2014-01-03

In research regarding postural stability, leg preference is often tested and controlled for. However, leg preference may vary between tasks. As athletes are a group of interest for postural stability testing, we evaluated the effect of five leg preference tasks categorization (step up, hop, ball kick, balance, pick up) on single-leg postural stability of 16 field hockey athletes. The 'center of pressure speed' was calculated as the primary outcome variable of single-leg postural stability. Secondary variables were 'mean length of the GRF vector in the horizontal plane', 'mean length of the ankle angular velocity vector', and 'mean length of the hip angular velocity vector', as well as the separate outcomes per degree of freedom. Results showed that leg preference was inconsistent between leg preference tasks. Moreover, the primary and secondary variables yielded no significant difference between the preferred and non-preferred legs, regardless of the applied leg preference task categorization (p>0.05). The present findings do not support the usability of leg preference tasks in controlling for bias of postural stability. In conclusion, none of the applied leg preference tasks revealed a significant effect on postural stability in healthy field hockey athletes. © 2013 Published by Elsevier Ltd.

Retrovirus-mediated transfer of a hygromycin phosphotransferase-thymidine kinase fusion gene into human CD34+ bone marrow cells.

PubMed

Akatsuka, Y; Emi, N; Kato, H; Abe, A; Tanimoto, M; Lupton, S D; Saito, H

1994-12-01

Retrovirus-mediated gene transfer into human hematopoietic stem cells has been proposed as a means of therapy for various inherited diseases and as a method of gene marking. The transduction efficiency of an amphotropic retroviral vector (PA317/HyTK) containing a hygromycin phosphotransferase-thymidine kinase fusion gene was examined with human CD34+ bone marrow cells in the presence of interleukin-3 (IL-3), interleukin-6 (IL-6), and stem cell factor. Transduction efficiencies determined from the ability of transduced granulocyte-macrophage colony forming units (CFU-GM) to grow in hygromycin B and from polymerase chain reaction analysis of individual transduced CFU-GM growing in the presence of hygromycin B were 0.3-3.0% (mean +/- S.D., 1.1 +/- 0.9%) and 0.1-1.2% (mean +/- S.D., 0.5 +/- 0.4%), respectively. Ganciclovir at a dose of approximately 1 microM reduced the number of CFU-GM derived from vector-infected CD34+ cells by 50%. These findings demonstrate that human hematopoietic stem cells infected with this retroviral vector are susceptible to ganciclovir, offering the potential to control transduced gene expression in vivo.

Peptide-Based Technologies to Alter Adenoviral Vector Tropism: Ways and Means for Systemic Treatment of Cancer

PubMed Central

Reetz, Julia; Herchenröder, Ottmar; Pützer, Brigitte M.

2014-01-01

Due to the fundamental progress in elucidating the molecular mechanisms of human diseases and the arrival of the post-genomic era, increasing numbers of therapeutic genes and cellular targets are available for gene therapy. Meanwhile, the most important challenge is to develop gene delivery vectors with high efficiency through target cell selectivity, in particular under in situ conditions. The most widely used vector system to transduce cells is based on adenovirus (Ad). Recent endeavors in the development of selective Ad vectors that target cells or tissues of interest and spare the alteration of all others have focused on the modification of the virus broad natural tropism. A popular way of Ad targeting is achieved by directing the vector towards distinct cellular receptors. Redirecting can be accomplished by linking custom-made peptides with specific affinity to cellular surface proteins via genetic integration, chemical coupling or bridging with dual-specific adapter molecules. Ideally, targeted vectors are incapable of entering cells via their native receptors. Such altered vectors offer new opportunities to delineate functional genomics in a natural environment and may enable efficient systemic therapeutic approaches. This review provides a summary of current state-of-the-art techniques to specifically target adenovirus-based gene delivery vectors. PMID:24699364

[Use of a novel baculovirus vector to express nucleoprotein gene of Crimean-Congo hemorrhagic fever virus in both insect and mammalian cells].

PubMed

Ma, Benjiang; Hang, Changshou; Zhao, Yun; Wang, Shiwen; Xie, Yanxiang

2002-09-01

To construct a novel baculovirus vector which is capable of promoting the high-yield expression of foreign gene in mammalian cells and to express by this vector the nucleoprotein (NP) gene of Crimean-Congo hemorrhagic fever virus (CCHFV) Chinese isolate (Xinjiang hemorrhagic fever virus, XHFV) BA88166 in insect and Vero cells. Human cytomegalovirus (CMV) immediate early (IE) promoter was ligated to the baculovirus vector pFastBac1 downstream of the polyhedrin promoter to give rise to the novel vector pCB1. XHFV NP gene was cloned to this vector and was well expressed in COS-7 cells and Vero cells by means of recombinant plasmid transfection and baculovirus infection. The XHFV NP gene in vector pCB1 could be well expressed in mammalian cells. Vero cells infected with recombinant baculovirus harboring NP gene could be employed as antigens to detect XHF serum specimens whose results were in good correlation with those of ELISA and in parallel with clinical diagnoses. This novel baculovirus vector is able to express the foreign gene efficiently in both insect and mammalian cells, which provides not only the convenient diagnostic antigens but also the potential for developing recombinant virus vaccines and gene therapies.

Vector design for liver specific expression of multiple interfering RNAs that target hepatitis B virus transcripts

PubMed Central

Snyder, Lindsey L.; Esser, Jonathan M.; Pachuk, Catherine J.; Steel, Laura F.

2008-01-01

RNA interference (RNAi) is a process that can target intracellular RNAs for degradation in a highly sequence specific manner, making it a powerful tool that is being pursued in both research and therapeutic applications. Hepatitis B virus (HBV) is a serious public health problem in need of better treatment options, and aspects of its life cycle make it an excellent target for RNAi-based therapeutics. We have designed a vector that expresses interfering RNAs that target HBV transcripts, including both viral RNA replicative intermediates and mRNAs encoding viral proteins. Our vector design incorporates many features of endogenous microRNA (miRNA) gene organization that are proving useful for the development of reagents for RNAi. In particular, our vector contains an RNA pol II driven gene cassette that leads to tissue specific expression and efficient processing of multiple interfering RNAs from a single transcript, without the co-expression of any protein product. This vector shows potent silencing of HBV targets in cell culture models of HBV infection. The vector design will be applicable to silencing of additional cellular or disease-related genes. PMID:18499277

Random mechanics: Nonlinear vibrations, turbulences, seisms, swells, fatigue

NASA Astrophysics Data System (ADS)

Kree, P.; Soize, C.

The random modeling of physical phenomena, together with probabilistic methods for the numerical calculation of random mechanical forces, are analytically explored. Attention is given to theoretical examinations such as probabilistic concepts, linear filtering techniques, and trajectory statistics. Applications of the methods to structures experiencing atmospheric turbulence, the quantification of turbulence, and the dynamic responses of the structures are considered. A probabilistic approach is taken to study the effects of earthquakes on structures and to the forces exerted by ocean waves on marine structures. Theoretical analyses by means of vector spaces and stochastic modeling are reviewed, as are Markovian formulations of Gaussian processes and the definition of stochastic differential equations. Finally, random vibrations with a variable number of links and linear oscillators undergoing the square of Gaussian processes are investigated.

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

DOEpatents

Gschwind, Michael K [Chappaqua, NY

2011-03-01

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

Diffusion theory of decision making in continuous report.

PubMed

Smith, Philip L

2016-07-01

I present a diffusion model for decision making in continuous report tasks, in which a continuous, circularly distributed, stimulus attribute in working memory is matched to a representation of the attribute in the stimulus display. Memory retrieval is modeled as a 2-dimensional diffusion process with vector-valued drift on a disk, whose bounding circle represents the decision criterion. The direction and magnitude of the drift vector describe the identity of the stimulus and the quality of its representation in memory, respectively. The point at which the diffusion exits the disk determines the reported value of the attribute and the time to exit the disk determines the decision time. Expressions for the joint distribution of decision times and report outcomes are obtained by means of the Girsanov change-of-measure theorem, which allows the properties of the nonzero-drift diffusion process to be characterized as a function of a Euclidian-distance Bessel process. Predicted report precision is equal to the product of the decision criterion and the drift magnitude and follows a von Mises distribution, in agreement with the treatment of precision in the working memory literature. Trial-to-trial variability in criterion and drift rate leads, respectively, to direct and inverse relationships between report accuracy and decision times, in agreement with, and generalizing, the standard diffusion model of 2-choice decisions. The 2-dimensional model provides a process account of working memory precision and its relationship with the diffusion model, and a new way to investigate the properties of working memory, via the distributions of decision times. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

NASA Astrophysics Data System (ADS)

Sun, J.; Li, Y.

2017-12-01

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

Soft-sensing model of temperature for aluminum reduction cell on improved twin support vector regression

NASA Astrophysics Data System (ADS)

Li, Tao

2018-06-01

The complexity of aluminum electrolysis process leads the temperature for aluminum reduction cells hard to measure directly. However, temperature is the control center of aluminum production. To solve this problem, combining some aluminum plant's practice data, this paper presents a Soft-sensing model of temperature for aluminum electrolysis process on Improved Twin Support Vector Regression (ITSVR). ITSVR eliminates the slow learning speed of Support Vector Regression (SVR) and the over-fit risk of Twin Support Vector Regression (TSVR) by introducing a regularization term into the objective function of TSVR, which ensures the structural risk minimization principle and lower computational complexity. Finally, the model with some other parameters as auxiliary variable, predicts the temperature by ITSVR. The simulation result shows Soft-sensing model based on ITSVR has short time-consuming and better generalization.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

U boson search in the e+ + e- → μ+μ-γ process

NASA Astrophysics Data System (ADS)

Curciarello, Francesca; KLOE/KLOE2 Collaboration

2013-03-01

Following recent puzzling astrophysical results and recent theoretical studies, a search for a relatively low mass (1 GeV) new vector gauge boson (called the U boson) was performed by means of the KLOE detector. Investigations were carried out using the Initial State Radiation and searching for the signal from the U boson in the e+ + e- → μ+μ-γ process. The KLOE experiment, at the phi-factory DAΦNE (INFN-LNF), is the first to have exploited ISR to precisely determine cross sections of e+ + e- → π+π-γ(γ) and e+ + e- → μ+μ-γ(γ) processes below 1 GeV. Investigations were based on the data sample collected in 2002, which corresponds to integrated luminosity of 239.29 pb-1. No evidence was found and a preliminary upper limit in the mass range between 600 and 1000 MeV was extracted.

An Analytical Investigation of the Robustness and Power of ANCOVA with the Presence of Heterogeneous Regression Slopes.

ERIC Educational Resources Information Center

Hollingsworth, Holly H.

This study shows that the test statistic for Analysis of Covariance (ANCOVA) has a noncentral F-districution with noncentrality parameter equal to zero if and only if the regression planes are homogeneous and/or the vector of overall covariate means is the null vector. The effect of heterogeneous regression slope parameters is to either increase…

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.

Malaria transmission in two localities in north-western Argentina

PubMed Central

Dantur Juri, María J; Zaidenberg, Mario; Claps, Guillermo L; Santana, Mirta; Almirón, Walter R

2009-01-01

Background Malaria is one of the most important tropical diseases that affects people globally. The influence of environmental conditions in the patterns of temporal distribution of malaria vectors and the disease has been studied in different countries. In the present study, ecological aspects of the malaria vector Anopheles (Anopheles) pseudopunctipennis and their relationship with climatic variables, as well as the seasonality of malaria cases, were studied in two localities, El Oculto and Aguas Blancas, in north-western Argentina. Methods The fluctuation of An. pseudopunctipennis and the malaria cases distribution was analysed with Random Effect Poisson Regression. This analysis takes into account the effect of each climatic variable on the abundance of both vector and malaria cases, giving as results predicted values named Incidence Rate Radio. Results The number of specimens collected in El Oculto and Aguas Blancas was 4224 (88.07%) and 572 (11.93%), respectively. In El Oculto no marked seasonality was found, different from Aguas Blancas, where high abundance was detected at the end of spring and the beginning of summer. The maximum mean temperature affected the An. pseudopunctipennis fluctuation in El Oculto and Aguas Blancas. When considering the relationship between the number of malaria cases and the climatic variables in El Oculto, maximum mean temperature and accumulated rainfall were significant, in contrast with Aguas Blancas, where mean temperature and humidity showed a closer relationship to the fluctuation in the disease. Conclusion The temporal distribution patterns of An. pseudopunctipennis vary in both localities, but spring appears as the season with better conditions for mosquito development. Maximum mean temperature was the most important variable in both localities. Malaria cases were influenced by the maximum mean temperature in El Oculto, while the mean temperature and humidity were significant in Aguas Blancas. In Aguas Blancas peaks of mosquito abundance and three months later, peaks of malaria cases were observed. The study reported here will help to increase knowledge about not only vectors and malaria seasonality but also their relationships with the climatic variables that influence their appearances and abundances. PMID:19152707

Detectable reporter gene expression following transduction of adenovirus and adeno-associated virus serotype 2 vectors within full-thickness osteoarthritic and unaffected canine cartilage in vitro and unaffected guinea pig cartilage in vivo.

PubMed

Santangelo, Kelly S; Baker, Sarah A; Nuovo, Gerard; Dyce, Jonathan; Bartlett, Jeffrey S; Bertone, Alicia L

2010-02-01

This study quantified and compared the transduction efficiencies of adenoviral (Ad), Arg-Gly-Asp (RGD)-modified Ad, adeno-associated viral serotype 2 (AAV2), and self-complementary AAV2 (scAAV2) vectors within full-thickness osteoarthritic (OA) and unaffected canine cartilage explants in vitro. Intraarticular administration of Ad and scAAV2 vectors was performed to determine the ability of these vectors to transduce unaffected guinea pig cartilage in vivo. Following explant exposure to vector treatment or control, the onset and surface distribution of reporter gene expression was monitored daily with fluorescent microscopy. At termination, explants were divided: one half was digested for analysis using flow cytometry; the remaining portion was used for histology and immunohistochemistry (IHC). Intact articular joints were collected for real-time RT-PCR and IHC to detect reporter gene expression following injection of selected vectors. Ad vector transduced focal areas along the perimeters of explants; the remaining vectors transduced chondrocytes across 100% of the surface. Greater mean transduction efficiencies were found with both AAV2 vectors as compared to the Ad vector (p < or = 0.026). Ad and Ad-RGD vectors transduced only superficial chondrocytes of OA and unaffected cartilage. Uniform reporter gene expression from AAV2 and scAAV2 was detected in the tangential and transitional zones of OA cartilage, but not deeper zones. AAV2 and scAAV2 vectors achieved partial and full-thickness transduction of unaffected cartilage. In vivo work revealed that scAAV2 vector, but not Ad vector, transduced deeper zones of cartilage and menisci. This study demonstrates that AAV2 and scAAV2 are reliable vectors for use in cartilage in vitro and in vivo. (c) 2009 Orthopaedic Research Society.

A survey of basic reproductive ratios in vector-borne disease transmission modeling

NASA Astrophysics Data System (ADS)

Soewono, E.; Aldila, D.

2015-03-01

Vector-borne diseases are commonly known in tropical and subtropical countries. These diseases have contributed to more than 10% of world infectious disease cases. Among the vectors responsible for transmitting the diseases are mosquitoes, ticks, fleas, flies, bugs and worms. Several of the diseases are known to contribute to the increasing threat to human health such as malaria, dengue, filariasis, chikungunya, west nile fever, yellow fever, encephalistis, and anthrax. It is necessary to understand the real process of infection, factors which contribute to the complication of the transmission in order to come up with a good and sound mathematical model. Although it is not easy to simulate the real transmission process of the infection, we could say that almost all models have been developed from the already long known Host-Vector model. It constitutes the main transmission processes i.e. birth, death, infection and recovery. From this simple model, the basic concepts of Disease Free and Endemic Equilibria and Basic Reproductive Ratio can be well explained and understood. Theoretical, modeling, control and treatment aspects of disease transmission problems have then been developed for various related diseases. General construction as well as specific forms of basic reproductive ratios for vector-borne diseases are discusses here.

Descriptive Statistics of the Genome: Phylogenetic Classification of Viruses.

PubMed

Hernandez, Troy; Yang, Jie

2016-10-01

The typical process for classifying and submitting a newly sequenced virus to the NCBI database involves two steps. First, a BLAST search is performed to determine likely family candidates. That is followed by checking the candidate families with the pairwise sequence alignment tool for similar species. The submitter's judgment is then used to determine the most likely species classification. The aim of this article is to show that this process can be automated into a fast, accurate, one-step process using the proposed alignment-free method and properly implemented machine learning techniques. We present a new family of alignment-free vectorizations of the genome, the generalized vector, that maintains the speed of existing alignment-free methods while outperforming all available methods. This new alignment-free vectorization uses the frequency of genomic words (k-mers), as is done in the composition vector, and incorporates descriptive statistics of those k-mers' positional information, as inspired by the natural vector. We analyze five different characterizations of genome similarity using k-nearest neighbor classification and evaluate these on two collections of viruses totaling over 10,000 viruses. We show that our proposed method performs better than, or as well as, other methods at every level of the phylogenetic hierarchy. The data and R code is available upon request.

Data filtering with support vector machines in geometric camera calibration.

PubMed

Ergun, B; Kavzoglu, T; Colkesen, I; Sahin, C

2010-02-01

The use of non-metric digital cameras in close-range photogrammetric applications and machine vision has become a popular research agenda. Being an essential component of photogrammetric evaluation, camera calibration is a crucial stage for non-metric cameras. Therefore, accurate camera calibration and orientation procedures have become prerequisites for the extraction of precise and reliable 3D metric information from images. The lack of accurate inner orientation parameters can lead to unreliable results in the photogrammetric process. A camera can be well defined with its principal distance, principal point offset and lens distortion parameters. Different camera models have been formulated and used in close-range photogrammetry, but generally sensor orientation and calibration is performed with a perspective geometrical model by means of the bundle adjustment. In this study, support vector machines (SVMs) using radial basis function kernel is employed to model the distortions measured for Olympus Aspherical Zoom lens Olympus E10 camera system that are later used in the geometric calibration process. It is intended to introduce an alternative approach for the on-the-job photogrammetric calibration stage. Experimental results for DSLR camera with three focal length settings (9, 18 and 36 mm) were estimated using bundle adjustment with additional parameters, and analyses were conducted based on object point discrepancies and standard errors. Results show the robustness of the SVMs approach on the correction of image coordinates by modelling total distortions on-the-job calibration process using limited number of images.

Recognition of acute lymphoblastic leukemia cells in microscopic images using k-means clustering and support vector machine classifier.

PubMed

Amin, Morteza Moradi; Kermani, Saeed; Talebi, Ardeshir; Oghli, Mostafa Ghelich

2015-01-01

Acute lymphoblastic leukemia is the most common form of pediatric cancer which is categorized into three L1, L2, and L3 and could be detected through screening of blood and bone marrow smears by pathologists. Due to being time-consuming and tediousness of the procedure, a computer-based system is acquired for convenient detection of Acute lymphoblastic leukemia. Microscopic images are acquired from blood and bone marrow smears of patients with Acute lymphoblastic leukemia and normal cases. After applying image preprocessing, cells nuclei are segmented by k-means algorithm. Then geometric and statistical features are extracted from nuclei and finally these cells are classified to cancerous and noncancerous cells by means of support vector machine classifier with 10-fold cross validation. These cells are also classified into their sub-types by multi-Support vector machine classifier. Classifier is evaluated by these parameters: Sensitivity, specificity, and accuracy which values for cancerous and noncancerous cells 98%, 95%, and 97%, respectively. These parameters are also used for evaluation of cell sub-types which values in mean 84.3%, 97.3%, and 95.6%, respectively. The results show that proposed algorithm could achieve an acceptable performance for the diagnosis of Acute lymphoblastic leukemia and its sub-types and can be used as an assistant diagnostic tool for pathologists.

