LINEARIZATION OF EMPIRICAL RHEOLOGICAL DATA FOR USE IN COMPOSITION CONTROL OF MULTICOMPONENT FOODSTUFFS.

PubMed

Drake, Birger; Nádai, Béla

1970-03-01

An empirical measure of viscosity, which is often far from being a linear function of composition, was used together with refractive index to build up a function which bears a linear relationship to the composition of tomato paste-water-sucrose mixtures. The new function can be used directly for rapid composition control by linear vector-vector transformation.

Prediction of heterotrimeric protein complexes by two-phase learning using neighboring kernels

PubMed Central

2014-01-01

Background Protein complexes play important roles in biological systems such as gene regulatory networks and metabolic pathways. Most methods for predicting protein complexes try to find protein complexes with size more than three. It, however, is known that protein complexes with smaller sizes occupy a large part of whole complexes for several species. In our previous work, we developed a method with several feature space mappings and the domain composition kernel for prediction of heterodimeric protein complexes, which outperforms existing methods. Results We propose methods for prediction of heterotrimeric protein complexes by extending techniques in the previous work on the basis of the idea that most heterotrimeric protein complexes are not likely to share the same protein with each other. We make use of the discriminant function in support vector machines (SVMs), and design novel feature space mappings for the second phase. As the second classifier, we examine SVMs and relevance vector machines (RVMs). We perform 10-fold cross-validation computational experiments. The results suggest that our proposed two-phase methods and SVM with the extended features outperform the existing method NWE, which was reported to outperform other existing methods such as MCL, MCODE, DPClus, CMC, COACH, RRW, and PPSampler for prediction of heterotrimeric protein complexes. Conclusions We propose two-phase prediction methods with the extended features, the domain composition kernel, SVMs and RVMs. The two-phase method with the extended features and the domain composition kernel using SVM as the second classifier is particularly useful for prediction of heterotrimeric protein complexes. PMID:24564744

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine

PubMed Central

Manavalan, Balachandran; Shin, Tae H.; Lee, Gwang

2018-01-01

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html. PMID:29616000

PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine.

PubMed

Manavalan, Balachandran; Shin, Tae H; Lee, Gwang

2018-01-01

Accurately identifying bacteriophage virion proteins from uncharacterized sequences is important to understand interactions between the phage and its host bacteria in order to develop new antibacterial drugs. However, identification of such proteins using experimental techniques is expensive and often time consuming; hence, development of an efficient computational algorithm for the prediction of phage virion proteins (PVPs) prior to in vitro experimentation is needed. Here, we describe a support vector machine (SVM)-based PVP predictor, called PVP-SVM, which was trained with 136 optimal features. A feature selection protocol was employed to identify the optimal features from a large set that included amino acid composition, dipeptide composition, atomic composition, physicochemical properties, and chain-transition-distribution. PVP-SVM achieved an accuracy of 0.870 during leave-one-out cross-validation, which was 6% higher than control SVM predictors trained with all features, indicating the efficiency of the feature selection method. Furthermore, PVP-SVM displayed superior performance compared to the currently available method, PVPred, and two other machine-learning methods developed in this study when objectively evaluated with an independent dataset. For the convenience of the scientific community, a user-friendly and publicly accessible web server has been established at www.thegleelab.org/PVP-SVM/PVP-SVM.html.

Floral traits influence pollen vectors' choices in higher elevation communities in the Himalaya-Hengduan Mountains.

PubMed

Zhao, Yan-Hui; Ren, Zong-Xin; Lázaro, Amparo; Wang, Hong; Bernhardt, Peter; Li, Hai-Dong; Li, De-Zhu

2016-05-24

How floral traits and community composition influence plant specialization is poorly understood and the existing evidence is restricted to regions where plant diversity is low. Here, we assessed whether plant specialization varied among four species-rich subalpine/alpine communities on the Yulong Mountain, SW China (elevation from 2725 to 3910 m). We analyzed two factors (floral traits and pollen vector community composition: richness and density) to determine the degree of plant specialization across 101 plant species in all four communities. Floral visitors were collected and pollen load analyses were conducted to identify and define pollen vectors. Plant specialization of each species was described by using both pollen vector diversity (Shannon's diversity index) and plant selectiveness (d' index), which reflected how selective a given species was relative to available pollen vectors. Pollen vector diversity tended to be higher in communities at lower elevations, while plant selectiveness was significantly lower in a community with the highest proportion of unspecialized flowers (open flowers and clusters of flowers in open inflorescences). In particular, we found that plant species with large and unspecialized flowers attracted a greater diversity of pollen vectors and showed higher selectiveness in their use of pollen vectors. Plant species with large floral displays and high flower abundance were more selective in their exploitation of pollen vectors. Moreover, there was a negative relationship between plant selectiveness and pollen vector density. These findings suggest that flower shape and flower size can increase pollen vector diversity but they also increased plant selectiveness. This indicated that those floral traits that were more attractive to insects increased the diversity of pollen vectors to plants while decreasing overlap among co-blooming plant species for the same pollen vectors. Furthermore, floral traits had a more important impact on the diversity of pollen vectors than the composition of anthophilous insect communities. Plant selectiveness of pollen vectors was strongly influenced by both floral traits and insect community composition. These findings provide a basis for a better understanding of how floral traits and community context shape interactions between flowers and their pollen vectors in species-rich communities.

Preparation and infrared/raman classification of 630 spectroscopically encoded styrene copolymers.

PubMed

Fenniri, Hicham; Chun, Sangki; Terreau, Owen; Bravo-Vasquez, Juan-Pablo

2008-01-01

The barcoded resins (BCRs) were introduced recently as a platform for encoded combinatorial chemistry. One of the main challenges yet to be overcome is the demonstration that a large number of BCRs could be generated and classified with high confidence. Here, we describe the synthesis and classification of 630 polystyrene-based copolymers prepared from the combinatorial association of 15 spectroscopically active styrene monomers. Each of the 630 copolymers displayed a unique vibrational fingerprint (infrared and Raman), which was converted into a spectral vector. To each of the 630 copolymers, a vector of the known (reference) composition was assigned. Unknown (prediction) vectors were decoded using multivariate data analysis. From the inner product of the reference and prediction vectors, a correlation map comparing 396 900 copolymer pairs (630 x 630) was generated. In 100% of the cases, the highest correlation was obtained for polymer pairs in which the reference and prediction vectors correspond to copolymers prepared from identical styrene monomers, thus demonstrating the high reliability of this encoding strategy. We have also established that the spectroscopic barcodes generated from the Raman and infrared spectra are independent of the copolymers' morphology (beaded versus bulk polymers). Besides the demonstration of the generality of the polymer barcoding strategy, the analytical methods developed here could in principle be extended to the investigation of the composition and purity of any other synthetic polymer and biopolymer library, or even scaffold-based combinatorial libraries.

Dynamic measurement of local displacements within curing resin-based dental composite using optical coherence elastography

NASA Astrophysics Data System (ADS)

Tomlins, Peter H.; Rahman, Mohammed Wahidur; Donnan, Robert S.

2016-04-01

This study aimed to determine the feasibility of using optical coherence elastography to measure internal displacements during the curing phase of a light-activated, resin-based composite material. Displacement vectors were spatially mapped over time within a commercial dental composite. Measurements revealed that the orientation of cure-induced displacement vectors varied spatially in a complex manner; however, each vector showed a systematic evolution with time. Precision of individual displacements was estimated to be ˜1 to 2 μm, enabling submicrometer time-varying displacements to be detected.

Cytoplasmic bacteriophage display system

DOEpatents

Studier, F.W.; Rosenberg, A.H.

1998-06-16

Disclosed are display vectors comprising DNA encoding a portion of a structural protein from a cytoplasmic bacteriophage, joined covalently to a protein or peptide of interest. Exemplified are display vectors wherein the structural protein is the T7 bacteriophage capsid protein. More specifically, in the exemplified display vectors the C-terminal amino acid residue of the portion of the capsid protein is joined to the N-terminal residue of the protein or peptide of interest. The portion of the T7 capsid protein exemplified comprises an N-terminal portion corresponding to form 10B of the T7 capsid protein. The display vectors are useful for high copy number display or lower copy number display (with larger fusion). Compositions of the type described herein are useful in connection with methods for producing a virus displaying a protein or peptide of interest. 1 fig.

Cytoplasmic bacteriophage display system

DOEpatents

Studier, F. William; Rosenberg, Alan H.

1998-06-16

Disclosed are display vectors comprising DNA encoding a portion of a structural protein from a cytoplasmic bacteriophage, joined covalently to a protein or peptide of interest. Exemplified are display vectors wherein the structural protein is the T7 bacteriophage capsid protein. More specifically, in the exemplified display vectors the C-terminal amino acid residue of the portion of the capsid protein is joined to the N-terminal residue of the protein or peptide of interest. The portion of the T7 capsid protein exemplified comprises an N-terminal portion corresponding to form 10B of the T7 capsid protein. The display vectors are useful for high copy number display or lower copy number display (with larger fusion). Compositions of the type described herein are useful in connection with methods for producing a virus displaying a protein or peptide of interest.

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

PubMed

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

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

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

Method of increasing conversion of a fatty acid to its corresponding dicarboxylic acid

DOEpatents

Craft, David L.; Wilson, C. Ron; Eirich, Dudley; Zhang, Yeyan

2004-09-14

A nucleic acid sequence including a CYP promoter operably linked to nucleic acid encoding a heterologous protein is provided to increase transcription of the nucleic acid. Expression vectors and host cells containing the nucleic acid sequence are also provided. The methods and compositions described herein are especially useful in the production of polycarboxylic acids by yeast cells.

Producing biofuels using polyketide synthases

DOEpatents

Katz, Leonard; Fortman, Jeffrey L; Keasling, Jay D

2013-04-16

The present invention provides for a non-naturally occurring polyketide synthase (PKS) capable of synthesizing a carboxylic acid or a lactone, and a composition such that a carboxylic acid or lactone is included. The carboxylic acid or lactone, or derivative thereof, is useful as a biofuel. The present invention also provides for a recombinant nucleic acid or vector that encodes such a PKS, and host cells which also have such a recombinant nucleic acid or vector. The present invention also provides for a method of producing such carboxylic acids or lactones using such a PKS.

Estimation of regionalized compositions: A comparison of three methods

USGS Publications Warehouse

Pawlowsky, V.; Olea, R.A.; Davis, J.C.

1995-01-01

A regionalized composition is a random vector function whose components are positive and sum to a constant at every point of the sampling region. Consequently, the components of a regionalized composition are necessarily spatially correlated. This spatial dependence-induced by the constant sum constraint-is a spurious spatial correlation and may lead to misinterpretations of statistical analyses. Furthermore, the cross-covariance matrices of the regionalized composition are singular, as is the coefficient matrix of the cokriging system of equations. Three methods of performing estimation or prediction of a regionalized composition at unsampled points are discussed: (1) the direct approach of estimating each variable separately; (2) the basis method, which is applicable only when a random function is available that can he regarded as the size of the regionalized composition under study; (3) the logratio approach, using the additive-log-ratio transformation proposed by J. Aitchison, which allows statistical analysis of compositional data. We present a brief theoretical review of these three methods and compare them using compositional data from the Lyons West Oil Field in Kansas (USA). It is shown that, although there are no important numerical differences, the direct approach leads to invalid results, whereas the basis method and the additive-log-ratio approach are comparable. ?? 1995 International Association for Mathematical Geology.

.beta.-glucosidase 5 (BGL5) compositions

DOEpatents

Dunn-Coleman, Nigel; Goedegebuur, Frits; Ward, Michael; Yao, Jian

2010-06-01

The present invention provides a novel .beta.-glucosidase nucleic acid sequence, designated bgl5, and the corresponding BGL5 amino acid sequence. The invention also provides expression vectors and host cells comprising a nucleic acid sequence encoding BGL5, recombinant BGL5 proteins and methods for producing the same.

Body fluid volume and nutritional status in hemodialysis: vector bioelectric impedance analysis.

PubMed

Espinosa Cuevas, M A; Navarrete Rodriguez, G; Villeda Martinez, M E; Atilano Carsi, X; Miranda Alatriste, P; Tostado Gutiérrez, T; Correa-Rotter, R

2010-04-01

Protein-energy malnutrition and hypervolemia are major causes of morbidity and mortality in patients on chronic hemodialysis (CHD). The methods used to evaluate nutritional status and volume status remain controversial. Vector bioelectric impedance analysis (vector- BIA) has recently been developed to assess both nutritional status and tissue hydration. The purpose of the study was to assess the nutritional status and volume status of patients on CHD with conventional nutritional assessment methods and with vector-BIA and then to compare the resulting findings. 76 Mexican patients on CHD were studied. Nutritional status and body composition were assessed with anthropometry, biochemical variables, and the modified Bilbrey nutritional index (mBNI), the results were compared with both conventional BIA and vector-BIA. The BNI was used to determine the number of patients with normal nutritional status (n = 27, 35.5%), and mild (n = 31, 40.8%), moderate (n = 10, 13.2%) and severe malnutrition (n = 8, 10.5%). Patients displayed shorter vectors with smaller phase angles or with an overhydration vectorial pattern before the initiation of their hemodialysis session. There was general improvement to normal hydration status post-dialysis (p < 0.05); however, 28% remained overhydrated as assessed by vector-BIA. The vector-BIA results showed that worse malnutrition status was associated with greater volume overload (p < 0.05). Diabetes mellitus (DM) was associated with shorter vectors with smaller phase angles (a vectorial pattern of overhydration and cachexia) (p < 0.05). Patients with lower serum creatinine presented with shorter vectors and smaller phase angles (vectorial patterns of malnutrition and/or overhydration) (p < 0.05). In women, lower serum albumin (< 3.4 g/dl) correlated with greater overhydration and malnutrition (p < 0.05). In this population, the vector-BIA showed that 28% of the population remained overhydrated after their hemodialysis session. Diabetics and those with moderate or severe malnutrition were more overhydrated, which is a condition that may be associated with increased cardiovascular morbidity. Because nutritional and volume status are important factors associated with morbidity and mortality in CHD patients, we focused on optimizing the use of existing methods. Our studies suggest that vector-BIA offers a comprehensive and reliable reproducible means of assessing both volume and masses at the bedside and can complement the traditional methods.

Vector representation of lithium and other mica compositions

NASA Technical Reports Server (NTRS)

Burt, Donald M.

1991-01-01

In contrast to mathematics, where a vector of one component defines a line, in chemical petrology a one-component system is a point, and two components are needed to define a line, three for a plane, and four for a space. Here, an attempt is made to show how these differences in the definition of a component can be resolved, with lithium micas used as an example. In particular, the condensed composition space theoretically accessible to Li-Fe-Al micas is shown to be an irregular three-dimensional polyhedron, rather than the triangle Al(3+)-Fe(2+)-Li(+), used by some researchers. This result is demonstrated starting with the annite composition and using exchange operators graphically as vectors that generate all of the other mica compositions.

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

PubMed

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

2011-10-11

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

Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition.

PubMed

Tamura, Takeyuki; Akutsu, Tatsuya

2007-11-30

Subcellular location prediction of proteins is an important and well-studied problem in bioinformatics. This is a problem of predicting which part in a cell a given protein is transported to, where an amino acid sequence of the protein is given as an input. This problem is becoming more important since information on subcellular location is helpful for annotation of proteins and genes and the number of complete genomes is rapidly increasing. Since existing predictors are based on various heuristics, it is important to develop a simple method with high prediction accuracies. In this paper, we propose a novel and general predicting method by combining techniques for sequence alignment and feature vectors based on amino acid composition. We implemented this method with support vector machines on plant data sets extracted from the TargetP database. Through fivefold cross validation tests, the obtained overall accuracies and average MCC were 0.9096 and 0.8655 respectively. We also applied our method to other datasets including that of WoLF PSORT. Although there is a predictor which uses the information of gene ontology and yields higher accuracy than ours, our accuracies are higher than existing predictors which use only sequence information. Since such information as gene ontology can be obtained only for known proteins, our predictor is considered to be useful for subcellular location prediction of newly-discovered proteins. Furthermore, the idea of combination of alignment and amino acid frequency is novel and general so that it may be applied to other problems in bioinformatics. Our method for plant is also implemented as a web-system and available on http://sunflower.kuicr.kyoto-u.ac.jp/~tamura/slpfa.html.

Predicting protein-protein interactions by combing various sequence- derived features into the general form of Chou's Pseudo amino acid composition.

PubMed

Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

2012-05-01

Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

Hybrid state vector methods for structural dynamic and aeroelastic boundary value problems

NASA Technical Reports Server (NTRS)

Lehman, L. L.

1982-01-01

A computational technique is developed that is suitable for performing preliminary design aeroelastic and structural dynamic analyses of large aspect ratio lifting surfaces. The method proves to be quite general and can be adapted to solving various two point boundary value problems. The solution method, which is applicable to both fixed and rotating wing configurations, is based upon a formulation of the structural equilibrium equations in terms of a hybrid state vector containing generalized force and displacement variables. A mixed variational formulation is presented that conveniently yields a useful form for these state vector differential equations. Solutions to these equations are obtained by employing an integrating matrix method. The application of an integrating matrix provides a discretization of the differential equations that only requires solutions of standard linear matrix systems. It is demonstrated that matrix partitioning can be used to reduce the order of the required solutions. Results are presented for several example problems in structural dynamics and aeroelasticity to verify the technique and to demonstrate its use. These problems examine various types of loading and boundary conditions and include aeroelastic analyses of lifting surfaces constructed from anisotropic composite materials.

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

Butler, W; Merrick, G; Kurko, B

Purpose: To quantify the effect of metal hip prosthesis on the ability to track and localize electromagnetic transponders. Methods: Three Calypso transponders were implanted into two prostate phantoms. The geometric center of the transponders were identified on computed tomography and set as the isocenter. With the phantom stationary on the treatment table and the tracking array 14-cm above the isocenter, data was acquired by the Calypso system at 10 Hz to establish the uncertainty in measurements. Transponder positional data was acquired with unilateral hip prostheses of different metallic compositions and then with bilateral hips placed at variable separation from themore » phantom. Results: Regardless of hip prosthesis composition, the average vector displacement in the presence of a unilateral prosthesis was < 0.5 mm. The greatest contribution to overall vector displacement occurred in the lateral dimension. With bilateral hip prosthesis, the average vector displacement was 0.3 mm. The displacement in the lateral dimension was markedly reduced compared with a unilateral hip, suggesting that there was a countervailing effect with bilateral hip prosthesis. The greatest average vector displacement was 0.6 mm and occurred when bilateral hip prostheses were placed within 4 cm of the detector array. Conclusion: Unilateral and bilateral hip prostheses did not have any meaningful effect on the ability to accurately track electromagnetic transponders implanted in a prostate phantom. At clinically realistic distances between the hip and detection array, the average tracking error is negligible.« less

Two-Dimensional DOA and Polarization Estimation for a Mixture of Uncorrelated and Coherent Sources with Sparsely-Distributed Vector Sensor Array

PubMed Central

Si, Weijian; Zhao, Pinjiao; Qu, Zhiyu

2016-01-01

This paper presents an L-shaped sparsely-distributed vector sensor (SD-VS) array with four different antenna compositions. With the proposed SD-VS array, a novel two-dimensional (2-D) direction of arrival (DOA) and polarization estimation method is proposed to handle the scenario where uncorrelated and coherent sources coexist. The uncorrelated and coherent sources are separated based on the moduli of the eigenvalues. For the uncorrelated sources, coarse estimates are acquired by extracting the DOA information embedded in the steering vectors from estimated array response matrix of the uncorrelated sources, and they serve as coarse references to disambiguate fine estimates with cyclical ambiguity obtained from the spatial phase factors. For the coherent sources, four Hankel matrices are constructed, with which the coherent sources are resolved in a similar way as for the uncorrelated sources. The proposed SD-VS array requires only two collocated antennas for each vector sensor, thus the mutual coupling effects across the collocated antennas are reduced greatly. Moreover, the inter-sensor spacings are allowed beyond a half-wavelength, which results in an extended array aperture. Simulation results demonstrate the effectiveness and favorable performance of the proposed method. PMID:27258271

Cultivation-independent methods reveal differences among bacterial gut microbiota in triatomine vectors of Chagas disease.

PubMed

da Mota, Fabio Faria; Marinho, Lourena Pinheiro; Moreira, Carlos José de Carvalho; Lima, Marli Maria; Mello, Cícero Brasileiro; Garcia, Eloi Souza; Carels, Nicolas; Azambuja, Patricia

2012-01-01

Chagas disease is a trypanosomiasis whose agent is the protozoan parasite Trypanosoma cruzi, which is transmitted to humans by hematophagous bugs known as triatomines. Even though insecticide treatments allow effective control of these bugs in most Latin American countries where Chagas disease is endemic, the disease still affects a large proportion of the population of South America. The features of the disease in humans have been extensively studied, and the genome of the parasite has been sequenced, but no effective drug is yet available to treat Chagas disease. The digestive tract of the insect vectors in which T. cruzi develops has been much less well investigated than blood from its human hosts and constitutes a dynamic environment with very different conditions. Thus, we investigated the composition of the predominant bacterial species of the microbiota in insect vectors from Rhodnius, Triatoma, Panstrongylus and Dipetalogaster genera. Microbiota of triatomine guts were investigated using cultivation-independent methods, i.e., phylogenetic analysis of 16s rDNA using denaturing gradient gel electrophoresis (DGGE) and cloned-based sequencing. The Chao index showed that the diversity of bacterial species in triatomine guts is low, comprising fewer than 20 predominant species, and that these species vary between insect species. The analyses showed that Serratia predominates in Rhodnius, Arsenophonus predominates in Triatoma and Panstrongylus, while Candidatus Rohrkolberia predominates in Dipetalogaster. The microbiota of triatomine guts represents one of the factors that may interfere with T. cruzi transmission and virulence in humans. The knowledge of its composition according to insect species is important for designing measures of biological control for T. cruzi. We found that the predominant species of the bacterial microbiota in triatomines form a group of low complexity whose structure differs according to the vector genus.

Bidirectional composition on lie groups for gradient-based image alignment.

PubMed

Mégret, Rémi; Authesserre, Jean-Baptiste; Berthoumieu, Yannick

2010-09-01

In this paper, a new formulation based on bidirectional composition on Lie groups (BCL) for parametric gradient-based image alignment is presented. Contrary to the conventional approaches, the BCL method takes advantage of the gradients of both template and current image without combining them a priori. Based on this bidirectional formulation, two methods are proposed and their relationship with state-of-the-art gradient based approaches is fully discussed. The first one, i.e., the BCL method, relies on the compositional framework to provide the minimization of the compensated error with respect to an augmented parameter vector. The second one, the projected BCL (PBCL), corresponds to a close approximation of the BCL approach. A comparative study is carried out dealing with computational complexity, convergence rate and frequence of convergence. Numerical experiments using a conventional benchmark show the performance improvement especially for asymmetric levels of noise, which is also discussed from a theoretical point of view.

Chemical Compositions of the Peel Essential Oil of Citrus aurantium and Its Natural Larvicidal Activity against the Malaria Vector Anopheles stephensi (Diptera: Culicidae) in Comparison with Citrus paradisi

PubMed Central

Sanei-Dehkordi, Alireza; Sedaghat, Mohammad Mehdi; Vatandoost, Hassan; Abai, Mohammad Reza

2016-01-01

Background: Recently, essential oils and extracts derived from plants have received much interest as potential bio-active agents against mosquito vectors. Methods: The essential oils extract from fresh peel of ripe fruit of Citrus aurantium and Citrus paradisi were tested against mosquito vector Anopheles stephensi (Diptera: Culicidae) under laboratory condition. Then chemical composition of the essential oil of C. aurantium was analyzed using gas chromatography-mass spectrometry (GC–MS). Results: The essential oils obtained from C. aurantium, and C. paradisi showed good larviciding effect against An. stephensi with LC50 values 31.20 ppm and 35.71 ppm respectively. Clear dose response relationships were established with the highest dose of 80 ppm plant extract evoking almost 100% mortality. Twenty-one (98.62%) constituents in the leaf oil were identified. The main constituent of the leaf oil was Dl-limonene (94.81). Conclusion: The results obtained from this study suggest that the limonene of peel essential oil of C. aurantium is promising as larvicide against An. stephensi larvae and could be useful in the search for new natural larvicidal compounds. PMID:28032110

Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

PubMed

Sabooh, M Fazli; Iqbal, Nadeem; Khan, Mukhtaj; Khan, Muslim; Maqbool, H F

2018-05-01

This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (m 5 C) plays a vital role in a number of biological processes. For better comprehension of the biological functions and mechanism it is necessary to recognize m 5 C sites in RNA precisely. The laboratory techniques and procedures are available to identify m 5 C sites in RNA, but these procedures require a lot of time and resources. This study develops a new computational method for extracting the features of RNA sequence. In this method, first the RNA sequence is encoded via composite feature vector, then, for the selection of discriminate features, the minimum-redundancy-maximum-relevance algorithm was used. Secondly, the classification method used has been based on a support vector machine by using jackknife cross validation test. The suggested method efficiently identifies m 5 C sites from non- m 5 C sites and the outcome of the suggested algorithm is 93.33% with sensitivity of 90.0 and specificity of 96.66 on bench mark datasets. The result exhibits that proposed algorithm shown significant identification performance compared to the existing computational techniques. This study extends the knowledge about the occurrence sites of RNA modification which paves the way for better comprehension of the biological uses and mechanism. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fermi wave vector for the partially spin-polarized composite-fermion Fermi sea

NASA Astrophysics Data System (ADS)

Balram, Ajit C.; Jain, J. K.

2017-12-01

The fully spin-polarized composite-fermion (CF) Fermi sea at the half-filled lowest Landau level has a Fermi wave vector kF*=√{4 π ρe } , where ρe is the density of electrons or composite fermions, supporting the notion that the interaction between composite fermions can be treated perturbatively. Away from ν =1 /2 , the area is seen to be consistent with kF*=√{4 π ρe } for ν <1 /2 but kF*=√{4 π ρh } for ν >1 /2 , where ρh is the density of holes in the lowest Landau level. This result is consistent with particle-hole symmetry in the lowest Landau level. We investigate in this article the Fermi wave vector of the spin-singlet CF Fermi sea (CFFS) at ν =1 /2 , for which particle-hole symmetry is not a consideration. Using the microscopic CF theory, we find that for the spin-singlet CFFS the Fermi wave vectors for up- and down-spin CFFSs at ν =1 /2 are consistent with kF*↑,↓=√{4 π ρe↑,↓ } , where ρe↑=ρe↓=ρe/2 , which implies that the residual interactions between composite fermions do not cause a nonperturbative correction for spin-singlet CFFS either. Our results suggest the natural conjecture that for arbitrary spin polarization the CF Fermi wave vectors are given by kF*↑=√{4 π ρe↑ } and kF*↓=√{4 π ρe↓ } .

An implementation of support vector machine on sentiment classification of movie reviews

NASA Astrophysics Data System (ADS)

Yulietha, I. M.; Faraby, S. A.; Adiwijaya; Widyaningtyas, W. C.

2018-03-01

With technological advances, all information about movie is available on the internet. If the information is processed properly, it will get the quality of the information. This research proposes to the classify sentiments on movie review documents. This research uses Support Vector Machine (SVM) method because it can classify high dimensional data in accordance with the data used in this research in the form of text. Support Vector Machine is a popular machine learning technique for text classification because it can classify by learning from a collection of documents that have been classified previously and can provide good result. Based on number of datasets, the 90-10 composition has the best result that is 85.6%. Based on SVM kernel, kernel linear with constant 1 has the best result that is 84.9%

Automated classification of optical coherence tomography images of human atrial tissue

NASA Astrophysics Data System (ADS)

Gan, Yu; Tsay, David; Amir, Syed B.; Marboe, Charles C.; Hendon, Christine P.

2016-10-01

Tissue composition of the atria plays a critical role in the pathology of cardiovascular disease, tissue remodeling, and arrhythmogenic substrates. Optical coherence tomography (OCT) has the ability to capture the tissue composition information of the human atria. In this study, we developed a region-based automated method to classify tissue compositions within human atria samples within OCT images. We segmented regional information without prior information about the tissue architecture and subsequently extracted features within each segmented region. A relevance vector machine model was used to perform automated classification. Segmentation of human atrial ex vivo datasets was correlated with trichrome histology and our classification algorithm had an average accuracy of 80.41% for identifying adipose, myocardium, fibrotic myocardium, and collagen tissue compositions.

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.

Combined hairpin-antisense compositions and methods for modulating expression

DOEpatents

Shanklin, John; Nguyen, Tam

2014-08-05

A nucleotide construct comprising a nucleotide sequence that forms a stem and a loop, wherein the loop comprises a nucleotide sequence that modulates expression of a target, wherein the stem comprises a nucleotide sequence that modulates expression of a target, and wherein the target modulated by the nucleotide sequence in the loop and the target modulated by the nucleotide sequence in the stem may be the same or different. Vectors, methods of regulating target expression, methods of providing a cell, and methods of treating conditions comprising the nucleotide sequence are also disclosed.

Combined hairpin-antisense compositions and methods for modulating expression

DOEpatents

Shanklin, John; Nguyen, Tam Huu

2015-11-24

A nucleotide construct comprising a nucleotide sequence that forms a stem and a loop, wherein the loop comprises a nucleotide sequence that modulates expression of a target, wherein the stem comprises a nucleotide sequence that modulates expression of a target, and wherein the target modulated by the nucleotide sequence in the loop and the target modulated by the nucleotide sequence in the stem may be the same or different. Vectors, methods of regulating target expression, methods of providing a cell, and methods of treating conditions comprising the nucleotide sequence are also disclosed.

Compositional and phase relations among rare earth element minerals

NASA Technical Reports Server (NTRS)

Burt, D. M.

1990-01-01

This paper discusses the compositional and phase relationships among minerals in which rare earth elements (REE) occur as essential constituents (e.g., bastnaesite, monazite, xenotime, aeschynite, allanite). Particular consideration is given to the vector representation of complex coupled substitutions in selected REE-bearing minerals and to the REE partitioning between minerals as related to the acid-base tendencies and mineral stabilities. It is shown that the treatment of coupled substitutions as vector quantities facilitates graphical representation of mineral composition spaces.

MLACP: machine-learning-based prediction of anticancer peptides

PubMed Central

Manavalan, Balachandran; Basith, Shaherin; Shin, Tae Hwan; Choi, Sun; Kim, Myeong Ok; Lee, Gwang

2017-01-01

Cancer is the second leading cause of death globally, and use of therapeutic peptides to target and kill cancer cells has received considerable attention in recent years. Identification of anticancer peptides (ACPs) through wet-lab experimentation is expensive and often time consuming; therefore, development of an efficient computational method is essential to identify potential ACP candidates prior to in vitro experimentation. In this study, we developed support vector machine- and random forest-based machine-learning methods for the prediction of ACPs using the features calculated from the amino acid sequence, including amino acid composition, dipeptide composition, atomic composition, and physicochemical properties. We trained our methods using the Tyagi-B dataset and determined the machine parameters by 10-fold cross-validation. Furthermore, we evaluated the performance of our methods on two benchmarking datasets, with our results showing that the random forest-based method outperformed the existing methods with an average accuracy and Matthews correlation coefficient value of 88.7% and 0.78, respectively. To assist the scientific community, we also developed a publicly accessible web server at www.thegleelab.org/MLACP.html. PMID:29100375

Nigeria Anopheles Vector Database: An Overview of 100 Years' Research

PubMed Central

Okorie, Patricia Nkem; McKenzie, F. Ellis; Ademowo, Olusegun George; Bockarie, Moses; Kelly-Hope, Louise

2011-01-01

Anopheles mosquitoes are important vectors of malaria and lymphatic filariasis (LF), which are major public health diseases in Nigeria. Malaria is caused by infection with a protozoan parasite of the genus Plasmodium and LF by the parasitic worm Wuchereria bancrofti. Updating our knowledge of the Anopheles species is vital in planning and implementing evidence based vector control programs. To present a comprehensive report on the spatial distribution and composition of these vectors, all published data available were collated into a database. Details recorded for each source were the locality, latitude/longitude, time/period of study, species, abundance, sampling/collection methods, morphological and molecular species identification methods, insecticide resistance status, including evidence of the kdr allele, and P. falciparum sporozoite rate and W. bancrofti microfilaria prevalence. This collation resulted in a total of 110 publications, encompassing 484,747 Anopheles mosquitoes in 632 spatially unique descriptions at 142 georeferenced locations being identified across Nigeria from 1900 to 2010. Overall, the highest number of vector species reported included An. gambiae complex (65.2%), An. funestus complex (17.3%), An. gambiae s.s. (6.5%). An. arabiensis (5.0%) and An. funestus s.s. (2.5%), with the molecular forms An. gambiae M and S identified at 120 locations. A variety of sampling/collection and species identification methods were used with an increase in molecular techniques in recent decades. Insecticide resistance to pyrethroids and organochlorines was found in the main Anopheles species across 45 locations. Presence of P. falciparum and W. bancrofti varied between species with the highest sporozoite rates found in An. gambiae s.s, An. funestus s.s. and An. moucheti, and the highest microfilaria prevalence in An. gambiae s.l., An. arabiensis, and An. gambiae s.s. This comprehensive geo-referenced database provides an essential baseline on Anopheles vectors and will be an important resource for malaria and LF vector control programmes in Nigeria. PMID:22162764

Chemical composition and insecticidal activity of plant essential oils from Benin against Anopheles gambiae (Giles)

PubMed Central

2013-01-01

Background Insecticide resistance in sub-Saharan Africa and especially in Benin is a major public health issue hindering the control of the malaria vectors. Each Anopheles species has developed a resistance to one or several classes of the insecticides currently in use in the field. Therefore, it is urgent to find alternative compounds to conquer the vector. In this study, the efficacies of essential oils of nine plant species, which are traditionally used to avoid mosquito bites in Benin, were investigated. Methods Essential oils of nine plant species were extracted by hydrodistillation, and their chemical compositions were identified by GC-MS. These oils were tested on susceptible “kisumu” and resistant “ladji-Cotonou” strains of Anopheles gambiae, following WHO test procedures for insecticide resistance monitoring in malaria vector mosquitoes. Results Different chemical compositions were obtained from the essential oils of the plant species. The major constituents identified were as follows: neral and geranial for Cymbopogon citratus, Z-carveol, E-p-mentha-1(7),8-dien-2-ol and E-p-mentha-2,8-dienol for Cymbopogon giganteus, piperitone for Cymbopogon schoenanthus, citronellal and citronellol for Eucalyptus citriodora, p-cymene, caryophyllene oxide and spathulenol for Eucalyptus tereticornis, 3-tetradecanone for Cochlospermum tinctorium and Cochlospermum planchonii, methyl salicylate for Securidaca longepedunculata and ascaridole for Chenopodium ambrosioides. The diagnostic dose was 0.77% for C. citratus, 2.80% for E. tereticornis, 3.37% for E. citriodora, 4.26% for C. ambrosioides, 5.48% for C. schoenanthus and 7.36% for C. giganteus. The highest diagnostic doses were obtained with S. longepedunculata (9.84%), C. tinctorium (11.56%) and C. planchonii (15.22%), compared to permethrin 0.75%. A. gambiae cotonou, which is resistant to pyrethroids, showed significant tolerance to essential oils from C. tinctorium and S. longepedunculata as expected but was highly susceptible to all the other essential oils at the diagnostic dose. Conclusions C. citratus, E. tereticornis, E. citriodora, C. ambrosioides and C. schoenanthus are potential promising plant sources for alternative compounds to pyrethroids, for the control of the Anopheles malaria vector in Benin. The efficacy of their essential oils is possibly based on their chemical compositions in which major and/or minor compounds have reported insecticidal activities on various pests and disease vectors such as Anopheles. PMID:24298981

Manipulation of group-velocity-locked vector dissipative solitons and properties of the generated high-order vector soliton structure.

PubMed

Zhu, S N; Wu, Z C; Fu, S N; Zhao, L M

2018-03-20

Details of various composites of the projections originated from a fundamental group-velocity-locked vector dissipative soliton (GVLVDS) are both experimentally and numerically explored. By combining the projections from the orthogonal polarization components of the GVLVDS, a high-order vector soliton structure with a double-humped pulse profile along one polarization and a single-humped pulse profile along the orthogonal polarization can be observed. Moreover, by de-chirping the composite double-humped pulse, the time separation between the two humps is reduced from 15.36 ps to 1.28 ps, indicating that the frequency chirp of the GVLVDS contributes significantly to the shaping of the double-humped pulse profile.

Feature-space-based FMRI analysis using the optimal linear transformation.

PubMed

Sun, Fengrong; Morris, Drew; Lee, Wayne; Taylor, Margot J; Mills, Travis; Babyn, Paul S

2010-09-01

The optimal linear transformation (OLT), an image analysis technique of feature space, was first presented in the field of MRI. This paper proposes a method of extending OLT from MRI to functional MRI (fMRI) to improve the activation-detection performance over conventional approaches of fMRI analysis. In this method, first, ideal hemodynamic response time series for different stimuli were generated by convolving the theoretical hemodynamic response model with the stimulus timing. Second, constructing hypothetical signature vectors for different activity patterns of interest by virtue of the ideal hemodynamic responses, OLT was used to extract features of fMRI data. The resultant feature space had particular geometric clustering properties. It was then classified into different groups, each pertaining to an activity pattern of interest; the applied signature vector for each group was obtained by averaging. Third, using the applied signature vectors, OLT was applied again to generate fMRI composite images with high SNRs for the desired activity patterns. Simulations and a blocked fMRI experiment were employed for the method to be verified and compared with the general linear model (GLM)-based analysis. The simulation studies and the experimental results indicated the superiority of the proposed method over the GLM-based analysis in detecting brain activities.

Regulating nutrient allocation in plants

DOEpatents

Udvardi, Michael; Yang, Jiading; Worley, Eric

2014-12-09

The invention provides coding and promoter sequences for a VS-1 and AP-2 gene, which affects the developmental process of senescence in plants. Vectors, transgenic plants, seeds, and host cells comprising heterologous VS-1 and AP-2 genes are also provided. Additionally provided are methods of altering nutrient allocation and composition in a plant using the VS-1 and AP-2 genes.

Use of CYP52A2A promoter to increase gene expression in yeast

DOEpatents

Craft, David L.; Wilson, C. Ron; Eirich, Dudley; Zhang, Yeyan

2004-01-06

A nucleic acid sequence including a CYP promoter operably linked to nucleic acid encoding a heterologous protein is provided to increase transcription of the nucleic acid. Expression vectors and host cells containing the nucleic acid sequence are also provided. The methods and compositions described herein are especially useful in the production of polycarboxylic acids by yeast cells.

Visualization of Microbiota in Tick Guts by Whole-mount In Situ Hybridization.

PubMed

Moss, Caitlin E; Robson, Andrew; Fikrig, Erol; Narasimhan, Sukanya

2018-06-01

Infectious diseases transmitted by arthropod vectors continue to pose a significant threat to human health worldwide. The pathogens causing these diseases, do not exist in isolation when they colonize the vector; rather, they likely engage in interactions with resident microorganisms in the gut lumen. The vector microbiota has been demonstrated to play an important role in pathogen transmission for several vector-borne diseases. Whether resident bacteria in the gut of the Ixodes scapularis tick, the vector of several human pathogens including Borrelia burgdorferi, influence tick transmission of pathogens is not determined. We require methods for characterizing the composition of the bacteria associated with the tick gut to facilitate a better understanding of potential interspecies interactions in the tick gut. Using whole-mount in situ hybridization to visualize RNA transcripts associated with particular bacterial species allows for the collection of qualitative data regarding the abundance and distribution of the microbiota in intact tissue. This technique can be used to examine changes in the gut microbiota milieu over the course of tick feeding and can also be applied to analyze expression of tick genes. Staining of whole tick guts yield information about the gross spatial distribution of target RNA in the tissue without the need for three-dimensional reconstruction and is less affected by environmental contamination, which often confounds the sequencing-based methods frequently used to study complex microbial communities. Overall, this technique is a valuable tool that can be used to better understand vector-pathogen-microbiota interactions and their role in disease transmission.

A 2D Daubechies finite wavelet domain method for transient wave response analysis in shear deformable laminated composite plates

NASA Astrophysics Data System (ADS)

Nastos, C. V.; Theodosiou, T. C.; Rekatsinas, C. S.; Saravanos, D. A.

2018-03-01

An efficient numerical method is developed for the simulation of dynamic response and the prediction of the wave propagation in composite plate structures. The method is termed finite wavelet domain method and takes advantage of the outstanding properties of compactly supported 2D Daubechies wavelet scaling functions for the spatial interpolation of displacements in a finite domain of a plate structure. The development of the 2D wavelet element, based on the first order shear deformation laminated plate theory is described and equivalent stiffness, mass matrices and force vectors are calculated and synthesized in the wavelet domain. The transient response is predicted using the explicit central difference time integration scheme. Numerical results for the simulation of wave propagation in isotropic, quasi-isotropic and cross-ply laminated plates are presented and demonstrate the high spatial convergence and problem size reduction obtained by the present method.

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

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

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

Path analyses of cross-sectional and longitudinal data suggest that variability in natural communities of blood-associated parasites is derived from host characteristics and not interspecific interactions.

PubMed

Cohen, Carmit; Einav, Monica; Hawlena, Hadas

2015-08-19

The parasite composition of wild host individuals often impacts their behavior and physiology, and the transmission dynamics of pathogenic species thereby determines disease risk in natural communities. Yet, the determinants of parasite composition in natural communities are still obscure. In particular, three fundamental questions remain open: (1) what are the relative roles of host and environmental characteristics compared with direct interactions between parasites in determining the community composition of parasites? (2) do these determinants affect parasites belonging to the same guild and those belonging to different guilds in similar manners? and (3) can cross-sectional and longitudinal analyses work interchangeably in detecting community determinants? Our study was designed to answer these three questions in a natural community of rodents and their fleas, ticks, and two vector-borne bacteria. We sampled a natural population of Gerbillus andersoni rodents and their blood-associated parasites on two occasions. By combining path analysis and model selection approaches, we then explored multiple direct and indirect paths that connect (i) the environmental and host-related characteristics to the infection probability of a host by each of the four parasite species, and (ii) the infection probabilities of the four species by each other. Our results suggest that the majority of paths shaping the blood-associated communities are indirect, mostly determined by host characteristics and not by interspecific interactions or environmental conditions. The exact effects of host characteristics on infection probability by a given parasite depend on its life history and on the method of sampling, in which the cross-sectional and longitudinal methods are complementary. Despite the awareness of the need of ecological investigations into natural host-vector-parasite communities in light of the emergence and re-emergence of vector-borne diseases, we lack sampling methods that are both practical and reliable. Here we illustrated how comprehensive patterns can be revealed from observational data by applying path analysis and model selection approaches and combining cross-sectional and longitudinal analyses. By employing this combined approach on blood-associated parasites, we were able to distinguish between direct and indirect effects and to predict the causal relationships between host-related characteristics and the parasite composition over time and space. We concluded that direct interactions within the community play only a minor role in determining community composition relative to host characteristics and the life history of the community members.

Thin-layer chromatographic identification of Chinese propolis using chemometric fingerprinting.

PubMed

Tang, Tie-xin; Guo, Wei-yan; Xu, Ye; Zhang, Si-ming; Xu, Xin-jun; Wang, Dong-mei; Zhao, Zhi-min; Zhu, Long-ping; Yang, De-po

2014-01-01

Poplar tree gum has a similar chemical composition and appearance to Chinese propolis (bee glue) and has been widely used as a counterfeit propolis because Chinese propolis is typically the poplar-type propolis, the chemical composition of which is determined mainly by the resin of poplar trees. The discrimination of Chinese propolis from poplar tree gum is a challenging task. To develop a rapid thin-layer chromatographic (TLC) identification method using chemometric fingerprinting to discriminate Chinese propolis from poplar tree gum. A new TLC method using a combination of ammonia and hydrogen peroxide vapours as the visualisation reagent was developed to characterise the chemical profile of Chinese propolis. Three separate people performed TLC on eight Chinese propolis samples and three poplar tree gum samples of varying origins. Five chemometric methods, including similarity analysis, hierarchical clustering, k-means clustering, neural network and support vector machine, were compared for use in classifying the samples based on their densitograms obtained from the TLC chromatograms via image analysis. Hierarchical clustering, neural network and support vector machine analyses achieved a correct classification rate of 100% in classifying the samples. A strategy for TLC identification of Chinese propolis using chemometric fingerprinting was proposed and it provided accurate sample classification. The study has shown that the TLC identification method using chemometric fingerprinting is a rapid, low-cost method for the discrimination of Chinese propolis from poplar tree gum and may be used for the quality control of Chinese propolis. Copyright © 2014 John Wiley & Sons, Ltd.

Elements of the quality management in the materials' industry

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

StruLocPred: structure-based protein subcellular localisation prediction using multi-class support vector machine.

PubMed

Zhou, Wengang; Dickerson, Julie A

2012-01-01

Knowledge of protein subcellular locations can help decipher a protein's biological function. This work proposes new features: sequence-based: Hybrid Amino Acid Pair (HAAP) and two structure-based: Secondary Structural Element Composition (SSEC) and solvent accessibility state frequency. A multi-class Support Vector Machine is developed to predict the locations. Testing on two established data sets yields better prediction accuracies than the best available systems. Comparisons with existing methods show comparable results to ESLPred2. When StruLocPred is applied to the entire Arabidopsis proteome, over 77% of proteins with known locations match the prediction results. An implementation of this system is at http://wgzhou.ece. iastate.edu/StruLocPred/.

Asymptotic stability and instability of large-scale systems. [using vector Liapunov functions

NASA Technical Reports Server (NTRS)

Grujic, L. T.; Siljak, D. D.

1973-01-01

The purpose of this paper is to develop new methods for constructing vector Lyapunov functions and broaden the application of Lyapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. By redefining interconnection functions among the subsystems according to interconnection matrices, the same mathematical machinery can be used to determine connective asymptotic stability of large-scale systems under arbitrary structural perturbations.

Thyra Abstract Interface Package

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

Bartlett, Roscoe A.

2005-09-01

Thrya primarily defines a set of abstract C++ class interfaces needed for the development of abstract numerical atgorithms (ANAs) such as iterative linear solvers, transient solvers all the way up to optimization. At the foundation of these interfaces are abstract C++ classes for vectors, vector spaces, linear operators and multi-vectors. Also included in the Thyra package is C++ code for creating concrete vector, vector space, linear operator, and multi-vector subclasses as well as other utilities to aid in the development of ANAs. Currently, very general and efficient concrete subclass implementations exist for serial and SPMD in-core vectors and multi-vectors. Codemore » also currently exists for testing objects and providing composite objects such as product vectors.« less

Reflection and Transmission Coefficient of Yttrium Iron Garnet Filled Polyvinylidene Fluoride Composite Using Rectangular Waveguide at Microwave Frequencies

PubMed Central

Soleimani, Hassan; Abbas, Zulkifly; Yahya, Noorhana; Shameli, Kamyar; Soleimani, Hojjatollah; Shabanzadeh, Parvaneh

2012-01-01

The sol-gel method was carried out to synthesize nanosized Yttrium Iron Garnet (YIG). The nanomaterials with ferrite structure were heat-treated at different temperatures from 500 to 1000 °C. The phase identification, morphology and functional groups of the prepared samples were characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR), respectively. The YIG ferrite nanopowder was composited with polyvinylidene fluoride (PVDF) by a solution casting method. The magnitudes of reflection and transmission coefficients of PVDF/YIG containing 6, 10 and 13% YIG, respectively, were measured using rectangular waveguide in conjunction with a microwave vector network analyzer (VNA) in X-band frequencies. The results indicate that the presence of YIG in polymer composites causes an increase in reflection coefficient and decrease in transmission coefficient of the polymer. PMID:22942718

Compositions and methods for xylem-specific expression in plant cells

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

Han, Kyung-Hwan; Ko, Jae-Heung

The invention provides promoter sequences that regulate specific expression of operably linked sequences in developing xylem cells and/or in developing xylem tissue. The developing xylem-specific sequences are exemplified by the DX5, DX8, DX11, and DX15 promoters, portions thereof, and homologs thereof. The invention further provides expression vectors, cells, tissues and plants that contain the invention's sequences. The compositions of the invention and methods of using them are useful in, for example, improving the quantity (biomass) and/or the quality (wood density, lignin content, sugar content etc.) of expressed biomass feedstock products that may be used for bioenergy, biorefinary, and generating woodmore » products such as pulp, paper, and solid wood.« less

A stochastic global identification framework for aerospace structures operating under varying flight states

NASA Astrophysics Data System (ADS)

Kopsaftopoulos, Fotis; Nardari, Raphael; Li, Yu-Hung; Chang, Fu-Kuo

2018-01-01

In this work, a novel data-based stochastic "global" identification framework is introduced for aerospace structures operating under varying flight states and uncertainty. In this context, the term "global" refers to the identification of a model that is capable of representing the structure under any admissible flight state based on data recorded from a sample of these states. The proposed framework is based on stochastic time-series models for representing the structural dynamics and aeroelastic response under multiple flight states, with each state characterized by several variables, such as the airspeed, angle of attack, altitude and temperature, forming a flight state vector. The method's cornerstone lies in the new class of Vector-dependent Functionally Pooled (VFP) models which allow the explicit analytical inclusion of the flight state vector into the model parameters and, hence, system dynamics. This is achieved via the use of functional data pooling techniques for optimally treating - as a single entity - the data records corresponding to the various flight states. In this proof-of-concept study the flight state vector is defined by two variables, namely the airspeed and angle of attack of the vehicle. The experimental evaluation and assessment is based on a prototype bio-inspired self-sensing composite wing that is subjected to a series of wind tunnel experiments under multiple flight states. Distributed micro-sensors in the form of stretchable sensor networks are embedded in the composite layup of the wing in order to provide the sensing capabilities. Experimental data collected from piezoelectric sensors are employed for the identification of a stochastic global VFP model via appropriate parameter estimation and model structure selection methods. The estimated VFP model parameters constitute two-dimensional functions of the flight state vector defined by the airspeed and angle of attack. The identified model is able to successfully represent the wing's aeroelastic response under the admissible flight states via a minimum number of estimated parameters compared to standard identification approaches. The obtained results demonstrate the high accuracy and effectiveness of the proposed global identification framework, thus constituting a first step towards the next generation of "fly-by-feel" aerospace vehicles with state awareness capabilities.

Exo-endo cellulase fusion protein

DOEpatents

Bower, Benjamin S [Palo Alto, CA; Larenas, Edmund A [Palo Alto, CA; Mitchinson, Colin [Palo Alto, CA

2012-01-17

The present invention relates to a heterologous exo-endo cellulase fusion construct, which encodes a fusion protein having cellulolytic activity comprising a catalytic domain derived from a fungal exo-cellobiohydrolase and a catalytic domain derived from an endoglucanase. The invention also relates to vectors and fungal host cells comprising the heterologous exo-endo cellulase fusion construct as well as methods for producing a cellulase fusion protein and enzymatic cellulase compositions.

Land use change and human health

NASA Astrophysics Data System (ADS)

Patz, Jonathan A.; Norris, Douglas E.