Integrating an artificial intelligence approach with k-means clustering to model groundwater salinity: the case of Gaza coastal aquifer (Palestine)

NASA Astrophysics Data System (ADS)

Alagha, Jawad S.; Seyam, Mohammed; Md Said, Md Azlin; Mogheir, Yunes

2017-12-01

Artificial intelligence (AI) techniques have increasingly become efficient alternative modeling tools in the water resources field, particularly when the modeled process is influenced by complex and interrelated variables. In this study, two AI techniques—artificial neural networks (ANNs) and support vector machine (SVM)—were employed to achieve deeper understanding of the salinization process (represented by chloride concentration) in complex coastal aquifers influenced by various salinity sources. Both models were trained using 11 years of groundwater quality data from 22 municipal wells in Khan Younis Governorate, Gaza, Palestine. Both techniques showed satisfactory prediction performance, where the mean absolute percentage error (MAPE) and correlation coefficient ( R) for the test data set were, respectively, about 4.5 and 99.8% for the ANNs model, and 4.6 and 99.7% for SVM model. The performances of the developed models were further noticeably improved through preprocessing the wells data set using a k-means clustering method, then conducting AI techniques separately for each cluster. The developed models with clustered data were associated with higher performance, easiness and simplicity. They can be employed as an analytical tool to investigate the influence of input variables on coastal aquifer salinity, which is of great importance for understanding salinization processes, leading to more effective water-resources-related planning and decision making.

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.

Policy-based secure communication with automatic key management for industrial control and automation systems

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

Chernoguzov, Alexander; Markham, Thomas R.; Haridas, Harshal S.

A method includes generating at least one access vector associated with a specified device in an industrial process control and automation system. The specified device has one of multiple device roles. The at least one access vector is generated based on one or more communication policies defining communications between one or more pairs of devices roles in the industrial process control and automation system, where each pair of device roles includes the device role of the specified device. The method also includes providing the at least one access vector to at least one of the specified device and one ormore » more other devices in the industrial process control and automation system in order to control communications to or from the specified device.« less

Reporter gene expression in fish following cutaneous infection with pantropic retroviral vectors.

PubMed

Paul, T A; Burns, J C; Shike, H; Getchell, R; Bowser, P R; Whitlock, K E; Casey, J W

2001-06-01

A central issue in gene delivery systems is choosing promoters that will direct defined and sustainable levels of gene expression. Pantropic retroviral vectors provide a means to insert genes into either somatic or germline cells. In this study, we focused on somatic cell infection by evaluating the activity of 3 promoters inserted by vectors into fish cell lines and fish skin using pantropic retroviruses. In bluegill and zebrafish cell lines, the highest levels of luciferase expression were observed from the 5' murine leukemia virus long terminal repeat of the retroviral vector. The Rous sarcoma virus long terminal repeat and cytomegalovirus early promoter, as internal promoters, generated lower levels of luciferase. Luciferase reporter vectors infected zebrafish skin, as measured by the presence of viral DNA, and expressed luciferase. We infected developing walleye dermal sarcomas with retroviral vectors to provide an environment with enhanced cell proliferation, a condition necessary for integration of the provirus into the host genome. We demonstrated a 4-fold to 7-fold increase in luciferase gene expression in tumor tissue over infections in normal walleye skin.

Cascades on a stochastic pulse-coupled network

NASA Astrophysics Data System (ADS)

Wray, C. M.; Bishop, S. R.

2014-09-01

While much recent research has focused on understanding isolated cascades of networks, less attention has been given to dynamical processes on networks exhibiting repeated cascades of opposing influence. An example of this is the dynamic behaviour of financial markets where cascades of buying and selling can occur, even over short timescales. To model these phenomena, a stochastic pulse-coupled oscillator network with upper and lower thresholds is described and analysed. Numerical confirmation of asynchronous and synchronous regimes of the system is presented, along with analytical identification of the fixed point state vector of the asynchronous mean field system. A lower bound for the finite system mean field critical value of network coupling probability is found that separates the asynchronous and synchronous regimes. For the low-dimensional mean field system, a closed-form equation is found for cascade size, in terms of the network coupling probability. Finally, a description of how this model can be applied to interacting agents in a financial market is provided.

Cascades on a stochastic pulse-coupled network

PubMed Central

Wray, C. M.; Bishop, S. R.

2014-01-01

While much recent research has focused on understanding isolated cascades of networks, less attention has been given to dynamical processes on networks exhibiting repeated cascades of opposing influence. An example of this is the dynamic behaviour of financial markets where cascades of buying and selling can occur, even over short timescales. To model these phenomena, a stochastic pulse-coupled oscillator network with upper and lower thresholds is described and analysed. Numerical confirmation of asynchronous and synchronous regimes of the system is presented, along with analytical identification of the fixed point state vector of the asynchronous mean field system. A lower bound for the finite system mean field critical value of network coupling probability is found that separates the asynchronous and synchronous regimes. For the low-dimensional mean field system, a closed-form equation is found for cascade size, in terms of the network coupling probability. Finally, a description of how this model can be applied to interacting agents in a financial market is provided. PMID:25213626

Ecology of Yersinia pestis and the Epidemiology of Plague.

PubMed

Dubyanskiy, Vladimir M; Yeszhanov, Aidyn B

2016-01-01

This chapter summarizes information about the natural foci of plague in the world. We describe the location, main hosts, and vectors of Yersinia pestis. The ecological features of the hosts and vectors of plague are listed, including predators - birds and mammals and their role in the epizootic. The epizootic process in plague and the factors affecting the dynamics of epizootic activity of natural foci of Y. pestis are described in detail. The mathematical models of the epizootic process in plague and predictive models are briefly described. The most comprehensive list of the hosts and vectors of Y. pestis in the world is presented as well.

An Efficient and Robust Singular Value Method for Star Pattern Recognition and Attitude Determination

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Kim, Hye-Young; Junkins, John L.

2003-01-01

A new star pattern recognition method is developed using singular value decomposition of a measured unit column vector matrix in a measurement frame and the corresponding cataloged vector matrix in a reference frame. It is shown that singular values and right singular vectors are invariant with respect to coordinate transformation and robust under uncertainty. One advantage of singular value comparison is that a pairing process for individual measured and cataloged stars is not necessary, and the attitude estimation and pattern recognition process are not separated. An associated method for mission catalog design is introduced and simulation results are presented.

Dynamic visualization of data streams

DOEpatents

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

2009-07-07

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

The vectorization of a ray tracing program for image generation

NASA Technical Reports Server (NTRS)

Plunkett, D. J.; Cychosz, J. M.; Bailey, M. J.

1984-01-01

Ray tracing is a widely used method for producing realistic computer generated images. Ray tracing involves firing an imaginary ray from a view point, through a point on an image plane, into a three dimensional scene. The intersections of the ray with the objects in the scene determines what is visible at the point on the image plane. This process must be repeated many times, once for each point (commonly called a pixel) in the image plane. A typical image contains more than a million pixels making this process computationally expensive. A traditional ray tracing program processes one ray at a time. In such a serial approach, as much as ninety percent of the execution time is spent computing the intersection of a ray with the surface in the scene. With the CYBER 205, many rays can be intersected with all the bodies im the scene with a single series of vector operations. Vectorization of this intersection process results in large decreases in computation time. The CADLAB's interest in ray tracing stems from the need to produce realistic images of mechanical parts. A high quality image of a part during the design process can increase the productivity of the designer by helping him visualize the results of his work. To be useful in the design process, these images must be produced in a reasonable amount of time. This discussion will explain how the ray tracing process was vectorized and gives examples of the images obtained.

MISR Level 3 Cloud Motion Vector Versioning

Atmospheric Science Data Center

2016-11-04

... Versioning   Cloud Motion Vector Product (CMV) - Monthly, Quarterly, Yearly products Processing Status ... MI3MCMVN, MI3QCMVN, MI3YCMVN MISR_AM1_CMV Stage 1 Validated:  All parameters MISR maturity ...

Computing approximate random Delta v magnitude probability densities. [for spacecraft trajectory correction

NASA Technical Reports Server (NTRS)

Chadwick, C.

1984-01-01

This paper describes the development and use of an algorithm to compute approximate statistics of the magnitude of a single random trajectory correction maneuver (TCM) Delta v vector. The TCM Delta v vector is modeled as a three component Cartesian vector each of whose components is a random variable having a normal (Gaussian) distribution with zero mean and possibly unequal standard deviations. The algorithm uses these standard deviations as input to produce approximations to (1) the mean and standard deviation of the magnitude of Delta v, (2) points of the probability density function of the magnitude of Delta v, and (3) points of the cumulative and inverse cumulative distribution functions of Delta v. The approximates are based on Monte Carlo techniques developed in a previous paper by the author and extended here. The algorithm described is expected to be useful in both pre-flight planning and in-flight analysis of maneuver propellant requirements for space missions.

Hybrid biosynthetic gene therapy vector development and dual engineering capacity.

PubMed

Jones, Charles H; Ravikrishnan, Anitha; Chen, Mingfu; Reddinger, Ryan; Kamal Ahmadi, Mahmoud; Rane, Snehal; Hakansson, Anders P; Pfeifer, Blaine A

2014-08-26

Genetic vaccines offer a treatment opportunity based upon successful gene delivery to specific immune cell modulators. Driving the process is the vector chosen for gene cargo packaging and subsequent delivery to antigen-presenting cells (APCs) capable of triggering an immune cascade. As such, the delivery process must successfully navigate a series of requirements and obstacles associated with the chosen vector and target cell. In this work, we present the development and assessment of a hybrid gene delivery vector containing biological and biomaterial components. Each component was chosen to design and engineer gene delivery separately in a complimentary and fundamentally distinct fashion. A bacterial (Escherichia coli) inner core and a biomaterial [poly(beta-amino ester)]-coated outer surface allowed the simultaneous application of molecular biology and polymer chemistry to address barriers associated with APC gene delivery, which include cellular uptake and internalization, phagosomal escape, and intracellular cargo concentration. The approach combined and synergized normally disparate vector properties and tools, resulting in increased in vitro gene delivery beyond individual vector components or commercially available transfection agents. Furthermore, the hybrid device demonstrated a strong, efficient, and safe in vivo humoral immune response compared with traditional forms of antigen delivery. In summary, the flexibility, diversity, and potential of the hybrid design were developed and featured in this work as a platform for multivariate engineering at the vector and cellular scales for new applications in gene delivery immunotherapy.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Diamond-Based Magnetic Imaging with Fourier Optical Processing

NASA Astrophysics Data System (ADS)

Backlund, Mikael P.; Kehayias, Pauli; Walsworth, Ronald L.

2017-11-01

Diamond-based magnetic field sensors have attracted great interest in recent years. In particular, wide-field magnetic imaging using nitrogen-vacancy (NV) centers in diamond has been previously demonstrated in condensed matter, biological, and paleomagnetic applications. Vector magnetic imaging with NV ensembles typically requires a significant applied field (>10 G ) to resolve the contributions from four crystallographic orientations, hindering studies of magnetic samples that require measurement in low or independently specified bias fields. Here we model and measure the complex amplitude distribution of NV emission at the microscope's Fourier plane and show that by modulating this collected light at the Fourier plane, one can decompose the NV ensemble magnetic resonance spectrum into its constituent orientations by purely optical means. This decomposition effectively extends the dynamic range at a given bias field and enables wide-field vector magnetic imaging at arbitrarily low bias fields, thus broadening potential applications of NV imaging and sensing. Our results demonstrate that NV-based microscopy stands to benefit greatly from Fourier optical approaches, which have already found widespread utility in other branches of microscopy.

Localization of thermal anomalies in electrical equipment using Infrared Thermography and support vector machine

NASA Astrophysics Data System (ADS)

Laib dit Leksir, Y.; Mansour, M.; Moussaoui, A.

2018-03-01

Analysis and processing of databases obtained from infrared thermal inspections made on electrical installations require the development of new tools to obtain more information to visual inspections. Consequently, methods based on the capture of thermal images show a great potential and are increasingly employed in this field. However, there is a need for the development of effective techniques to analyse these databases in order to extract significant information relating to the state of the infrastructures. This paper presents a technique explaining how this approach can be implemented and proposes a system that can help to detect faults in thermal images of electrical installations. The proposed method classifies and identifies the region of interest (ROI). The identification is conducted using support vector machine (SVM) algorithm. The aim here is to capture the faults that exist in electrical equipments during an inspection of some machines using A40 FLIR camera. After that, binarization techniques are employed to select the region of interest. Later the comparative analysis of the obtained misclassification errors using the proposed method with Fuzzy c means and Ostu, has also be addressed.

Efficient solution of 3D electromagnetic eddy-current problems within the finite volume framework of OpenFOAM

NASA Astrophysics Data System (ADS)

Beckstein, Pascal; Galindo, Vladimir; Vukčević, Vuko

2017-09-01

Eddy-current problems occur in a wide range of industrial and metallurgical applications where conducting material is processed inductively. Motivated by realising coupled multi-physics simulations, we present a new method for the solution of such problems in the finite volume framework of foam-extend, an extended version of the very popular OpenFOAM software. The numerical procedure involves a semi-coupled multi-mesh approach to solve Maxwell's equations for non-magnetic materials by means of the Coulomb gauged magnetic vector potential A and the electric scalar potential ϕ. The concept is further extended on the basis of the impressed and reduced magnetic vector potential and its usage in accordance with Biot-Savart's law to achieve a very efficient overall modelling even for complex three-dimensional geometries. Moreover, we present a special discretisation scheme to account for possible discontinuities in the electrical conductivity. To complement our numerical method, an extensive validation is completing the paper, which provides insight into the behaviour and the potential of our approach.

Study to determine cloud motion from meteorological satellite data

NASA Technical Reports Server (NTRS)

Clark, B. B.

1972-01-01

Processing techniques were tested for deducing cloud motion vectors from overlapped portions of pairs of pictures made from meteorological satellites. This was accomplished by programming and testing techniques for estimating pattern motion by means of cross correlation analysis with emphasis placed upon identifying and reducing errors resulting from various factors. Techniques were then selected and incorporated into a cloud motion determination program which included a routine which would select and prepare sample array pairs from the preprocessed test data. The program was then subjected to limited testing with data samples selected from the Nimbus 4 THIR data provided by the 11.5 micron channel.

Discrete Fourier Transform in a Complex Vector Space

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2015-01-01

An image-based phase retrieval technique has been developed that can be used on board a space based iterative transformation system. Image-based wavefront sensing is computationally demanding due to the floating-point nature of the process. The discrete Fourier transform (DFT) calculation is presented in "diagonal" form. By diagonal we mean that a transformation of basis is introduced by an application of the similarity transform of linear algebra. The current method exploits the diagonal structure of the DFT in a special way, particularly when parts of the calculation do not have to be repeated at each iteration to converge to an acceptable solution in order to focus an image.

Multi-rate, real time image compression for images dominated by point sources

NASA Technical Reports Server (NTRS)

Huber, A. Kris; Budge, Scott E.; Harris, Richard W.

1993-01-01

An image compression system recently developed for compression of digital images dominated by point sources is presented. Encoding consists of minimum-mean removal, vector quantization, adaptive threshold truncation, and modified Huffman encoding. Simulations are presented showing that the peaks corresponding to point sources can be transmitted losslessly for low signal-to-noise ratios (SNR) and high point source densities while maintaining a reduced output bit rate. Encoding and decoding hardware has been built and tested which processes 552,960 12-bit pixels per second at compression rates of 10:1 and 4:1. Simulation results are presented for the 10:1 case only.

Systems thinking in combating infectious diseases.

PubMed

Xia, Shang; Zhou, Xiao-Nong; Liu, Jiming

2017-09-11

The transmission of infectious diseases is a dynamic process determined by multiple factors originating from disease pathogens and/or parasites, vector species, and human populations. These factors interact with each other and demonstrate the intrinsic mechanisms of the disease transmission temporally, spatially, and socially. In this article, we provide a comprehensive perspective, named as systems thinking, for investigating disease dynamics and associated impact factors, by means of emphasizing the entirety of a system's components and the complexity of their interrelated behaviors. We further develop the general steps for performing systems approach to tackling infectious diseases in the real-world settings, so as to expand our abilities to understand, predict, and mitigate infectious diseases.

Effect of filtration of signals of brain activity on quality of recognition of brain activity patterns using artificial intelligence methods

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Musatov, Vyachaslav Yu.

2018-02-01

In present work we studied features of the human brain states classification, corresponding to the real movements of hands and legs. For this purpose we used supervised learning algorithm based on feed-forward artificial neural networks (ANNs) with error back-propagation along with the support vector machine (SVM) method. We compared the quality of operator movements classification by means of EEG signals obtained experimentally in the absence of preliminary processing and after filtration in different ranges up to 25 Hz. It was shown that low-frequency filtering of multichannel EEG data significantly improved accuracy of operator movements classification.

Research on the technique of large-aperture off-axis parabolic surface processing using tri-station machine and its applicability.

PubMed

Zhang, Xin; Luo, Xiao; Hu, Haixiang; Zhang, Xuejun

2015-09-01

In order to process large-aperture aspherical mirrors, we designed and constructed a tri-station machine processing center with a three station device, which bears vectored feed motion of up to 10 axes. Based on this processing center, an aspherical mirror-processing model is proposed, in which each station implements traversal processing of large-aperture aspherical mirrors using only two axes, while the stations are switchable, thus lowering cost and enhancing processing efficiency. The applicability of the tri-station machine is also analyzed. At the same time, a simple and efficient zero-calibration method for processing is proposed. To validate the processing model, using our processing center, we processed an off-axis parabolic SiC mirror with an aperture diameter of 1450 mm. The experimental results indicate that, with a one-step iterative process, the peak to valley (PV) and root mean square (RMS) of the mirror converged from 3.441 and 0.5203 μm to 2.637 and 0.2962 μm, respectively, where the RMS reduced by 43%. The validity and high accuracy of the model are thereby demonstrated.