Disease emergence events have been documented following several types of land use change. This chapter reviews several health-relevant land use changes recognized today, including: 1) urbanization and urban sprawl; 2) water projects and agricultural development; 3) road construction and deforestation in the tropics; and 4) regeneration of temperate forests. Because habitat or climatic change substantially affects intermediate invertebrate hosts involved in many prevalent diseases, this chapter provides a basic description of vector-borne disease biology as a foundation for analyzing the effects of land use change. Urban sprawl poses health challenges stemming from heat waves exacerbated by the "urban heat island" effect, as well as from water contamination due to expanses of impervious road and concrete surfaces. Dams, irrigation and agricultural development have long been associated with diseases such as schistosomiasis and filariasis. Better management methods are required to address the trade-offs between expanded food production and altered habitats promoting deadly diseases. Deforestation can increase the nature and number of breeding sites for vector-borne diseases, such as malaria and onchocerciasis. Human host and disease vector interaction further increases risk, as can a change in arthropod-vector species composition.

Low-Angle Radar Tracking

DTIC Science & Technology

1976-02-01

Transition from Specular Reflection to Diffuse Scattering. . . 10 Composition of the Electric-Field Vector as Seen at the Radar...r t (16) R • FIGURE P COMPOSITION OF THE ELECTRIC-FIELD VECTOR AS SEEN AT THE RADAR, R, IN FIG. 2. The electric field at the radar, E, is the sum...wavelengths in the VHP and UHF ranges even subsurface characteristics can be important. So in a field experiment one must be careful to measure

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

PubMed

Zou, Lingyun; Wang, Zhengzhi; Huang, Jiaomin

2007-12-01

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

Pupicidal and repellent activities of Pogostemon cablin essential oil chemical compounds against medically important human vector mosquitoes

PubMed Central

Gokulakrishnan, J; Kuppusamy, Elumalai; Shanmugam, Dhanasekaran; Appavu, Anandan; Kaliyamoorthi, Krishnappa

2013-01-01

Objective To determine the repellent and pupicidal activities of Pogostemon cablin (P. cablin) chemical compositions were assayed for their toxicity against selected important vector mosquitoes, viz., Aedes aegypti (Ae. aegypti), Anopheles stephensi (An. stephensi) and Culex quinquefasciatus (Cx. quinquefasciatus) (Diptera: Culicidae). Methods The plants dry aerial parts were subjected to hydrodistillation using a modified Clevenger-type apparatus. The composition of the essential oil was analyzed by Gas Chromatography (GC) and GC mass spectrophotometry. Evaluation was carried out in a net cage (45 cm×30 cm×45 cm) containing 100 blood starved female mosquitoes and were assayed in the laboratory condition by using the protocol of WHO 2010. The repellent activity of P. cablin chemical compositions at concentration of 2mg/cm2were applied on skin of fore arm in man and exposed against adult female mosquitoes. The pupicidal activity was determined against selected important vector mosquitoes to concentration of 100 mg/L and mortality of each pupa was recorded after 24 h of exposure to the compounds. Results Chemical constituents of 15 compounds were identified in the oil of P.cablin compounds representing to 98.96%. The major components in essential oil were â-patchoulene, á-guaiene, ã-patchoulene, á-bulnesene and patchouli alcohol. The repellent activity of patchouli alcohol compound was found to be most effective for repellent activity and 2 mg/cm2 concentration provided 100% protection up to 280 min against Ae. aegypti, An. stephensi and Cx. quinquefasciatus, respectively. Similarly, pupae exposed to 100 mg/L concentrations of P. cablin chemical compositions. Among five compounds tested patchouli alcoholwas found to be most effective for pupicidal activity provided 28.44, 26.28 and 25.36 against Ae.aegypti, An.stephensi and Cx. quinquefasciatus, respectively. The percent adult emergence was inversely proportional to the concentration of compounds and directly proportional to the pupal mortality. Conclusion These results suggest that the P. cablin chemical compositions have the potential to be used as an ideal eco-friendly approach for the control of mosquitoes. This is the first report on the mosquito repellent and pupicidal activities of the reported P. cablin chemical compositions.

Strongly nonlinear composite dielectrics: A perturbation method for finding the potential field and bulk effective properties

NASA Astrophysics Data System (ADS)

Blumenfeld, Raphael; Bergman, David J.

1991-10-01

A class of strongly nonlinear composite dielectrics is studied. We develop a general method to reduce the scalar-potential-field problem to the solution of a set of linear Poisson-type equations in rescaled coordinates. The method is applicable for a large variety of nonlinear materials. For a power-law relation between the displacement and the electric fields, it is used to solve explicitly for the value of the bulk effective dielectric constant ɛe to second order in the fluctuations of its local value. A simlar procedure for the vector potential, whose curl is the displacement field, yields a quantity analogous to the inverse dielectric constant in linear dielectrics. The bulk effective dielectric constant is given by a set of linear integral expressions in the rescaled coordinates and exact bounds for it are derived.

Structural vibration-based damage classification of delaminated smart composite laminates

NASA Astrophysics Data System (ADS)

Khan, Asif; Kim, Heung Soo; Sohn, Jung Woo

2018-03-01

Separation along the interfaces of layers (delamination) is a principal mode of failure in laminated composites and its detection is of prime importance for structural integrity of composite materials. In this work, structural vibration response is employed to detect and classify delaminations in piezo-bonded laminated composites. Improved layerwise theory and finite element method are adopted to develop the electromechanically coupled governing equation of a smart composite laminate with and without delaminations. Transient responses of the healthy and damaged structures are obtained through a surface bonded piezoelectric sensor by solving the governing equation in the time domain. Wavelet packet transform (WPT) and linear discriminant analysis (LDA) are employed to extract discriminative features from the structural vibration response of the healthy and delaminated structures. Dendrogram-based support vector machine (DSVM) is used to classify the discriminative features. The confusion matrix of the classification algorithm provided physically consistent results.

Impact damage imaging in a curved composite panel with wavenumber index via Riesz transform

NASA Astrophysics Data System (ADS)

Chang, Huan-Yu; Yuan, Fuh-Gwo

2018-03-01

The barely visible impact damages reduce the strength of composite structures significantly; however, they are difficult to be detected during regular visual inspection. A guided wave based damage imaging condition method is developed and applied on a curved composite panel, which is a part of an aileron from a retired Boeing C-17 Globemaster III. Ultrasonic guided waves are excited by a piezoelectric transducer (PZT) and then captured by a laser Doppler vibrometer (LDV). The wavefield images are constructed by measuring the out-of-plane velocity point by point within interrogation region, and the anomalies at the damage area can be observed with naked eye. The discontinuities of material properties leads to the change of wavenumber while the wave propagating through the damaged area. These differences in wavenumber can be observed by deriving instantaneous wave vector via Riesz transform (RT), and then be shown and highlighted with the proposed imaging condition named wavenumber index (WI). RT can be introduced as a two-dimensional (2-D) generalization of Hilbert transform (HT) to derive instantaneous phases, amplitudes, orientations of a guided-wave field. WI employs the instantaneous wave vector and weighted instantaneous wave energy computed from the instantaneous amplitudes, yielding high sensitivity and sharp damage image with computational efficiency. The BVID of the composite structure becomes therefore "visible" with the developed technique.

The effect of BaM/PANI composition with epoxy paint matrix on single and double layers coating with spray coating method for radar absorbing materials applications

NASA Astrophysics Data System (ADS)

Widyastuti, Fajarin, Rindang; Pratiwi, Vania Mitha; Kholid, Rifki Rachman; Habib, Abdulloh

2018-04-01

In this study, RAM composite has been succesfully synthesized by mixing BaM as magnetic materials and PANI as conductive materials. BaM and PANI materials were prepared separately by solid state method and polymerization method, respectively. To investigated the presence of BaM phase and magnetic property of the as prepared BaM, XRD pert PAN analytical and VSM 250 Dexing Magnet were employed. Inductance Capacitance Resistance technique was carried out to measure electrical conductivity of the synthesized PANI materials. In order to further characterized the structural features of BaM and PANI, SEM-EDX FEI 850 and FTIR characterizations were conducted. RAM composite was prepared by mixing BaM and PANI powders with ultrasonic cleaner. Afterwards, VNA (Vector Network Analyzer) characterization was carried out to determine reflection loss value of RAM by applying mixed RAM composite and epoxy paint on aluminum plate using spray gun. Microscopic characterization was employed to investigated the distribution of RAM particles on the substrate. It was found that reflection loss value as low as -27.153 dB was achieved when applied 15 wt% BaM/PANi composite at 100.6 µm thickness. In addition, the absorption of electromagnetic waves value increase as the addition of RAM composite composition increases.

Shifts in malaria vector species composition and transmission dynamics along the Kenyan coast over the past 20 years.

PubMed

Mwangangi, Joseph M; Mbogo, Charles M; Orindi, Benedict O; Muturi, Ephantus J; Midega, Janet T; Nzovu, Joseph; Gatakaa, Hellen; Githure, John; Borgemeister, Christian; Keating, Joseph; Beier, John C

2013-01-08

Over the past 20 years, numerous studies have investigated the ecology and behaviour of malaria vectors and Plasmodium falciparum malaria transmission on the coast of Kenya. Substantial progress has been made to control vector populations and reduce high malaria prevalence and severe disease. The goal of this paper was to examine trends over the past 20 years in Anopheles species composition, density, blood-feeding behaviour, and P. falciparum sporozoite transmission along the coast of Kenya. Using data collected from 1990 to 2010, vector density, species composition, blood-feeding patterns, and malaria transmission intensity was examined along the Kenyan coast. Mosquitoes were identified to species, based on morphological characteristics and DNA extracted from Anopheles gambiae for amplification. Using negative binomial generalized estimating equations, mosquito abundance over the period were modelled while adjusting for season. A multiple logistic regression model was used to analyse the sporozoite rates. Results show that in some areas along the Kenyan coast, Anopheles arabiensis and Anopheles merus have replaced An. gambiae sensu stricto (s.s.) and Anopheles funestus as the major mosquito species. Further, there has been a shift from human to animal feeding for both An. gambiae sensu lato (s.l.) (99% to 16%) and An. funestus (100% to 3%), and P. falciparum sporozoite rates have significantly declined over the last 20 years, with the lowest sporozoite rates being observed in 2007 (0.19%) and 2008 (0.34%). There has been, on average, a significant reduction in the abundance of An. gambiae s.l. over the years (IRR = 0.94, 95% CI 0.90-0.98), with the density standing at low levels of an average 0.006 mosquitoes/house in the year 2010. Reductions in the densities of the major malaria vectors and a shift from human to animal feeding have contributed to the decreased burden of malaria along the Kenyan coast. Vector species composition remains heterogeneous but in many areas An. arabiensis has replaced An. gambiae as the major malaria vector. This has important implications for malaria epidemiology and control given that this vector predominately rests and feeds on humans outdoors. Strategies for vector control need to continue focusing on tools for protecting residents inside houses but additionally employ outdoor control tools because these are essential for further reducing the levels of malaria transmission.

Identification of DNA-binding proteins by combining auto-cross covariance transformation and ensemble learning.

PubMed

Liu, Bin; Wang, Shanyi; Dong, Qiwen; Li, Shumin; Liu, Xuan

2016-04-20

DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. With the rapid development of next generation of sequencing technique, the number of protein sequences is unprecedentedly increasing. Thus it is necessary to develop computational methods to identify the DNA-binding proteins only based on the protein sequence information. In this study, a novel method called iDNA-KACC is presented, which combines the Support Vector Machine (SVM) and the auto-cross covariance transformation. The protein sequences are first converted into profile-based protein representation, and then converted into a series of fixed-length vectors by the auto-cross covariance transformation with Kmer composition. The sequence order effect can be effectively captured by this scheme. These vectors are then fed into Support Vector Machine (SVM) to discriminate the DNA-binding proteins from the non DNA-binding ones. iDNA-KACC achieves an overall accuracy of 75.16% and Matthew correlation coefficient of 0.5 by a rigorous jackknife test. Its performance is further improved by employing an ensemble learning approach, and the improved predictor is called iDNA-KACC-EL. Experimental results on an independent dataset shows that iDNA-KACC-EL outperforms all the other state-of-the-art predictors, indicating that it would be a useful computational tool for DNA binding protein identification. .

Transformation of Rhodococcus fascians by High-Voltage Electroporation and Development of R. fascians Cloning Vectors

PubMed Central

Desomer, Jan; Dhaese, Patrick; Montagu, Marc Van

1990-01-01

The analysis of the virulence determinants of phytopathogenic Rhodococcus fascians has been hampered by the lack of a system for introducing exogenous DNA. We investigated the possibility of genetic transformation of R. fascians by high-voltage electroporation of intact bacterial cells in the presence of plasmid DNA. Electrotransformation in R. fascians D188 resulted in transformation frequencies ranging from 105/μg of DNA to 107/μg of DNA, depending on the DNA concentration. The effects of different electrical parameters and composition of electroporation medium on transformation efficiency are presented. By this transformation method, a cloning vector (pRF28) for R. fascians based on an indigenous 160-kilobase (chloramphenicol and cadmium resistance-encoding) plasmid pRF2 from strain NCPPB 1675 was developed. The origin of replication and the chloramphenicol resistance gene on pRF28 were used to construct cloning vectors that are capable of replication in R. fascians and Escherichia coli. The electroporation method presented was efficient enough to allow detection of the rare integration of replication-deficient pRF28 derivatives in the R. fascians D188 genome via either homologous or illegitimate recombination. Images PMID:16348290

Support vector machine prediction of enzyme function with conjoint triad feature and hierarchical context.

PubMed

Wang, Yong-Cui; Wang, Yong; Yang, Zhi-Xia; Deng, Nai-Yang

2011-06-20

Enzymes are known as the largest class of proteins and their functions are usually annotated by the Enzyme Commission (EC), which uses a hierarchy structure, i.e., four numbers separated by periods, to classify the function of enzymes. Automatically categorizing enzyme into the EC hierarchy is crucial to understand its specific molecular mechanism. In this paper, we introduce two key improvements in predicting enzyme function within the machine learning framework. One is to introduce the efficient sequence encoding methods for representing given proteins. The second one is to develop a structure-based prediction method with low computational complexity. In particular, we propose to use the conjoint triad feature (CTF) to represent the given protein sequences by considering not only the composition of amino acids but also the neighbor relationships in the sequence. Then we develop a support vector machine (SVM)-based method, named as SVMHL (SVM for hierarchy labels), to output enzyme function by fully considering the hierarchical structure of EC. The experimental results show that our SVMHL with the CTF outperforms SVMHL with the amino acid composition (AAC) feature both in predictive accuracy and Matthew's correlation coefficient (MCC). In addition, SVMHL with the CTF obtains the accuracy and MCC ranging from 81% to 98% and 0.82 to 0.98 when predicting the first three EC digits on a low-homologous enzyme dataset. We further demonstrate that our method outperforms the methods which do not take account of hierarchical relationship among enzyme categories and alternative methods which incorporate prior knowledge about inter-class relationships. Our structure-based prediction model, SVMHL with the CTF, reduces the computational complexity and outperforms the alternative approaches in enzyme function prediction. Therefore our new method will be a useful tool for enzyme function prediction community.

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

PubMed

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

2011-12-01

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

Synthesis, characterization and microwave characteristics of ATP/BaFe12O19/PANI ternary composites

NASA Astrophysics Data System (ADS)

Bai, Dezhong; Feng, Huixia; Chen, Nali; Tan, Lin; Qiu, Jianhui

2018-07-01

In this paper, we introduced attapulgite (ATP) into the system of ferrite composites for the first time. By sol-gel self-propagating combustion method, attapulgite/barium ferrite (ATP/BaFe12O19) was prepared, and then ternary composites of attapulgite/barium ferrite/polyaniline (ATP/BaFe12O19/PANI) were obtained by in-situ oxidative polymerization of aniline on ATP/BaFe12O19 mixture. The phase composition, morphology and electromagnetic properties of the as-prepared composites were characterized by X-ray diffraction (XRD), Transmission election microscope (TEM), Fourier transform infrared (FTIR), vibrating sample magnetometer (VSM) and vector network analyzer (VNA). We found that the ATP/BaFe12O19/PANI composites at a thickness of 2 mm have the minimum reflection loss of -11.89 dB at 11.28 GHz, besides the effective absorption bandwidth (less than -5 dB) reached 6.39 GHz (from 8.42 GHz to 14.81 GHz).

Microwave absorbing property of silicone rubber composites with added carbonyl iron particles and graphite platelet

NASA Astrophysics Data System (ADS)

Xu, Yonggang; Zhang, Deyuan; Cai, Jun; Yuan, Liming; Zhang, Wenqiang

2013-02-01

Silicone rubber composites filled with carbonyl iron particles (CIPs) and graphite platelet (GP) were prepared using non-coating or coating processes. The complex permittivity and permeability of the composites were measured using a vector network analyzer in the frequency range of 1-18 GHz and dc electric conductivity was measured by the standard four-point contact method. The results showed that CIPs/GP composites fabricated in the coating process had the highest permittivity and permeability due to the particle orientation and interactions between the two absorbents. The coating process resulted in a decreased effective eccentricity of the absorbents, and the dc conductivity increased according to Neelakanta's equations. The reflection loss (RL) value showed that the composites had an excellent absorbing property in the L-band, minimum -11.85 dB at 1.5 mm and -15.02 dB at 2 mm. Thus, GP could be an effective additive in preparing thin absorbing composites in the L-band.

Classification of protein quaternary structure by functional domain composition

PubMed Central

Yu, Xiaojing; Wang, Chuan; Li, Yixue

2006-01-01

Background The number and the arrangement of subunits that form a protein are referred to as quaternary structure. Quaternary structure is an important protein attribute that is closely related to its function. Proteins with quaternary structure are called oligomeric proteins. Oligomeric proteins are involved in various biological processes, such as metabolism, signal transduction, and chromosome replication. Thus, it is highly desirable to develop some computational methods to automatically classify the quaternary structure of proteins from their sequences. Results To explore this problem, we adopted an approach based on the functional domain composition of proteins. Every protein was represented by a vector calculated from the domains in the PFAM database. The nearest neighbor algorithm (NNA) was used for classifying the quaternary structure of proteins from this information. The jackknife cross-validation test was performed on the non-redundant protein dataset in which the sequence identity was less than 25%. The overall success rate obtained is 75.17%. Additionally, to demonstrate the effectiveness of this method, we predicted the proteins in an independent dataset and achieved an overall success rate of 84.11% Conclusion Compared with the amino acid composition method and Blast, the results indicate that the domain composition approach may be a more effective and promising high-throughput method in dealing with this complicated problem in bioinformatics. PMID:16584572

Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques.

PubMed

Alejo, Luz; Atkinson, John; Guzmán-Fierro, Víctor; Roeckel, Marlene

2018-05-16

Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. The analytical method considers the protein as the only source of ammonia production in AD after degradation. Total ammonia nitrogen (TAN), total solids (TS), chemical oxygen demand (COD), and total volatile solids (TVS) were measured in the influent and effluent of the process. The TAN concentration in the effluent was predicted, this being the most inhibiting and polluting compound in AD. Despite the limited data available, the SVM-based model outperformed the analytical method for the TAN prediction, achieving a relative average error of 15.2% against 43% for the analytical method. Moreover, SVM showed higher prediction accuracy in comparison with Artificial Neural Networks. This result reveals the future promise of SVM for prediction in non-linear and dynamic AD processes. Graphical abstract ᅟ.

Subatomic-scale force vector mapping above a Ge(001) dimer using bimodal atomic force microscopy

NASA Astrophysics Data System (ADS)

Naitoh, Yoshitaka; Turanský, Robert; Brndiar, Ján; Li, Yan Jun; Štich, Ivan; Sugawara, Yasuhiro

2017-07-01

Probing physical quantities on the nanoscale that have directionality, such as magnetic moments, electric dipoles, or the force response of a surface, is essential for characterizing functionalized materials for nanotechnological device applications. Currently, such physical quantities are usually experimentally obtained as scalars. To investigate the physical properties of a surface on the nanoscale in depth, these properties must be measured as vectors. Here we demonstrate a three-force-component detection method, based on multi-frequency atomic force microscopy on the subatomic scale and apply it to a Ge(001)-c(4 × 2) surface. We probed the surface-normal and surface-parallel force components above the surface and their direction-dependent anisotropy and expressed them as a three-dimensional force vector distribution. Access to the atomic-scale force distribution on the surface will enable better understanding of nanoscale surface morphologies, chemical composition and reactions, probing nanostructures via atomic or molecular manipulation, and provide insights into the behaviour of nano-machines on substrates.

Lanczos eigensolution method for high-performance computers

NASA Technical Reports Server (NTRS)

Bostic, Susan W.

1991-01-01

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

Damping mathematical modelling and dynamic responses for FRP laminated composite plates with polymer matrix

NASA Astrophysics Data System (ADS)

Liu, Qimao

2018-02-01

This paper proposes an assumption that the fibre is elastic material and polymer matrix is viscoelastic material so that the energy dissipation depends only on the polymer matrix in dynamic response process. The damping force vectors in frequency and time domains, of FRP (Fibre-Reinforced Polymer matrix) laminated composite plates, are derived based on this assumption. The governing equations of FRP laminated composite plates are formulated in both frequency and time domains. The direct inversion method and direct time integration method for nonviscously damped systems are employed to solve the governing equations and achieve the dynamic responses in frequency and time domains, respectively. The computational procedure is given in detail. Finally, dynamic responses (frequency responses with nonzero and zero initial conditions, free vibration, forced vibrations with nonzero and zero initial conditions) of a FRP laminated composite plate are computed using the proposed methodology. The proposed methodology in this paper is easy to be inserted into the commercial finite element analysis software. The proposed assumption, based on the theory of material mechanics, needs to be further proved by experiment technique in the future.

A support vector machine for spectral classification of emission-line galaxies from the Sloan Digital Sky Survey

NASA Astrophysics Data System (ADS)

Shi, Fei; Liu, Yu-Yan; Sun, Guang-Lan; Li, Pei-Yu; Lei, Yu-Ming; Wang, Jian

2015-10-01

The emission-lines of galaxies originate from massive young stars or supermassive blackholes. As a result, spectral classification of emission-line galaxies into star-forming galaxies, active galactic nucleus (AGN) hosts, or compositions of both relates closely to formation and evolution of galaxy. To find efficient and automatic spectral classification method, especially in large surveys and huge data bases, a support vector machine (SVM) supervised learning algorithm is applied to a sample of emission-line galaxies from the Sloan Digital Sky Survey (SDSS) data release 9 (DR9) provided by the Max Planck Institute and the Johns Hopkins University (MPA/JHU). A two-step approach is adopted. (i) The SVM must be trained with a subset of objects that are known to be AGN hosts, composites or star-forming galaxies, treating the strong emission-line flux measurements as input feature vectors in an n-dimensional space, where n is the number of strong emission-line flux ratios. (ii) After training on a sample of emission-line galaxies, the remaining galaxies are automatically classified. In the classification process, we use a 10-fold cross-validation technique. We show that the classification diagrams based on the [N II]/Hα versus other emission-line ratio, such as [O III]/Hβ, [Ne III]/[O II], ([O III]λ4959+[O III]λ5007)/[O III]λ4363, [O II]/Hβ, [Ar III]/[O III], [S II]/Hα, and [O I]/Hα, plus colour, allows us to separate unambiguously AGN hosts, composites or star-forming galaxies. Among them, the diagram of [N II]/Hα versus [O III]/Hβ achieved an accuracy of 99 per cent to separate the three classes of objects. The other diagrams above give an accuracy of ˜91 per cent.

Cell culture compositions

DOEpatents

Dunn-Coleman, Nigel; Goedegebuur, Frits; Ward, Michael; Yiao, Jian

2014-03-18

The present invention provides a novel endoglucanase nucleic acid sequence, designated egl6 (SEQ ID NO:1 encodes the full length endoglucanase; SEQ ID NO:4 encodes the mature form), and the corresponding endoglucanase VI amino acid sequence ("EGVI"; SEQ ID NO:3 is the signal sequence; SEQ ID NO:2 is the mature sequence). The invention also provides expression vectors and host cells comprising a nucleic acid sequence encoding EGVI, recombinant EGVI proteins and methods for producing the same.

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

PubMed

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

2016-01-01

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

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

PubMed

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

2018-02-03

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

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

PubMed Central

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

2018-01-01

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

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

PubMed Central

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

2017-01-01

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

Wavelet images and Chou's pseudo amino acid composition for protein classification.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2012-08-01

The last decade has seen an explosion in the collection of protein data. To actualize the potential offered by this wealth of data, it is important to develop machine systems capable of classifying and extracting features from proteins. Reliable machine systems for protein classification offer many benefits, including the promise of finding novel drugs and vaccines. In developing our system, we analyze and compare several feature extraction methods used in protein classification that are based on the calculation of texture descriptors starting from a wavelet representation of the protein. We then feed these texture-based representations of the protein into an Adaboost ensemble of neural network or a support vector machine classifier. In addition, we perform experiments that combine our feature extraction methods with a standard method that is based on the Chou's pseudo amino acid composition. Using several datasets, we show that our best approach outperforms standard methods. The Matlab code of the proposed protein descriptors is available at http://bias.csr.unibo.it/nanni/wave.rar .

Chemical composition, toxicity and non-target effects of Pinus kesiya essential oil: An eco-friendly and novel larvicide against malaria, dengue and lymphatic filariasis mosquito vectors.

PubMed

Govindarajan, Marimuthu; Rajeswary, Mohan; Benelli, Giovanni

2016-07-01

Mosquitoes (Diptera: Culicidae) are vectors of important parasites and pathogens causing death, poverty and social disability worldwide, with special reference to tropical and subtropical countries. The overuse of synthetic insecticides to control mosquito vectors lead to resistance, adverse environmental effects and high operational costs. Therefore, the development of eco-friendly control tools is an important public health challenge. In this study, the mosquito larvicidal activity of Pinus kesiya leaf essential oil (EO) was evaluated against the malaria vector Anopheles stephensi, the dengue vector Aedes aegypti and the lymphatic filariasis vector Culex quinquefasciatus. The chemical composition of the EO was analyzed by gas chromatography-mass spectroscopy. GC-MS revealed that the P. kesiya EO contained 18 compounds. Major constituents were α-pinene, β-pinene, myrcene and germacrene D. In acute toxicity assays, the EO showed significant toxicity against early third-stage larvae of An. stephensi, Ae. aegypti and Cx. quinquefasciatus, with LC50 values of 52, 57, and 62µg/ml, respectively. Notably, the EO was safer towards several aquatic non-target organisms Anisops bouvieri, Diplonychus indicus and Gambusia affinis, with LC50 values ranging from 4135 to 8390µg/ml. Overall, this research adds basic knowledge to develop newer and safer natural larvicides from Pinaceae plants against malaria, dengue and filariasis mosquito vectors. Copyright © 2016 Elsevier Inc. All rights reserved.

VIP Barcoding: composition vector-based software for rapid species identification based on DNA barcoding.

PubMed

Fan, Long; Hui, Jerome H L; Yu, Zu Guo; Chu, Ka Hou

2014-07-01

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/. © 2014 John Wiley & Sons Ltd.

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

Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile.

PubMed

Verma, Ruchi; Varshney, Grish C; Raghava, G P S

2010-06-01

The rate of human death due to malaria is increasing day-by-day. Thus the malaria causing parasite Plasmodium falciparum (PF) remains the cause of concern. With the wealth of data now available, it is imperative to understand protein localization in order to gain deeper insight into their functional roles. In this manuscript, an attempt has been made to develop prediction method for the localization of mitochondrial proteins. In this study, we describe a method for predicting mitochondrial proteins of malaria parasite using machine-learning technique. All models were trained and tested on 175 proteins (40 mitochondrial and 135 non-mitochondrial proteins) and evaluated using five-fold cross validation. We developed a Support Vector Machine (SVM) model for predicting mitochondrial proteins of P. falciparum, using amino acids and dipeptides composition and achieved maximum MCC 0.38 and 0.51, respectively. In this study, split amino acid composition (SAAC) is used where composition of N-termini, C-termini, and rest of protein is computed separately. The performance of SVM model improved significantly from MCC 0.38 to 0.73 when SAAC instead of simple amino acid composition was used as input. In addition, SVM model has been developed using composition of PSSM profile with MCC 0.75 and accuracy 91.38%. We achieved maximum MCC 0.81 with accuracy 92% using a hybrid model, which combines PSSM profile and SAAC. When evaluated on an independent dataset our method performs better than existing methods. A web server PFMpred has been developed for predicting mitochondrial proteins of malaria parasites ( http://www.imtech.res.in/raghava/pfmpred/).

Modelling malaria control by introduction of larvivorous fish.

PubMed

Lou, Yijun; Zhao, Xiao-Qiang

2011-10-01

Malaria creates serious health and economic problems which call for integrated management strategies to disrupt interactions among mosquitoes, the parasite and humans. In order to reduce the intensity of malaria transmission, malaria vector control may be implemented to protect individuals against infective mosquito bites. As a sustainable larval control method, the use of larvivorous fish is promoted in some circumstances. To evaluate the potential impacts of this biological control measure on malaria transmission, we propose and investigate a mathematical model describing the linked dynamics between the host-vector interaction and the predator-prey interaction. The model, which consists of five ordinary differential equations, is rigorously analysed via theories and methods of dynamical systems. We derive four biologically plausible and insightful quantities (reproduction numbers) that completely determine the community composition. Our results suggest that the introduction of larvivorous fish can, in principle, have important consequences for malaria dynamics, but also indicate that this would require strong predators on larval mosquitoes. Integrated strategies of malaria control are analysed to demonstrate the biological application of our developed theory.

Chagas disease vector blood meal sources identified by protein mass spectrometry

PubMed Central

Keller, Judith I.; Ballif, Bryan A.; St. Clair, Riley M.; Vincent, James J.; Monroy, M. Carlota

2017-01-01

Chagas disease is a complex vector borne parasitic disease involving blood feeding Triatominae (Hemiptera: Reduviidae) insects, also known as kissing bugs, and the vertebrates they feed on. This disease has tremendous impacts on millions of people and is a global health problem. The etiological agent of Chagas disease, Trypanosoma cruzi (Kinetoplastea: Trypanosomatida: Trypanosomatidae), is deposited on the mammalian host in the insect’s feces during a blood meal, and enters the host’s blood stream through mucous membranes or a break in the skin. Identifying the blood meal sources of triatomine vectors is critical in understanding Chagas disease transmission dynamics, can lead to identification of other vertebrates important in the transmission cycle, and aids management decisions. The latter is particularly important as there is little in the way of effective therapeutics for Chagas disease. Several techniques, mostly DNA-based, are available for blood meal identification. However, further methods are needed, particularly when sample conditions lead to low-quality DNA or to assess the risk of human cross-contamination. We demonstrate a proteomics-based approach, using liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify host-specific hemoglobin peptides for blood meal identification in mouse blood control samples and apply LC-MS/MS for the first time to Triatoma dimidiata insect vectors, tracing blood sources to species. In contrast to most proteins, hemoglobin, stabilized by iron, is incredibly stable even being preserved through geologic time. We compared blood stored with and without an anticoagulant and examined field-collected insect specimens stored in suboptimal conditions such as at room temperature for long periods of time. To our knowledge, this is the first study using LC-MS/MS on field-collected arthropod disease vectors to identify blood meal composition, and where blood meal identification was confirmed with more traditional DNA-based methods. We also demonstrate the potential of synthetic peptide standards to estimate relative amounts of hemoglobin acquired when insects feed on multiple blood sources. These LC-MS/MS methods can contribute to developing Ecohealth control strategies for Chagas disease transmission and can be applied to other arthropod disease vectors. PMID:29232402

An almost symmetric Strang splitting scheme for nonlinear evolution equations.

PubMed

Einkemmer, Lukas; Ostermann, Alexander

2014-07-01

In this paper we consider splitting methods for the time integration of parabolic and certain classes of hyperbolic partial differential equations, where one partial flow cannot be computed exactly. Instead, we use a numerical approximation based on the linearization of the vector field. This is of interest in applications as it allows us to apply splitting methods to a wider class of problems from the sciences. However, in the situation described, the classic Strang splitting scheme, while still being a method of second order, is not longer symmetric. This, in turn, implies that the construction of higher order methods by composition is limited to order three only. To remedy this situation, based on previous work in the context of ordinary differential equations, we construct a class of Strang splitting schemes that are symmetric up to a desired order. We show rigorously that, under suitable assumptions on the nonlinearity, these methods are of second order and can then be used to construct higher order methods by composition. In addition, we illustrate the theoretical results by conducting numerical experiments for the Brusselator system and the KdV equation.

An almost symmetric Strang splitting scheme for nonlinear evolution equations☆

PubMed Central

Einkemmer, Lukas; Ostermann, Alexander

2014-01-01

In this paper we consider splitting methods for the time integration of parabolic and certain classes of hyperbolic partial differential equations, where one partial flow cannot be computed exactly. Instead, we use a numerical approximation based on the linearization of the vector field. This is of interest in applications as it allows us to apply splitting methods to a wider class of problems from the sciences. However, in the situation described, the classic Strang splitting scheme, while still being a method of second order, is not longer symmetric. This, in turn, implies that the construction of higher order methods by composition is limited to order three only. To remedy this situation, based on previous work in the context of ordinary differential equations, we construct a class of Strang splitting schemes that are symmetric up to a desired order. We show rigorously that, under suitable assumptions on the nonlinearity, these methods are of second order and can then be used to construct higher order methods by composition. In addition, we illustrate the theoretical results by conducting numerical experiments for the Brusselator system and the KdV equation. PMID:25844017

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

Dengue in Java, Indonesia: Relevance of Mosquito Indices as Risk Predictors

PubMed Central

Wijayanti, Siwi P. M.; Sunaryo, Sunaryo; Suprihatin, Suprihatin; McFarlane, Melanie; Rainey, Stephanie M.; Dietrich, Isabelle; Schnettler, Esther; Biek, Roman; Kohl, Alain

2016-01-01

Background No vaccine is currently available for dengue virus (DENV), therefore control programmes usually focus on managing mosquito vector populations. Entomological surveys provide the most common means of characterising vector populations and predicting the risk of local dengue virus transmission. Despite Indonesia being a country strongly affected by DENV, only limited information is available on the local factors affecting DENV transmission and the suitability of available survey methods for assessing risk. Methodology/principal findings We conducted entomological surveys in the Banyumas Regency (Central Java) where dengue cases occur on an annual basis. Four villages were sampled during the dry and rainy seasons: two villages where dengue was endemic, one where dengue cases occurred sporadically and one which was dengue-free. In addition to data for conventional larvae indices, we collected data on pupae indices, and collected adult mosquitoes for species identification in order to determine mosquito species composition and population density. Traditionally used larval indices (House indices, Container indices and Breteau indices) were found to be inadequate as indicators for DENV transmission risk. In contrast, species composition of adult mosquitoes revealed that competent vector species were dominant in dengue endemic and sporadic villages. Conclusions/significance Our data suggested that the utility of traditional larvae indices, which continue to be used in many dengue endemic countries, should be re-evaluated locally. The results highlight the need for validation of risk indicators and control strategies across DENV affected areas here and perhaps elsewhere in SE Asia. PMID:26967524

Dengue in Java, Indonesia: Relevance of Mosquito Indices as Risk Predictors.

PubMed

Wijayanti, Siwi P M; Sunaryo, Sunaryo; Suprihatin, Suprihatin; McFarlane, Melanie; Rainey, Stephanie M; Dietrich, Isabelle; Schnettler, Esther; Biek, Roman; Kohl, Alain

2016-03-01

No vaccine is currently available for dengue virus (DENV), therefore control programmes usually focus on managing mosquito vector populations. Entomological surveys provide the most common means of characterising vector populations and predicting the risk of local dengue virus transmission. Despite Indonesia being a country strongly affected by DENV, only limited information is available on the local factors affecting DENV transmission and the suitability of available survey methods for assessing risk. We conducted entomological surveys in the Banyumas Regency (Central Java) where dengue cases occur on an annual basis. Four villages were sampled during the dry and rainy seasons: two villages where dengue was endemic, one where dengue cases occurred sporadically and one which was dengue-free. In addition to data for conventional larvae indices, we collected data on pupae indices, and collected adult mosquitoes for species identification in order to determine mosquito species composition and population density. Traditionally used larval indices (House indices, Container indices and Breteau indices) were found to be inadequate as indicators for DENV transmission risk. In contrast, species composition of adult mosquitoes revealed that competent vector species were dominant in dengue endemic and sporadic villages. Our data suggested that the utility of traditional larvae indices, which continue to be used in many dengue endemic countries, should be re-evaluated locally. The results highlight the need for validation of risk indicators and control strategies across DENV affected areas here and perhaps elsewhere in SE Asia.

Predict and Analyze Protein Glycation Sites with the mRMR and IFS Methods

PubMed Central

Gu, Wenxiang; Zhang, Wenyi; Wang, Jianan

2015-01-01

Glycation is a nonenzymatic process in which proteins react with reducing sugar molecules. The identification of glycation sites in protein may provide guidelines to understand the biological function of protein glycation. In this study, we developed a computational method to predict protein glycation sites by using the support vector machine classifier. The experimental results showed that the prediction accuracy was 85.51% and an overall MCC was 0.70. Feature analysis indicated that the composition of k-spaced amino acid pairs feature contributed the most for glycation sites prediction. PMID:25961025

Investigation of propagation dynamics of truncated vector vortex beams.

PubMed

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

2018-06-01

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

Effective genetic modification and differentiation of hMSCs upon controlled release of rAAV vectors using alginate/poloxamer composite systems.

PubMed

Díaz-Rodríguez, P; Rey-Rico, A; Madry, H; Landin, M; Cucchiarini, M

2015-12-30

Viral vectors are common tools in gene therapy to deliver foreign therapeutic sequences in a specific target population via their natural cellular entry mechanisms. Incorporating such vectors in implantable systems may provide strong alternatives to conventional gene transfer procedures. The goal of the present study was to generate different hydrogel structures based on alginate (AlgPH155) and poloxamer PF127 as new systems to encapsulate and release recombinant adeno-associated viral (rAAV) vectors. Inclusion of rAAV in such polymeric capsules revealed an influence of the hydrogel composition and crosslinking temperature upon the vector release profiles, with alginate (AlgPH155) structures showing the fastest release profiles early on while over time vector release was more effective from AlgPH155+PF127 [H] capsules crosslinked at a high temperature (50°C). Systems prepared at room temperature (AlgPH155+PF127 [C]) allowed instead to achieve a more controlled release profile. When tested for their ability to target human mesenchymal stem cells, the different systems led to high transduction efficiencies over time and to gene expression levels in the range of those achieved upon direct vector application, especially when using AlgPH155+PF127 [H]. No detrimental effects were reported on either cell viability or on the potential for chondrogenic differentiation. Inclusion of PF127 in the capsules was also capable of delaying undesirable hypertrophic cell differentiation. These findings are of promising value for the further development of viral vector controlled release strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting DNA binding proteins using support vector machine with hybrid fractal features.

PubMed

Niu, Xiao-Hui; Hu, Xue-Hai; Shi, Feng; Xia, Jing-Bo

2014-02-21

DNA-binding proteins play a vitally important role in many biological processes. Prediction of DNA-binding proteins from amino acid sequence is a significant but not fairly resolved scientific problem. Chaos game representation (CGR) investigates the patterns hidden in protein sequences, and visually reveals previously unknown structure. Fractal dimensions (FD) are good tools to measure sizes of complex, highly irregular geometric objects. In order to extract the intrinsic correlation with DNA-binding property from protein sequences, CGR algorithm, fractal dimension and amino acid composition are applied to formulate the numerical features of protein samples in this paper. Seven groups of features are extracted, which can be computed directly from the primary sequence, and each group is evaluated by the 10-fold cross-validation test and Jackknife test. Comparing the results of numerical experiments, the group of amino acid composition and fractal dimension (21-dimension vector) gets the best result, the average accuracy is 81.82% and average Matthew's correlation coefficient (MCC) is 0.6017. This resulting predictor is also compared with existing method DNA-Prot and shows better performances. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

Rainfall and Coconut Accession Explain the Composition and Abundance of the Community of Potential Auchenorrhyncha Phytoplasma Vectors in Brazil.

PubMed

Silva, Flaviana G; Passos, Eliana M; Diniz, Leandro E C; Farias, Adriano P; Teodoro, Adenir V; Fernandes, Marcelo F; Dollet, Michel

2018-04-05

Coconut plantations are attacked by the lethal yellowing (LY), which is spreading rapidly with extremely destructive effects in several countries. The disease is caused by phytoplasmas that occur in the plant phloem and are transmitted by Haplaxius crudus (Van Duzee) (Auchenorrhyncha: Cixiidae). Owing to their phloem-sap feeding habit, other planthopper species possibly act as vectors. Here, we aimed at assessing the seasonal variation in the Auchenorrhyncha community in six dwarf coconut accessions. Also, we assessed the relative contribution of biotic (coconut accession) and abiotic (rainfall, temperature) in explaining Auchenorrhyncha composition and abundance. The Auchenorrhyncha community was monthly evaluated for 1 yr using yellow sticky traps. Among the most abundant species, Oecleus sp., Balclutha sp., Deltocephalinae sp.2, Deltocephalinae sp.3, Cenchreini sp., Omolicna nigripennis Caldwell (Derbidae), and Cedusa sp. are potential phytoplasma vectors. The composition of the Auchenorrhyncha community differed between dwarf coconut accessions and periods, namely, in March and April (transition from dry to rainy season) and August (transition from rainy to dry season). In these months, Oecleus sp. was predominantly found in the accessions Cameroon Red Dwarf, Malayan Red Dwarf, and Brazilian Red Dwarf Gramame, while Cenchreini sp. and Bolbonota sp. were dominant in the accessions Brazilian Yellow Dwarf Gramame, Malayan Yellow Dwarf, and Brazilian Green Dwarf Jequi. We conclude that dwarf coconut host several Auchenorrhyncha species potential phytoplasma vectors. Furthermore, coconut accessions could be exploited in breeding programs aiming at prevention of LY. However, rainfall followed by accessions mostly explained the composition and abundance of the Auchenorrhyncha community.

Search for single production of a vector-like quark via a heavy gluon in the 4b final state with the ATLAS detector in pp collisions at s = 8   TeV

DOE PAGES

Aad, G.

2016-05-03

In this study, a search is performed for the process pp → G* → B Hmore » $$\\bar{b}$$/$$\\bar{B}$$ Hb → H$$b\\bar{b}$$→ $$b\\bar{b}b\\bar{b}$$, predicted in composite Higgs scenarios, where G* is a heavy colour octet vector resonance and BHBH a vector-like quark of charge –1/3. The data were obtained from pp collisions at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 19.5 fb –1, recorded by the ATLAS detector at the LHC. The largest background, multijet production, is estimated using a data-driven method. No significant excess of events with respect to Standard Model predictions is observed, and upper limits on the production cross section times branching ratio are set. Comparisons to the predictions from a specific benchmark model are made, resulting in lower mass limits in the two-dimensional mass plane of m G* vs. m BH.« less

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PubMed Central

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

PubMed

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

Co-occurrence Patterns of the Dengue Vector Aedes aegypti and Aedes mediovitattus, a Dengue Competent Mosquito in Puerto Rico

PubMed Central

Little, Eliza; Barrera, Roberto; Seto, Karen C.; Diuk-Wasser, Maria

2015-01-01

Aedes aegypti is implicated in dengue transmission in tropical and subtropical urban areas around the world. Ae. aegypti populations are controlled through integrative vector management. However, the efficacy of vector control may be undermined by the presence of alternative, competent species. In Puerto Rico, a native mosquito, Ae. mediovittatus, is a competent dengue vector in laboratory settings and spatially overlaps with Ae. aegypti. It has been proposed that Ae. mediovittatus may act as a dengue reservoir during inter-epidemic periods, perpetuating endemic dengue transmission in rural Puerto Rico. Dengue transmission dynamics may therefore be influenced by the spatial overlap of Ae. mediovittatus, Ae. aegypti, dengue viruses, and humans. We take a landscape epidemiology approach to examine the association between landscape composition and configuration and the distribution of each of these Aedes species and their co-occurrence. We used remotely sensed imagery from a newly launched satellite to map landscape features at very high spatial resolution. We found that the distribution of Ae. aegypti is positively predicted by urban density and by the number of tree patches, Ae. mediovittatus is positively predicted by the number of tree patches, but negatively predicted by large contiguous urban areas, and both species are predicted by urban density and the number of tree patches. This analysis provides evidence that landscape composition and configuration is a surrogate for mosquito community composition, and suggests that mapping landscape structure can be used to inform vector control efforts as well as to inform urban planning. PMID:21989642

Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Cheng, Junsheng

2017-02-01

To timely detect the incipient failure of rolling bearing and find out the accurate fault location, a novel rolling bearing fault diagnosis method is proposed based on the composite multiscale fuzzy entropy (CMFE) and ensemble support vector machines (ESVMs). Fuzzy entropy (FuzzyEn), as an improvement of sample entropy (SampEn), is a new nonlinear method for measuring the complexity of time series. Since FuzzyEn (or SampEn) in single scale can not reflect the complexity effectively, multiscale fuzzy entropy (MFE) is developed by defining the FuzzyEns of coarse-grained time series, which represents the system dynamics in different scales. However, the MFE values will be affected by the data length, especially when the data are not long enough. By combining information of multiple coarse-grained time series in the same scale, the CMFE algorithm is proposed in this paper to enhance MFE, as well as FuzzyEn. Compared with MFE, with the increasing of scale factor, CMFE obtains much more stable and consistent values for a short-term time series. In this paper CMFE is employed to measure the complexity of vibration signals of rolling bearings and is applied to extract the nonlinear features hidden in the vibration signals. Also the physically meanings of CMFE being suitable for rolling bearing fault diagnosis are explored. Based on these, to fulfill an automatic fault diagnosis, the ensemble SVMs based multi-classifier is constructed for the intelligent classification of fault features. Finally, the proposed fault diagnosis method of rolling bearing is applied to experimental data analysis and the results indicate that the proposed method could effectively distinguish different fault categories and severities of rolling bearings.

First record of Anopheles minimus C and significant decrease of An. minimus A in central Vietnam.

PubMed

Garros, Claire; Marchand, Ron P; Quang, Nguyen Tuyen; Hai, Nguyen Son; Manguin, Sylvie

2005-06-01

Before August 1998, in the Khanh Phu commune (central Vietnam), Anopheles minimus s.l. individuals were identified as species A and showed the typical species A wing form. After a significant decrease over the 3 years 1999-2001, an increase in 2002 of An. minimus s.l. possessing a different wing pattern was observed. To determine the specific status of the An. minimus species collected in 2002 and to follow changes in the species composition, an allele-specific polymerase chain reaction was applied to samples collected from 1993 to 2002. This study reports the first record of An. minimus C in central Vietnam and, since 1998, a significant reduction of An. minimus A that coincided with the wide use of permethrin-treated bednets. This change in anopheline composition may have important consequences on malaria transmission. This work shows that the geographic distribution of malaria vectors in southeast Asia is only partially known and highlights the importance of species identification for understanding changes in the vector composition as a result of selective vector control.

Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

2015-10-01

The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

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

Carle, S F

Compositional data are represented as vector variables with individual vector components ranging between zero and a positive maximum value representing a constant sum constraint, usually unity (or 100 percent). The earth sciences are flooded with spatial distributions of compositional data, such as concentrations of major ion constituents in natural waters (e.g. mole, mass, or volume fractions), mineral percentages, ore grades, or proportions of mutually exclusive categories (e.g. a water-oil-rock system). While geostatistical techniques have become popular in earth science applications since the 1970s, very little attention has been paid to the unique mathematical properties of geostatistical formulations involving compositional variables.more » The book 'Geostatistical Analysis of Compositional Data' by Vera Pawlowsky-Glahn and Ricardo Olea (Oxford University Press, 2004), unlike any previous book on geostatistics, directly confronts the mathematical difficulties inherent to applying geostatistics to compositional variables. The book righteously justifies itself with prodigious referencing to previous work addressing nonsensical ranges of estimated values and error, spurious correlation, and singular cross-covariance matrices.« less

Possible implication of the genetic composition of the Lutzomyia longipalpis (Diptera: Psychodidae) populations in the epidemiology of the visceral leishmaniasis.

PubMed

Rocha, Leonardo de Souza; Falqueto, Aloisio; Dos Santos, Claudiney Biral; Grimaldi, Gabriel Júnior; Cupolillo, Elisa

2011-09-01

Lutzomyia longipalpis (Diptera: Psychodidae) is the principal vector of American visceral leishmaniasis. Several studies have indicated that the Lu. longipalpis population structure is complex. It has been suggested that genetic divergence caused by genetic drift, selection, or both may affect the vectorial capacity of Lu. longipalpis. However, it remains unclear whether genetic differences among Lu. longipalpis populations are directly implicated in the transmission features of visceral leishmaniasis. We evaluated the genetic composition and the patterns of genetic differentiation among Lu. longipalpis populations collected from regions with different patterns of transmission of visceral leishmaniasis by analyzing the sequence variation in the mitochondrial cytochrome b gene. Furthermore, we investigated the temporal distribution of haplotypes and compared our results with those obtained in a previous study. Our data indicate that there are differences in the haplotype composition and that there has been significant differentiation between the analyzed populations. Our results reveal that measures used to control visceral leishmaniasis might have influenced the genetic composition of the vector population. This finding raises important questions concerning the epidemiology of visceral leishmaniasis, because these differences in the genetic structures among populations of Lu. longipalpis may have implications with respect to their efficiency as vectors for visceral leishmaniasis.

Improvement of tissue culture, genetic transformation, and applications of biotechnology to Brassica.

PubMed

Ravanfar, Seyed Ali; Orbovic, Vladimir; Moradpour, Mahdi; Abdul Aziz, Maheran; Karan, Ratna; Wallace, Simon; Parajuli, Saroj

2017-04-01

Development of in vitro plant regeneration method from Brassica explants via organogenesis and somatic embryogenesis is influenced by many factors such as culture environment, culture medium composition, explant sources, and genotypes which are reviewed in this study. An efficient in vitro regeneration system to allow genetic transformation of Brassica is a crucial tool for improving its economical value. Methods to optimize transformation protocols for the efficient introduction of desirable traits, and a comparative analysis of these methods are also reviewed. Hence, binary vectors, selectable marker genes, minimum inhibitory concentration of selection agents, reporter marker genes, preculture media, Agrobacterium concentration and regeneration ability of putative transformants for improvement of Agrobacterium-mediated transformation of Brassica are discussed.

International Symposium on Numerical Methods in Engineering, 5th, Ecole Polytechnique Federale de Lausanne, Switzerland, Sept. 11-15, 1989, Proceedings. Volumes 1 & 2

NASA Astrophysics Data System (ADS)

Gruber, Ralph; Periaux, Jaques; Shaw, Richard Paul

Recent advances in computational mechanics are discussed in reviews and reports. Topics addressed include spectral superpositions on finite elements for shear banding problems, strain-based finite plasticity, numerical simulation of hypersonic viscous continuum flow, constitutive laws in solid mechanics, dynamics problems, fracture mechanics and damage tolerance, composite plates and shells, contact and friction, metal forming and solidification, coupling problems, and adaptive FEMs. Consideration is given to chemical flows, convection problems, free boundaries and artificial boundary conditions, domain-decomposition and multigrid methods, combustion and thermal analysis, wave propagation, mixed and hybrid FEMs, integral-equation methods, optimization, software engineering, and vector and parallel computing.