Multi-Contrast Multi-Atlas Parcellation of Diffusion Tensor Imaging of the Human Brain

PubMed Central

Tang, Xiaoying; Yoshida, Shoko; Hsu, John; Huisman, Thierry A. G. M.; Faria, Andreia V.; Oishi, Kenichi; Kutten, Kwame; Poretti, Andrea; Li, Yue; Miller, Michael I.; Mori, Susumu

2014-01-01

In this paper, we propose a novel method for parcellating the human brain into 193 anatomical structures based on diffusion tensor images (DTIs). This was accomplished in the setting of multi-contrast diffeomorphic likelihood fusion using multiple DTI atlases. DTI images are modeled as high dimensional fields, with each voxel exhibiting a vector valued feature comprising of mean diffusivity (MD), fractional anisotropy (FA), and fiber angle. For each structure, the probability distribution of each element in the feature vector is modeled as a mixture of Gaussians, the parameters of which are estimated from the labeled atlases. The structure-specific feature vector is then used to parcellate the test image. For each atlas, a likelihood is iteratively computed based on the structure-specific vector feature. The likelihoods from multiple atlases are then fused. The updating and fusing of the likelihoods is achieved based on the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation problems. We first demonstrate the performance of the algorithm by examining the parcellation accuracy of 18 structures from 25 subjects with a varying degree of structural abnormality. Dice values ranging 0.8–0.9 were obtained. In addition, strong correlation was found between the volume size of the automated and the manual parcellation. Then, we present scan-rescan reproducibility based on another dataset of 16 DTI images – an average of 3.73%, 1.91%, and 1.79% for volume, mean FA, and mean MD respectively. Finally, the range of anatomical variability in the normal population was quantified for each structure. PMID:24809486

Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

PubMed

Alcaide-Leon, P; Dufort, P; Geraldo, A F; Alshafai, L; Maralani, P J; Spears, J; Bharatha, A

2017-06-01

Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purpose of the study was to evaluate the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma and enhancing glioma. Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, and the resulting volumes of interest were mined for textural features and subjected to a support vector machine-based machine-learning protocol. Three readers classified the tumors independently on contrast-enhanced T1WI. Areas under the receiver operating characteristic curves were estimated for each reader and for the support vector machine classifier. A noninferiority test for diagnostic accuracy based on paired areas under the receiver operating characteristic curve was performed with a noninferiority margin of 0.15. The mean areas under the receiver operating characteristic curve were 0.877 (95% CI, 0.798-0.955) for the support vector machine classifier; 0.878 (95% CI, 0.807-0.949) for reader 1; 0.899 (95% CI, 0.833-0.966) for reader 2; and 0.845 (95% CI, 0.757-0.933) for reader 3. The mean area under the receiver operating characteristic curve of the support vector machine classifier was significantly noninferior to the mean area under the curve of reader 1 ( P = .021), reader 2 ( P = .035), and reader 3 ( P = .007). Support vector machine classification based on textural features of contrast-enhanced T1WI is noninferior to expert human evaluation in the differentiation of primary central nervous system lymphoma and enhancing glioma. © 2017 by American Journal of Neuroradiology.

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...

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

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).

Prediction of Broadband Shock-Associated Noise Including Propagation Effects Originating NASA

NASA Technical Reports Server (NTRS)

Miller, Steven; Morris, Philip J.

2012-01-01

An acoustic analogy is developed based on the Euler equations for broadband shock-associated noise (BBSAN) that directly incorporates the vector Green s function of the linearized Euler equations and a steady Reynolds-Averaged Navier-Stokes solution (SRANS) to describe the mean flow. The vector Green s function allows the BBSAN propagation through the jet shear layer to be determined. The large-scale coherent turbulence is modeled by two-point second order velocity cross-correlations. Turbulent length and time scales are related to the turbulent kinetic energy and dissipation rate. An adjoint vector Green s function solver is implemented to determine the vector Green s function based on a locally parallel mean flow at different streamwise locations. The newly developed acoustic analogy can be simplified to one that uses the Green s function associated with the Helmholtz equation, which is consistent with a previous formulation by the authors. A large number of predictions are generated using three different nozzles over a wide range of fully-expanded jet Mach numbers and jet stagnation temperatures. These predictions are compared with experimental data from multiple jet noise experimental facilities. In addition, two models for the so-called fine-scale mixing noise are included in the comparisons. Improved BBSAN predictions are obtained relative to other models that do not include propagation effects.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Noise-induced drift in two-dimensional anisotropic systems

NASA Astrophysics Data System (ADS)

Farago, Oded

2017-10-01

We study the isothermal Brownian dynamics of a particle in a system with spatially varying diffusivity. Due to the heterogeneity of the system, the particle's mean displacement does not vanish even if it does not experience any physical force. This phenomenon has been termed "noise-induced drift," and has been extensively studied for one-dimensional systems. Here, we examine the noise-induced drift in a two-dimensional anisotropic system, characterized by a symmetric diffusion tensor with unequal diagonal elements. A general expression for the mean displacement vector is derived and presented as a sum of two vectors, depicting two distinct drifting effects. The first vector describes the tendency of the particle to drift toward the high diffusivity side in each orthogonal principal diffusion direction. This is a generalization of the well-known expression for the noise-induced drift in one-dimensional systems. The second vector represents a novel drifting effect, not found in one-dimensional systems, originating from the spatial rotation in the directions of the principal axes. The validity of the derived expressions is verified by using Langevin dynamics simulations. As a specific example, we consider the relative diffusion of two transmembrane proteins, and demonstrate that the average distance between them increases at a surprisingly fast rate of several tens of micrometers per second.

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

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

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

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

PubMed

Illés, Tamás

2011-03-01

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

3D reconstruction of the magnetic vector potential using model based iterative reconstruction.

PubMed

Prabhat, K C; Aditya Mohan, K; Phatak, Charudatta; Bouman, Charles; De Graef, Marc

2017-11-01

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model for image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. A comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Does the arthropod microbiota impact the establishment of vector-borne diseases in mammalian hosts?

PubMed

Finney, Constance A M; Kamhawi, Shaden; Wasmuth, James D

2015-04-01

The impact of the microbiota on the immune status of its host is a source of intense research and publicity. In comparison, the effect of arthropod microbiota on vector-borne infectious diseases has received little attention. A better understanding of the vector microbiota in relation to mammalian host immune responses is vital, as it can lead to strategies that affect transmission and improve vaccine design in a field of research where few vaccines exist and effective treatment is rare. Recent demonstrations of how microbiota decrease pathogen development in arthropods, and thus alter vector permissiveness to vector-borne diseases (VBDs), have led to renewed interest. However, hypotheses on the interactions between the arthropod-derived microbiota and the mammalian hosts have yet to be addressed. Advances in DNA sequencing technology, increased yield and falling costs, mean that these studies are now feasible for many microbiologists and entomologists. Here, we distill current knowledge and put forward key questions and experimental designs to shed light on this burgeoning research topic.

Does the Arthropod Microbiota Impact the Establishment of Vector-Borne Diseases in Mammalian Hosts?

PubMed Central

Finney, Constance A. M.; Kamhawi, Shaden; Wasmuth, James D.

2015-01-01

The impact of the microbiota on the immune status of its host is a source of intense research and publicity. In comparison, the effect of arthropod microbiota on vector-borne infectious diseases has received little attention. A better understanding of the vector microbiota in relation to mammalian host immune responses is vital, as it can lead to strategies that affect transmission and improve vaccine design in a field of research where few vaccines exist and effective treatment is rare. Recent demonstrations of how microbiota decrease pathogen development in arthropods, and thus alter vector permissiveness to vector-borne diseases (VBDs), have led to renewed interest. However, hypotheses on the interactions between the arthropod-derived microbiota and the mammalian hosts have yet to be addressed. Advances in DNA sequencing technology, increased yield and falling costs, mean that these studies are now feasible for many microbiologists and entomologists. Here, we distill current knowledge and put forward key questions and experimental designs to shed light on this burgeoning research topic. PMID:25856431

3D reconstruction of the magnetic vector potential using model based iterative reconstruction

DOE PAGES

Prabhat, K. C.; Aditya Mohan, K.; Phatak, Charudatta; ...

2017-07-03

Lorentz transmission electron microscopy (TEM) observations of magnetic nanoparticles contain information on the magnetic and electrostatic potentials. Vector field electron tomography (VFET) can be used to reconstruct electromagnetic potentials of the nanoparticles from their corresponding LTEM images. The VFET approach is based on the conventional filtered back projection approach to tomographic reconstructions and the availability of an incomplete set of measurements due to experimental limitations means that the reconstructed vector fields exhibit significant artifacts. In this paper, we outline a model-based iterative reconstruction (MBIR) algorithm to reconstruct the magnetic vector potential of magnetic nanoparticles. We combine a forward model formore » image formation in TEM experiments with a prior model to formulate the tomographic problem as a maximum a-posteriori probability estimation problem (MAP). The MAP cost function is minimized iteratively to determine the vector potential. Here, a comparative reconstruction study of simulated as well as experimental data sets show that the MBIR approach yields quantifiably better reconstructions than the VFET approach.« less

Iris recognition using image moments and k-means algorithm.

PubMed

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%.

Iris Recognition Using Image Moments and k-Means Algorithm

PubMed Central

Khan, Yaser Daanial; Khan, Sher Afzal; Ahmad, Farooq; Islam, Saeed

2014-01-01

This paper presents a biometric technique for identification of a person using the iris image. The iris is first segmented from the acquired image of an eye using an edge detection algorithm. The disk shaped area of the iris is transformed into a rectangular form. Described moments are extracted from the grayscale image which yields a feature vector containing scale, rotation, and translation invariant moments. Images are clustered using the k-means algorithm and centroids for each cluster are computed. An arbitrary image is assumed to belong to the cluster whose centroid is the nearest to the feature vector in terms of Euclidean distance computed. The described model exhibits an accuracy of 98.5%. PMID:24977221

Hyperspectral recognition of processing tomato early blight based on GA and SVM

NASA Astrophysics Data System (ADS)

Yin, Xiaojun; Zhao, SiFeng

2013-03-01

Processing tomato early blight seriously affect the yield and quality of its.Determine the leaves spectrum of different disease severity level of processing tomato early blight.We take the sensitive bands of processing tomato early blight as support vector machine input vector.Through the genetic algorithm(GA) to optimize the parameters of SVM, We could recognize different disease severity level of processing tomato early blight.The result show:the sensitive bands of different disease severity levels of processing tomato early blight is 628-643nm and 689-692nm.The sensitive bands are as the GA and SVM input vector.We get the best penalty parameters is 0.129 and kernel function parameters is 3.479.We make classification training and testing by polynomial nuclear,radial basis function nuclear,Sigmoid nuclear.The best classification model is the radial basis function nuclear of SVM. Training accuracy is 84.615%,Testing accuracy is 80.681%.It is combined GA and SVM to achieve multi-classification of processing tomato early blight.It is provided the technical support of prediction processing tomato early blight occurrence, development and diffusion rule in large areas.

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

NASA Astrophysics Data System (ADS)

Lohe, M. A.

2018-06-01

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

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.

Long-term modulation of cosmic rays during solar cycle 21

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

MANCOVA for one way classification with homogeneity of regression coefficient vectors

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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.

Switching non-local vector median filter

NASA Astrophysics Data System (ADS)

Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji

2016-04-01

This paper describes a novel image filtering method that removes random-valued impulse noise superimposed on a natural color image. In impulse noise removal, it is essential to employ a switching-type filtering method, as used in the well-known switching median filter, to preserve the detail of an original image with good quality. In color image filtering, it is generally preferable to deal with the red (R), green (G), and blue (B) components of each pixel of a color image as elements of a vectorized signal, as in the well-known vector median filter, rather than as component-wise signals to prevent a color shift after filtering. By taking these fundamentals into consideration, we propose a switching-type vector median filter with non-local processing that mainly consists of a noise detector and a noise removal filter. Concretely, we propose a noise detector that proactively detects noise-corrupted pixels by focusing attention on the isolation tendencies of pixels of interest not in an input image but in difference images between RGB components. Furthermore, as the noise removal filter, we propose an extended version of the non-local median filter, we proposed previously for grayscale image processing, named the non-local vector median filter, which is designed for color image processing. The proposed method realizes a superior balance between the preservation of detail and impulse noise removal by proactive noise detection and non-local switching vector median filtering, respectively. The effectiveness and validity of the proposed method are verified in a series of experiments using natural color images.

Drop-out phagemid vector for switching from phage displayed affinity reagents to expression formats.

PubMed

Pershad, Kritika; Sullivan, Mark A; Kay, Brian K

2011-05-15

Affinity reagents that are generated by phage display are typically subcloned into an expression vector for further biochemical characterization. This insert transfer process is time consuming and laborious especially if many inserts are to be subcloned. To simplify the transfer process, we have constructed a "drop-out" phagemid vector that can be rapidly converted to an expression vector by a simple restriction enzyme digestion with MfeI (to "drop-out" the gene III coding sequence), which generates alkaline phosphatase (AP) fusions of the affinity reagents on religation. Subsequently, restriction digestion with AscI drops out the AP coding region and religation generates affinity reagents with a C-terminal six-histidine tag. To validate the usefulness of this vector, four different human single chain Fragments of variable regions (scFv) were tested, three of which show specific binding to three zebrafish (Danio rerio) proteins, namely suppression of tumorigenicity 13, recoverin, and Ppib and the fourth binds to human Lactoferrin protein. For each of the constructs tested, the gene III and AP drop-out efficiency was between 90% and 100%. This vector is especially useful in speeding up the downstream screening of affinity reagents and bypassing the time-consuming subcloning experiments. Copyright © 2011 Elsevier Inc. All rights reserved.

The Effects of Climate Change and Globalization on Mosquito Vectors: Evidence from Jeju Island, South Korea on the Potential for Asian Tiger Mosquito (Aedes albopictus) Influxes and Survival from Vietnam Rather Than Japan

PubMed Central

Jeong, Ji Yeon; Yoo, Seung Jin; Koh, Young-Sang; Lee, Seogjae; Heo, Sang Taek; Seong, Seung-Yong; Lee, Keun Hwa

2013-01-01

Background Climate change affects the survival and transmission of arthropod vectors as well as the development rates of vector-borne pathogens. Increased international travel is also an important factor in the spread of vector-borne diseases (VBDs) such as dengue, West Nile, yellow fever, chikungunya, and malaria. Dengue is the most important vector-borne viral disease. An estimated 2.5 billion people are at risk of infection in the world and there are approximately 50 million dengue infections and an estimated 500,000 individuals are hospitalized with dengue haemorrhagic fever annually. The Asian tiger mosquito (Aedes albopictus) is one of the vectors of dengue virus, and populations already exist on Jeju Island, South Korea. Currently, colder winter temperatures kill off Asian tiger mosquito populations and there is no evidence of the mosquitos being vectors for the dengue virus in this location. However, dengue virus-bearing mosquito vectors can inflow to Jeju Island from endemic area such as Vietnam by increased international travel, and this mosquito vector's survival during colder winter months will likely occur due to the effects of climate change. Methods and Results In this section, we show the geographical distribution of medically important mosquito vectors such as Ae. albopictus, a vector of both dengue and chikungunya viruses; Culex pipiens, a vector of West Nile virus; and Anopheles sinensis, a vector of Plasmodium vivax, within Jeju Island, South Korea. We found a significant association between the mean temperature, amount of precipitation, and density of mosquitoes. The phylogenetic analyses show that an Ae. albopictus, collected in southern area of Jeju Island, was identical to specimens found in Ho Chi Minh, Vietnam, and not Nagasaki, Japan. Conclusion Our results suggest that mosquito vectors or virus-bearing vectors can transmit from epidemic regions of Southeast Asia to Jeju Island and can survive during colder winter months. Therefore, Jeju Island is no longer safe from vector borne diseases (VBDs) due to the effects of globalization and climate change, and we should immediately monitor regional climate change to identify newly emerging VBDs. PMID:23894312

The effects of climate change and globalization on mosquito vectors: evidence from Jeju Island, South Korea on the potential for Asian tiger mosquito (Aedes albopictus) influxes and survival from Vietnam rather than Japan.

PubMed

Lee, Su Hyun; Nam, Kwang Woo; Jeong, Ji Yeon; Yoo, Seung Jin; Koh, Young-Sang; Lee, Seogjae; Heo, Sang Taek; Seong, Seung-Yong; Lee, Keun Hwa

2013-01-01

Climate change affects the survival and transmission of arthropod vectors as well as the development rates of vector-borne pathogens. Increased international travel is also an important factor in the spread of vector-borne diseases (VBDs) such as dengue, West Nile, yellow fever, chikungunya, and malaria. Dengue is the most important vector-borne viral disease. An estimated 2.5 billion people are at risk of infection in the world and there are approximately 50 million dengue infections and an estimated 500,000 individuals are hospitalized with dengue haemorrhagic fever annually. The Asian tiger mosquito (Aedes albopictus) is one of the vectors of dengue virus, and populations already exist on Jeju Island, South Korea. Currently, colder winter temperatures kill off Asian tiger mosquito populations and there is no evidence of the mosquitos being vectors for the dengue virus in this location. However, dengue virus-bearing mosquito vectors can inflow to Jeju Island from endemic area such as Vietnam by increased international travel, and this mosquito vector's survival during colder winter months will likely occur due to the effects of climate change. In this section, we show the geographical distribution of medically important mosquito vectors such as Ae. albopictus, a vector of both dengue and chikungunya viruses; Culex pipiens, a vector of West Nile virus; and Anopheles sinensis, a vector of Plasmodium vivax, within Jeju Island, South Korea. We found a significant association between the mean temperature, amount of precipitation, and density of mosquitoes. The phylogenetic analyses show that an Ae. albopictus, collected in southern area of Jeju Island, was identical to specimens found in Ho Chi Minh, Vietnam, and not Nagasaki, Japan. Our results suggest that mosquito vectors or virus-bearing vectors can transmit from epidemic regions of Southeast Asia to Jeju Island and can survive during colder winter months. Therefore, Jeju Island is no longer safe from vector borne diseases (VBDs) due to the effects of globalization and climate change, and we should immediately monitor regional climate change to identify newly emerging VBDs.

Robust resolution enhancement optimization methods to process variations based on vector imaging model

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong

2012-03-01

Optical proximity correction (OPC) and phase shifting mask (PSM) are the most widely used resolution enhancement techniques (RET) in the semiconductor industry. Recently, a set of OPC and PSM optimization algorithms have been developed to solve for the inverse lithography problem, which are only designed for the nominal imaging parameters without giving sufficient attention to the process variations due to the aberrations, defocus and dose variation. However, the effects of process variations existing in the practical optical lithography systems become more pronounced as the critical dimension (CD) continuously shrinks. On the other hand, the lithography systems with larger NA (NA>0.6) are now extensively used, rendering the scalar imaging models inadequate to describe the vector nature of the electromagnetic field in the current optical lithography systems. In order to tackle the above problems, this paper focuses on developing robust gradient-based OPC and PSM optimization algorithms to the process variations under a vector imaging model. To achieve this goal, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. The steepest descent algorithm is used to optimize the mask iteratively. In order to improve the efficiency of the proposed algorithms, a set of algorithm acceleration techniques (AAT) are exploited during the optimization procedure.

42 CFR 71.50 - Scope and definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... importations of various animal hosts or vectors or other etiological agents from foreign countries into the... the following meanings: Animal product or Product means the hide, hair, skull, teeth, bones, claws, blood, tissue, or other biological samples from an animal, including trophies, mounts, rugs, or other...

42 CFR 71.50 - Scope and definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... importations of various animal hosts or vectors or other etiological agents from foreign countries into the... the following meanings: Animal product or Product means the hide, hair, skull, teeth, bones, claws, blood, tissue, or other biological samples from an animal, including trophies, mounts, rugs, or other...

Support Vector Data Descriptions and k-Means Clustering: One Class?