Quantitative characterization of the carbon/carbon composites components based on video of polarized light microscope.

PubMed

Li, Yixian; Qi, Lehua; Song, Yongshan; Chao, Xujiang

2017-06-01

The components of carbon/carbon (C/C) composites have significant influence on the thermal and mechanical properties, so a quantitative characterization of component is necessary to study the microstructure of C/C composites, and further to improve the macroscopic properties of C/C composites. Considering the extinction crosses of the pyrocarbon matrix have significant moving features, the polarized light microscope (PLM) video is used to characterize C/C composites quantitatively because it contains sufficiently dynamic and structure information. Then the optical flow method is introduced to compute the optical flow field between the adjacent frames, and segment the components of C/C composites from PLM image by image processing. Meanwhile the matrix with different textures is re-segmented by the length difference of motion vectors, and then the component fraction of each component and extinction angle of pyrocarbon matrix are calculated directly. Finally, the C/C composites are successfully characterized from three aspects of carbon fiber, pyrocarbon, and pores by a series of image processing operators based on PLM video, and the errors of component fractions are less than 15%. © 2017 Wiley Periodicals, Inc.

[Application of chemometrics in composition-activity relationship research of traditional Chinese medicine].

PubMed

Han, Sheng-Nan

2014-07-01

Chemometrics is a new branch of chemistry which is widely applied to various fields of analytical chemistry. Chemometrics can use theories and methods of mathematics, statistics, computer science and other related disciplines to optimize the chemical measurement process and maximize access to acquire chemical information and other information on material systems by analyzing chemical measurement data. In recent years, traditional Chinese medicine has attracted widespread attention. In the research of traditional Chinese medicine, it has been a key problem that how to interpret the relationship between various chemical components and its efficacy, which seriously restricts the modernization of Chinese medicine. As chemometrics brings the multivariate analysis methods into the chemical research, it has been applied as an effective research tool in the composition-activity relationship research of Chinese medicine. This article reviews the applications of chemometrics methods in the composition-activity relationship research in recent years. The applications of multivariate statistical analysis methods (such as regression analysis, correlation analysis, principal component analysis, etc. ) and artificial neural network (such as back propagation artificial neural network, radical basis function neural network, support vector machine, etc. ) are summarized, including the brief fundamental principles, the research contents and the advantages and disadvantages. Finally, the existing main problems and prospects of its future researches are proposed.

Assessing transmission of crop diseases by insect vectors in a landscape context.

PubMed

Carrière, Y; Degain, B; Hartfield, K A; Nolte, K D; Marsh, S E; Ellers-Kirk, C; Van Leeuwen, W J D; Liesner, L; Dutilleul, P; Palumbo, J C

2014-02-01

Theory indicates that landscape composition affects transmission of vector-borne crop diseases, but few empirical studies have investigated how landscape composition affects plant disease epidemiology. Since 2006, Bemisia tabaci (Gennadius) has vectored the cucurbit yellow stunting disorder virus (CYSDV) to cantaloupe and honeydew melons (Cucumis melo L.) in the southwestern United States and northern Mexico, causing significant reductions in yield of fall melons and increased use of insecticides. Here, we show that a landscape-based approach allowing simultaneous assessment of impacts of local (i.e., planting date) and regional (i.e., landscape composition) factors provides valuable insights on how to reduce crop disease risks. Specifically, we found that planting fall melon fields early in the growing season, eliminating plants germinating from seeds produced by spring melons after harvest, and planting fall melon fields away from cotton and spring melon fields may significantly reduce the incidence of CYSDV infection in fall melons. Because the largest scale of significance of the positive association between abundance of cotton and spring melon fields and CYSDV incidence was 1,750 and 3,000 m, respectively, reducing areas of cotton and spring melon fields within these distances from fall melon fields may decrease CYSDV incidence. Our results indicate that landscape-based studies will be fruitful to alleviate limitations imposed on crop production by vector-borne diseases.

Electromagnetic wave absorbing properties of amorphous carbon nanotubes.

PubMed

Zhao, Tingkai; Hou, Cuilin; Zhang, Hongyan; Zhu, Ruoxing; She, Shengfei; Wang, Jungao; Li, Tiehu; Liu, Zhifu; Wei, Bingqing

2014-07-10

Amorphous carbon nanotubes (ACNTs) with diameters in the range of 7-50 nm were used as absorber materials for electromagnetic waves. The electromagnetic wave absorbing composite films were prepared by a dip-coating method using a uniform mixture of rare earth lanthanum nitrate doped ACNTs and polyvinyl chloride (PVC). The microstructures of ACNTs and ACNT/PVC composites were characterized using transmission electron microscope and X-ray diffraction, and their electromagnetic wave absorbing properties were measured using a vector-network analyzer. The experimental results indicated that the electromagnetic wave absorbing properties of ACNTs are superior to multi-walled CNTs, and greatly improved by doping 6 wt% lanthanum nitrate. The reflection loss (R) value of a lanthanum nitrate doped ACNT/PVC composite was -25.02 dB at 14.44 GHz, and the frequency bandwidth corresponding to the reflector loss at -10 dB was up to 5.8 GHz within the frequency range of 2-18 GHz.

Mosquitocidal Effect of Glycosmis pentaphylla Leaf Extracts against Three Mosquito Species (Diptera: Culicidae).

PubMed

Ramkumar, Govindaraju; Karthi, Sengodan; Muthusamy, Ranganathan; Suganya, Ponnusamy; Natarajan, Devarajan; Kweka, Eliningaya J; Shivakumar, Muthugounder S

2016-01-01

The resistance status of malaria vectors to different classes of insecticides used for public health has raised concern for vector control programmes. Alternative compounds to supplement the existing tools are important to be searched to overcome the existing resistance and persistence of pesticides in vectors and the environment respectively. The mosquitocidal effects of Glycosmis pentaphylla using different solvents of acetone, methanol, chloroform and ethyl acetate extracts against three medically important mosquito vectors was conducted. Glycosmis pentaphylla plant leaves were collected from Kolli Hills, India. The WHO test procedures for larval and adult bioassays were used to evaluate extracts against mosquito vectors, and the chemical composition of extracts identified using GC-MS analysis. The larvicidal and adulticidal activity of G. pentaphylla plant extracts clearly impacted the three species of major mosquitoes vectors. Acetone extracts had the highest larvicidal effect against An. stephensi, Cx. quinquefasciatus and Ae. aegypti with the LC50 and LC90 values of 0.0004, 138.54; 0.2669, 73.7413 and 0.0585, 303.746 mg/ml, respectively. The LC50 and LC90 adulticide values of G. pentaphylla leaf extracts in acetone, methanol, chloroform and ethyl acetate, solvents were as follows for Cx. quinquefasciatus, An. stephensi and Ae. Aegypti: 2.957, 5.458, 2.708, and 4.777, 3.449, 6.676 mg/ml respectively. The chemical composition of G. pentaphylla leaf extract has been found in 20 active compounds. The plant leaf extracts of G. pentaphylla bioactive molecules which are effective and can be developed as an eco-friendly approach for larvicides and adulticidal mosquitoes vector control. Detailed identification and characterization of mosquitocidal effect of individual bioactive molecules ingredient may result into biodegradable effective tools for the control of mosquito vectors.

Ovicidal and larvicidal effects of garlic and asafoetida essential oils against West Nile virus vectors

USDA-ARS?s Scientific Manuscript database

We examined the chemical composition of garlic and asafoetida essential oils and their individual and combined toxicity against larvae of two West Nile virus vectors, Culex pipiens pipiens and Cx. restuans. The effect of the two essential oils on egg hatch was also examined. Ten and twelve compounds...

A Mathematical Motivation for Complex-Valued Convolutional Networks.

PubMed

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

2016-05-01

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

Mosquito vector-associated microbiota: Metabarcoding bacteria and eukaryotic symbionts across habitat types in Thailand endemic for dengue and other arthropod-borne diseases.

PubMed

Thongsripong, Panpim; Chandler, James Angus; Green, Amy B; Kittayapong, Pattamaporn; Wilcox, Bruce A; Kapan, Durrell D; Bennett, Shannon N

2018-01-01

Vector-borne diseases are a major health burden, yet factors affecting their spread are only partially understood. For example, microbial symbionts can impact mosquito reproduction, survival, and vectorial capacity, and hence affect disease transmission. Nonetheless, current knowledge of mosquito-associated microbial communities is limited. To characterize the bacterial and eukaryotic microbial communities of multiple vector species collected from different habitat types in disease endemic areas, we employed next-generation 454 pyrosequencing of 16S and 18S rRNA amplicon libraries, also known as metabarcoding. We investigated pooled whole adult mosquitoes of three medically important vectors, Aedes aegypti , Ae. albopictus , and Culex quinquefasciatus, collected from different habitats across central Thailand where we previously characterized mosquito diversity. Our results indicate that diversity within the mosquito microbiota is low, with the majority of microbes assigned to one or a few taxa. Two of the most common eukaryotic and bacterial genera recovered ( Ascogregarina and Wolbachia, respectively) are known mosquito endosymbionts with potentially parasitic and long evolutionary relationships with their hosts. Patterns of microbial composition and diversity appeared to differ by both vector species and habitat for a given species, although high variability between samples suggests a strong stochastic element to microbiota assembly. In general, our findings suggest that multiple factors, such as habitat condition and mosquito species identity, may influence overall microbial community composition, and thus provide a basis for further investigations into the interactions between vectors, their microbial communities, and human-impacted landscapes that may ultimately affect vector-borne disease risk.

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

NASA Technical Reports Server (NTRS)

Deere, Karen A.

2003-01-01

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

Prominent feature extraction for review analysis: an empirical study

NASA Astrophysics Data System (ADS)

Agarwal, Basant; Mittal, Namita

2016-05-01

Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.

Distribution and abundance of host-seeking Culex species at three proximate locations with different levels of West Nile virus activity

USGS Publications Warehouse

Rochlin, I.; Ginsberg, H.S.; Campbell, S.R.

2009-01-01

Culex species were monitored at three proximate sites with historically different West Nile virus (WNV) activities. The site with human WNV transmission (epidemic) had the lowest abundance of the putative bridge vectors, Culex pipiens and Cx. salinarius. The site with horse cases but not human cases (epizootic) had the highest percent composition of Cx. salinarius, whereas the site with WNV-positive birds only (enzootic) had the highest Cx. pipiens abundance and percent composition. A total of 29 WNV-positive Culex pools were collected at the enzootic site, 17 at the epidemic site, and 14 at the epizootic site. Published models of human risk using Cx. pipiens and Cx. salinarius as the primary bridge vectors did not explain WNV activity at our sites. Other variables, such as additional vector species, environmental components, and socioeconomic factors, need to be examined to explain the observed patterns of WNV epidemic activity.

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

USGS Publications Warehouse

Ginsberg, H.S.

2001-01-01

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

Versatile generation of optical vector fields and vector beams using a non-interferometric approach.

PubMed

Tripathi, Santosh; Toussaint, Kimani C

2012-05-07

We present a versatile, non-interferometric method for generating vector fields and vector beams which can produce all the states of polarization represented on a higher-order Poincaré sphere. The versatility and non-interferometric nature of this method is expected to enable exploration of various exotic properties of vector fields and vector beams. To illustrate this, we study the propagation properties of some vector fields and find that, in general, propagation alters both their intensity and polarization distribution, and more interestingly, converts some vector fields into vector beams. In the article, we also suggest a modified Jones vector formalism to represent vector fields and vector beams.

Support vector machine with a Pearson VII function kernel for discriminating halophilic and non-halophilic proteins.

PubMed

Zhang, Guangya; Ge, Huihua

2013-10-01

Understanding of proteins adaptive to hypersaline environment and identifying them is a challenging task and would help to design stable proteins. Here, we have systematically analyzed the normalized amino acid compositions of 2121 halophilic and 2400 non-halophilic proteins. The results showed that halophilic protein contained more Asp at the expense of Lys, Ile, Cys and Met, fewer small and hydrophobic residues, and showed a large excess of acidic over basic amino acids. Then, we introduce a support vector machine method to discriminate the halophilic and non-halophilic proteins, by using a novel Pearson VII universal function based kernel. In the three validation check methods, it achieved an overall accuracy of 97.7%, 91.7% and 86.9% and outperformed other machine learning algorithms. We also address the influence of protein size on prediction accuracy and found the worse performance for small size proteins might be some significant residues (Cys and Lys) were missing in the proteins. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

PubMed

Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

2017-02-01

Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest.

PubMed

Manavalan, Balachandran; Shin, Tae Hwan; Lee, Gwang

2018-01-05

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html.

DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest

PubMed Central

Manavalan, Balachandran; Shin, Tae Hwan; Lee, Gwang

2018-01-01

DNase I hypersensitive sites (DHSs) are genomic regions that provide important information regarding the presence of transcriptional regulatory elements and the state of chromatin. Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. Although many experimental methods have been proposed to identify DHSs, they have proven to be expensive for genome-wide application. Therefore, it is necessary to develop computational methods for DHS prediction. In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal features. The optimal combination of features was identified from a large set that included nucleotide composition and di- and trinucleotide physicochemical properties, using a random forest algorithm. DHSpred achieved a Matthews correlation coefficient and accuracy of 0.660 and 0.871, respectively, which were 3% higher than those of control SVM predictors trained with non-optimized features, indicating the efficiency of the feature selection method. Furthermore, the performance of DHSpred was superior to that of state-of-the-art predictors. An online prediction server has been developed to assist the scientific community, and is freely available at: http://www.thegleelab.org/DHSpred.html PMID:29416743

Nutritional status and body composition by bioelectrical impedance vector analysis: A cross sectional study in mild cognitive impairment and Alzheimer's disease.

PubMed

Cova, Ilaria; Pomati, Simone; Maggiore, Laura; Forcella, Marica; Cucumo, Valentina; Ghiretti, Roberta; Grande, Giulia; Muzio, Fulvio; Mariani, Claudio

2017-01-01

Analysis of nutritional status and body composition in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). A cross-sectional study was performed in a University-Hospital setting, recruiting 59 patients with AD, 34 subjects with MCI and 58 elderly healthy controls (HC). Nutritional status was assessed by anthropometric parameters (body mass index; calf, upper arm and waist circumferences), Mini Nutritional Assessment (MNA) and body composition by bioelectrical impedance vector analysis (BIVA). Variables were analyzed by analysis of variance and subjects were grouped by cognitive status and gender. Sociodemographic variables did not differ among the three groups (AD, MCI and HC), except for females' age, which was therefore used as covariate in a general linear multivariate model. MNA score was significantly lower in AD patients than in HC; MCI subjects achieved intermediate scores. AD patients (both sexes) had significantly (p<0.05) higher height-normalized impedance values and lower phase angles (body cell mass) compared with HC; a higher ratio of impedance to height was found in men with MCI with respect to HC. With BIVA method, MCI subjects showed a significant displacement on the RXc graph on the right side indicating lower soft tissues (Hotelling's T2 test: men = 10.6; women = 7.9;p < 0,05) just like AD patients (Hotelling's T2 test: men = 18.2; women = 16.9; p<0,001). Bioelectrical parameters significantly differ from MCI and AD to HC; MCI showed an intermediate pattern between AD and HC. Longitudinal studies are required to investigate if BIVA could reflect early AD-changes in body composition in subjects with MCI.

A Support Vector Machine based method to distinguish proteobacterial proteins from eukaryotic plant proteins

PubMed Central

2012-01-01

Background Members of the phylum Proteobacteria are most prominent among bacteria causing plant diseases that result in a diminution of the quantity and quality of food produced by agriculture. To ameliorate these losses, there is a need to identify infections in early stages. Recent developments in next generation nucleic acid sequencing and mass spectrometry open the door to screening plants by the sequences of their macromolecules. Such an approach requires the ability to recognize the organismal origin of unknown DNA or peptide fragments. There are many ways to approach this problem but none have emerged as the best protocol. Here we attempt a systematic way to determine organismal origins of peptides by using a machine learning algorithm. The algorithm that we implement is a Support Vector Machine (SVM). Result The amino acid compositions of proteobacterial proteins were found to be different from those of plant proteins. We developed an SVM model based on amino acid and dipeptide compositions to distinguish between a proteobacterial protein and a plant protein. The amino acid composition (AAC) based SVM model had an accuracy of 92.44% with 0.85 Matthews correlation coefficient (MCC) while the dipeptide composition (DC) based SVM model had a maximum accuracy of 94.67% and 0.89 MCC. We also developed SVM models based on a hybrid approach (AAC and DC), which gave a maximum accuracy 94.86% and a 0.90 MCC. The models were tested on unseen or untrained datasets to assess their validity. Conclusion The results indicate that the SVM based on the AAC and DC hybrid approach can be used to distinguish proteobacterial from plant protein sequences. PMID:23046503

Prediction of endoplasmic reticulum resident proteins using fragmented amino acid composition and support vector machine.

PubMed

Kumar, Ravindra; Kumari, Bandana; Kumar, Manish

2017-01-01

The endoplasmic reticulum plays an important role in many cellular processes, which includes protein synthesis, folding and post-translational processing of newly synthesized proteins. It is also the site for quality control of misfolded proteins and entry point of extracellular proteins to the secretory pathway. Hence at any given point of time, endoplasmic reticulum contains two different cohorts of proteins, (i) proteins involved in endoplasmic reticulum-specific function, which reside in the lumen of the endoplasmic reticulum, called as endoplasmic reticulum resident proteins and (ii) proteins which are in process of moving to the extracellular space. Thus, endoplasmic reticulum resident proteins must somehow be distinguished from newly synthesized secretory proteins, which pass through the endoplasmic reticulum on their way out of the cell. Approximately only 50% of the proteins used in this study as training data had endoplasmic reticulum retention signal, which shows that these signals are not essentially present in all endoplasmic reticulum resident proteins. This also strongly indicates the role of additional factors in retention of endoplasmic reticulum-specific proteins inside the endoplasmic reticulum. This is a support vector machine based method, where we had used different forms of protein features as inputs for support vector machine to develop the prediction models. During training leave-one-out approach of cross-validation was used. Maximum performance was obtained with a combination of amino acid compositions of different part of proteins. In this study, we have reported a novel support vector machine based method for predicting endoplasmic reticulum resident proteins, named as ERPred. During training we achieved a maximum accuracy of 81.42% with leave-one-out approach of cross-validation. When evaluated on independent dataset, ERPred did prediction with sensitivity of 72.31% and specificity of 83.69%. We have also annotated six different proteomes to predict the candidate endoplasmic reticulum resident proteins in them. A webserver, ERPred, was developed to make the method available to the scientific community, which can be accessed at http://proteininformatics.org/mkumar/erpred/index.html. We found that out of 124 proteins of the training dataset, only 66 proteins had endoplasmic reticulum retention signals, which shows that these signals are not an absolute necessity for endoplasmic reticulum resident proteins to remain inside the endoplasmic reticulum. This observation also strongly indicates the role of additional factors in retention of proteins inside the endoplasmic reticulum. Our proposed predictor, ERPred, is a signal independent tool. It is tuned for the prediction of endoplasmic reticulum resident proteins, even if the query protein does not contain specific ER-retention signal.

Killing-Yano tensors in spaces admitting a hypersurface orthogonal Killing vector

NASA Astrophysics Data System (ADS)

Garfinkle, David; Glass, E. N.

2013-03-01

Methods are presented for finding Killing-Yano tensors, conformal Killing-Yano tensors, and conformal Killing vectors in spacetimes with a hypersurface orthogonal Killing vector. These methods are similar to a method developed by the authors for finding Killing tensors. In all cases one decomposes both the tensor and the equation it satisfies into pieces along the Killing vector and pieces orthogonal to the Killing vector. Solving the separate equations that result from this decomposition requires less computing than integrating the original equation. In each case, examples are given to illustrate the method.

A Bayesian method for detecting pairwise associations in compositional data

PubMed Central

Ventz, Steffen; Huttenhower, Curtis

2017-01-01

Compositional data consist of vectors of proportions normalized to a constant sum from a basis of unobserved counts. The sum constraint makes inference on correlations between unconstrained features challenging due to the information loss from normalization. However, such correlations are of long-standing interest in fields including ecology. We propose a novel Bayesian framework (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix through a LASSO prior. The resulting posterior, generated by MCMC sampling, allows uncertainty quantification of any function of the precision matrix, including the correlation matrix. We also use a first-order Taylor expansion to approximate the transformation from the unobserved counts to the composition in order to investigate what characteristics of the unobserved counts can make the correlations more or less difficult to infer. On simulated datasets, we show that BAnOCC infers the true network as well as previous methods while offering the advantage of posterior inference. Larger and more realistic simulated datasets further showed that BAnOCC performs well as measured by type I and type II error rates. Finally, we apply BAnOCC to a microbial ecology dataset from the Human Microbiome Project, which in addition to reproducing established ecological results revealed unique, competition-based roles for Proteobacteria in multiple distinct habitats. PMID:29140991

Max-plus and min-plus projection autoassociative morphological memories and their compositions for pattern classification.

PubMed

Dos Santos, Alex Santana; Valle, Marcos Eduardo

2018-04-01

Autoassociative morphological memories (AMMs) are robust and computationally efficient memory models with unlimited storage capacity. In this paper, we present the max-plus and min-plus projection autoassociative morphological memories (PAMMs) as well as their compositions. Briefly, the max-plus PAMM yields the largest max-plus combination of the stored vectors which is less than or equal to the input. Dually, the vector recalled by the min-plus PAMM corresponds to the smallest min-plus combination which is larger than or equal to the input. Apart from unlimited absolute storage capacity and one step retrieval, PAMMs and their compositions exhibit an excellent noise tolerance. Furthermore, the new memories yielded quite promising results in classification problems with a large number of features and classes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Terrain representation impact on periurban catchment morphological properties

NASA Astrophysics Data System (ADS)

Rodriguez, F.; Bocher, E.; Chancibault, K.

2013-04-01

SummaryModelling the hydrological behaviour of suburban catchments requires an estimation of environmental features, including land use and hydrographic networks. Suburban areas display a highly heterogeneous composition and encompass many anthropogenic elements that affect water flow paths, such as ditches, sewers, culverts and embankments. The geographical data available, either raster or vector data, may be of various origins and resolutions. Urban databases often offer very detailed data for sewer networks and 3D streets, yet the data covering rural zones may be coarser. This study is intended to highlight the sensitivity of geographical data as well as the data discretisation method used on the essential features of a periurban catchment, i.e. the catchment border and the drainage network. Three methods are implemented for this purpose. The first is the DEM (for digital elevation model) treatment method, which has traditionally been applied in the field of catchment hydrology. The second is based on urban database analysis and focuses on vector data, i.e. polygons and segments. The third method is a TIN (or triangular irregular network), which provides a consistent description of flow directions from an accurate representation of slope. It is assumed herein that the width function is representative of the catchment's hydrological response. The periurban Chézine catchment, located within the Nantes metropolitan area in western France, serves as the case study. The determination of both the main morphological features and the hydrological response of a suburban catchment varies significantly according to the discretization method employed, especially on upstream rural areas. Vector- and TIN-based methods allow representing the higher drainage density of urban areas, and consequently reveal the impact of these areas on the width function, since the DEM method fails. TINs seem to be more appropriate to take streets into account, because it allows a finer representation of topographical discontinuities. These results may help future developments of distributed hydrological models on periurban areas.

Analysis models for the estimation of oceanic fields

NASA Technical Reports Server (NTRS)

Carter, E. F.; Robinson, A. R.

1987-01-01

A general model for statistically optimal estimates is presented for dealing with scalar, vector and multivariate datasets. The method deals with anisotropic fields and treats space and time dependence equivalently. Problems addressed include the analysis, or the production of synoptic time series of regularly gridded fields from irregular and gappy datasets, and the estimate of fields by compositing observations from several different instruments and sampling schemes. Technical issues are discussed, including the convergence of statistical estimates, the choice of representation of the correlations, the influential domain of an observation, and the efficiency of numerical computations.

Species Composition of Sand Flies (Diptera: Psychodidae) and Modeling the Spatial Distribution of Main Vectors of Cutaneous Leishmaniasis in Hormozgan Province, Southern Iran.

PubMed

Hanafi-Bojd, Ahmad Ali; Khoobdel, Mehdi; Soleimani-Ahmadi, Moussa; Azizi, Kourosh; Aghaei Afshar, Abbas; Jaberhashemi, Seyed Aghil; Fekri, Sajjad; Safari, Reza

2018-02-28

Cutaneous Leishmaniasis (CL) is one of the main neglected vector-borne diseases in the Middle East, including Iran. This study aimed to map the spatial distribution and species composition of sand flies in Hormozgan Province and to predict the best ecological niches for main CL vectors in this area. A database that included all earlier studies on sand flies in Hormozgan Province was established. Sand flies were also collected from some localities across the province. Prediction maps for main vectors were developed using MaxEnt model. A total of 27 sand fly species were reported from the study area. Phlebotomus papatasi Scopoli, Phlebotomus sergenti s.l. Parrot, Phlebotomus alexandri Sinton, Sergentomyia sintoni Pringle, Sergentomyia clydei Sinton, Sergentomyia tiberiadis Adler, and Sergentomyia baghdadis Adler (Diptera: Psychodidae) had the widest distribution range. The probability of their presence as the main vectors of CL was calculated to be 0.0003-0.9410 and 0.0031-0.8880 for P. papatasi and P. sergenti s.l., respectively. The best ecological niches for P. papatasi were found in the central south, southeast, and a narrow area in southwest, whereas central south to northern area had better niches for P. sergenti s.l. The endemic areas are in Bandar-e Jask, where transmission occurs, whereas in Bastak, the cases were imported from endemic foci of Fars province. In conclusion, proven and suspected vectors of CL and VL were recorded in this study. Due to the existence of endemic foci of CL, and favorite ecological niches for its vectors, there is potential risk of emerging CL in new areas.

MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads.

PubMed

Tyakht, Alexander V; Popenko, Anna S; Belenikin, Maxim S; Altukhov, Ilya A; Pavlenko, Alexander V; Kostryukova, Elena S; Selezneva, Oksana V; Larin, Andrei K; Karpova, Irina Y; Alexeev, Dmitry G

2012-12-07

MALINA is a web service for bioinformatic analysis of whole-genome metagenomic data obtained from human gut microbiota sequencing. As input data, it accepts metagenomic reads of various sequencing technologies, including long reads (such as Sanger and 454 sequencing) and next-generation (including SOLiD and Illumina). It is the first metagenomic web service that is capable of processing SOLiD color-space reads, to authors' knowledge. The web service allows phylogenetic and functional profiling of metagenomic samples using coverage depth resulting from the alignment of the reads to the catalogue of reference sequences which are built into the pipeline and contain prevalent microbial genomes and genes of human gut microbiota. The obtained metagenomic composition vectors are processed by the statistical analysis and visualization module containing methods for clustering, dimension reduction and group comparison. Additionally, the MALINA database includes vectors of bacterial and functional composition for human gut microbiota samples from a large number of existing studies allowing their comparative analysis together with user samples, namely datasets from Russian Metagenome project, MetaHIT and Human Microbiome Project (downloaded from http://hmpdacc.org). MALINA is made freely available on the web at http://malina.metagenome.ru. The website is implemented in JavaScript (using Ext JS), Microsoft .NET Framework, MS SQL, Python, with all major browsers supported.

Design of smart composite platforms for adaptive trust vector control and adaptive laser telescope for satellite applications

NASA Astrophysics Data System (ADS)

Ghasemi-Nejhad, Mehrdad N.

2013-04-01

This paper presents design of smart composite platforms for adaptive trust vector control (TVC) and adaptive laser telescope for satellite applications. To eliminate disturbances, the proposed adaptive TVC and telescope systems will be mounted on two analogous smart composite platform with simultaneous precision positioning (pointing) and vibration suppression (stabilizing), SPPVS, with micro-radian pointing resolution, and then mounted on a satellite in two different locations. The adaptive TVC system provides SPPVS with large tip-tilt to potentially eliminate the gimbals systems. The smart composite telescope will be mounted on a smart composite platform with SPPVS and then mounted on a satellite. The laser communication is intended for the Geosynchronous orbit. The high degree of directionality increases the security of the laser communication signal (as opposed to a diffused RF signal), but also requires sophisticated subsystems for transmission and acquisition. The shorter wavelength of the optical spectrum increases the data transmission rates, but laser systems require large amounts of power, which increases the mass and complexity of the supporting systems. In addition, the laser communication on the Geosynchronous orbit requires an accurate platform with SPPVS capabilities. Therefore, this work also addresses the design of an active composite platform to be used to simultaneously point and stabilize an intersatellite laser communication telescope with micro-radian pointing resolution. The telescope is a Cassegrain receiver that employs two mirrors, one convex (primary) and the other concave (secondary). The distance, as well as the horizontal and axial alignment of the mirrors, must be precisely maintained or else the optical properties of the system will be severely degraded. The alignment will also have to be maintained during thruster firings, which will require vibration suppression capabilities of the system as well. The innovative platform has been designed to have tip-tilt pointing and simultaneous multi-degree-of-freedom vibration isolation capability for pointing stabilization. Analytical approaches have been employed for determining the loads in the components as well as optimizing the design of the system. The different critical components such as telescope tube struts, flexure joints, and the secondary mirror mount have been designed and analyzed using finite element technique. The Simultaneous Precision Positioning and Vibration Suppression (SPPVS) smart composites platforms for the adaptive TVC and adaptive composite telescope are analogous (e.g., see work by Ghasemi-Nejhad and co-workers [1, 2]), where innovative concepts and control strategies are introduced, and experimental verifications of simultaneous thrust vector control and vibration isolation of satellites were performed. The smart composite platforms function as an active structural interface between the main thruster of a satellite and the satellite structure for the adaptive TVC application and as an active structural interface between the main smart composite telescope and the satellite structure for the adaptive laser communication application. The cascaded multiple feedback loops compensate the hysteresis (for piezoelectric stacks inside the three linear actuators that individually have simultaneous precision positioning and vibration suppression), dead-zone, back-lash, and friction nonlinearities very well, and provide precision and quick smart platform control and satisfactory thrust vector control capability. In addition, for example for the adaptive TVC, the experimental results show that the smart composite platform satisfactorily provided precision and fast smart platform control as well as the satisfactory thrust vector control capability. The vibration controller isolated 97% of the vibration energy due to the thruster firing.

Numerical and experimental investigation of plasma plume deflection with MHD flow control

NASA Astrophysics Data System (ADS)

Kai, ZHAO; Feng, LI; Baigang, SUN; Hongyu, YANG; Tao, ZHOU; Ruizhi, SUN

2018-04-01

This paper presents a composite magneto hydrodynamics (MHD) method to control the low-temperature micro-ionized plasma flow generated by injecting alkali salt into the combustion gas to realize the thrust vector of an aeroengine. The principle of plasma flow with MHD control is analyzed. The feasibility of plasma jet deflection is investigated using numerical simulation with MHD control by loading the User-Defined Function model. A test rig with plasma flow controlled by MHD is established. An alkali salt compound with a low ionization energy is injected into combustion gas to obtain the low-temperature plasma flow. Finally, plasma plume deflection is obtained in different working conditions. The results demonstrate that plasma plume deflection with MHD control can be realized via numerical simulation. A low-temperature plasma flow can be obtained by injecting an alkali metal salt compound with low ionization energy into a combustion gas at 1800–2500 K. The vector angle of plasma plume deflection increases with the increase of gas temperature and the magnetic field intensity. It is feasible to realize the aim of the thrust vector of aeroengine by using MHD to control plasma flow deflection.

Large-scale production of lentiviral vector in a closed system hollow fiber bioreactor

PubMed Central

Sheu, Jonathan; Beltzer, Jim; Fury, Brian; Wilczek, Katarzyna; Tobin, Steve; Falconer, Danny; Nolta, Jan; Bauer, Gerhard

2015-01-01

Lentiviral vectors are widely used in the field of gene therapy as an effective method for permanent gene delivery. While current methods of producing small scale vector batches for research purposes depend largely on culture flasks, the emergence and popularity of lentiviral vectors in translational, preclinical and clinical research has demanded their production on a much larger scale, a task that can be difficult to manage with the numbers of producer cell culture flasks required for large volumes of vector. To generate a large scale, partially closed system method for the manufacturing of clinical grade lentiviral vector suitable for the generation of induced pluripotent stem cells (iPSCs), we developed a method employing a hollow fiber bioreactor traditionally used for cell expansion. We have demonstrated the growth, transfection, and vector-producing capability of 293T producer cells in this system. Vector particle RNA titers after subsequent vector concentration yielded values comparable to lentiviral iPSC induction vector batches produced using traditional culture methods in 225 cm2 flasks (T225s) and in 10-layer cell factories (CF10s), while yielding a volume nearly 145 times larger than the yield from a T225 flask and nearly three times larger than the yield from a CF10. Employing a closed system hollow fiber bioreactor for vector production offers the possibility of manufacturing large quantities of gene therapy vector while minimizing reagent usage, equipment footprint, and open system manipulation. PMID:26151065

Balancing aggregation and smoothing errors in inverse models

DOE PAGES

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

2015-06-30

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

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Balancing aggregation and smoothing errors in inverse models

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Discrimination of tooth layers and dental restorative materials using cutting sounds.

PubMed

Zakeri, Vahid; Arzanpour, Siamak; Chehroudi, Babak

2015-03-01

Dental restoration begins with removing carries and affected tissues with air-turbine rotary cutting handpieces, and later restoring the lost tissues with appropriate restorative materials to retain the functionality. Most restoration materials eventually fail as they age and need to be replaced. One of the difficulties in replacing failing restorations is discerning the boundary of restorative materials, which causes inadvertent removal of healthy tooth layers. Developing an objective and sensor-based method is a promising approach to monitor dental restorative operations and to prevent excessive tooth losses. This paper has analyzed cutting sounds of an air-turbine handpiece to discriminate between tooth layers and two commonly used restorative materials, amalgam and composite. Support vector machines were employed for classification, and the averaged short-time Fourier transform coefficients were selected as the features. The classifier performance was evaluated from different aspects such as the number of features, feature scaling methods, classification schemes, and utilized kernels. The total classification accuracies were 89% and 92% for cases included composite and amalgam materials, respectively. The obtained results indicated the feasibility and effectiveness of the proposed method.

Impact localization on composite laminates using fiber Bragg grating sensors and a novel technique based on strain amplitude

NASA Astrophysics Data System (ADS)

Zhao, Gang; Li, Shuxin; Hu, Haixiao; Zhong, Yucheng; Li, Kun

2018-01-01

Carbon fiber reinforced composite materials have been widely used in aerospace and other high-tech fields because of their excellent performance. However barely visible impact damage can be introduced by low velocity impact, which might bring out tremendous risk. In this paper, a new method is proposed to predict the position of low velocity impact. The dynamic strain signal that is caused by low velocity impact is obtained by the fiber Bragg grating (FBG) sensor. The amplitude of the first K order natural frequency is extracted by Fast Fourier Transform (FFT). The amplitude data is normalized, and then establish k order vector matrix model is established. It is proposed that K order sum of squares of deviations can be used as the basis to predict positioning. Two different validation tests were performed. The experimental model was made of different layers. FBG were used to embed and paste type method, experiments were conducted with impact of different energy levels. The results show that proposed method is feasible.

Application of finite elements heterogeneous multi-scale method to eddy currents non destructive testing of carbon composites material

NASA Astrophysics Data System (ADS)

Khebbab, Mohamed; Feliachi, Mouloud; El Hadi Latreche, Mohamed

2018-03-01

In this present paper, a simulation of eddy current non-destructive testing (EC NDT) on unidirectional carbon fiber reinforced polymer is performed; for this magneto-dynamic formulation in term of magnetic vector potential is solved using finite element heterogeneous multi-scale method (FE HMM). FE HMM has as goal to compute the homogenized solution without calculating the homogenized tensor explicitly, the solution is based only on the physical characteristic known in micro domain. This feature is well adapted to EC NDT to evaluate defect in carbon composite material in microscopic scale, where the defect detection is performed by coil impedance measurement; the measurement value is intimately linked to material characteristic in microscopic level. Based on this, our model can handle different defects such as: cracks, inclusion, internal electrical conductivity changes, heterogeneities, etc. The simulation results were compared with the solution obtained with homogenized material using mixture law, a good agreement was found.

Analysis of the low gravity tolerance of Bridgman-Stockbarger crystal growth. I - Steady and impulse accelerations

NASA Technical Reports Server (NTRS)

Alexander, J. Iwan D.; Ouazzani, Jalil; Rosenberger, Franz

1989-01-01

The effects of steady and impulse-type residual accelerations on dopant distributions during directional solidification in 2D and 3D 'generic' models of the Bridgman-Stockbarger technique are investigated using numerical methods. The calculations are based on the thermophysical properties of molten germanium doped with a low concentration of gallium. A Chebyshev collocation pseudospectral method is used for the solution of the governing momentum-, mass-, species-, and heat-transfer equations. Only convection caused by temperature gradients is considered. It is found that lateral nonuniformity in composition is very sensitive to the orientation of the steady component of the residual gravity vector and to the particular operating conditions under consideration. It is also found that laterally or radially averaged composition profiles are alone insufficient to describe the extent of residual convection in a spacecraft environment. The effects of impulse-type disturbances can be severe and can extend for times on the order of 1000 sec after the termination of the impulse.

Vectorized Jiles-Atherton hysteresis model

NASA Astrophysics Data System (ADS)

Szymański, Grzegorz; Waszak, Michał

2004-01-01

This paper deals with vector hysteresis modeling. A vector model consisting of individual Jiles-Atherton components placed along principal axes is proposed. The cross-axis coupling ensures general vector model properties. Minor loops are obtained using scaling method. The model is intended for efficient finite element method computations defined in terms of magnetic vector potential. Numerical efficiency is ensured by differential susceptibility approach.

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

NASA Astrophysics Data System (ADS)

Wang, Yu

2018-04-01

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

Plate Wave Resonance with Air-Coupled Ultrasonics

NASA Astrophysics Data System (ADS)

Bar, H. N.; Dayal, V.; Barnard, D.; Hsu, D. K.

2010-02-01

Air-coupled ultrasonic transducers can excite plate waves in metals and composites. The coincidence effect, i.e., the wave vector of plate wave coincides with projection of exciting airborne sound vector, leads to a resonance which strongly amplifies the sound transmission through the plate. The resonance depends on the angle of incidence and the frequency. In the present study, the incidence angle for maximum transmission (θmax) is measured in plates of steel, aluminum, carbon fiber reinforced composites and honeycomb sandwich panels. The variations of (θmax) with plate thickness are compared with theoretical values in steel, aluminum and quasi-isotropic carbon fiber composites. The enhanced transmission of air-coupled ultrasound at oblique incidence can substantially improve the probability of flaw detection in plates and especially in honeycomb structures. Experimental air-coupled ultrasonic scan of subtle flaws in CFRP laminates showed definite improvement of signal-to-noise ratio with oblique incidence at θmax.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Analysis of wave propagation in a two-dimensional photonic crystal with negative index of refraction: plane wave decomposition of the Bloch modes.

PubMed

Martínez, Alejandro; Míguez, Hernán; Sánchez-Dehesa, José; Martí, Javier

2005-05-30

This work presents a comprehensive analysis of electromagnetic wave propagation inside a two-dimensional photonic crystal in a spectral region in which the crystal behaves as an effective medium to which a negative effective index of refraction can be associated. It is obtained that the main plane wave component of the Bloch mode that propagates inside the photonic crystal has its wave vector k' out of the first Brillouin zone and it is parallel to the Poynting vector ( S' ? k'> 0 ), so light propagation in these composites is different from that reported for left-handed materials despite the fact that negative refraction can take place at the interface between air and both kinds of composites. However, wave coupling at the interfaces is well explained using the reduced wave vector ( k' ) in the first Brillouin zone, which is opposed to the energy flow, and agrees well with previous works dealing with negative refraction in photonic crystals.

Searches for vector-like quarks at future colliders and implications for composite Higgs models with dark matter

NASA Astrophysics Data System (ADS)

Chala, Mikael; Gröber, Ramona; Spannowsky, Michael

2018-03-01

Many composite Higgs models predict the existence of vector-like quarks with masses outside the reach of the LHC, e.g. m Q ≳ 2 TeV, in particular if these models contain a dark matter candidate. In such models the mass of the new resonances is bounded from above to satisfy the constraint from the observed relic density. We therefore develop new strategies to search for vector-like quarks at a future 100 TeV collider and evaluate what masses and interactions can be probed. We find that masses as large as ˜ 6.4 (˜9) TeV can be tested if the fermionic resonances decay into Standard Model (dark matter) particles. We also discuss the complementarity of dark matter searches, showing that most of the parameter space can be closed. On balance, this study motivates further the consideration of a higher-energy hadron collider for a next generation of facilities.

Review of the bioenvironmental methods for malaria control with special reference to the use of larvivorous fishes and composite fish culture in central Gujarat, India.

PubMed

Kant, Rajni; Haq, S; Srivastava, H C; Sharma, V P

2013-03-01

Mosquito control with the use of insecticides is faced with the challenges of insecticide resistance in disease vectors, community refusal, their high cost, operational difficulties, and environmental concern. In view of this, integrated vector control strategies with the use of larvivorous fishes such as Guppy (Poecilia reticulata) and Gambusia (G. affinis) as biological control agents were used in controlling mosquito breeding in different types of breeding places such as intradomestic containers, various types of wells, rice-fields, pools, ponds and elsewhere in malaria prone rural areas of central Gujarat. Attempts were also made to demonstrate composite fish culture in unused abandoned village ponds by culturing Guppy along with the food fishes such as Rohu (Labeo rohita), Catla (Catla catla) and Mrigal (Cirrhinus mrigala). Income generated from these ponds through sale of fishes was utilized for mosquito control and village development. The technology was later adopted by the villagers themselves and food fish culture was practised in 23 ponds which generated an income of Rs 1,02,50,992 between 1985 and 2008. The number of villages increased from 13 to 23 in 2008 and there was also gradual increase of income from Rs 3,66,245 in 1985-90 to Rs 55,06,127 in 2002-08 block. It is concluded that larvivorous fishes can be useful tool in controlling mosquito breeding in certain situations and their use along with composite fish culture may also generate income to make the programme self-sustainable.

Change in Anopheles richness and composition in response to artificial flooding during the creation of the Jirau hydroelectric dam in Porto Velho, Brazil.

PubMed

Rodrigures, Moreno S; Batista, Elis P; Silva, Alexandre A; Costa, Fábio M; Neto, Verissimo A S; Gil, Luiz Herman S

2017-02-22

Anopheles mosquitoes are the only vectors of human malaria. Anopheles species use standing water as breeding sites. Human activities, like the creation of an artificial lake during the implementation of hydroelectric power plants, lead to changes in environmental characteristics and, therefore, may changes the species richness and composition of Anopheles mosquitoes. The aim of the present study was to verify whether or not there is an association between the artificial flooding resulting from the construction of the Jirau hydroelectric power plant, and the richness and composition of anophelines. Mosquitoes samples were obtained monthly from the Jirau hydroelectric power plant area located at Porto Velho, Rondônia State, using Human Landing Catch (06:00-10:00 PM). Mosquitoes collected were transported to Laboratório de Entomologia Médica FIOCRUZ-RO where they were identified until species using dichotomous key. A total of 6347 anophelines belonging to eight different species were collected. The anophelines species richness was significantly lower during the first flooding stage. Differences in anophelines species composition were found when comparing the first flooding stage with the other stages. Furthermore, the mean number of Anopheles darlingi, the main vector of malaria in the region, increases during the first and the third flooding stages. The continual monitoring of these vectors during the late operational phase may be useful in order to understand how anophelines will behave in this area.

Electromagnetic Wave Absorbing Properties of Amorphous Carbon Nanotubes

PubMed Central

Zhao, Tingkai; Hou, Cuilin; Zhang, Hongyan; Zhu, Ruoxing; She, Shengfei; Wang, Jungao; Li, Tiehu; Liu, Zhifu; Wei, Bingqing

2014-01-01

Amorphous carbon nanotubes (ACNTs) with diameters in the range of 7–50 nm were used as absorber materials for electromagnetic waves. The electromagnetic wave absorbing composite films were prepared by a dip-coating method using a uniform mixture of rare earth lanthanum nitrate doped ACNTs and polyvinyl chloride (PVC). The microstructures of ACNTs and ACNT/PVC composites were characterized using transmission electron microscope and X-ray diffraction, and their electromagnetic wave absorbing properties were measured using a vector-network analyzer. The experimental results indicated that the electromagnetic wave absorbing properties of ACNTs are superior to multi-walled CNTs, and greatly improved by doping 6 wt% lanthanum nitrate. The reflection loss (R) value of a lanthanum nitrate doped ACNT/PVC composite was −25.02 dB at 14.44 GHz, and the frequency bandwidth corresponding to the reflector loss at −10 dB was up to 5.8 GHz within the frequency range of 2–18 GHz. PMID:25007783

The Theory and Fundamentals of Bioimpedance Analysis in Clinical Status Monitoring and Diagnosis of Diseases

PubMed Central

Khalil, Sami F.; Mohktar, Mas S.; Ibrahim, Fatimah

2014-01-01

Bioimpedance analysis is a noninvasive, low cost and a commonly used approach for body composition measurements and assessment of clinical condition. There are a variety of methods applied for interpretation of measured bioimpedance data and a wide range of utilizations of bioimpedance in body composition estimation and evaluation of clinical status. This paper reviews the main concepts of bioimpedance measurement techniques including the frequency based, the allocation based, bioimpedance vector analysis and the real time bioimpedance analysis systems. Commonly used prediction equations for body composition assessment and influence of anthropometric measurements, gender, ethnic groups, postures, measurements protocols and electrode artifacts in estimated values are also discussed. In addition, this paper also contributes to the deliberations of bioimpedance analysis assessment of abnormal loss in lean body mass and unbalanced shift in body fluids and to the summary of diagnostic usage in different kinds of conditions such as cardiac, pulmonary, renal, and neural and infection diseases. PMID:24949644

Preparation and microwave absorbing properties of carbon/cobalt ferromagnetic composites.

PubMed

Li, Wangchang; Qiao, Xiaojing; Zhao, Hui; Wang, Shuman; Ren, Qingguo

2013-02-01

Carbon/cobalt ferromagnetic light composites with high performance of microwave absorbing properties were prepared by hydrothermal method using starch and hollow cobalt ferrites. It was concluded that after carbonization the spinel structure ferrites changed to Co3Fe7 alloys and the temperature of graphitization was significantly decreased for the catalytic of CoFe2O4/Co3Fe7. The increase of carbon content, and exist of CoFe2O4/Co3Fe7 heightened the microwave absorbing properties. Electromagnetic parameters were tested with 40% of the titled materials and 60% of paraffin wax composites by using HP8722ES vector network analyzer. The reflection was also simulated through transmission line theory. The microwave absorbers exhibited a maximum reflection loss -43 dB and the electromagnetic wave absorption less than -10 dB was found to exceed 3.0 GHz between 11.6 GHz and 15 GHz for an absorber thickness of 2 mm.

Stability of large-scale systems with stable and unstable subsystems.

NASA Technical Reports Server (NTRS)

Grujic, Lj. T.; Siljak, D. D.

1972-01-01

The purpose of this paper is to develop new methods for constructing vector Liapunov functions and broaden the application of Liapunov's theory to stability analysis of large-scale dynamic systems. The application, so far limited by the assumption that the large-scale systems are composed of exponentially stable subsystems, is extended via the general concept of comparison functions to systems which can be decomposed into asymptotically stable subsystems. Asymptotic stability of the composite system is tested by a simple algebraic criterion. With minor technical adjustments, the same criterion can be used to determine connective asymptotic stability of large-scale systems subject to structural perturbations. By redefining the constraints imposed on the interconnections among the subsystems, the considered class of systems is broadened in an essential way to include composite systems with unstable subsystems. In this way, the theory is brought substantially closer to reality since stability of all subsystems is no longer a necessary assumption in establishing stability of the overall composite system.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis

PubMed Central

Steele, Joe; Bastola, Dhundy

2014-01-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base–base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel–Ziv techniques from data compression. PMID:23904502

Elliptic surface grid generation on minimal and parmetrized surfaces

NASA Technical Reports Server (NTRS)

Spekreijse, S. P.; Nijhuis, G. H.; Boerstoel, J. W.

1995-01-01

An elliptic grid generation method is presented which generates excellent boundary conforming grids in domains in 2D physical space. The method is based on the composition of an algebraic and elliptic transformation. The composite mapping obeys the familiar Poisson grid generation system with control functions specified by the algebraic transformation. New expressions are given for the control functions. Grid orthogonality at the boundary is achieved by modification of the algebraic transformation. It is shown that grid generation on a minimal surface in 3D physical space is in fact equivalent to grid generation in a domain in 2D physical space. A second elliptic grid generation method is presented which generates excellent boundary conforming grids on smooth surfaces. It is assumed that the surfaces are parametrized and that the grid only depends on the shape of the surface and is independent of the parametrization. Concerning surface modeling, it is shown that bicubic Hermite interpolation is an excellent method to generate a smooth surface which is passing through a given discrete set of control points. In contrast to bicubic spline interpolation, there is extra freedom to model the tangent and twist vectors such that spurious oscillations are prevented.

ARK: Aggregation of Reads by K-Means for Estimation of Bacterial Community Composition.

PubMed

Koslicki, David; Chatterjee, Saikat; Shahrivar, Damon; Walker, Alan W; Francis, Suzanna C; Fraser, Louise J; Vehkaperä, Mikko; Lan, Yueheng; Corander, Jukka

2015-01-01

Estimation of bacterial community composition from high-throughput sequenced 16S rRNA gene amplicons is a key task in microbial ecology. Since the sequence data from each sample typically consist of a large number of reads and are adversely impacted by different levels of biological and technical noise, accurate analysis of such large datasets is challenging. There has been a recent surge of interest in using compressed sensing inspired and convex-optimization based methods to solve the estimation problem for bacterial community composition. These methods typically rely on summarizing the sequence data by frequencies of low-order k-mers and matching this information statistically with a taxonomically structured database. Here we show that the accuracy of the resulting community composition estimates can be substantially improved by aggregating the reads from a sample with an unsupervised machine learning approach prior to the estimation phase. The aggregation of reads is a pre-processing approach where we use a standard K-means clustering algorithm that partitions a large set of reads into subsets with reasonable computational cost to provide several vectors of first order statistics instead of only single statistical summarization in terms of k-mer frequencies. The output of the clustering is then processed further to obtain the final estimate for each sample. The resulting method is called Aggregation of Reads by K-means (ARK), and it is based on a statistical argument via mixture density formulation. ARK is found to improve the fidelity and robustness of several recently introduced methods, with only a modest increase in computational complexity. An open source, platform-independent implementation of the method in the Julia programming language is freely available at https://github.com/dkoslicki/ARK. A Matlab implementation is available at http://www.ee.kth.se/ctsoftware.

[A prediction model for the activity of insecticidal crystal proteins from Bacillus thuringiensis based on support vector machine].

PubMed

Lin, Yi; Cai, Fu-Ying; Zhang, Guang-Ya

2007-01-01

A quantitative structure-property relationship (QSPR) model in terms of amino acid composition and the activity of Bacillus thuringiensis insecticidal crystal proteins was established. Support vector machine (SVM) is a novel general machine-learning tool based on the structural risk minimization principle that exhibits good generalization when fault samples are few; it is especially suitable for classification, forecasting, and estimation in cases where small amounts of samples are involved such as fault diagnosis; however, some parameters of SVM are selected based on the experience of the operator, which has led to decreased efficiency of SVM in practical application. The uniform design (UD) method was applied to optimize the running parameters of SVM. It was found that the average accuracy rate approached 73% when the penalty factor was 0.01, the epsilon 0.2, the gamma 0.05, and the range 0.5. The results indicated that UD might be used an effective method to optimize the parameters of SVM and SVM and could be used as an alternative powerful modeling tool for QSPR studies of the activity of Bacillus thuringiensis (Bt) insecticidal crystal proteins. Therefore, a novel method for predicting the insecticidal activity of Bt insecticidal crystal proteins was proposed by the authors of this study.

A comprehensive study of the delay vector variance method for quantification of nonlinearity in dynamical systems

PubMed Central

Mandic, D. P.; Ryan, K.; Basu, B.; Pakrashi, V.

2016-01-01

Although vibration monitoring is a popular method to monitor and assess dynamic structures, quantification of linearity or nonlinearity of the dynamic responses remains a challenging problem. We investigate the delay vector variance (DVV) method in this regard in a comprehensive manner to establish the degree to which a change in signal nonlinearity can be related to system nonlinearity and how a change in system parameters affects the nonlinearity in the dynamic response of the system. A wide range of theoretical situations are considered in this regard using a single degree of freedom (SDOF) system to obtain numerical benchmarks. A number of experiments are then carried out using a physical SDOF model in the laboratory. Finally, a composite wind turbine blade is tested for different excitations and the dynamic responses are measured at a number of points to extend the investigation to continuum structures. The dynamic responses were measured using accelerometers, strain gauges and a Laser Doppler vibrometer. This comprehensive study creates a numerical and experimental benchmark for structurally dynamical systems where output-only information is typically available, especially in the context of DVV. The study also allows for comparative analysis between different systems driven by the similar input. PMID:26909175

Direct model-based predictive control scheme without cost function for voltage source inverters with reduced common-mode voltage

NASA Astrophysics Data System (ADS)

Kim, Jae-Chang; Moon, Sung-Ki; Kwak, Sangshin

2018-04-01

This paper presents a direct model-based predictive control scheme for voltage source inverters (VSIs) with reduced common-mode voltages (CMVs). The developed method directly finds optimal vectors without using repetitive calculation of a cost function. To adjust output currents with the CMVs in the range of -Vdc/6 to +Vdc/6, the developed method uses voltage vectors, as finite control resources, excluding zero voltage vectors which produce the CMVs in the VSI within ±Vdc/2. In a model-based predictive control (MPC), not using zero voltage vectors increases the output current ripples and the current errors. To alleviate these problems, the developed method uses two non-zero voltage vectors in one sampling step. In addition, the voltage vectors scheduled to be used are directly selected at every sampling step once the developed method calculates the future reference voltage vector, saving the efforts of repeatedly calculating the cost function. And the two non-zero voltage vectors are optimally allocated to make the output current approach the reference current as close as possible. Thus, low CMV, rapid current-following capability and sufficient output current ripple performance are attained by the developed method. The results of a simulation and an experiment verify the effectiveness of the developed method.

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.

Magnetic and electromagnetic properties of composites of iron oxide and Co-B alloy prepared by chemical reduction

NASA Astrophysics Data System (ADS)

Li, XueAi; Han, XiJiang; Du, YunChen; Xu, Ping

2011-01-01

Magnetic and electromagnetic properties were investigated on the composites of iron oxide and Co-B alloy, which were prepared by a modified chemical reduction method. The composites are characterized by scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDXA), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and vibrating sample magnetometry (VSM). The complex electromagnetic parameters (permittivity ɛr= ɛr'+j ɛr″ and permeability μr= μr'+j μr″) of paraffin mixed composite samples (paraffin:composites=1:1 in mass ratio) were measured in the frequency range 2-18 GHz by vector network analyzer. The measured real part ( ɛr') and imaginary part ( ɛr″) of the relative permittivity show two resonant peaks in the range of 2-18 GHz. The imaginary parts of relative permeability ( μr″) of all samples exhibited one broad resonant peak over the 2-8 GHz range. The μr″ of samples with higher molar ratio of Co to Fe (C and D) shows negative values within 13-18 GHz, which exhibit resonant and antiresonant permeabilities simultaneously. Calculation results indicated that the reflection loss values of the composites and paraffin wax mixtures are less than -10 dB with frequency width of about 6 GHz at the matching thickness.

Detection of ferromagnetic target based on mobile magnetic gradient tensor system

NASA Astrophysics Data System (ADS)

Gang, Y. I. N.; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

2016-03-01

Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source-sensor displacement vector. Secondly, unit source-sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source-sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source-sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source-sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method.

Land-Use Change Alters Host and Vector Communities and May Elevate Disease Risk.

PubMed

Guo, Fengyi; Bonebrake, Timothy C; Gibson, Luke

2018-04-24

Land-use change has transformed most of the planet. Concurrently, recent outbreaks of various emerging infectious diseases have raised great attention to the health consequences of anthropogenic environmental degradation. Here, we assessed the global impacts of habitat conversion and other land-use changes on community structures of infectious disease hosts and vectors, using a meta-analysis of 37 studies. From 331 pairwise comparisons of disease hosts/vectors in pristine (undisturbed) and disturbed areas, we found a decrease in species diversity but an increase in body size associated with land-use changes, potentially suggesting higher risk of infectious disease transmission in disturbed habitats. Neither host nor vector abundance, however, changed significantly following disturbance. When grouped by subcategories like disturbance type, taxonomic group, pathogen type and region, changes in host/vector community composition varied considerably. Fragmentation and agriculture in particular benefit host and vector communities and therefore might elevate disease risk. Our results indicate that while habitat disturbance could alter disease host/vector communities in ways that exacerbate pathogen prevalence, the relationship is highly context-dependent and influenced by multiple factors.

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

PubMed

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

2012-03-01

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

An improved method for identification of small non-coding RNAs in bacteria using support vector machine

NASA Astrophysics Data System (ADS)

Barman, Ranjan Kumar; Mukhopadhyay, Anirban; Das, Santasabuj

2017-04-01

Bacterial small non-coding RNAs (sRNAs) are not translated into proteins, but act as functional RNAs. They are involved in diverse biological processes like virulence, stress response and quorum sensing. Several high-throughput techniques have enabled identification of sRNAs in bacteria, but experimental detection remains a challenge and grossly incomplete for most species. Thus, there is a need to develop computational tools to predict bacterial sRNAs. Here, we propose a computational method to identify sRNAs in bacteria using support vector machine (SVM) classifier. The primary sequence and secondary structure features of experimentally-validated sRNAs of Salmonella Typhimurium LT2 (SLT2) was used to build the optimal SVM model. We found that a tri-nucleotide composition feature of sRNAs achieved an accuracy of 88.35% for SLT2. We validated the SVM model also on the experimentally-detected sRNAs of E. coli and Salmonella Typhi. The proposed model had robustly attained an accuracy of 81.25% and 88.82% for E. coli K-12 and S. Typhi Ty2, respectively. We confirmed that this method significantly improved the identification of sRNAs in bacteria. Furthermore, we used a sliding window-based method and identified sRNAs from complete genomes of SLT2, S. Typhi Ty2 and E. coli K-12 with sensitivities of 89.09%, 83.33% and 67.39%, respectively.

Feature Vector Construction Method for IRIS Recognition

NASA Astrophysics Data System (ADS)

Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

2017-05-01

One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

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.

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.

Comparison of algorithms for computing the two-dimensional discrete Hartley transform

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Burton, John C.; Miller, Keith W.

1989-01-01

Three methods have been described for computing the two-dimensional discrete Hartley transform. Two of these employ a separable transform, the third method, the vector-radix algorithm, does not require separability. In-place computation of the vector-radix method is described. Operation counts and execution times indicate that the vector-radix method is fastest.

Shrinkage vectors of a flowable composite in artificial cavity models with different boundary conditions: Ceramic and Teflon.

PubMed

Kaisarly, Dalia; El Gezawi, Moataz; Xu, Xiaohui; Rösch, Peter; Kunzelmann, Karl-Heinz

2018-01-01

Polymerization shrinkage of dental resin composites leads to stress build-up at the tooth-restoration interface that predisposes the restoration to debonding. In contrast to the heterogeneity of enamel and dentin, this study investigated the effect of boundary conditions in artificial cavity models such as ceramic and Teflon. Ceramic serves as a homogenous substrate that provides optimal bonding conditions, which we presented in the form of etched and silanized ceramic in addition to an etched, silanized and bonded ceramic cavity. In contrast, the Teflon cavity presented a non-adhesive boundary condition that provided an exaggerated condition of poor bonding as in the case of contamination during the application procedure or a poor bonding substrate such as sclerotic or deep dentin. The greatest 3D shrinkage vectors and movement in the axial direction were observed in the ceramic cavity with the bonding agent followed by the silanized ceramic cavity, and smallest shrinkage vectors and axial movements were observed in the Teflon cavity. The shrinkage vectors in the ceramic cavities exhibited downward movement toward the cavity bottom with great downward shrinkage of the free surface. The shrinkage vectors in the Teflon cavity pointed towards the center of the restoration with lateral movement greater at one side denoting the site of first detachment from the cavity walls. These results proved that the boundary conditions, in terms of bonding substrates, significantly influenced the shrinkage direction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust and accurate vectorization of line drawings.

PubMed

Hilaire, Xavier; Tombre, Karl

2006-06-01

This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.

Method and system for operating an electric motor

DOEpatents

Gallegos-Lopez, Gabriel; Hiti, Silva; Perisic, Milun

2013-01-22

Methods and systems for operating an electric motor having a plurality of windings with an inverter having a plurality of switches coupled to a voltage source are provided. A first plurality of switching vectors is applied to the plurality of switches. The first plurality of switching vectors includes a first ratio of first magnitude switching vectors to second magnitude switching vectors. A direct current (DC) current associated with the voltage source is monitored during the applying of the first plurality of switching vectors to the plurality of switches. A second ratio of the first magnitude switching vectors to the second magnitude switching vectors is selected based on the monitoring of the DC current associated with the voltage source. A second plurality of switching vectors is applied to the plurality of switches. The second plurality of switching vectors includes the second ratio of the first magnitude switching vectors to the second magnitude switching vectors.

Sine Rotation Vector Method for Attitude Estimation of an Underwater Robot

PubMed Central

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

2016-01-01

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

Improved method for predicting protein fold patterns with ensemble classifiers.

PubMed

Chen, W; Liu, X; Huang, Y; Jiang, Y; Zou, Q; Lin, C

2012-01-27

Protein folding is recognized as a critical problem in the field of biophysics in the 21st century. Predicting protein-folding patterns is challenging due to the complex structure of proteins. In an attempt to solve this problem, we employed ensemble classifiers to improve prediction accuracy. In our experiments, 188-dimensional features were extracted based on the composition and physical-chemical property of proteins and 20-dimensional features were selected using a coupled position-specific scoring matrix. Compared with traditional prediction methods, these methods were superior in terms of prediction accuracy. The 188-dimensional feature-based method achieved 71.2% accuracy in five cross-validations. The accuracy rose to 77% when we used a 20-dimensional feature vector. These methods were used on recent data, with 54.2% accuracy. Source codes and dataset, together with web server and software tools for prediction, are available at: http://datamining.xmu.edu.cn/main/~cwc/ProteinPredict.html.

Silkworms transformed with chimeric silkworm/spider silk genes spin composite silk fibers with improved mechanical properties

USDA-ARS?s Scientific Manuscript database

The development of a spider silk manufacturing process is of great interest. piggyBac vectors were used to create transgenic silkworms encoding chimeric silkworm/spider silk proteins. The silk fibers produced by these animals were composite materials that included chimeric silkworm/spider silk prote...

Using Chou's pseudo amino acid composition based on approximate entropy and an ensemble of AdaBoost classifiers to predict protein subnuclear location.

PubMed

Jiang, Xiaoying; Wei, Rong; Zhao, Yanjun; Zhang, Tongliang

2008-05-01

The knowledge of subnuclear localization in eukaryotic cells is essential for understanding the life function of nucleus. Developing prediction methods and tools for proteins subnuclear localization become important research fields in protein science for special characteristics in cell nuclear. In this study, a novel approach has been proposed to predict protein subnuclear localization. Sample of protein is represented by Pseudo Amino Acid (PseAA) composition based on approximate entropy (ApEn) concept, which reflects the complexity of time series. A novel ensemble classifier is designed incorporating three AdaBoost classifiers. The base classifier algorithms in three AdaBoost are decision stumps, fuzzy K nearest neighbors classifier, and radial basis-support vector machines, respectively. Different PseAA compositions are used as input data of different AdaBoost classifier in ensemble. Genetic algorithm is used to optimize the dimension and weight factor of PseAA composition. Two datasets often used in published works are used to validate the performance of the proposed approach. The obtained results of Jackknife cross-validation test are higher and more balance than them of other methods on same datasets. The promising results indicate that the proposed approach is effective and practical. It might become a useful tool in protein subnuclear localization. The software in Matlab and supplementary materials are available freely by contacting the corresponding author.

Evaluation of nutritional indicators and body composition in patients with advanced liver disease enrolled for liver transplantation.

PubMed

Vulcano, Daniela Salate Biagioni; Carvalhaes, Maria Antonieta de Barros Leite; Bakonyi Neto, Alexandre

2013-10-01

Malnutrition is prevalent in patients with advanced liver disease (LD) related to multifactorial causes. Fluid retention can underestimate the nutritional status based on anthropometric measures. We evaluated nutritional indicators and body composition (BC) in patients with liver cirrhosis and correlated them with LD severity. Forty three patients with LD enrolled for liver transplantation were evaluated by Anthropometric measures, subjective evaluation (Global Assessment of Nutritional Status - SGA) and biochemical indicators. Single-frequency electrical bioimpedance (SFE-BIA) was used to evaluate body composition (BC). It measured resistance (R), reactance (Xc) and the phase angle (PA). LD severity was estimated by Child-Pugh and Meld criteria (Model for End-Stage Liver Disease). Child-Pugh index between patients was 7.11 ± 1.70 and Meld was 12.23 ± 4.22. Arm Circumference, Arm Muscle Circumference and Arm Muscle Area, SGA, hemoglobin, hematocrit and albumin showed better correlation with disease severity. Xc and PA showed correlation both with Meld and Child-Pugh score when BC were evaluated. PA was depleted in 55.8% of the patients. Diagnosis of malnutrition varied according to the method. Global assessment of nutritional status showed better correlation with disease severity than with objective methods. Single-frequency electrical bioimpedance for body composition analysis in cirrhotic patients must be cautiously used; however, primary vectors seems to be valid and promising in clinical practice.

Video Vectorization via Tetrahedral Remeshing.

PubMed

Wang, Chuan; Zhu, Jie; Guo, Yanwen; Wang, Wenping

2017-02-09

We present a video vectorization method that generates a video in vector representation from an input video in raster representation. A vector-based video representation offers the benefits of vector graphics, such as compactness and scalability. The vector video we generate is represented by a simplified tetrahedral control mesh over the spatial-temporal video volume, with color attributes defined at the mesh vertices. We present novel techniques for simplification and subdivision of a tetrahedral mesh to achieve high simplification ratio while preserving features and ensuring color fidelity. From an input raster video, our method is capable of generating a compact video in vector representation that allows a faithful reconstruction with low reconstruction errors.

Development of versatile non-homologous end joining-based knock-in module for genome editing.

PubMed

Sawatsubashi, Shun; Joko, Yudai; Fukumoto, Seiji; Matsumoto, Toshio; Sugano, Shigeo S

2018-01-12

CRISPR/Cas9-based genome editing has dramatically accelerated genome engineering. An important aspect of genome engineering is efficient knock-in technology. For improved knock-in efficiency, the non-homologous end joining (NHEJ) repair pathway has been used over the homology-dependent repair pathway, but there remains a need to reduce the complexity of the preparation of donor vectors. We developed the versatile NHEJ-based knock-in module for genome editing (VIKING). Using the consensus sequence of the time-honored pUC vector to cut donor vectors, any vector with a pUC backbone could be used as the donor vector without customization. Conditions required to minimize random integration rates of the donor vector were also investigated. We attempted to isolate null lines of the VDR gene in human HaCaT keratinocytes using knock-in/knock-out with a selection marker cassette, and found 75% of clones isolated were successfully knocked-in. Although HaCaT cells have hypotetraploid genome composition, the results suggest multiple clones have VDR null phenotypes. VIKING modules enabled highly efficient knock-in of any vectors harboring pUC vectors. Users now can insert various existing vectors into an arbitrary locus in the genome. VIKING will contribute to low-cost genome engineering.

[Extraction Optimization of Rhizome of Curcuma longa by Response Surface Methodology and Support Vector Regression].

PubMed

Zhou, Pei-pei; Shan, Jin-feng; Jiang, Jian-lan

2015-12-01

To optimize the optimal microwave-assisted extraction method of curcuminoids from Curcuma longa. On the base of single factor experiment, the ethanol concentration, the ratio of liquid to solid and the microwave time were selected for further optimization. Support Vector Regression (SVR) and Central Composite Design-Response Surface Methodology (CCD) algorithm were utilized to design and establish models respectively, while Particle Swarm Optimization (PSO) was introduced to optimize the parameters of SVR models and to search optimal points of models. The evaluation indicator, the sum of curcumin, demethoxycurcumin and bisdemethoxycurcumin by HPLC, were used. The optimal parameters of microwave-assisted extraction were as follows: ethanol concentration of 69%, ratio of liquid to solid of 21 : 1, microwave time of 55 s. On those conditions, the sum of three curcuminoids was 28.97 mg/g (per gram of rhizomes powder). Both the CCD model and the SVR model were credible, for they have predicted the similar process condition and the deviation of yield were less than 1.2%.

Prediction and analysis of protein solubility using a novel scoring card method with dipeptide composition

PubMed Central

2012-01-01

Background Existing methods for predicting protein solubility on overexpression in Escherichia coli advance performance by using ensemble classifiers such as two-stage support vector machine (SVM) based classifiers and a number of feature types such as physicochemical properties, amino acid and dipeptide composition, accompanied with feature selection. It is desirable to develop a simple and easily interpretable method for predicting protein solubility, compared to existing complex SVM-based methods. Results This study proposes a novel scoring card method (SCM) by using dipeptide composition only to estimate solubility scores of sequences for predicting protein solubility. SCM calculates the propensities of 400 individual dipeptides to be soluble using statistic discrimination between soluble and insoluble proteins of a training data set. Consequently, the propensity scores of all dipeptides are further optimized using an intelligent genetic algorithm. The solubility score of a sequence is determined by the weighted sum of all propensity scores and dipeptide composition. To evaluate SCM by performance comparisons, four data sets with different sizes and variation degrees of experimental conditions were used. The results show that the simple method SCM with interpretable propensities of dipeptides has promising performance, compared with existing SVM-based ensemble methods with a number of feature types. Furthermore, the propensities of dipeptides and solubility scores of sequences can provide insights to protein solubility. For example, the analysis of dipeptide scores shows high propensity of α-helix structure and thermophilic proteins to be soluble. Conclusions The propensities of individual dipeptides to be soluble are varied for proteins under altered experimental conditions. For accurately predicting protein solubility using SCM, it is better to customize the score card of dipeptide propensities by using a training data set under the same specified experimental conditions. The proposed method SCM with solubility scores and dipeptide propensities can be easily applied to the protein function prediction problems that dipeptide composition features play an important role. Availability The used datasets, source codes of SCM, and supplementary files are available at http://iclab.life.nctu.edu.tw/SCM/. PMID:23282103

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

NASA Astrophysics Data System (ADS)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Assessment of geraniol-incorporated polymers to control Aedes albopictus (Diptera: culicidae)

PubMed Central

Chuaycharoensuk, T.; Manguin, S.; Duvallet, G.; Chareonviriyaphap, T.

2012-01-01

Effective control of mosquito borne diseases has proven extremely difficult with both vector and pathogen remaining entrenched and expanding in many disease endemic areas. When lacking an effective vaccine, vector control methods targeting both larval habitats and adult mosquito populations remain the primary strategy for reducing risk. Aedes albopictus from Thailand was used as a reference baseline for evaluation of natural insecticides incorporated in polymer disks and pellets and tested both in laboratory and field conditions. In laboratory and field tests, the highest larval mortality was obtained with disks or pellets containing IKHC (Insect Killer Highly Concentrate) from Fulltec AG Company. This product is reputed to contain geraniol as an active ingredient. With pellets, high mortality of Ae. albopictus larvae (92%) was observed in presence of 1 g of pellets per 500 ml of water at day 1st, and the mortality was 100% at day 1st for larvae in presence of 5 or 10 g of pellets. Fulltec AG Company has not accepted to give us the exact composition of their IKHC product. Therefore, we cannot recommend it, but the principle of using monoterpenes like geraniol, incorporated into polymer disks or pellets as natural larvicide needs more attention as it could be considered as a powerful alternative in mosquito vector control. PMID:22910616

Field Worker Evaluation of Dengue Vector Surveillance Methods: Factors That Determine Perceived Ease, Difficulty, Value, and Time Effectiveness in Australia and Malaysia.

PubMed

Azil, Aishah H; Ritchie, Scott A; Williams, Craig R

2015-10-01

This qualitative study aimed to describe field worker perceptions, evaluations of worth, and time costs of routine dengue vector surveillance methods in Cairns (Australia), Kuala Lumpur and Petaling District (Malaysia). In Cairns, the BG-Sentinel trap is a favored method for field workers because of its user-friendliness, but is not as cost-efficient as the sticky ovitrap. In Kuala Lumpur, the Mosquito Larvae Trapping Device is perceived as a solution for the inaccessibility of premises to larval surveys. Nonetheless, the larval survey method is retained in Malaysia for prompt detection of dengue vectors. For dengue vector surveillance to be successful, there needs to be not only technical, quantitative evaluations of method performance but also an appreciation of how amenable field workers are to using particular methods. Here, we report novel field worker perceptions of dengue vector surveillance methods in addition to time analysis for each method. © 2014 APJPH.

Vector and Raster Data Storage Based on Morton Code

NASA Astrophysics Data System (ADS)

Zhou, G.; Pan, Q.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Liu, X.

2018-05-01

Even though geomatique is so developed nowadays, the integration of spatial data in vector and raster formats is still a very tricky problem in geographic information system environment. And there is still not a proper way to solve the problem. This article proposes a method to interpret vector data and raster data. In this paper, we saved the image data and building vector data of Guilin University of Technology to Oracle database. Then we use ADO interface to connect database to Visual C++ and convert row and column numbers of raster data and X Y of vector data to Morton code in Visual C++ environment. This method stores vector and raster data to Oracle Database and uses Morton code instead of row and column and X Y to mark the position information of vector and raster data. Using Morton code to mark geographic information enables storage of data make full use of storage space, simultaneous analysis of vector and raster data more efficient and visualization of vector and raster more intuitive. This method is very helpful for some situations that need to analyse or display vector data and raster data at the same time.

Gene-carried hepatoma targeting complex induced high gene transfection efficiency with low toxicity and significant antitumor activity.

PubMed

Zhao, Qing-Qing; Hu, Yu-Lan; Zhou, Yang; Li, Ni; Han, Min; Tang, Gu-Ping; Qiu, Feng; Tabata, Yasuhiko; Gao, Jian-Qing

2012-01-01

The success of gene transfection is largely dependent on the development of a vehicle or vector that can efficiently deliver a gene to cells with minimal toxicity. A liver cancer-targeted specific peptide (FQHPSF sequence) was successfully synthesized and linked with chitosan-linked polyethylenimine (CP) to form a new targeted gene delivery vector called CPT (CP/peptide). The structure of CPT was confirmed by (1)H nuclear magnetic resonance spectroscopy and ultraviolet spectrophotometry. The particle size of CPT/ DNA complexes was measured using laser diffraction spectrometry and the cytotoxicity of the copolymer was evaluated by methylthiazol tetrazolium method. The transfection efficiency evaluation of the CP copolymer was performed using luciferase activity assay. Cellular internalization of the CP/DNA complex was observed under confocal laser scanning microscopy. The targeting specificity of the polymer coupled to peptide was measured by competitive inhibition transfection study. The liver targeting specificity of the CPT copolymer in vivo was demonstrated by combining the copolymer with a therapeutic gene, interleukin-12, and assessed by its abilities in suppressing the growth of ascites tumor in mouse model. The results showed that the liver cancer-targeted specific peptide was successfully synthesized and linked with CP to form a new targeted gene delivery vector called CPT. The composition of CPT was confirmed and the vector showed low cytotoxicity and strong targeting specificity to liver tumors in vitro. The in vivo study results showed that interleukin-12 delivered by the new gene vector CPT/DNA significantly enhanced the antitumor effect on ascites tumor-bearing imprinting control region mice as compared with polyethylenimine (25 kDa), CP, and other controls, which further demonstrate the targeting specificity of the new synthesized polymer. The synthesized CPT copolymer was proven to be an effective liver cancer-targeted vector for therapeutic gene delivery, which could be a potential candidate for targeted cancer gene therapy.

R0 for vector-borne diseases: impact of the assumption for the duration of the extrinsic incubation period.

PubMed

Hartemink, Nienke; Cianci, Daniela; Reiter, Paul

2015-03-01

Mathematical modeling and notably the basic reproduction number R0 have become popular tools for the description of vector-borne disease dynamics. We compare two widely used methods to calculate the probability of a vector to survive the extrinsic incubation period. The two methods are based on different assumptions for the duration of the extrinsic incubation period; one method assumes a fixed period and the other method assumes a fixed daily rate of becoming infectious. We conclude that the outcomes differ substantially between the methods when the average life span of the vector is short compared to the extrinsic incubation period.