PubMed

Gornitz, Nico; Lima, Luiz Alberto; Muller, Klaus-Robert; Kloft, Marius; Nakajima, Shinichi

2017-09-27

We present ClusterSVDD, a methodology that unifies support vector data descriptions (SVDDs) and k-means clustering into a single formulation. This allows both methods to benefit from one another, i.e., by adding flexibility using multiple spheres for SVDDs and increasing anomaly resistance and flexibility through kernels to k-means. In particular, our approach leads to a new interpretation of k-means as a regularized mode seeking algorithm. The unifying formulation further allows for deriving new algorithms by transferring knowledge from one-class learning settings to clustering settings and vice versa. As a showcase, we derive a clustering method for structured data based on a one-class learning scenario. Additionally, our formulation can be solved via a particularly simple optimization scheme. We evaluate our approach empirically to highlight some of the proposed benefits on artificially generated data, as well as on real-world problems, and provide a Python software package comprising various implementations of primal and dual SVDD as well as our proposed ClusterSVDD.

[Comparison of the temperature-driven seasonality of campylobacteriosis and salmonellosis and the annual phenology of Eristalis tenax (Diptera: Syrphidae)].

PubMed

Trájer, Attila; Schoffhauzer, Judit

2016-04-03

Ambient temperature and the activity of Diptera species are the primary factors of the seasonality of bacterial enteral diseases. The authors analyzed the effect of the weekly mean ambient temperature on salmonellosis and campylobacteriosis incidence and the annual phenology of the potential vector Eristalis tenax. Weekly case number data of the period between 2004 and 2014 were derived from the Hungarian National Center for Epidemiology. European Climate Assessment Dataset was the source of the weekly mean temperature data for the grid overlapping Hungary. While in the case of campylobacteriosis weak correlation was found (r(2) = 0.39), salmonellosis showed strong correlation with mean temperature (r(2) = 0.71) using 8-weeks lag before the outbreak of the cases. Comparing the mean weekly incidence of campylobacteriosis and salmonellosis with the modeled weekly activity of Eristalis tenax it was found that vector Diptera species may influence the incidence of enteric diseases in late spring and summer, in July and August particularly.

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.

Meta-analysis of the effects of insect vector saliva on host immune responses and infection of vector-transmitted pathogens: a focus on leishmaniasis.

PubMed

Ockenfels, Brittany; Michael, Edwin; McDowell, Mary Ann

2014-10-01

A meta-analysis of the effects of vector saliva on the immune response and progression of vector-transmitted disease, specifically with regard to pathology, infection level, and host cytokine levels was conducted. Infection in the absence or presence of saliva in naïve mice was compared. In addition, infection in mice pre-exposed to uninfected vector saliva was compared to infection in unexposed mice. To control for differences in vector and pathogen species, mouse strain, and experimental design, a random effects model was used to compare the ratio of the natural log of the experimental to the control means of the studies. Saliva was demonstrated to enhance pathology, infection level, and the production of Th2 cytokines (IL-4 and IL-10) in naïve mice. This effect was observed across vector/pathogen pairings, whether natural or unnatural, and with single salivary proteins used as a proxy for whole saliva. Saliva pre-exposure was determined to result in less severe leishmaniasis pathology when compared with unexposed mice infected either in the presence or absence of sand fly saliva. The results of further analyses were not significant, but demonstrated trends toward protection and IFN-γ elevation for pre-exposed mice.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Algorithms for solving large sparse systems of simultaneous linear equations on vector processors

NASA Technical Reports Server (NTRS)

David, R. E.

1984-01-01

Very efficient algorithms for solving large sparse systems of simultaneous linear equations have been developed for serial processing computers. These involve a reordering of matrix rows and columns in order to obtain a near triangular pattern of nonzero elements. Then an LU factorization is developed to represent the matrix inverse in terms of a sequence of elementary Gaussian eliminations, or pivots. In this paper it is shown how these algorithms are adapted for efficient implementation on vector processors. Results obtained on the CYBER 200 Model 205 are presented for a series of large test problems which show the comparative advantages of the triangularization and vector processing algorithms.

Vectorized Monte Carlo methods for reactor lattice analysis

NASA Technical Reports Server (NTRS)

Brown, F. B.

1984-01-01

Some of the new computational methods and equivalent mathematical representations of physics models used in the MCV code, a vectorized continuous-enery Monte Carlo code for use on the CYBER-205 computer are discussed. While the principal application of MCV is the neutronics analysis of repeating reactor lattices, the new methods used in MCV should be generally useful for vectorizing Monte Carlo for other applications. For background, a brief overview of the vector processing features of the CYBER-205 is included, followed by a discussion of the fundamentals of Monte Carlo vectorization. The physics models used in the MCV vectorized Monte Carlo code are then summarized. The new methods used in scattering analysis are presented along with details of several key, highly specialized computational routines. Finally, speedups relative to CDC-7600 scalar Monte Carlo are discussed.

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

PubMed Central

Shafapour Tehrany, Mahyat; Solhjouy-fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion. PMID:29576954

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

PubMed

Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion.

Virtual head rotation reveals a process of route reconstruction from human vestibular signals

PubMed Central

Day, Brian L; Fitzpatrick, Richard C

2005-01-01

The vestibular organs can feed perceptual processes that build a picture of our route as we move about in the world. However, raw vestibular signals do not define the path taken because, during travel, the head can undergo accelerations unrelated to the route and also be orientated in any direction to vary the signal. This study investigated the computational process by which the brain transforms raw vestibular signals for the purpose of route reconstruction. We electrically stimulated the vestibular nerves of human subjects to evoke a virtual head rotation fixed in skull co-ordinates and measure its perceptual effect. The virtual head rotation caused subjects to perceive an illusory whole-body rotation that was a cyclic function of head-pitch angle. They perceived whole-body yaw rotation in one direction with the head pitched forwards, the opposite direction with the head pitched backwards, and no rotation with the head in an intermediate position. A model based on vector operations and the anatomy and firing properties of semicircular canals precisely predicted these perceptions. In effect, a neural process computes the vector dot product between the craniocentric vestibular vector of head rotation and the gravitational unit vector. This computation yields the signal of body rotation in the horizontal plane that feeds our perception of the route travelled. PMID:16002439

Can Horton hear the whos? The importance of scale in mosquito-borne disease.

PubMed

Lord, C C; Alto, B W; Anderson, S L; Connelly, C R; Day, J F; Richards, S L; Smartt, C T; Tabachnick, W J

2014-03-01

The epidemiology of vector-borne pathogens is determined by mechanisms and interactions at different scales of biological organization, from individual-level cellular processes to community interactions between species and with the environment. Most research, however, focuses on one scale or level with little integration between scales or levels within scales. Understanding the interactions between levels and how they influence our perception of vector-borne pathogens is critical. Here two examples of biological scales (pathogen transmission and mosquito mortality) are presented to illustrate some of the issues of scale and to explore how processes on different levels may interact to influence mosquito-borne pathogen transmission cycles. Individual variation in survival, vector competence, and other traits affect population abundance, transmission potential, and community structure. Community structure affects interactions between individuals such as competition and predation, and thus influences the individual-level dynamics and transmission potential. Modeling is a valuable tool to assess interactions between scales and how processes at different levels can affect transmission dynamics. We expand an existing model to illustrate the types of studies needed, showing that individual-level variation in viral dose acquired or needed for infection can influence the number of infectious vectors. It is critical that interactions within and among biological scales and levels of biological organization are understood for greater understanding of pathogen transmission with the ultimate goal of improving control of vector-borne pathogens.

A Fast SVM-Based Tongue's Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis.

PubMed

Kamarudin, Nur Diyana; Ooi, Chia Yee; Kawanabe, Tadaaki; Odaguchi, Hiroshi; Kobayashi, Fuminori

2017-01-01

In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k -means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k -means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds.

A Fast SVM-Based Tongue's Colour Classification Aided by k-Means Clustering Identifiers and Colour Attributes as Computer-Assisted Tool for Tongue Diagnosis

PubMed Central

Ooi, Chia Yee; Kawanabe, Tadaaki; Odaguchi, Hiroshi; Kobayashi, Fuminori

2017-01-01

In tongue diagnosis, colour information of tongue body has kept valuable information regarding the state of disease and its correlation with the internal organs. Qualitatively, practitioners may have difficulty in their judgement due to the instable lighting condition and naked eye's ability to capture the exact colour distribution on the tongue especially the tongue with multicolour substance. To overcome this ambiguity, this paper presents a two-stage tongue's multicolour classification based on a support vector machine (SVM) whose support vectors are reduced by our proposed k-means clustering identifiers and red colour range for precise tongue colour diagnosis. In the first stage, k-means clustering is used to cluster a tongue image into four clusters of image background (black), deep red region, red/light red region, and transitional region. In the second-stage classification, red/light red tongue images are further classified into red tongue or light red tongue based on the red colour range derived in our work. Overall, true rate classification accuracy of the proposed two-stage classification to diagnose red, light red, and deep red tongue colours is 94%. The number of support vectors in SVM is improved by 41.2%, and the execution time for one image is recorded as 48 seconds. PMID:29065640

Current observations offshore Punta Tuna, Puerto Rico, 21 June-7 December 1980. Part A

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

Frye, D.; Leavitt, K.; Whitney, A.

1981-08-01

An oceanographic measurement program was conducted in the vicinity of a proposed ocean thermal energy conversion (OTEC) site about 20 km offshore of Punta Tuna, Puerto Rico. As part of the program, a mooring consisting of five current meters was maintained between 21 June and 7 December, 1980. The current data collected are summarized according to frequency of occurrence within 5 cm/sec speed and 15/sup 0/ direction intervals. Sums and percentages of total occurrence are given for each speed and direction class, along with mean speed, extreme speeds, mean component speeds, and standard deviations. Hourly averages of current speed, truemore » direction, current vector, temperature, and pressure are plotted as a function of time. On 13 December, 1980, a current meter array was deployed at the Punta Tuna site and recovered on May 16, 1981. The processed current data from this current meter array are described. (LEW)« less

Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux

PubMed Central

Lee, Jonghwan; Jiang, James Y.; Wu, Weicheng; Lesage, Frederic; Boas, David A.

2014-01-01

We present a novel optical coherence tomography (OCT)-based technique for rapid volumetric imaging of red blood cell (RBC) flux in capillary networks. Previously we reported that OCT can capture individual RBC passage within a capillary, where the OCT intensity signal at a voxel fluctuates when an RBC passes the voxel. Based on this finding, we defined a metric of statistical intensity variation (SIV) and validated that the mean SIV is proportional to the RBC flux [RBC/s] through simulations and measurements. From rapidly scanned volume data, we used Hessian matrix analysis to vectorize a segment path of each capillary and estimate its flux from the mean of the SIVs gathered along the path. Repeating this process led to a 3D flux map of the capillary network. The present technique enabled us to trace the RBC flux changes over hundreds of capillaries with a temporal resolution of ~1 s during functional activation. PMID:24761298

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

PubMed

Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

2015-08-01

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

3-D Vector Flow Estimation With Row-Column-Addressed Arrays.

PubMed

Holbek, Simon; Christiansen, Thomas Lehrmann; Stuart, Matthias Bo; Beers, Christopher; Thomsen, Erik Vilain; Jensen, Jorgen Arendt

2016-11-01

Simulation and experimental results from 3-D vector flow estimations for a 62 + 62 2-D row-column (RC) array with integrated apodization are presented. A method for implementing a 3-D transverse oscillation (TO) velocity estimator on a 3-MHz RC array is developed and validated. First, a parametric simulation study is conducted, where flow direction, ensemble length, number of pulse cycles, steering angles, transmit/receive apodization, and TO apodization profiles and spacing are varied, to find the optimal parameter configuration. The performance of the estimator is evaluated with respect to relative mean bias ~B and mean standard deviation ~σ . Second, the optimal parameter configuration is implemented on the prototype RC probe connected to the experimental ultrasound scanner SARUS. Results from measurements conducted in a flow-rig system containing a constant laminar flow and a straight-vessel phantom with a pulsating flow are presented. Both an M-mode and a steered transmit sequence are applied. The 3-D vector flow is estimated in the flow rig for four representative flow directions. In the setup with 90° beam-to-flow angle, the relative mean bias across the entire velocity profile is (-4.7, -0.9, 0.4)% with a relative standard deviation of (8.7, 5.1, 0.8)% for ( v x , v y , v z ). The estimated peak velocity is 48.5 ± 3 cm/s giving a -3% bias. The out-of-plane velocity component perpendicular to the cross section is used to estimate volumetric flow rates in the flow rig at a 90° beam-to-flow angle. The estimated mean flow rate in this setup is 91.2 ± 3.1 L/h corresponding to a bias of -11.1%. In a pulsating flow setup, flow rate measured during five cycles is 2.3 ± 0.1 mL/stroke giving a negative 9.7% bias. It is concluded that accurate 3-D vector flow estimation can be obtained using a 2-D RC-addressed array.

Tightly-wound miniknot vectors for gene therapy: a potential improvement over supercoiled minicircle DNA.

PubMed

Tolmachov, Oleg E

2010-04-01

Minimized derivatives of bacterial plasmids with removed bacterial backbones are promising vectors for the efficient delivery and for the long-term expression of therapeutic genes. The absence of the bacterial plasmid backbone, a known inducer of innate immune response and a known silencer of transgene expression, provides a partial explanation for the high efficiency of gene transfer using minimized DNA vectors. Supercoiled minicircle DNA is a type of minimized DNA vector obtained via intra-plasmid recombination in bacteria. Minicircle vectors seem to get an additional advantage from their physical compactness, which reduces DNA damage due to the mechanical stress during gene delivery. An independent topological means for DNA compression is knotting, with some knotted DNA isoforms offering superior compactness. I propose that, firstly, knotted DNA can be a suitable compact DNA form for the efficient transfection of a range of human cells with therapeutic genes, and, secondly, that knotted minimized DNA vectors without bacterial backbones ("miniknot" vectors) can surpass supercoiled minicircle DNA vectors in the efficiency of therapeutic gene delivery. Crucially, while the introduction of a single nick to a supercoiled DNA molecule leads to the loss of the compact supercoiled status, the introduction of nicks to knotted DNA does not change knotting. Tight miniknot vectors can be readily produced by the direct action of highly concentrated type II DNA topoisomerase on minicircle DNA or, alternatively, by annealing of the 19-base cohesive ends of the minimized vectors confined within the capsids of Escherichia coli bacteriophage P2 or its satellite bacteriophage P4. After reaching the nucleoplasm of the target cell, the knotted DNA is expected to be unknotted through type II topoisomerase activity and thus to become available for transcription, chromosomal integration or episomal maintenance. The hypothesis can be tested by comparing the gene transfer efficiency achieved with the proposed miniknot vectors, the minicircle vectors described previously, knotted plasmid vectors and standard plasmid vectors. Tightly-wound miniknots can be particularly useful in the gene administration procedures involving considerable forces acting on vector DNA: aerosol inhalation, jet-injection, electroporation, particle bombardment and ultrasound DNA transfer. (c) 2009 Elsevier Ltd. All rights reserved.

Construction of fusion vectors of corynebacteria: expression of glutathione-S-transferase fusion protein in Corynebacterium acetoacidophilum ATCC 21476.

PubMed

Srivastava, Preeti; Deb, J K

2002-07-02

A series of fusion vectors containing glutathione-S-transferase (GST) were constructed by inserting GST fusion cassette of Escherichia coli vectors pGEX4T-1, -2 and -3 in corynebacterial vector pBK2. Efficient expression of GST driven by inducible tac promoter of E. coli was observed in Corynebacterium acetoacidophilum. Fusion of enhanced green fluorescent protein (EGFP) and streptokinase genes in this vector resulted in the synthesis of both the fusion proteins. The ability of this recombinant organism to produce several-fold more of the product in the extracellular medium than in the intracellular space would make this system quite attractive as far as the downstream processing of the product is concerned.

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

PubMed

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

2018-01-01

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

The Utility of SAR to Monitor Ocean Processes.

DTIC Science & Technology

1981-11-01

echo received from ocean waves include the motion of the a horizontally polarized wave will have its E vector parallel to scattering surfaces, the so...radiation is defined by the direction of the electric field intensity, E, vector . For example, a horizontally polarized wave will have its E vector ...Oil Spill Off the East Coast of the United States ................ .... 55 19. L-band Parallel and Cross Polarized SAR Imagery of Ice in the Beaufort

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

DTIC Science & Technology

2013-05-28

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

[Lymphoscintigrams with anatomical landmarks obtained with vector graphics].

PubMed

Rubini, Giuseppe; Antonica, Filippo; Renna, Maria Antonia; Ferrari, Cristina; Iuele, Francesca; Stabile Ianora, Antonio Amato; Losco, Matteo; Niccoli Asabella, Artor

2012-11-01

Nuclear medicine images are difficult to interpret because they do not include anatomical details. The aim of this study was to obtain lymphoscintigrams with anatomical landmarks that could be easily interpreted by General Physicians. Traditional lymphoscintigrams were processed with Adobe© Photoshop® CS6 and converted into vector images created by Illustrator®. The combination with a silhouette vector improved image interpretation, without resulting in longer radiation exposure or acquisition times.

International solar polar mission: The vector helium magnetometer

NASA Technical Reports Server (NTRS)

1982-01-01

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

Split Octonion Reformulation for Electromagnetic Chiral Media of Massive Dyons

NASA Astrophysics Data System (ADS)

Chanyal, B. C.

2017-12-01

In an explicit, unified, and covariant formulation of an octonion algebra, we study and generalize the electromagnetic chiral fields equations of massive dyons with the split octonionic representation. Starting with 2×2 Zorn’s vector matrix realization of split-octonion and its dual Euclidean spaces, we represent the unified structure of split octonionic electric and magnetic induction vectors for chiral media. As such, in present paper, we describe the chiral parameter and pairing constants in terms of split octonionic matrix representation of Drude-Born-Fedorov constitutive relations. We have expressed a split octonionic electromagnetic field vector for chiral media, which exhibits the unified field structure of electric and magnetic chiral fields of dyons. The beauty of split octonionic representation of Zorn vector matrix realization is that, the every scalar and vector components have its own meaning in the generalized chiral electromagnetism of dyons. Correspondingly, we obtained the alternative form of generalized Proca-Maxwell’s equations of massive dyons in chiral media. Furthermore, the continuity equations, Poynting theorem and wave propagation for generalized electromagnetic fields of chiral media of massive dyons are established by split octonionic form of Zorn vector matrix algebra.

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.

Regularized estimation of Euler pole parameters

NASA Astrophysics Data System (ADS)

Aktuğ, Bahadir; Yildirim, Ömer

2013-07-01

Euler vectors provide a unified framework to quantify the relative or absolute motions of tectonic plates through various geodetic and geophysical observations. With the advent of space geodesy, Euler parameters of several relatively small plates have been determined through the velocities derived from the space geodesy observations. However, the available data are usually insufficient in number and quality to estimate both the Euler vector components and the Euler pole parameters reliably. Since Euler vectors are defined globally in an Earth-centered Cartesian frame, estimation with the limited geographic coverage of the local/regional geodetic networks usually results in highly correlated vector components. In the case of estimating the Euler pole parameters directly, the situation is even worse, and the position of the Euler pole is nearly collinear with the magnitude of the rotation rate. In this study, a new method, which consists of an analytical derivation of the covariance matrix of the Euler vector in an ideal network configuration, is introduced and a regularized estimation method specifically tailored for estimating the Euler vector is presented. The results show that the proposed method outperforms the least squares estimation in terms of the mean squared error.

Extraction of inland Nypa fruticans (Nipa Palm) using Support Vector Machine

NASA Astrophysics Data System (ADS)

Alberto, R. T.; Serrano, S. C.; Damian, G. B.; Camaso, E. E.; Biagtan, A. R.; Panuyas, N. Z.; Quibuyen, J. S.

2017-09-01

Mangroves are considered as one of the major habitats in coastal ecosystem, providing a lot of economic and ecological services in human society. Nypa fruticans (Nipa palm) is one of the important species of mangroves because of its versatility and uniqueness as halophytic palm. However, nipas are not only adaptable in saline areas, they can also managed to thrive away from the coastline depending on the favorable soil types available in the area. Because of this, mapping of this species are not limited alone in the near shore areas, but in areas where this species are present as well. The extraction process of Nypa fruticans were carried out using the available LiDAR data. Support Vector Machine (SVM) classification process was used to extract nipas in inland areas. The SVM classification process in mapping Nypa fruticans produced high accuracy of 95+%. The Support Vector Machine classification process to extract inland nipas was proven to be effective by utilizing different terrain derivatives from LiDAR data.

The Anopheles gambiae transcriptome - a turning point for malaria control.

PubMed

Domingos, A; Pinheiro-Silva, R; Couto, J; do Rosário, V; de la Fuente, J

2017-04-01

Mosquitoes are important vectors of several pathogens and thereby contribute to the spread of diseases, with social, economic and public health impacts. Amongst the approximately 450 species of Anopheles, about 60 are recognized as vectors of human malaria, the most important parasitic disease. In Africa, Anopheles gambiae is the main malaria vector mosquito. Current malaria control strategies are largely focused on drugs and vector control measures such as insecticides and bed-nets. Improvement of current, and the development of new, mosquito-targeted malaria control methods rely on a better understanding of mosquito vector biology. An organism's transcriptome is a reflection of its physiological state and transcriptomic analyses of different conditions that are relevant to mosquito vector competence can therefore yield important information. Transcriptomic analyses have contributed significant information on processes such as blood-feeding parasite-vector interaction, insecticide resistance, and tissue- and stage-specific gene regulation, thereby facilitating the path towards the development of new malaria control methods. Here, we discuss the main applications of transcriptomic analyses in An. gambiae that have led to a better understanding of mosquito vector competence. © 2017 The Royal Entomological Society.

Correlated Topic Vector for Scene Classification.

PubMed

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

2017-07-01

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

Rotation invariants of vector fields from orthogonal moments

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

Yang, Bo; Kostková, Jitka; Flusser, Jan

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

Rate determination from vector observations

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.

1993-01-01

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

Product-Related Impurities in Clinical-Grade Recombinant AAV Vectors: Characterization and Risk Assessment

PubMed Central

Wright, J. Fraser

2014-01-01

Adeno-associated virus (AAV)-based vectors expressing therapeutic genes continue to demonstrate great promise for the treatment of a wide variety of diseases and together with other gene transfer vectors represent an emerging new therapeutic paradigm comparable in potential impact on human health to that achieved by recombinant proteins and vaccines. A challenge for the current pipeline of AAV-based investigational products as they advance through clinical development is the identification, characterization and lot-to-lot control of the process- and product-related impurities present in even highly purified preparations. Especially challenging are AAV vector product-related impurities that closely resemble the vector itself and are, in some cases, without clear precedent in established biotherapeutic products. The determination of acceptable levels of these impurities in vectors prepared for human clinical product development, with the goal of new product licensure, requires careful risk and feasibility assessment. This review focuses primarily on the AAV product-related impurities that have been described in vectors prepared for clinical development. PMID:28548061

Rotation invariants of vector fields from orthogonal moments

DOE PAGES

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

2017-09-11

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

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

PubMed Central

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

2007-01-01

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

Peculiar liquid-feeding and pathogen transmission behavior of Aedes togoi and comparison with Anopheles sinensis.

PubMed

Lee, Sang Joon; Kang, Dooho; Lee, Seung Chul; Ha, Young-Ran

2016-02-03

Female mosquitoes transmit various diseases as vectors during liquid-feeding. Identifying the determinants of vector efficiency is a major scientific challenge in establishing strategies against these diseases. Infection rate and transmission efficiency are interconnected with the mosquito-induced liquid-feeding flow as main indexes of vector efficiency. However, the relationship between liquid-feeding characteristics and pathogen remains poorly understood. The liquid-feeding behavior of Aedes togoi and Anopheles sinensis was comparatively investigated in conjunction with vector efficiency via micro-particle image velocimetry. The flow rates and ratio of the ejection volume of Aedes togoi were markedly higher than those of Anophels sinensis. These differences would influence pathogen re-ingestion. Wall shear stresses of these mosquito species were also clearly discriminatory affecting the infective rates of vector-borne diseases. The variations in volume of two pump chambers and diameter of proboscis of these mosquito species were compared to determine the differences in the liquid-feeding process. Liquid-feeding characteristics influence vector efficiency; hence, this study can elucidate the vector efficiency of mosquitoes and the vector-pathogen interactions and contribute to the development of strategies against vector-borne diseases.

Peculiar liquid-feeding and pathogen transmission behavior of Aedes togoi and comparison with Anopheles sinensis

NASA Astrophysics Data System (ADS)

Lee, Sang Joon; Kang, Dooho; Lee, Seung Chul; Ha, Young-Ran

2016-02-01

Female mosquitoes transmit various diseases as vectors during liquid-feeding. Identifying the determinants of vector efficiency is a major scientific challenge in establishing strategies against these diseases. Infection rate and transmission efficiency are interconnected with the mosquito-induced liquid-feeding flow as main indexes of vector efficiency. However, the relationship between liquid-feeding characteristics and pathogen remains poorly understood. The liquid-feeding behavior of Aedes togoi and Anopheles sinensis was comparatively investigated in conjunction with vector efficiency via micro-particle image velocimetry. The flow rates and ratio of the ejection volume of Aedes togoi were markedly higher than those of Anophels sinensis. These differences would influence pathogen re-ingestion. Wall shear stresses of these mosquito species were also clearly discriminatory affecting the infective rates of vector-borne diseases. The variations in volume of two pump chambers and diameter of proboscis of these mosquito species were compared to determine the differences in the liquid-feeding process. Liquid-feeding characteristics influence vector efficiency; hence, this study can elucidate the vector efficiency of mosquitoes and the vector-pathogen interactions and contribute to the development of strategies against vector-borne diseases.

On hidden symmetries of extremal Kerr-NUT-AdS-dS black holes

NASA Astrophysics Data System (ADS)

Rasmussen, Jørgen

2011-05-01

It is well known that the Kerr-NUT-AdS-dS black hole admits two linearly independent Killing vectors and possesses a hidden symmetry generated by a rank-2 Killing tensor. The near-horizon geometry of an extremal Kerr-NUT-AdS-dS black hole admits four linearly independent Killing vectors, and we show how the hidden symmetry of the black hole itself is carried over by means of a modified Killing-Yano potential which is given explicitly. We demonstrate that the corresponding Killing tensor of the near-horizon geometry is reducible as it can be expressed in terms of the Casimir operators formed by the four Killing vectors.

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Cyclotron-based of plant gravisensing

NASA Astrophysics Data System (ADS)

Kordyum, E.; Kalinina, Ia.; Bogatina, N.; Kondrachuk, A.

Roots exhibit positive gravitropism they grow in the direction of a gravitational vector while shoots respond negatively and grow opposite to a gravitational vector We first demonstrated the inversion of roots gravitropism from positive to negative one under gravistimulation in the weak combined magnetic field WCMF consisted of permanent magnetic field PMF with the magnitude of order of 50 mu T and altering magnetic field AMF with the 6 mu T magnitude and a frequency of 32 Hz It was found that the effect of inversion has a resonance nature It means that in the interval of frequencies 1-45 Hz inversion of root gravitropism occurs only at frequency 32 Hz 2-3-day old cress seedlings were gravistimulated in moist chambers which are placed in mu -metal shields Inside mu -metal shields combined magnetic fields have been created The magnitude of magnetic fields was measured by a flux-gate magnetometer Experiments were performed in darkness at temperature 20 pm 1 0 C We measured the divergence angle of a growing root from its horizontal position After 1 h of gravistimulation in the WCMF we observed negative gravitropism of cress roots i e they grow in the opposite direction to a gravitational vector Frequency of 32 Hz for the magnitude of the PMF applied formally corresponds to cyclotron frequency of Ca 2 ions This indicates possible participation of calcium ions in root gravitropism There are many evidences of resonance effects of the WCMF on the biological processes that involve Ca 2 but the nature of

Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

NASA Astrophysics Data System (ADS)

Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

2016-10-01

The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

Bio-inspired piezoelectric artificial hair cell sensor fabricated by powder injection molding

NASA Astrophysics Data System (ADS)

Han, Jun Sae; Oh, Keun Ha; Moon, Won Kyu; Kim, Kyungseop; Joh, Cheeyoung; Seo, Hee Seon; Bollina, Ravi; Park, Seong Jin

2015-12-01

A piezoelectric artificial hair cell sensor was fabricated by the powder injection molding process in order to make an acoustic vector hydrophone. The entire process of powder injection molding was developed and optimized for PMN-PZT ceramic powder. The artificial hair cell sensor, which consists of high aspect ratio hair cell and three rectangular mechanoreceptors, was precisely fabricated through the developed powder injection molding process. The density and the dielectric property of the fabricated sensor shows 98% of the theoretical density and 85% of reference dielectric property of PMN-PZT ceramic powder. With regard to homogeneity, three rectangular mechanoreceptors have the same dimensions, with 3 μm of tolerance with 8% of deviation of dielectric property. Packaged vector hydrophones measure the underwater acoustic signals from 500 to 800 Hz with -212 dB of sensitivity. Directivity of vector hydrophone was acquired at 600 Hz as analyzing phase differences of electric signals.

Vectorization with SIMD extensions speeds up reconstruction in electron tomography.

PubMed

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

2010-06-01

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

Divergent movements of walrus and sea ice in the Nothern Bering Sea

USGS Publications Warehouse

Jay, Chadwick V.; Udevitz, Mark S.; Kwok, Ron; Fischbach, Anthony S.; Douglas, David C.

2010-01-01

The Pacific walrus Odobenus rosmarus divergens is a large Arctic pinniped of the Chukchi and Bering Seas. Reductions of sea ice projected to occur in the Arctic by mid-century raise concerns for conservation of the Pacific walrus. To understand the significance of sea ice loss to the viability of walruses, it would be useful to better understand the spatial associations between the movements of sea ice and walruses. We investigated whether local-scale (~1 to 100 km) walrus movements correspond to movements of sea ice in the Bering Sea in early spring, using locations from radio-tracked walruses and measures of ice floe movements from processed synthetic aperture radar satellite imagery. We used generalized linear mixed-effects models to analyze the angle between walrus and ice floe movement vectors and the distance between the final geographic position of walruses and their associated ice floes (displacement), as functions of observation duration, proportion of time the walrus was in water, and geographic region. Analyses were based on 121 walrus-ice vector pairs and observations lasting 12 to 36 h. Angles and displacements increased with observation duration, proportion of time the walrus spent in the water, and varied among regions (regional mean angles ranged from 40° to 81° and mean displacements ranged from 15 to 35 km). Our results indicated a lack of correspondence between walruses and their initially associated ice floes, suggesting that local areas of walrus activities were independent of the movement of ice floes.

Anatomical Reconstruction and Functional Imaging Reveal an Ordered Array of Skylight Polarization Detectors in Drosophila

PubMed Central

Bleul, Christiane; Baumann-Klausener, Franziska; Labhart, Thomas; Dickinson, Michael H.

2016-01-01

Many insects exploit skylight polarization as a compass cue for orientation and navigation. In the fruit fly, Drosophila melanogaster, photoreceptors R7 and R8 in the dorsal rim area (DRA) of the compound eye are specialized to detect the electric vector (e-vector) of linearly polarized light. These photoreceptors are arranged in stacked pairs with identical fields of view and spectral sensitivities, but mutually orthogonal microvillar orientations. As in larger flies, we found that the microvillar orientation of the distal photoreceptor R7 changes in a fan-like fashion along the DRA. This anatomical arrangement suggests that the DRA constitutes a detector for skylight polarization, in which different e-vectors maximally excite different positions in the array. To test our hypothesis, we measured responses to polarized light of varying e-vector angles in the terminals of R7/8 cells using genetically encoded calcium indicators. Our data confirm a progression of preferred e-vector angles from anterior to posterior in the DRA, and a strict orthogonality between the e-vector preferences of paired R7/8 cells. We observed decreased activity in photoreceptors in response to flashes of light polarized orthogonally to their preferred e-vector angle, suggesting reciprocal inhibition between photoreceptors in the same medullar column, which may serve to increase polarization contrast. Together, our results indicate that the polarization-vision system relies on a spatial map of preferred e-vector angles at the earliest stage of sensory processing. SIGNIFICANCE STATEMENT The fly's visual system is an influential model system for studying neural computation, and much is known about its anatomy, physiology, and development. The circuits underlying motion processing have received the most attention, but researchers are increasingly investigating other functions, such as color perception and object recognition. In this work, we investigate the early neural processing of a somewhat exotic sense, called polarization vision. Because skylight is polarized in an orientation that is rigidly determined by the position of the sun, this cue provides compass information. Behavioral experiments have shown that many species use the polarization pattern in the sky to direct locomotion. Here we describe the input stage of the fly's polarization-vision system. PMID:27170135

Wolbachia: A biological control strategy against arboviral diseases.

PubMed

Mohanty, Ipsita; Rath, Animesha; Mahapatra, Namita; Hazra, Rupenangshu K

2016-01-01

Vector-borne diseases particularly those transmitted by mosquitoes like Dengue are among the leading causes of mortality and morbidity in human population. There are no effective vaccines or treatment against dengue fever till date and the control methods are limited. So, new approaches are urgently in need to reverse these trends. Vector control is currently the primary intervention tool. Strategies that reduce or block pathogen transmission by mosquitoes have been proposed as a means of augmenting current control measures to reduce the growing burden of vector-borne diseases. Wolbachia an endosymbiont of arthropod vectors is being explored as a novel ecofriendly control strategy. Studies in Drosophila have shown that Wolbachia can confer resistance to diverse RNA viruses and protect flies from virus-induced mortality. This review was focused on biology of the Wolbachia and its implication as a control measure for arboviral diseases mainly Dengue and Chikungunya.

On the Lamb vector divergence as a momentum field diagnostic employed in turbulent channel flow

NASA Astrophysics Data System (ADS)

Hamman, Curtis W.; Kirby, Robert M.; Klewicki, Joseph C.

2006-11-01

Vorticity, enstrophy, helicity, and other derived field variables provide invaluable information about the kinematics and dynamics of fluids. However, whether or not derived field variables exist that intrinsically identify spatially localized motions having a distinct capacity to affect a time rate of change of linear momentum is seldom addressed in the literature. The purpose of the present study is to illustrate the unique attributes of the divergence of the Lamb vector in order to qualify its potential for characterizing such spatially localized motions. Toward this aim, we describe the mathematical properties, near-wall behavior, and scaling characteristics of the divergence of the Lamb vector for turbulent channel flow. When scaled by inner variables, the mean divergence of the Lamb vector merges to a single curve in the inner layer, and the fluctuating quantities exhibit a strong correlation with the Bernoulli function throughout much of the inner layer.

Derivation of the Lorentz force law, the magnetic field concept and the Faraday Lenz and magnetic Gauss laws using an invariant formulation of the Lorentz transformation

NASA Astrophysics Data System (ADS)

Field, J. H.

2006-06-01

It is demonstrated how the right-hand sides of the Lorentz transformation equations may be written, in a Lorentz-invariant manner, as 4-vector scalar products. This implies the existence of invariant length intervals analogous to invariant proper time intervals. An important distinction between the physical meanings of the space time and energy momentum 4-vectors is pointed out. The formalism is shown to provide a short derivation of the Lorentz force law of classical electrodynamics, and the conventional definition of the magnetic field, in terms of spatial derivatives of the 4-vector potential, as well as the Faraday Lenz law and the Gauss law for magnetic fields. The connection between the Gauss law for the electric field and the electrodynamic Ampère law, due to the 4-vector character of the electromagnetic potential, is also pointed out.

Nonperturbative interpretation of the Bloch vector's path beyond the rotating-wave approximation

NASA Astrophysics Data System (ADS)

Benenti, Giuliano; Siccardi, Stefano; Strini, Giuliano

2013-09-01

The Bloch vector's path of a two-level system exposed to a monochromatic field exhibits, in the regime of strong coupling, complex corkscrew trajectories. By considering the infinitesimal evolution of the two-level system when the field is treated as a classical object, we show that the Bloch vector's rotation speed oscillates between zero and twice the rotation speed predicted by the rotating wave approximation. Cusps appear when the rotation speed vanishes. We prove analytically that in correspondence to cusps the curvature of the Bloch vector's path diverges. On the other hand, numerical data show that the curvature is very large even for a quantum field in the deep quantum regime with mean number of photons n¯≲1. We finally compute numerically the typical error size in a quantum gate when the terms beyond rotating wave approximation are neglected.

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

PubMed

Bennett, Charles R; Kelly, Brian P

2013-08-09

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

Host Life History Strategy, Species Diversity, and Habitat Influence Trypanosoma cruzi Vector Infection in Changing Landscapes

PubMed Central

Gottdenker, Nicole L.; Chaves, Luis Fernando; Calzada, José E.; Saldaña, Azael; Carroll, C. Ronald

2012-01-01

Background Anthropogenic land use may influence transmission of multi-host vector-borne pathogens by changing diversity, relative abundance, and community composition of reservoir hosts. These reservoir hosts may have varying competence for vector-borne pathogens depending on species-specific characteristics, such as life history strategy. The objective of this study is to evaluate how anthropogenic land use change influences blood meal species composition and the effects of changing blood meal species composition on the parasite infection rate of the Chagas disease vector Rhodnius pallescens in Panama. Methodology/Principal Findings R. pallescens vectors (N = 643) were collected in different habitat types across a gradient of anthropogenic disturbance. Blood meal species in DNA extracted from these vectors was identified in 243 (40.3%) vectors by amplification and sequencing of a vertebrate-specific fragment of the 12SrRNA gene, and T. cruzi vector infection was determined by pcr. Vector infection rate was significantly greater in deforested habitats as compared to contiguous forests. Forty-two different species of blood meal were identified in R. pallescens, and species composition of blood meals varied across habitat types. Mammals (88.3%) dominated R. pallescens blood meals. Xenarthrans (sloths and tamanduas) were the most frequently identified species in blood meals across all habitat types. A regression tree analysis indicated that blood meal species diversity, host life history strategy (measured as rmax, the maximum intrinsic rate of population increase), and habitat type (forest fragments and peridomiciliary sites) were important determinants of vector infection with T. cruzi. The mean intrinsic rate of increase and the skewness and variability of rmax were positively associated with higher vector infection rate at a site. Conclusions/Significance In this study, anthropogenic landscape disturbance increased vector infection with T. cruzi, potentially by changing host community structure to favor hosts that are short-lived with high reproductive rates. Study results apply to potential environmental management strategies for Chagas disease. PMID:23166846

The Host Range of Gammaretroviruses and Gammaretroviral Vectors Includes Post-Mitotic Neural Cells

PubMed Central

Liu, Xiu-Huai; Xu, Wenqin; Russ, Jill; Eiden, Lee E.; Eiden, Maribeth V.

2011-01-01

Background Gammaretroviruses and gammaretroviral vectors, in contrast to lentiviruses and lentiviral vectors, are reported to be restricted in their ability to infect growth-arrested cells. The block to this restriction has never been clearly defined. The original assessment of the inability of gammaretroviruses and gammaretroviral vectors to infect growth-arrested cells was carried out using established cell lines that had been growth-arrested by chemical means, and has been generalized to neurons, which are post-mitotic. We re-examined the capability of gammaretroviruses and their derived vectors to efficiently infect terminally differentiated neuroendocrine cells and primary cortical neurons, a target of both experimental and therapeutic interest. Methodology/Principal Findings Using GFP expression as a marker for infection, we determined that both growth-arrested (NGF-differentiated) rat pheochromocytoma cells (PC12 cells) and primary rat cortical neurons could be efficiently transduced, and maintained long-term protein expression, after exposure to murine leukemia virus (MLV) and MLV-based retroviral vectors. Terminally differentiated PC12 cells transduced with a gammaretroviral vector encoding the anti-apoptotic protein Bcl-xL were protected from cell death induced by withdrawal of nerve growth factor (NGF), demonstrating gammaretroviral vector-mediated delivery and expression of genes at levels sufficient for therapeutic effect in non-dividing cells. Post-mitotic rat cortical neurons were also shown to be susceptible to transduction by murine replication-competent gammaretroviruses and gammaretroviral vectors. Conclusions/Significance These findings suggest that the host range of gammaretroviruses includes post-mitotic and other growth-arrested cells in mammals, and have implications for re-direction of gammaretroviral gene therapy to neurological disease. PMID:21464894

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

NASA Astrophysics Data System (ADS)

Mortari, Daniele; Rogers, Jonathan

2013-12-01

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

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.

Reconstruction of an 8-lead surface ECG from two subcutaneous ICD vectors.

PubMed

Wilson, David G; Cronbach, Peter L; Panfilo, D; Greenhut, Saul E; Stegemann, Berthold P; Morgan, John M

2017-06-01

Techniques exist which allow surface ECGs to be reconstructed from reduced lead sets. We aimed to reconstruct an 8-lead ECG from two independent S-ICD sensing electrodes vectors as proof of this principle. Participants with ICDs (N=61) underwent 3minute ECGs using a TMSi Porti7 multi-channel signal recorder (TMS international, The Netherlands) with electrodes in the standard S-ICD and 12-lead positions. Participants were randomised to either a training (N=31) or validation (N=30) group. The transformation used was a linear combination of the 2 independent S-ICD vectors to each of the 8 independent leads of the 12-lead ECG, with coefficients selected that minimized the root mean square error (RMSE) between recorded and derived ECGs when applied to the training group. The transformation was then applied to the validation group and agreement between the recorded and derived lead pairs was measured by Pearson correlation coefficient (r) and normalised RMSE (NRMSE). In total, 27 patients with complete data sets were included in the validation set consisting of 57,888 data points from 216 full lead sets. The distribution of the r and NRMSE were skewed. Mean r=0.770 (SE 0.024), median r=0.925. NRMSE mean=0.233 (SE 0.015) median=0.171. We have demonstrated that the reconstruction of an 8-lead ECG from two S-ICD vectors is possible. If perfected, the ability to generate accurate multi-lead surface ECG data from an S-ICD would potentially allow recording and review of clinical arrhythmias at follow-up. Copyright © 2017 Elsevier B.V. All rights reserved.

Vectorial mask optimization methods for robust optical lithography

NASA Astrophysics Data System (ADS)

Ma, Xu; Li, Yanqiu; Guo, Xuejia; Dong, Lisong; Arce, Gonzalo R.

2012-10-01

Continuous shrinkage of critical dimension in an integrated circuit impels the development of resolution enhancement techniques for low k1 lithography. Recently, several pixelated optical proximity correction (OPC) and phase-shifting mask (PSM) approaches were developed under scalar imaging models to account for the process variations. However, the lithography systems with larger-NA (NA>0.6) are predominant for current technology nodes, rendering the scalar models inadequate to describe the vector nature of the electromagnetic field that propagates through the optical lithography system. In addition, OPC and PSM algorithms based on scalar models can compensate for wavefront aberrations, but are incapable of mitigating polarization aberrations in practical lithography systems, which can only be dealt with under the vector model. To this end, we focus on developing robust pixelated gradient-based OPC and PSM optimization algorithms aimed at canceling defocus, dose variation, wavefront and polarization aberrations under a vector model. First, an integrative and analytic vector imaging model is applied to formulate the optimization problem, where the effects of process variations are explicitly incorporated in the optimization framework. A steepest descent algorithm is then used to iteratively optimize the mask patterns. Simulations show that the proposed algorithms can effectively improve the process windows of the optical lithography systems.

Diagnostic approach for monitoring hydroclimatic conditions related to emergence of west nile virus in west virginia.

PubMed

Jutla, Antarpreet; Huq, Anwar; Colwell, Rita R

2015-01-01

West Nile virus (WNV), mosquito-borne and water-based disease, is increasingly a global threat to public health. Since its appearance in the northeastern United States in 1999, WNV has since been reported in several states in the continental United States. The objective of this study is to highlight role of hydroclimatic processes estimated through satellite sensors in capturing conditions for emergence of the vectors in historically disease free regions. We tested the hypothesis that an increase in surface temperature, in combination with intensification of vegetation, and enhanced precipitation, lead to conditions favorable for vector (mosquito) growth. Analysis of land surface temperature (LST) pattern shows that temperature values >16°C, with heavy precipitation, may lead to abundance of the mosquito population. This hypothesis was tested in West Virginia where a sudden epidemic of WNV infection was reported in 2012. Our results emphasize the value of hydroclimatic processes estimated by satellite remote sensing, as well as continued environmental surveillance of mosquitoes, because when a vector-borne infection like WNV is discovered in contiguous regions, the risk of spread of WNV mosquitoes increase at points where appropriate hydroclimatic processes intersect with the vector niche.

Large-scale manufacture and characterization of a lentiviral vector produced for clinical ex vivo gene therapy application.

PubMed

Merten, Otto-Wilhelm; Charrier, Sabine; Laroudie, Nicolas; Fauchille, Sylvain; Dugué, Céline; Jenny, Christine; Audit, Muriel; Zanta-Boussif, Maria-Antonietta; Chautard, Hélène; Radrizzani, Marina; Vallanti, Giuliana; Naldini, Luigi; Noguiez-Hellin, Patricia; Galy, Anne

2011-03-01

From the perspective of a pilot clinical gene therapy trial for Wiskott-Aldrich syndrome (WAS), we implemented a process to produce a lentiviral vector under good manufacturing practices (GMP). The process is based on the transient transfection of 293T cells in Cell Factory stacks, scaled up to harvest 50 liters of viral stock per batch, followed by purification of the vesicular stomatitis virus glycoprotein-pseudotyped particles through several membrane-based and chromatographic steps. The process leads to a 200-fold volume concentration and an approximately 3-log reduction in protein and DNA contaminants. An average yield of 13% of infectious particles was obtained in six full-scale preparations. The final product contained low levels of contaminants such as simian virus 40 large T antigen or E1A sequences originating from producer cells. Titers as high as 2 × 10(9) infectious particles per milliliter were obtained, generating up to 6 × 10(11) infectious particles per batch. The purified WAS vector was biologically active, efficiently expressing the genetic insert in WAS protein-deficient B cell lines and transducing CD34(+) cells. The vector introduced 0.3-1 vector copy per cell on average in CD34(+) cells when used at the concentration of 10(8) infectious particles per milliliter, which is comparable to preclinical preparations. There was no evidence of cellular toxicity. These results show the implementation of large-scale GMP production, purification, and control of advanced HIV-1-derived lentiviral technology. Results obtained with the WAS vector provide the initial manufacturing and quality control benchmarking that should be helpful to further development and clinical applications.

LBP and SIFT based facial expression recognition

NASA Astrophysics Data System (ADS)

Sumer, Omer; Gunes, Ece O.

2015-02-01

This study compares the performance of local binary patterns (LBP) and scale invariant feature transform (SIFT) with support vector machines (SVM) in automatic classification of discrete facial expressions. Facial expression recognition is a multiclass classification problem and seven classes; happiness, anger, sadness, disgust, surprise, fear and comtempt are classified. Using SIFT feature vectors and linear SVM, 93.1% mean accuracy is acquired on CK+ database. On the other hand, the performance of LBP-based classifier with linear SVM is reported on SFEW using strictly person independent (SPI) protocol. Seven-class mean accuracy on SFEW is 59.76%. Experiments on both databases showed that LBP features can be used in a fairly descriptive way if a good localization of facial points and partitioning strategy are followed.

Horizontal wind fluctuations in the stratosphere during large-scale cyclogenesis

NASA Technical Reports Server (NTRS)

Chan, K. R.; Scott, S. G.; Danielsen, Edwin F.; Pfister, L.; Bowen, S. W.; Gaines, Steven E.

1991-01-01

The meteorological measurement system (MMS) on the U-2 aircraft measured pressure, temperature, and the horizontal wind during a cyclogenesis event over western United States on April 20, 1984. The mean horizontal wind in the stratosphere decreases monotonically with altitude. Superimposed on the mean stratospheric wind is a perturbation wind vector, which is an elliptically polarized wave with an amplitude of 4 to 10 m/s and a vertical wavelength of 2 to 3 km. The perturbation wind vector rotates anticyclonically (clockwise) with altitude and produces alternating advection in the plane of the aircraft flight path. This differential advection folds surfaces of constant tracer mixing ratio and contributes to the observed tracer laminar structures and inferred cross-jet transport.

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

PubMed

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

2018-05-01

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

Uncertainty quantification applied to the radiological characterization of radioactive waste.

PubMed

Zaffora, B; Magistris, M; Saporta, G; Chevalier, J-P

2017-09-01

This paper describes the process adopted at the European Organization for Nuclear Research (CERN) to quantify uncertainties affecting the characterization of very-low-level radioactive waste. Radioactive waste is a by-product of the operation of high-energy particle accelerators. Radioactive waste must be characterized to ensure its safe disposal in final repositories. Characterizing radioactive waste means establishing the list of radionuclides together with their activities. The estimated activity levels are compared to the limits given by the national authority of the waste disposal. The quantification of the uncertainty affecting the concentration of the radionuclides is therefore essential to estimate the acceptability of the waste in the final repository but also to control the sorting, volume reduction and packaging phases of the characterization process. The characterization method consists of estimating the activity of produced radionuclides either by experimental methods or statistical approaches. The uncertainties are estimated using classical statistical methods and uncertainty propagation. A mixed multivariate random vector is built to generate random input parameters for the activity calculations. The random vector is a robust tool to account for the unknown radiological history of legacy waste. This analytical technique is also particularly useful to generate random chemical compositions of materials when the trace element concentrations are not available or cannot be measured. The methodology was validated using a waste population of legacy copper activated at CERN. The methodology introduced here represents a first approach for the uncertainty quantification (UQ) of the characterization process of waste produced at particle accelerators. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationships between infection, dissemination, and transmission of West Nile virus RNA in Culex pipiens quinquefasciatus (Diptera: Culicidae).

PubMed

Richards, Stephanie L; Anderson, Sheri L; Lord, Cynthia C; Smartt, Chelsea T; Tabachnick, Walter J

2012-01-01

Culex pipiens quinquefasciatus Say fed blood containing 6.8 +/- 0.3 logs (mean +/- SE) plaque-forming units of West Nile virus (WNV)/ml were maintained at 28 degrees C for incubation periods (IP) of 7, 14, or 21 d. Several attributes of vector competence were determined at each IP using quantitative real-time reverse transcriptase polymerase chain reaction to estimate plaque forming unit equivalents including: infection rate (WNV-positive abdomens), dissemination rate (WNV-positive legs or thoraces), combined dissemination rate (WNV-positive legs and thoraces), transmission rate (WNV-positive saliva), and WNV titers in abdomens, legs, thoraces, and saliva. Each rate increased or was equivalent with increasing IP. Mosquitoes transmitting WNV in saliva also had significantly higher IP-dependent WNV titers in abdomens, legs, and thoraces. Titers of WNV in abdomens were significantly correlated with titers in legs and thoraces, but the degree of association changed with IP. However, titers of abdomens, legs, and thoraces were not correlated with WNV presence or titer in the saliva. The results show that WNV presence or titer in the saliva of infected Cx. p. quinquefasciatus was not directly influenced by processes involved in WNV replication in other tissues. The processes controlling midgut infection and escape are, in part, independent from the infection processes in other tissues. The relationship between infection, dissemination, and transmission varied over time. The infection and replication of WNV in different tissues is likely influenced by different barriers encountered during the extrinsic incubation period. The significance of these observations for understanding vector competence is discussed.

Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri catchment

NASA Astrophysics Data System (ADS)

Kothari, Mahesh; Gharde, K. D.

2015-07-01

The streamflow prediction is an essentially important aspect of any watershed modelling. The black box models (soft computing techniques) have proven to be an efficient alternative to physical (traditional) methods for simulating streamflow and sediment yield of the catchments. The present study focusses on development of models using ANN and fuzzy logic (FL) algorithm for predicting the streamflow for catchment of Savitri River Basin. The input vector to these models were daily rainfall, mean daily evaporation, mean daily temperature and lag streamflow used. In the present study, 20 years (1992-2011) rainfall and other hydrological data were considered, of which 13 years (1992-2004) was for training and rest 7 years (2005-2011) for validation of the models. The mode performance was evaluated by R, RMSE, EV, CE, and MAD statistical parameters. It was found that, ANN model performance improved with increasing input vectors. The results with fuzzy logic models predict the streamflow with single input as rainfall better in comparison to multiple input vectors. While comparing both ANN and FL algorithms for prediction of streamflow, ANN model performance is quite superior.

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

NASA Astrophysics Data System (ADS)

Valizadeh, Maryam; Sohrabi, Mahmoud Reza

2018-03-01

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

A Model Framework to Estimate Impact and Cost of Genetics-Based Sterile Insect Methods for Dengue Vector Control

PubMed Central

Alphey, Nina; Alphey, Luke; Bonsall, Michael B.

2011-01-01

Vector-borne diseases impose enormous health and economic burdens and additional methods to control vector populations are clearly needed. The Sterile Insect Technique (SIT) has been successful against agricultural pests, but is not in large-scale use for suppressing or eliminating mosquito populations. Genetic RIDL technology (Release of Insects carrying a Dominant Lethal) is a proposed modification that involves releasing insects that are homozygous for a repressible dominant lethal genetic construct rather than being sterilized by irradiation, and could potentially overcome some technical difficulties with the conventional SIT technology. Using the arboviral disease dengue as an example, we combine vector population dynamics and epidemiological models to explore the effect of a program of RIDL releases on disease transmission. We use these to derive a preliminary estimate of the potential cost-effectiveness of vector control by applying estimates of the costs of SIT. We predict that this genetic control strategy could eliminate dengue rapidly from a human community, and at lower expense (approximately US$ 2∼30 per case averted) than the direct and indirect costs of disease (mean US$ 86–190 per case of dengue). The theoretical framework has wider potential use; by appropriately adapting or replacing each component of the framework (entomological, epidemiological, vector control bio-economics and health economics), it could be applied to other vector-borne diseases or vector control strategies and extended to include other health interventions. PMID:21998654

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2005-01-01

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

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

USGS Publications Warehouse

Peuquet, D.J.

1981-01-01

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

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.

Molecular design for recombinant adeno-associated virus (rAAV) vector production.

PubMed

Aponte-Ubillus, Juan Jose; Barajas, Daniel; Peltier, Joseph; Bardliving, Cameron; Shamlou, Parviz; Gold, Daniel

2018-02-01

Recombinant adeno-associated virus (rAAV) vectors are increasingly popular tools for gene therapy applications. Their non-pathogenic status, low inflammatory potential, availability of viral serotypes with different tissue tropisms, and prospective long-lasting gene expression are important attributes that make rAAVs safe and efficient therapeutic options. Over the last three decades, several groups have engineered recombinant AAV-producing platforms, yielding high titers of transducing vector particles. Current specific productivity yields from different platforms range from 10 3 to 10 5 vector genomes (vg) per cell, and there is an ongoing effort to improve vector yields in order to satisfy high product demands required for clinical trials and future commercialization.Crucial aspects of vector production include the molecular design of the rAAV-producing host cell line along with the design of AAV genes, promoters, and regulatory elements. Appropriately, configuring and balancing the expression of these elements not only contributes toward high productivity, it also improves process robustness and product quality. In this mini-review, the rational design of rAAV-producing expression systems is discussed, with special attention to molecular strategies that contribute to high-yielding, biomanufacturing-amenable rAAV production processes. Details on molecular optimization from four rAAV expression systems are covered: adenovirus, herpesvirus, and baculovirus complementation systems, as well as a recently explored yeast expression system.

Invariant object recognition based on the generalized discrete radon transform

NASA Astrophysics Data System (ADS)

Easley, Glenn R.; Colonna, Flavia

2004-04-01

We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.

A low-cost vector processor boosting compute-intensive image processing operations

NASA Technical Reports Server (NTRS)

Adorf, Hans-Martin

1992-01-01

Low-cost vector processing (VP) is within reach of everyone seriously engaged in scientific computing. The advent of affordable add-on VP-boards for standard workstations complemented by mathematical/statistical libraries is beginning to impact compute-intensive tasks such as image processing. A case in point in the restoration of distorted images from the Hubble Space Telescope. A low-cost implementation is presented of the standard Tarasko-Richardson-Lucy restoration algorithm on an Intel i860-based VP-board which is seamlessly interfaced to a commercial, interactive image processing system. First experience is reported (including some benchmarks for standalone FFT's) and some conclusions are drawn.

Diagnostic electrocardiographic dyad criteria of emphysema in left ventricular hypertrophy

PubMed Central

Lanjewar, Swapnil S; Chhabra, Lovely; Chaubey, Vinod K; Joshi, Saurabh; Kulkarni, Ganesh; Kothagundla, Chandrasekhar; Kaul, Sudesh; Spodick, David H

2013-01-01

Background The electrocardiographic diagnostic dyad of emphysema, namely a combination of the frontal vertical P-vector and a narrow QRS duration, can serve as a quasidiagnostic marker for emphysema, with specificity close to 100%. We postulated that the presence of left ventricular hypertrophy in emphysema may affect the sensitivity of this electrocardiographic criterion given that left ventricular hypertrophy generates prominent left ventricular forces and may increase the QRS duration. Methods We reviewed the electrocardiograms and echocardiograms for 73 patients with emphysema. The patients were divided into two groups based on the presence or absence of echocardiographic evidence of left ventricular hypertrophy. The P-vector, QRS duration, and forced expiratory volume in one second (FEV1) were computed and compared between the two subgroups. Results There was no statistically significant difference in qualitative lung function (FEV1) between the subgroups. There was no statistically significant difference in mean P-vector between the subgroups. The mean QRS duration was significantly longer in patients with left ventricular hypertrophy as compared with those without left ventricular hypertrophy. Conclusion The presence of left ventricular hypertrophy may not affect the sensitivity of the P-vector verticalization when used as a lone criterion for diagnosing emphysema. However, the presence of left ventricular hypertrophy may significantly reduce the sensitivity of the electrocardiographic diagnostic dyad in emphysema, as it causes a widening of the QRS duration. PMID:24293995

Diagnostic electrocardiographic dyad criteria of emphysema in left ventricular hypertrophy.

PubMed

Lanjewar, Swapnil S; Chhabra, Lovely; Chaubey, Vinod K; Joshi, Saurabh; Kulkarni, Ganesh; Kothagundla, Chandrasekhar; Kaul, Sudesh; Spodick, David H

2013-01-01

The electrocardiographic diagnostic dyad of emphysema, namely a combination of the frontal vertical P-vector and a narrow QRS duration, can serve as a quasidiagnostic marker for emphysema, with specificity close to 100%. We postulated that the presence of left ventricular hypertrophy in emphysema may affect the sensitivity of this electrocardiographic criterion given that left ventricular hypertrophy generates prominent left ventricular forces and may increase the QRS duration. We reviewed the electrocardiograms and echocardiograms for 73 patients with emphysema. The patients were divided into two groups based on the presence or absence of echocardiographic evidence of left ventricular hypertrophy. The P-vector, QRS duration, and forced expiratory volume in one second (FEV1) were computed and compared between the two subgroups. There was no statistically significant difference in qualitative lung function (FEV1) between the subgroups. There was no statistically significant difference in mean P-vector between the subgroups. The mean QRS duration was significantly longer in patients with left ventricular hypertrophy as compared with those without left ventricular hypertrophy. The presence of left ventricular hypertrophy may not affect the sensitivity of the P-vector verticalization when used as a lone criterion for diagnosing emphysema. However, the presence of left ventricular hypertrophy may significantly reduce the sensitivity of the electrocardiographic diagnostic dyad in emphysema, as it causes a widening of the QRS duration.

CFD Extraction Tool for TecPlot From DPLR Solutions

NASA Technical Reports Server (NTRS)

Norman, David

2013-01-01

This invention is a TecPlot macro of a computer program in the TecPlot programming language that processes data from DPLR solutions in TecPlot format. DPLR (Data-Parallel Line Relaxation) is a NASA computational fluid dynamics (CFD) code, and TecPlot is a commercial CFD post-processing tool. The Tec- Plot data is in SI units (same as DPLR output). The invention converts the SI units into British units. The macro modifies the TecPlot data with unit conversions, and adds some extra calculations. After unit conversions, the macro cuts a slice, and adds vectors on the current plot for output format. The macro can also process surface solutions. Existing solutions use manual conversion and superposition. The conversion is complicated because it must be applied to a range of inter-related scalars and vectors to describe a 2D or 3D flow field. It processes the CFD solution to create superposition/comparison of scalars and vectors. The existing manual solution is cumbersome, open to errors, slow, and cannot be inserted into an automated process. This invention is quick and easy to use, and can be inserted into an automated data-processing algorithm.

Design and experimental verification for optical module of optical vector-matrix multiplier.

PubMed

Zhu, Weiwei; Zhang, Lei; Lu, Yangyang; Zhou, Ping; Yang, Lin

2013-06-20

Optical computing is a new method to implement signal processing functions. The multiplication between a vector and a matrix is an important arithmetic algorithm in the signal processing domain. The optical vector-matrix multiplier (OVMM) is an optoelectronic system to carry out this operation, which consists of an electronic module and an optical module. In this paper, we propose an optical module for OVMM. To eliminate the cross talk and make full use of the optical elements, an elaborately designed structure that involves spherical lenses and cylindrical lenses is utilized in this optical system. The optical design software package ZEMAX is used to optimize the parameters and simulate the whole system. Finally, experimental data is obtained through experiments to evaluate the overall performance of the system. The results of both simulation and experiment indicate that the system constructed can implement the multiplication between a matrix with dimensions of 16 by 16 and a vector with a dimension of 16 successfully.

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

PubMed

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

2015-12-02

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

Fluidic Vectoring of a Planar Incompressible Jet Flow

NASA Astrophysics Data System (ADS)

Mendez, Miguel Alfonso; Scelzo, Maria Teresa; Enache, Adriana; Buchlin, Jean-Marie

2018-06-01

This paper presents an experimental, a numerical and a theoretical analysis of the performances of a fluidic vectoring device for controlling the direction of a turbulent, bi-dimensional and low Mach number (incompressible) jet flow. The investigated design is the co-flow secondary injection with Coanda surface, which allows for vectoring angles up to 25° with no need of moving mechanical parts. A simple empirical model of the vectoring process is presented and validated via experimental and numerical data. The experiments consist of flow visualization and image processing for the automatic detection of the jet centerline; the numerical simulations are carried out solving the Unsteady Reynolds Average Navier- Stokes (URANS) closed with the k - ω SST turbulence model, using the PisoFoam solver from OpenFOAM. The experimental validation on three different geometrical configurations has shown that the model is capable of providing a fast and reliable evaluation of the device performance as a function of the operating conditions.

Multifractal vector fields and stochastic Clifford algebra.

PubMed

Schertzer, Daniel; Tchiguirinskaia, Ioulia

2015-12-01

In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.

Effect of posterior corneal astigmatism on refractive outcomes after toric intraocular lens implantation.

PubMed

Zhang, Lijun; Sy, Mary Ellen; Mai, Harry; Yu, Fei; Hamilton, D Rex

2015-01-01

To compare the prediction error after toric intraocular lens (IOL) (Acrysof IQ) implantation using corneal astigmatism measurements obtained with an IOLMaster automated keratometer and a Galilei dual rotating camera Scheimpflug-Placido tomographer. Jules Stein Eye Institute, University of California Los Angeles, Los Angeles, California, USA. Retrospective case series. The predicted residual astigmatism after toric IOL implantation was calculated using preoperative astigmatism values from an automated keratometer and the total corneal power (TCP) determined by ray tracing through the measured anterior and posterior corneal surfaces using dual Scheimpflug-Placido tomography. The prediction error was calculated as the difference between the predicted astigmatism and the manifest astigmatism at least 1 month postoperatively. The calculations included vector analysis. The study evaluated 35 eyes (35 patients). The preoperative corneal posterior astigmatism mean magnitude was 0.33 diopter (D) ± 0.16 (SD) (vector mean 0.23 × 176). Twenty-six eyes (74.3%) had with-the-rule (WTR) posterior astigmatism. The postoperative manifest refractive astigmatism mean magnitude was 0.38 ± 0.18 D (vector mean 0.26 × 171). There was no statistically significant difference in the mean magnitude prediction error between the automated keratometer and TCP techniques. However, the automated keratometer method tended to overcorrect WTR astigmatism and undercorrect against-the-rule (ATR) astigmatism. The TCP technique lacked these biases. The automated keratometer and TCP methods for estimating the magnitude of corneal astigmatism gave similar results. However, the automated keratometer method tended to overcorrect WTR astigmatism and undercorrect ATR astigmatism. Dr. Hamilton has received honoraria for educational lectures from Ziemer Ophthalmic Systems. No other author has a financial or proprietary interest in any material or method mentioned. Copyright © 2015 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

The quest for a non-vector psyllid: Natural variation in acquisition and transmission of the huanglongbing pathogen ‘Candidatus Liberibacter asiaticus’ by Asian citrus psyllid isofemale lines

PubMed Central

Ammar, El-Desouky; Hall, David G.; Hosseinzadeh, Saeed

2018-01-01

Genetic variability in insect vectors is valuable to study vector competence determinants and to select non-vector populations that may help reduce the spread of vector-borne pathogens. We collected and tested vector competency of 15 isofemale lines of Asian citrus psyllid, Diaphorina citri, vector of ‘Candidatus Liberibacter asiaticus’ (CLas). CLas is associated with huanglongbing (citrus greening), the most serious citrus disease worldwide. D. citri adults were collected from orange jasmine (Murraya paniculata) hedges in Florida, and individual pairs (females and males) were caged on healthy Murraya plants for egg laying. The progeny from each pair that tested CLas-negative by qPCR were maintained on Murraya plants and considered an isofemale line. Six acquisition tests on D. citri adults that were reared as nymphs on CLas-infected citrus, from various generations of each line, were conducted to assess their acquisition rates (percentage of qPCR-positive adults). Three lines with mean acquisition rates of 28 to 32%, were classified as ‘good’ acquirers and three other lines were classified as ‘poor’ acquirers, with only 5 to 8% acquisition rates. All lines were further tested for their ability to inoculate CLas by confining CLas-exposed psyllids for one week onto healthy citrus leaves (6–10 adults/leaf/week), and testing the leaves for CLas by qPCR. Mean inoculation rates were 19 to 28% for the three good acquirer lines and 0 to 3% for the three poor acquirer lines. Statistical analyses indicated positive correlations between CLas acquisition and inoculation rates, as well as between CLas titer in the psyllids and CLas acquisition or inoculation rates. Phenotypic and molecular characterization of one of the good and one of the poor acquirer lines revealed differences between them in color morphs and hemocyanin expression, but not the composition of bacterial endosymbionts. Understanding the genetic architecture of CLas transmission will enable the development of new tools for combating this devastating citrus disease. PMID:29652934

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

System for Automated Calibration of Vector Modulators

NASA Technical Reports Server (NTRS)

Lux, James; Boas, Amy; Li, Samuel

2009-01-01

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

Surveillance of malaria vector population density and biting behaviour in western Kenya.

PubMed

Ototo, Ednah N; Mbugi, Jenard P; Wanjala, Christine L; Zhou, Guofa; Githeko, Andrew K; Yan, Guiyun

2015-06-17

Malaria is a great public health burden and Africa suffers the largest share of malaria-attributed deaths. Despite control efforts targeting indoor malaria transmission, such as insecticide-treated bed nets (ITNs) and deployment of indoor residual spraying, transmission of the parasite in western Kenya is still maintained. This study was carried out to determine the impact of ITNs on indoor vector densities and biting behaviour in western Kenya. Indoor collection of adult mosquitoes was done monthly in six study sites in western Kenya using pyrethrum spray collections from 2012 to 2014. The rotator trap collections were done in July-August in 2013 and May-June in 2014. Mosquitoes were collected every 2 h between 18.00 and 08.00 h. Human behaviour study was conducted via questionnaire surveys. Species within Anopheles gambiae complex was differentiated by PCR and sporozoite infectivity was determined by ELISA. Species distribution was determined and bed net coverage in the study sites was recorded. During the study a total of 5,469 mosquito vectors were collected from both PSC and Rotator traps comprising 3,181 (58.2%) Anopheles gambiae and 2,288 (41.8%) Anopheles funestus. Compared to all the study sites, Rae had the highest density of An. gambiae with a mean of 1.2 (P<0.001) while Kombewa had the highest density of An. funestus with a mean of 1.08 (P<0.001). Marani had the lowest density of vectors with 0.06 An. gambiae and 0.17 An. funestus (P<0.001). Among the 700 PCR confirmed An. gambiae s.l. individuals, An. gambiae s.s. accounted for 49% and An. arabiensis 51%. Over 50% of the study population stayed outdoors between 18.00 and 20.00 and 06.00 and 08.00 which was the time when highest densities of blood fed vectors were collected. Anopheles gambie s.s. was the main malaria parasite vector in the highland sites and An. arabiensis in the lowland sites. Bed net ownership in 2012 averaged 87% across the study sites. This study suggests that mass distribution of ITNs has had a significant impact on vector densities, species distribution and sporozoite rate. However, shift of biting time poses significant threats to the current malaria vector control strategies which heavily rely on indoor controls.

Process for structural geologic analysis of topography and point data

DOEpatents

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

1987-01-01

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

Vector analysis of postcardiotomy behavioral phenomena.

PubMed

Caston, J C; Miller, W C; Felber, W J

1975-04-01

The classification of postcardiotomy behavioral phenomena in Figure 1 is proposed for use as a clinical instrument to analyze etiological determinants. The utilization of a vector analysis analogy inherently denies absolutism. Classifications A-P are presented as prototypes of certain ratio imbalances of the metabolic, hemodynamic, environmental, and psychic vectors. Such a system allows for change from one type to another according to the individuality of the patient and the highly specific changes in his clinical presentation. A vector analysis also allows for infinite intermediary ratio imbalances between classification types as a function of time. Thus, postcardiotomy behavioral phenomena could be viewed as the vector summation of hemodynamic, metabolic, environmental, and psychic processes at a given point in time. Elaboration of unknown determinants in this complex syndrome appears to be task for the future.

Current Good Manufacturing Practice Production of an Oncolytic Recombinant Vesicular Stomatitis Viral Vector for Cancer Treatment

PubMed Central

Meseck, M.; Derecho, I.; Lopez, P.; Knoblauch, C.; McMahon, R.; Anderson, J.; Dunphy, N.; Quezada, V.; Khan, R.; Huang, P.; Dang, W.; Luo, M.; Hsu, D.; Woo, S.L.C.; Couture, L.

2011-01-01

Abstract Vesicular stomatitis virus (VSV) is an oncolytic virus currently being investigated as a promising tool to treat cancer because of its ability to selectively replicate in cancer cells. To enhance the oncolytic property of the nonpathologic laboratory strain of VSV, we generated a recombinant vector [rVSV(MΔ51)-M3] expressing murine gammaherpesvirus M3, a secreted viral chemokine-binding protein that binds to a broad range of mammalian chemokines with high affinity. As previously reported, when rVSV(MΔ51)-M3 was used in an orthotopic model of hepatocellular carcinoma (HCC) in rats, it suppressed inflammatory cell migration to the virus-infected tumor site, which allowed for enhanced intratumoral virus replication leading to increased tumor necrosis and substantially prolonged survival. These encouraging results led to the development of this vector for clinical translation in patients with HCC. However, a scalable current Good Manufacturing Practice (cGMP)-compliant manufacturing process has not been described for this vector. To produce the quantities of high-titer virus required for clinical trials, a process that is amenable to GMP manufacturing and scale-up was developed. We describe here a large-scale (50-liter) vector production process capable of achieving crude titers on the order of 109 plaque-forming units (PFU)/ml under cGMP. This process was used to generate a master virus seed stock and a clinical lot of the clinical trial agent under cGMP with an infectious viral titer of approximately 2 × 1010 PFU/ml (total yield, 1 × 1013 PFU). The lot has passed all U.S. Food and Drug Administration-mandated release testing and will be used in a phase 1 clinical translational trial in patients with advanced HCC. PMID:21083425

Current good manufacturing practice production of an oncolytic recombinant vesicular stomatitis viral vector for cancer treatment.

PubMed

Ausubel, L J; Meseck, M; Derecho, I; Lopez, P; Knoblauch, C; McMahon, R; Anderson, J; Dunphy, N; Quezada, V; Khan, R; Huang, P; Dang, W; Luo, M; Hsu, D; Woo, S L C; Couture, L

2011-04-01

Vesicular stomatitis virus (VSV) is an oncolytic virus currently being investigated as a promising tool to treat cancer because of its ability to selectively replicate in cancer cells. To enhance the oncolytic property of the nonpathologic laboratory strain of VSV, we generated a recombinant vector [rVSV(MΔ51)-M3] expressing murine gammaherpesvirus M3, a secreted viral chemokine-binding protein that binds to a broad range of mammalian chemokines with high affinity. As previously reported, when rVSV(MΔ51)-M3 was used in an orthotopic model of hepatocellular carcinoma (HCC) in rats, it suppressed inflammatory cell migration to the virus-infected tumor site, which allowed for enhanced intratumoral virus replication leading to increased tumor necrosis and substantially prolonged survival. These encouraging results led to the development of this vector for clinical translation in patients with HCC. However, a scalable current Good Manufacturing Practice (cGMP)-compliant manufacturing process has not been described for this vector. To produce the quantities of high-titer virus required for clinical trials, a process that is amenable to GMP manufacturing and scale-up was developed. We describe here a large-scale (50-liter) vector production process capable of achieving crude titers on the order of 10(9) plaque-forming units (PFU)/ml under cGMP. This process was used to generate a master virus seed stock and a clinical lot of the clinical trial agent under cGMP with an infectious viral titer of approximately 2 × 10(10) PFU/ml (total yield, 1 × 10(13) PFU). The lot has passed all U.S. Food and Drug Administration-mandated release testing and will be used in a phase 1 clinical translational trial in patients with advanced HCC.

Predictive Models for Tomato Spotted Wilt Virus Spread Dynamics, Considering Frankliniella occidentalis Specific Life Processes as Influenced by the Virus.

PubMed

Ogada, Pamella Akoth; Moualeu, Dany Pascal; Poehling, Hans-Michael

2016-01-01

Several models have been studied on predictive epidemics of arthropod vectored plant viruses in an attempt to bring understanding to the complex but specific relationship between the three cornered pathosystem (virus, vector and host plant), as well as their interactions with the environment. A large body of studies mainly focuses on weather based models as management tool for monitoring pests and diseases, with very few incorporating the contribution of vector's life processes in the disease dynamics, which is an essential aspect when mitigating virus incidences in a crop stand. In this study, we hypothesized that the multiplication and spread of tomato spotted wilt virus (TSWV) in a crop stand is strongly related to its influences on Frankliniella occidentalis preferential behavior and life expectancy. Model dynamics of important aspects in disease development within TSWV-F. occidentalis-host plant interactions were developed, focusing on F. occidentalis' life processes as influenced by TSWV. The results show that the influence of TSWV on F. occidentalis preferential behaviour leads to an estimated increase in relative acquisition rate of the virus, and up to 33% increase in transmission rate to healthy plants. Also, increased life expectancy; which relates to improved fitness, is dependent on the virus induced preferential behaviour, consequently promoting multiplication and spread of the virus in a crop stand. The development of vector-based models could further help in elucidating the role of tri-trophic interactions in agricultural disease systems. Use of the model to examine the components of the disease process could also boost our understanding on how specific epidemiological characteristics interact to cause diseases in crops. With this level of understanding we can efficiently develop more precise control strategies for the virus and the vector.

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

NASA Technical Reports Server (NTRS)

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

Common Ada (tradename) Missile Package (CAMP) Project. Missile Software Parts. Volume 8. Detail Design Document

DTIC Science & Technology

1988-03-01

PACKAGE BODY ) TLCSC P661 (CATALOG #P106-0) This package contains the CAMP parts required to do the vaypoint steering portion of navigation. The...3.3.4.1.6 PROCESSING The following describes the processing performed by this part: package body WaypointSteering is package body ...Steering_Vector_Operations is separate; package body Steering_Vector_Operations_with_Arcsin is separate; procedure Compute Turn_Angle_and Direction (UnitNormal C

Robust model predictive control for satellite formation keeping with eccentricity/inclination vector separation

NASA Astrophysics Data System (ADS)

Lim, Yeerang; Jung, Youeyun; Bang, Hyochoong

2018-05-01

This study presents model predictive formation control based on an eccentricity/inclination vector separation strategy. Alternative collision avoidance can be accomplished by using eccentricity/inclination vectors and adding a simple goal function term for optimization process. Real-time control is also achievable with model predictive controller based on convex formulation. Constraint-tightening approach is address as well improve robustness of the controller, and simulation results are presented to verify performance enhancement for the proposed approach.

Raster and vector processing for scanned linework

USGS Publications Warehouse

Greenlee, David D.

1987-01-01

An investigation of raster editing techniques, including thinning, filling, and node detecting, was performed by using specialized software. The techniques were based on encoding the state of the 3-by-3 neighborhood surrounding each pixel into a single byte. A prototypical method for converting the edited raster linkwork into vectors was also developed. Once vector representations of the lines were formed, they were formatted as a Digital Line Graph, and further refined by deletion of nonessential vertices and by smoothing with a curve-fitting technique.

Does ITV vaginal procedure ensure dosimetric coverage during IMRT of post-operative gynaecological tumours without instructions concerning rectal filling?

PubMed

Verges, Ramona; Giraldo, Alexandra; Seoane, Alejandro; Toral, Elisabet; Ruiz, M Carmen; Pons, Ariadna; Giralt, Jordi

2018-01-01

To find out whether the internal target volume (ITV) vaginal procedure ensures dosimetric coverage during intensity-modulated radiation therapy (IMRT) of post-operative gynaecological tumours without instructions on rectal filling. The ITV vaginal procedure does not necessarily include all movements of the bladder, and does not include changes in the rectal volume. We should know if the vaginal ITV is a useful tool in maintaining CTV coverage during treatment. A retrospective analysis of 24 patients treated between July 2012 and July 2014 with adjuvant IMRT for gynaecological cancer. All patients underwent empty and full bladder CT on simulation (CT-planning) and three weeks later (CT-control). ITV displacement was measured and the 3D vector was calculated. ITV coverage was then evaluated by comparing the volume covered by the prescription isodose on both CT's. Patients were asked to have full bladder but they did not follow recommendations for the rectum. The mean 3D vector was 0.64 ± 0.32 cm (0.09-1.30). The mean ITV coverage loss was 5.8 ± 5.7% (0-20.2). We found a significant positive correlation between the 3D vector and the loss of coverage (Pearson correlation, r  = 0.493, 95% CI: 0.111-0.748, p  = 0.0144). We did not find any significant correlation between the bladder and rectal parameters with the 3D vector and loss of dosimetric coverage. We found a trend between the maximum rectal diameter in CT-planning and 3D vector ( r  = 0.400, 95% CI: -0.004 to 0.692, p  = 0.0529). ITV vaginal procedure contributed to ensuring a good dose coverage without instructions on rectal filling.

Two Introductions of Lyme Disease into Connecticut: A Geospatial Analysis of Human Cases from 1984 to 2012.

PubMed

Xue, Ling; Scoglio, Caterina; McVey, D Scott; Boone, Rebecca; Cohnstaedt, Lee W

2015-09-01

Lyme disease has become the most prevalent vector-borne disease in the United States and results in morbidity in humans, especially children. We used historical case distributions to explain vector-borne disease introductions and subsequent geographic expansion in the absence of disease vector data. We used geographic information system analysis of publicly available Connecticut Department of Public Health case data from 1984, 1985, and 1991 to 2012 for the 169 towns in Connecticut to identify the yearly clusters of Lyme disease cases. Our analysis identified the spatial and temporal origins of two separate introductions of Lyme disease into Connecticut and identified the subsequent direction and rate of spread. We defined both epidemic clusters of cases using significant long-term spatial autocorrelation. The incidence-weighted geographic mean analysis indicates a northern trend of geographic expansion for both epidemic clusters. In eastern Connecticut, as the epidemic progressed, the yearly shift in the geographic mean (rate of epidemic expansion) decreased each year until spatial equilibrium was reached in 2007. The equilibrium indicates a transition from epidemic Lyme disease spread to stable endemic transmission, and we associate this with a reduction in incidence. In western Connecticut, the parabolic distribution of the yearly geographic mean indicates that following the establishment of Lyme disease (1988) the epidemic quickly expanded northward and established equilibrium in 2009.

Corrected Cephalometric Analysis to Determine the Distance and Vector of Distraction Osteogenesis for Syndromic Craniosynostosis

PubMed Central

Fukawa, Toshihiko; Hirakawa, Takashi; Satake, Toshihiko; Maegawa, Jiro

2017-01-01

Background: The purpose of this study was to confirm the utility of a corrected cephalometric analysis to facilitate the planning of distraction osteogenesis with Le Fort III osteotomy for syndromic craniosynostosis. Methods: This prospective study involved 4 male and 2 female patients (mean patient age, 8 years 9 months; age range, 4 years 6 months to 13 years 2 months) with Crouzon syndrome who were treated with Le Fort III maxillary distraction using our previously described system of analysis of a corrected cephalogram and who underwent clinical follow-up. Lateral cephalograms were obtained immediately after device removal. Results: Distraction of orbitale moved the vector downward to the adult profile, but there was slightly less elongation than the adult profile for the distraction distance. The desired and real mean angles after distraction of point A were 29.2 ± 7.9° and 6.1 ± 8.5°, respectively, and the desired and the real mean distances after distraction of point A were 30.6 ± 12.7 mm and 29.4 ± 4.1 mm, respectively. Conclusions: Using the corrected cephalometric analysis, the distance and vector of distraction osteogenesis with Le Fort III osteotomy could be determined in patients with syndromic craniosynostosis. The distraction system brought the patients' facial bones to the planned position using controlling devices. PMID:29062650

Comparison of Classifier Architectures for Online Neural Spike Sorting.

PubMed

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

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

PubMed

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

2015-01-01

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

EMMA: An Extensible Mammalian Modular Assembly Toolkit for the Rapid Design and Production of Diverse Expression Vectors.

PubMed

Martella, Andrea; Matjusaitis, Mantas; Auxillos, Jamie; Pollard, Steven M; Cai, Yizhi

2017-07-21

Mammalian plasmid expression vectors are critical reagents underpinning many facets of research across biology, biomedical research, and the biotechnology industry. Traditional cloning methods often require laborious manual design and assembly of plasmids using tailored sequential cloning steps. This process can be protracted, complicated, expensive, and error-prone. New tools and strategies that facilitate the efficient design and production of bespoke vectors would help relieve a current bottleneck for researchers. To address this, we have developed an extensible mammalian modular assembly kit (EMMA). This enables rapid and efficient modular assembly of mammalian expression vectors in a one-tube, one-step golden-gate cloning reaction, using a standardized library of compatible genetic parts. The high modularity, flexibility, and extensibility of EMMA provide a simple method for the production of functionally diverse mammalian expression vectors. We demonstrate the value of this toolkit by constructing and validating a range of representative vectors, such as transient and stable expression vectors (transposon based vectors), targeting vectors, inducible systems, polycistronic expression cassettes, fusion proteins, and fluorescent reporters. The method also supports simple assembly combinatorial libraries and hierarchical assembly for production of larger multigenetic cargos. In summary, EMMA is compatible with automated production, and novel genetic parts can be easily incorporated, providing new opportunities for mammalian synthetic biology.

NET: a new framework for the vectorization and examination of network data.

PubMed

Lasser, Jana; Katifori, Eleni

2017-01-01

The analysis of complex networks both in general and in particular as pertaining to real biological systems has been the focus of intense scientific attention in the past and present. In this paper we introduce two tools that provide fast and efficient means for the processing and quantification of biological networks like Drosophila tracheoles or leaf venation patterns: the Network Extraction Tool ( NET ) to extract data and the Graph-edit-GUI ( GeGUI ) to visualize and modify networks. NET is especially designed for high-throughput semi-automated analysis of biological datasets containing digital images of networks. The framework starts with the segmentation of the image and then proceeds to vectorization using methodologies from optical character recognition. After a series of steps to clean and improve the quality of the extracted data the framework produces a graph in which the network is represented only by its nodes and neighborhood-relations. The final output contains information about the adjacency matrix of the graph, the width of the edges and the positions of the nodes in space. NET also provides tools for statistical analysis of the network properties, such as the number of nodes or total network length. Other, more complex metrics can be calculated by importing the vectorized network to specialized network analysis packages. GeGUI is designed to facilitate manual correction of non-planar networks as these may contain artifacts or spurious junctions due to branches crossing each other. It is tailored for but not limited to the processing of networks from microscopy images of Drosophila tracheoles. The networks extracted by NET closely approximate the network depicted in the original image. NET is fast, yields reproducible results and is able to capture the full geometry of the network, including curved branches. Additionally GeGUI allows easy handling and visualization of the networks.

Acoustic nonreciprocity in Coriolis mean flow systems.

PubMed

Naghdi, Masoud; Farzbod, Farhad

2018-01-01

One way to break acoustic reciprocity is to have a moving wave propagation medium. If the acoustic wave vector and the moving fluid velocity are collinear, the wave vector shift caused by the fluid flow can be used to break. In this paper, an alternative approach is investigated in which the fluid velocity enters the differential equation of the system as a cross product term with the wave vector. A circular field where the fluid velocity increases radially has a Coriolis acceleration term. In such a system, the acoustic wave enters from the central wall and exits from the perimeter wall. In this paper, the differential equation is solved numerically and the effect of fluid velocity on the nonreciprocity factor is examined.

Dynamics and Synchronization of Nonlinear Oscillators with Time Delays: A Study with Fiber Lasers

DTIC Science & Technology

2007-07-19

or coupling lines PC Polarization Controller PD Photodetector VA Variable Attenuator WDM Wavelength Division Multiplexer x Chapter 1 Introduction 1.1...lasers and detectors. Injection locking of lasers is a common practice that can be used to lock the frequency and phase of a laser to an injected signal...finding a basis vector that maximizes the mean squared projection of the data. Succeeding basis vectors are found that max- imize the projection with the

About Phase: Synthetic Aperture Radar and the Phase Retrieval

DTIC Science & Technology

2014-03-01

Phys. Rev. A 70 (2004) 052107. 57. S . T. Flammia , A. Silberfarb, C. M. Caves, Minimal informationally complete measurements for pure states, Found...is not injective. To resolve this (technical) issue, throughout this thesis we consider sets of the form V/ S , where V is a vector space and S is a...multiplicative subgroup of the field of scalars. By this notation, we mean to identify vectors x, y ∈ V for which there exists a scalar c ∈ S such that y

Swarming Mechanisms in the Yellow Fever Mosquito: Aggregation Pheromones are Involved in the Mating Behavior of Aedes aegypti

DTIC Science & Technology

2014-12-01

behavior of Aedes aegypti Emadeldin Y. Fawaz1, Sandra A. Allan2, Ulrich R. Bernier2, Peter J. Obenauer3, and Joseph W. Diclaro II1 1Vector Biology... Aedes aegypti swarming behavior and identified associated chemical cues. Novel evidence is provided that Ae. aegypti females aggregate by means of...the isolated aggregation pheromones in controlling Ae. aegypti. Journal of Vector Ecology 39 (2): 347-354. 2014. Keyword Index: Aedes aegypti, swarm

The low-order wavefront control system for the PICTURE-C mission: high-speed image acquisition and processing

NASA Astrophysics Data System (ADS)

Hewawasam, Kuravi; Mendillo, Christopher B.; Howe, Glenn A.; Martel, Jason; Finn, Susanna C.; Cook, Timothy A.; Chakrabarti, Supriya

2017-09-01

The Planetary Imaging Concept Testbed Using a Recoverable Experiment - Coronagraph (PICTURE-C) mission will directly image debris disks and exozodiacal dust around nearby stars from a high-altitude balloon using a vector vortex coronagraph. The PICTURE-C low-order wavefront control (LOWC) system will be used to correct time-varying low-order aberrations due to pointing jitter, gravity sag, thermal deformation, and the gondola pendulum motion. We present the hardware and software implementation of the low-order ShackHartmann and reflective Lyot stop sensors. Development of the high-speed image acquisition and processing system is discussed with the emphasis on the reduction of hardware and computational latencies through the use of a real-time operating system and optimized data handling. By characterizing all of the LOWC latencies, we describe techniques to achieve a framerate of 200 Hz with a mean latency of ˜378 μs

A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM

PubMed Central

Li, Ke; Liu, Yi; Wang, Quanxin; Wu, Yalei; Song, Shimin; Sun, Yi; Liu, Tengchong; Wang, Jun; Li, Yang; Du, Shaoyi

2015-01-01

This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slow rate. Firstly, both the fuzzy c-means (FCM) offline clustering and the principal component feature extraction algorithms are applied for the feature selection process. Secondly, the approximate weighted proximal support vector machine (WPSVM) online classification algorithms is used to reduce the feature dimension and further improve the rate of recognition for electrical characteristics spacecraft. Finally, the data capture contribution method by using thresholds is proposed to guarantee the validity and consistency of the data selection. The experimental results indicate that the method proposed can obtain better data features of the spacecraft electrical characteristics, improve the accuracy of identification and shorten the computing time effectively. PMID:26544549

CNN based approach for activity recognition using a wrist-worn accelerometer.

PubMed

Panwar, Madhuri; Dyuthi, S Ram; Chandra Prakash, K; Biswas, Dwaipayan; Acharyya, Amit; Maharatna, Koushik; Gautam, Arvind; Naik, Ganesh R

2017-07-01

In recent years, significant advancements have taken place in human activity recognition using various machine learning approaches. However, feature engineering have dominated conventional methods involving the difficult process of optimal feature selection. This problem has been mitigated by using a novel methodology based on deep learning framework which automatically extracts the useful features and reduces the computational cost. As a proof of concept, we have attempted to design a generalized model for recognition of three fundamental movements of the human forearm performed in daily life where data is collected from four different subjects using a single wrist worn accelerometer sensor. The validation of the proposed model is done with different pre-processing and noisy data condition which is evaluated using three possible methods. The results show that our proposed methodology achieves an average recognition rate of 99.8% as opposed to conventional methods based on K-means clustering, linear discriminant analysis and support vector machine.

A decomposition approach to the design of a multiferroic memory bit

NASA Astrophysics Data System (ADS)

Acevedo, Ruben; Liang, Cheng-Yen; Carman, Gregory P.; Sepulveda, Abdon E.

2017-06-01

The objective of this paper is to present a methodology for the design of a memory bit to minimize the energy required to write data at the bit level. By straining a ferromagnetic nickel nano-dot by means of a piezoelectric substrate, its magnetization vector rotates between two stable states defined as a 1 and 0 for digital memory. The memory bit geometry, actuation mechanism and voltage control law were used as design variables. The approach used was to decompose the overall design process into simpler sub-problems whose structure can be exploited for a more efficient solution. This method minimizes the number of fully dynamic coupled finite element analyses required to converge to a near optimal design, thus decreasing the computational time for the design process. An in-plane sample design problem is presented to illustrate the advantages and flexibility of the procedure.

Prediction of interface residue based on the features of residue interaction network.

PubMed

Jiao, Xiong; Ranganathan, Shoba

2017-11-07

Protein-protein interaction plays a crucial role in the cellular biological processes. Interface prediction can improve our understanding of the molecular mechanisms of the related processes and functions. In this work, we propose a classification method to recognize the interface residue based on the features of a weighted residue interaction network. The random forest algorithm is used for the prediction and 16 network parameters and the B-factor are acting as the element of the input feature vector. Compared with other similar work, the method is feasible and effective. The relative importance of these features also be analyzed to identify the key feature for the prediction. Some biological meaning of the important feature is explained. The results of this work can be used for the related work about the structure-function relationship analysis via a residue interaction network model. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantifying the roles of host movement and vector dispersal in the transmission of vector-borne diseases of livestock.

PubMed

Sumner, Tom; Orton, Richard J; Green, Darren M; Kao, Rowland R; Gubbins, Simon

2017-04-01

The role of host movement in the spread of vector-borne diseases of livestock has been little studied. Here we develop a mathematical framework that allows us to disentangle and quantify the roles of vector dispersal and livestock movement in transmission between farms. We apply this framework to outbreaks of bluetongue virus (BTV) and Schmallenberg virus (SBV) in Great Britain, both of which are spread by Culicoides biting midges and have recently emerged in northern Europe. For BTV we estimate parameters by fitting the model to outbreak data using approximate Bayesian computation, while for SBV we use previously derived estimates. We find that around 90% of transmission of BTV between farms is a result of vector dispersal, while for SBV this proportion is 98%. This difference is a consequence of higher vector competence and shorter duration of viraemia for SBV compared with BTV. For both viruses we estimate that the mean number of secondary infections per infected farm is greater than one for vector dispersal, but below one for livestock movements. Although livestock movements account for a small proportion of transmission and cannot sustain an outbreak on their own, they play an important role in establishing new foci of infection. However, the impact of restricting livestock movements on the spread of both viruses depends critically on assumptions made about the distances over which vector dispersal occurs. If vector dispersal occurs primarily at a local scale (99% of transmission occurs <25 km), movement restrictions are predicted to be effective at reducing spread, but if dispersal occurs frequently over longer distances (99% of transmission occurs <50 km) they are not.

Quantifying the roles of host movement and vector dispersal in the transmission of vector-borne diseases of livestock

PubMed Central

Sumner, Tom; Orton, Richard J.; Green, Darren M.; Kao, Rowland R.

2017-01-01

The role of host movement in the spread of vector-borne diseases of livestock has been little studied. Here we develop a mathematical framework that allows us to disentangle and quantify the roles of vector dispersal and livestock movement in transmission between farms. We apply this framework to outbreaks of bluetongue virus (BTV) and Schmallenberg virus (SBV) in Great Britain, both of which are spread by Culicoides biting midges and have recently emerged in northern Europe. For BTV we estimate parameters by fitting the model to outbreak data using approximate Bayesian computation, while for SBV we use previously derived estimates. We find that around 90% of transmission of BTV between farms is a result of vector dispersal, while for SBV this proportion is 98%. This difference is a consequence of higher vector competence and shorter duration of viraemia for SBV compared with BTV. For both viruses we estimate that the mean number of secondary infections per infected farm is greater than one for vector dispersal, but below one for livestock movements. Although livestock movements account for a small proportion of transmission and cannot sustain an outbreak on their own, they play an important role in establishing new foci of infection. However, the impact of restricting livestock movements on the spread of both viruses depends critically on assumptions made about the distances over which vector dispersal occurs. If vector dispersal occurs primarily at a local scale (99% of transmission occurs <25 km), movement restrictions are predicted to be effective at reducing spread, but if dispersal occurs frequently over longer distances (99% of transmission occurs <50 km) they are not. PMID:28369082

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

DOEpatents

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

2004-06-15

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

A Semi-Vectorization Algorithm to Synthesis of Gravitational Anomaly Quantities on the Earth

NASA Astrophysics Data System (ADS)

Abdollahzadeh, M.; Eshagh, M.; Najafi Alamdari, M.

2009-04-01

The Earth's gravitational potential can be expressed by the well-known spherical harmonic expansion. The computational time of summing up this expansion is an important practical issue which can be reduced by an efficient numerical algorithm. This paper proposes such a method for block-wise synthesizing the anomaly quantities on the Earth surface using vectorization. Fully-vectorization means transformation of the summations to the simple matrix and vector products. It is not a practical for the matrices with large dimensions. Here a semi-vectorization algorithm is proposed to avoid working with large vectors and matrices. It speeds up the computations by using one loop for the summation either on degrees or on orders. The former is a good option to synthesize the anomaly quantities on the Earth surface considering a digital elevation model (DEM). This approach is more efficient than the two-step method which computes the quantities on the reference ellipsoid and continues them upward to the Earth surface. The algorithm has been coded in MATLAB which synthesizes a global grid of 5′Ã- 5′ (corresponding 9 million points) of gravity anomaly or geoid height using a geopotential model to degree 360 in 10000 seconds by an ordinary computer with 2G RAM.