Culicoides biting midges (Diptera, Ceratopogonidae) in various climatic zones of Russia and adjacent lands.

PubMed

Sprygin, A V; Fiodorova, O A; Babin, Yu Yu; Elatkin, N P; Mathieu, B; England, M E; Kononov, A V

2014-12-01

Culicoides biting midges play an important role in the epidemiology of many vector-borne infections, including bluetongue virus, an internationally important virus of ruminants. The territory of the Russian Federation includes regions with diverse climatic conditions and a wide range of habitats suitable for Culicoides. This review summarizes available data on Culicoides studied in the Russian Federation covering geographically different regions, as well as findings from adjacent countries. Previous literature on species composition, ranges of dominant species, breeding sites, and host preferences is reviewed and suggestions made for future studies to elucidate vector-virus relationships. © 2014 The Society for Vector Ecology.

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.

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.

Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles.

PubMed

Zou, Lingyun; Nan, Chonghan; Hu, Fuquan

2013-12-15

Various human pathogens secret effector proteins into hosts cells via the type IV secretion system (T4SS). These proteins play important roles in the interaction between bacteria and hosts. Computational methods for T4SS effector prediction have been developed for screening experimental targets in several isolated bacterial species; however, widely applicable prediction approaches are still unavailable In this work, four types of distinctive features, namely, amino acid composition, dipeptide composition, .position-specific scoring matrix composition and auto covariance transformation of position-specific scoring matrix, were calculated from primary sequences. A classifier, T4EffPred, was developed using the support vector machine with these features and their different combinations for effector prediction. Various theoretical tests were performed in a newly established dataset, and the results were measured with four indexes. We demonstrated that T4EffPred can discriminate IVA and IVB effectors in benchmark datasets with positive rates of 76.7% and 89.7%, respectively. The overall accuracy of 95.9% shows that the present method is accurate for distinguishing the T4SS effector in unidentified sequences. A classifier ensemble was designed to synthesize all single classifiers. Notable performance improvement was observed using this ensemble system in benchmark tests. To demonstrate the model's application, a genome-scale prediction of effectors was performed in Bartonella henselae, an important zoonotic pathogen. A number of putative candidates were distinguished. A web server implementing the prediction method and the source code are both available at http://bioinfo.tmmu.edu.cn/T4EffPred.

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

PubMed Central

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

2017-01-01

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

Composition of sand fly fauna (Diptera: Psychodidae) and detection of Leishmania DNA (Kinetoplastida: Trypanosomatidae) in different ecotopes from a rural settlement in the central Amazon, Brazil.

PubMed

Chagas, Erica Cristina da Silva; Silva, Arineia Soares; Fé, Nelson Ferreira; Ferreira, Lucas Silva; Sampaio, Vanderson de Souza; Terrazas, Wagner Cosme Morhy; Guerra, Jorge Augusto Oliveira; Souza, Rodrigo Augusto Ferreira de; Silveira, Henrique; Guerra, Maria das Graças Vale Barbosa

2018-03-13

Phlebotomine sand flies (Diptera: Psychodidae) are vectors of Leishmania species, the etiological agents of leishmaniasis, which is one of the most important emerging infectious diseases in the Americas. In the state of Amazonas in Brazil, anthropogenic activities encourage the presence of these insects around rural homes. The present study aimed to describe the composition and distribution of sand fly species diversity among the ecotopes (intradomicile, peridomicile and forest) in an area of American cutaneous leishmaniasis transmission and detect natural infection with Leishmania DNA to evaluate which vectors are inside houses and whether the presence of possible vectors represents a hazard of transmission. Phlebotomine sand flies were collected using light traps. A total of 2469 specimens representing 54 species, predominantly females (71.2%), were collected from four sites. Polymerase chain reaction analysis was performed on 670 samples to detect Leishmania DNA. Most of the samples (79.5%) were collected in the forest, with areas closer to rural dwellings yielding a greater abundance of suspected or proven vectors and a larger number of species containing Leishmania DNA. Nyssomyia umbratilis and Bichromomyia flaviscutellata were found near rural homes, and Ny. umbratilis was also found inside homes. Leishmania DNA was detected in different species of sand flies in all ecotopes, including species with no previous record of natural infection. There is no evidence that vectors of American cutaneous leishmaniasis are becoming established inside homes, but there are sand flies, including Ny. umbratilis and other possible vectors, in environments characterized by a human presence. These species continue to be predominant in the forest but are prevalent in areas closer to ecotopes with a greater human presence. The existence of proven or suspected vectors in this ecotope is due to the structural organization of rural settlements and may represent a hazard of transmission. Although the detection of Leishmania DNA in species that were not previously considered vectors does not mean that they are transmitting the parasite, it does show that the parasite is circulating in ecotopes where these species are found.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

PubMed

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

Malaria vector composition and insecticide susceptibility status in Guinea Conakry, West Africa.

PubMed

Vezenegho, S B; Brooke, B D; Hunt, R H; Coetzee, M; Koekemoer, L L

2009-12-01

This study provides data on malaria vector species composition and insecticide susceptibility status from three localities in Guinea Conakry. A total of 497 mosquitoes were collected resting indoors and morphologically identified as belonging to the Anopheles gambiae complex. The majority of these were An. gambiae s.s. (99.6%), but a small percentage (0.4%) were identified as Anopheles arabiensis. Thirty-four Anopheles funestus s.s. were also collected. The molecular S form of An. gambiae s.s. was predominant over the M form in Siguiri (95%) and Boffa (97.4%), whereas at Mt Nimba the M form was more abundant (61.4%) than the S form (38.1%). One hybrid M/S specimen was recorded from Mt Nimba. Siguiri populations showed high levels of resistance to DDT, dieldrin and bendiocarb. Anopheles gambiae from Boffa were largely susceptible to the insecticides tested. At Mt Nimba, resistance to DDT and bendicocarb was detected. Biochemical enzyme analysis showed that an altered acetylcholinesterase is operating in the field at low levels. The frequency of the 1014F kdr allele in the An. gambiae S form was 0.24 at Siguiri and 0.14 at Mt Nimba. A single RR specimen was found in the M form. The heterogeneity in species composition and resistance profiles between sites requires vector control interventions to be tailored to each site based on the data collected from ongoing monitoring and surveillance.

Colonization by Phloem-Feeding Herbivore Overrides Effects of Plant Virus on Amino Acid Composition in Phloem of Chili Plants.

PubMed

Ángeles-López, Yesenia Ithaí; Rivera-Bustamante, Rafael F; Heil, Martin

2016-10-01

The 'adaptive host manipulation' hypothesis predicts that parasites can enhance their transmission rates via manipulation of their host's phenotype. For example, many plant pathogens alter the nutritional quality of their host for herbivores that serve as their vectors. However, herbivores, including non-vectors, might cause additional alterations in the plant phenotype. Here, we studied changes in the amino acid (AA) content in the phloem of chilli (Capsicum annuum) plants infected with Pepper golden mosaic virus (PepGMV) upon subsequent colonization with a non-vector, the phloem-feeding whitefly (Trialeurodes vaporariorum). Virus infection alone caused an almost 30-fold increase in overall phloem AAs, but colonization by T. vaporariorum completely reversed this effect. At the level of individual AAs, contents of proline, tyrosine, and valine increased, and histidine and alanine decreased in PepGMV -infected as compared to control plants, whereas colonization by T. vaporariorum caused decreased contents of proline, tyrosine, and valine, and increased contents of histidine and alanine. Overall, the colonization by the whitefly had much stronger effects on phloem AA composition than virus infection. We conclude that the phloem composition of a virus-infected host plant can rapidly change upon arrival of an herbivore and that these changes need to be monitored to predict the nutritional quality of the plant in the long run.

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.

An Investigation into the Protein Composition of the Teneral Glossina morsitans morsitans Peritrophic Matrix

PubMed Central

Rose, Clair; Belmonte, Rodrigo; Armstrong, Stuart D.; Molyneux, Gemma; Haines, Lee R.; Lehane, Michael J.; Wastling, Jonathan; Acosta-Serrano, Alvaro

2014-01-01

Background Tsetse flies serve as biological vectors for several species of African trypanosomes. In order to survive, proliferate and establish a midgut infection, trypanosomes must cross the tsetse fly peritrophic matrix (PM), which is an acellular gut lining surrounding the blood meal. Crossing of this multi-layered structure occurs at least twice during parasite migration and development, but the mechanism of how trypanosomes do so is not understood. In order to better comprehend the molecular events surrounding trypanosome penetration of the tsetse PM, a mass spectrometry-based approach was applied to investigate the PM protein composition using Glossina morsitans morsitans as a model organism. Methods PMs from male teneral (young, unfed) flies were dissected, solubilised in urea/SDS buffer and the proteins precipitated with cold acetone/TCA. The PM proteins were either subjected to an in-solution tryptic digestion or fractionated on 1D SDS-PAGE, and the resulting bands digested using trypsin. The tryptic fragments from both preparations were purified and analysed by LC-MS/MS. Results Overall, nearly 300 proteins were identified from both analyses, several of those containing signature Chitin Binding Domains (CBD), including novel peritrophins and peritrophin-like glycoproteins, which are essential in maintaining PM architecture and may act as trypanosome adhesins. Furthermore, 27 proteins from the tsetse secondary endosymbiont, Sodalis glossinidius, were also identified, suggesting this bacterium is probably in close association with the tsetse PM. Conclusion To our knowledge this is the first report on the protein composition of teneral G. m. morsitans, an important vector of African trypanosomes. Further functional analyses of these proteins will lead to a better understanding of the tsetse physiology and may help identify potential molecular targets to block trypanosome development within the tsetse. PMID:24763256

Determination Of Constituent Concentration In Fluid Mixtures Using Magnetic Resonance Imaging

NASA Astrophysics Data System (ADS)

Galloway, Robert L.; Collins, Jerry C.; Carroll, Frank E.

1987-01-01

The primary application of magnetic resonance imaging (MRI) has been qualitative and anatomical evaluation of patient status. Recent efforts to analyze image information for quantitative evaluation centered on two relaxation parameters, Tl and T2, as the descriptors for the image data. In our work we have found that relaxation curves for biologic materials cannot be described by a monoexponential function and that, in a spin echo system, calculated Tl values are dependent on repetition time. This finding is not unexpected since, in physiologic imaging, any region of interest (ROI), is composed of a number of distinct substances and the response of that ROI will be a composite of the constituent materials. The purpose of our study was to develop a method by which the relaxation behaviors of a composite of physiological material might be characterized and use that characterization to determine its constituent materials. We created a phantom in which volumes of several "pure" materials (blood, plasma, saline and oil) were available as well as volumes which contained concentric enclosures of the pure materials. Images were formed at a number of repetition times, ranging from 160 milliseconds to 2 seconds. The image data was then transferred to a VAX 11/750 where regions of interest were marked and the mean image intensity for each ROI at each repetition time was calculated. The resultant relaxation curves of the pure materials formed basis vectors for the composite responses and the fractional content of each material was determined by a least-square error fit to the basis vectors. Excellent agreement was seen between known and measured mixture percentages. Ongoing work is centered around optimizing repetition time selection and accounting for the interaction between species in the mixtures.

PLATE WAVE RESONANCE WITH AIR-COUPLED ULTRASONICS

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

Bar, H. N.; Dayal, V.; Barnard, D.

2010-02-22

Air-coupled ultrasonic transducers can excite plate waves in metals and composites. The coincidence effect, i.e., the wave vector of plate wave coincides with projection of exciting airborne sound vector, leads to a resonance which strongly amplifies the sound transmission through the plate. The resonance depends on the angle of incidence and the frequency. In the present study, the incidence angle for maximum transmission (theta{sub max}) is measured in plates of steel, aluminum, carbon fiber reinforced composites and honeycomb sandwich panels. The variations of (theta{sub max}) with plate thickness are compared with theoretical values in steel, aluminum and quasi-isotropic carbon fibermore » composites. The enhanced transmission of air-coupled ultrasound at oblique incidence can substantially improve the probability of flaw detection in plates and especially in honeycomb structures. Experimental air-coupled ultrasonic scan of subtle flaws in CFRP laminates showed definite improvement of signal-to-noise ratio with oblique incidence at theta{sub max}.« less

Effects of landscape anthropization on mosquito community composition and abundance

NASA Astrophysics Data System (ADS)

Ferraguti, Martina; Martínez-de La Puente, Josué; Roiz, David; Ruiz, Santiago; Soriguer, Ramón; Figuerola, Jordi

2016-07-01

Anthropogenic landscape transformation has an important effect on vector-borne pathogen transmission. However, the effects of urbanization on mosquito communities are still only poorly known. Here, we evaluate how land-use characteristics are related to the abundance and community composition of mosquitoes in an area with endemic circulation of numerous mosquito-borne pathogens. We collected 340 829 female mosquitoes belonging to 13 species at 45 localities spatially grouped in 15 trios formed by 1 urban, 1 rural and 1 natural area. Mosquito abundance and species richness were greater in natural and rural areas than in urban areas. Environmental factors including land use, vegetation and hydrological characteristics were related to mosquito abundance and community composition. Given the differing competences of each species in pathogen transmission, these results provide valuable information on the transmission potential of mosquito-borne pathogens that will be of great use in public and animal health management by allowing, for instance, the identification of the priority areas for pathogen surveillance and vector control.

Effects of landscape anthropization on mosquito community composition and abundance

PubMed Central

Ferraguti, Martina; Martínez-de la Puente, Josué; Roiz, David; Ruiz, Santiago; Soriguer, Ramón; Figuerola, Jordi

2016-01-01

Anthropogenic landscape transformation has an important effect on vector-borne pathogen transmission. However, the effects of urbanization on mosquito communities are still only poorly known. Here, we evaluate how land-use characteristics are related to the abundance and community composition of mosquitoes in an area with endemic circulation of numerous mosquito-borne pathogens. We collected 340 829 female mosquitoes belonging to 13 species at 45 localities spatially grouped in 15 trios formed by 1 urban, 1 rural and 1 natural area. Mosquito abundance and species richness were greater in natural and rural areas than in urban areas. Environmental factors including land use, vegetation and hydrological characteristics were related to mosquito abundance and community composition. Given the differing competences of each species in pathogen transmission, these results provide valuable information on the transmission potential of mosquito-borne pathogens that will be of great use in public and animal health management by allowing, for instance, the identification of the priority areas for pathogen surveillance and vector control. PMID:27373794

In-plane time-harmonic elastic wave motion and resonance phenomena in a layered phononic crystal with periodic cracks.

PubMed

Golub, Mikhail V; Zhang, Chuanzeng

2015-01-01

This paper presents an elastodynamic analysis of two-dimensional time-harmonic elastic wave propagation in periodically multilayered elastic composites, which are also frequently referred to as one-dimensional phononic crystals, with a periodic array of strip-like interior or interface cracks. The transfer matrix method and the boundary integral equation method in conjunction with the Bloch-Floquet theorem are applied to compute the elastic wave fields in the layered periodic composites. The effects of the crack size, spacing, and location, as well as the incidence angle and the type of incident elastic waves on the wave propagation characteristics in the composite structure are investigated in details. In particular, the band-gaps, the localization and the resonances of elastic waves are revealed by numerical examples. In order to understand better the wave propagation phenomena in layered phononic crystals with distributed cracks, the energy flow vector of Umov and the corresponding energy streamlines are visualized and analyzed. The numerical results demonstrate that large energy vortices obstruct elastic wave propagation in layered phononic crystals at resonance frequencies. They occur before the cracks reflecting most of the energy transmitted by the incoming wave and disappear when the problem parameters are shifted from the resonant ones.

Environmental management through sluice gated bed-dam: a revived strategy for the control of Anopheles fluviatilis breeding in streams

PubMed Central

Sahu, S.S.; Gunasekaran, K.; Jambulingam, P.

2014-01-01

Background & objectives: Integrated vector management (IVM) emphasizes sustainable eco-friendly methods and minimal use of chemicals. In this context, the present study highlights the environmental control of breeding of Anopheles fluviatilis, the primary malaria vector, through water management in a natural stream in Koraput district, Odisha, India. Methods: The District Rural Development Agency (DRDA), Koraput, constructed two bed-dams across streams, one in Barigaon and the other in Pipalapodar village. The bed-dam in the former village was fitted with two sluice gates whereas the bed dam constructed in the latter village was without the sluice gate. The sluice gates were opened once in a week on a fixed day to flush out the water from the dam. Anopheles immatures were sampled systematically in the streams using a dipper for density measurement and species composition. Results: There was a reduction of 84.9 per cent in the proportion of positive dips for Anopheles larvae/pupae and a reduction of 98.4 per cent in immature density (number/dip) of An. fluviatilis in the experimental downstream compared to the control following opening of the sluice gates. Interpretation & conclusions: Our findins showed that opening of sluice gates of the bed-dam regularly once in a week resulted in the control of vector breeding in the downstream due to the flushing effect of the water released with a high flow from the bed-dam that stagnated water in the upstream. The outcome of the study encourages upscaling this measure to other areas, wherever feasible. PMID:25297364

Effects of Natural Rubber on Microwave Absorption Characteristics of Some Li-Ni-Zn Ferrite-Thermoplastic Natural Rubber Composites

NASA Astrophysics Data System (ADS)

Abdul Hamid, Siti Atkah; Abdullah, Mustaffa Hj.; Ahmad, Sahrim Hj.; Mansor, Abdul Aziz; Yusoff, Ahmad Nazlim

2002-09-01

A microwave (Li0.5Fe0.5)0.4Ni0.3Zn0.3Fe2O4 (LNZ) ferrite was prepared by a conventional sintering method in air. Thermoplastic natural rubber (TPNR) was prepared from polypropylene (PP) and natural rubber (NR) in the ratios of 80:20, 70:30, 60:40, 50:50 and 40:60 with liquid natural rubber as a compatibilizer by a melt blending technique. LNZ ferrite-TPNR composites with 20 wt% ferrite filler were prepared using a Brabender plasticorder internal mixer. The microwave electromagnetic properties of the composites were studied in the frequency range of 0.3-13.5 GHz using a microwave vector network analyzer (MVNA). The real and imaginary components of the relative complex dielectric permittivity (\\varepsilonr*=\\varepsilonr\\prime-j\\varepsilonr\\prime\\prime) and magnetic permeability (μr*=μr\\prime-jμr\\prime\\prime) were calculated from the measured complex scattering parameters (S11* and S12*) using the Nicolson-Ross model. The dielectric and magnetic properties were found to depend on the NR and PP content in the composites. The minimum reflection loss (RL) under the matching conditions increases with increasing NR content.

The sustained-release behavior and in vitro and in vivo transfection of pEGFP-loaded core-shell-structured chitosan-based composite particles

PubMed Central

Wang, Yun; Lin, Fu-xing; Zhao, Yu; Wang, Mo-zhen; Ge, Xue-wu; Gong, Zheng-xing; Bao, Dan-dan; Gu, Yu-fang

2014-01-01

Novel submicron core-shell-structured chitosan-based composite particles encapsulated with enhanced green fluorescent protein plasmids (pEGFP) were prepared by complex coacervation method. The core was pEGFP-loaded thiolated N-alkylated chitosan (TACS) and the shell was pH- and temperature-responsive hydroxybutyl chitosan (HBC). pEGFP-loaded TACS-HBC composite particles were spherical, and had a mean diameter of approximately 120 nm, as measured by transmission electron microscopy and particle size analyzer. pEGFP showed sustained release in vitro for >15 days. Furthermore, in vitro transfection in human embryonic kidney 293T and human cervix epithelial cells, and in vivo transfection in mice skeletal muscle of loaded pEGFP, were investigated. Results showed that the expression of loaded pEGFP, both in vitro and in vivo, was slow but could be sustained over a long period. pEGFP expression in mice skeletal muscle was sustained for >60 days. This work indicates that these submicron core-shell-structured chitosan-based composite particles could potentially be used as a gene vector for in vivo controlled gene transfection. PMID:25364253

The sustained-release behavior and in vitro and in vivo transfection of pEGFP-loaded core-shell-structured chitosan-based composite particles.

PubMed

Wang, Yun; Lin, Fu-xing; Zhao, Yu; Wang, Mo-zhen; Ge, Xue-wu; Gong, Zheng-xing; Bao, Dan-dan; Gu, Yu-fang

2014-01-01

Novel submicron core-shell-structured chitosan-based composite particles encapsulated with enhanced green fluorescent protein plasmids (pEGFP) were prepared by complex coacervation method. The core was pEGFP-loaded thiolated N-alkylated chitosan (TACS) and the shell was pH- and temperature-responsive hydroxybutyl chitosan (HBC). pEGFP-loaded TACS-HBC composite particles were spherical, and had a mean diameter of approximately 120 nm, as measured by transmission electron microscopy and particle size analyzer. pEGFP showed sustained release in vitro for >15 days. Furthermore, in vitro transfection in human embryonic kidney 293T and human cervix epithelial cells, and in vivo transfection in mice skeletal muscle of loaded pEGFP, were investigated. Results showed that the expression of loaded pEGFP, both in vitro and in vivo, was slow but could be sustained over a long period. pEGFP expression in mice skeletal muscle was sustained for >60 days. This work indicates that these submicron core-shell-structured chitosan-based composite particles could potentially be used as a gene vector for in vivo controlled gene transfection.

A scalable method for the production of high-titer and high-quality adeno-associated type 9 vectors using the HSV platform

PubMed Central

Adamson-Small, Laura; Potter, Mark; Falk, Darin J; Cleaver, Brian; Byrne, Barry J; Clément, Nathalie

2016-01-01

Recombinant adeno-associated vectors based on serotype 9 (rAAV9) have demonstrated highly effective gene transfer in multiple animal models of muscular dystrophies and other neurological indications. Current limitations in vector production and purification have hampered widespread implementation of clinical candidate vectors, particularly when systemic administration is considered. In this study, we describe a complete herpes simplex virus (HSV)-based production and purification process capable of generating greater than 1 × 1014 rAAV9 vector genomes per 10-layer CellSTACK of HEK 293 producer cells, or greater than 1 × 105 vector genome per cell, in a final, fully purified product. This represents a 5- to 10-fold increase over transfection-based methods. In addition, rAAV vectors produced by this method demonstrated improved biological characteristics when compared to transfection-based production, including increased infectivity as shown by higher transducing unit-to-vector genome ratios and decreased total capsid protein amounts, shown by lower empty-to-full ratios. Together, this data establishes a significant improvement in both rAAV9 yields and vector quality. Further, the method can be readily adapted to large-scale good laboratory practice (GLP) and good manufacturing practice (GMP) production of rAAV9 vectors to enable preclinical and clinical studies and provide a platform to build on toward late-phases and commercial production. PMID:27222839

Onchocerciasis transmission in Ghana: the human blood index of sibling species of the Simulium damnosum complex.

PubMed

Lamberton, Poppy H L; Cheke, Robert A; Walker, Martin; Winskill, Peter; Crainey, J Lee; Boakye, Daniel A; Osei-Atweneboana, Mike Y; Tirados, Iñaki; Wilson, Michael D; Tetteh-Kumah, Anthony; Otoo, Sampson; Post, Rory J; Basañez, María-Gloria

2016-08-05

Vector-biting behaviour is important for vector-borne disease (VBD) epidemiology. The proportion of blood meals taken on humans (the human blood index, HBI), is a component of the biting rate per vector on humans in VBD transmission models. Humans are the definitive host of Onchocerca volvulus, but the simuliid vectors feed on a range of animals and HBI is a key indicator of the potential for human onchocerciasis transmission. Ghana has a diversity of Simulium damnosum complex members, which are likely to vary in their HBIs, an important consideration for parameterization of onchocerciasis control and elimination models. Host-seeking and ovipositing S. damnosum (sensu lato) (s.l.) were collected from seven villages in four Ghanaian regions. Taxa were morphologically and molecularly identified. Blood meals from individually stored blackfly abdomens were used for DNA profiling, to identify previous host choice. Household, domestic animal, wild mammal and bird surveys were performed to estimate the density and diversity of potential blood hosts of blackflies. A total of 11,107 abdomens of simuliid females (which would have obtained blood meal(s) previously) were tested, with blood meals successfully amplified in 3,772 (34 %). A single-host species was identified in 2,857 (75.7 %) of the blood meals, of which 2,162 (75.7 %) were human. Simulium soubrense Beffa form, S. squamosum C and S. sanctipauli Pra form were the most anthropophagic (HBI = 0.92, 0.86 and 0.70, respectively); S. squamosum E, S. yahense and S. damnosum (sensu stricto) (s.s.)/S. sirbanum were the most zoophagic (HBI = 0.44, 0.53 and 0.63, respectively). The degree of anthropophagy decreased (but not statistically significantly) with increasing ratio of non-human/human blood hosts. Vector to human ratios ranged from 139 to 1,198 blackflies/person. DNA profiling can successfully identify blood meals from host-seeking and ovipositing blackflies. Host choice varies according to sibling species, season and capture site/method. There was no evidence that HBI is vector and/or host density dependent. Transmission breakpoints will vary among locations due to differing cytospecies compositions and vector abundances.

Electron backscatter diffraction as a domain analysis technique in BiFeO(3)-PbTiO(3) single crystals.

PubMed

Burnett, T L; Comyn, T P; Merson, E; Bell, A J; Mingard, K; Hegarty, T; Cain, M

2008-05-01

xBiFeO(3)-(1-x)PbTiO(3) single crystals were grown via a flux method for a range of compositions. Presented here is a study of the domain configuration in the 0.5BiFeO(3)-0.5PbTiO(3) composition using electron backscatter diffraction to demonstrate the ability of the technique to map ferroelastic domain structures at the micron and submicron scale. The micron-scale domains exhibit an angle of approximately 85 degrees between each variant, indicative of a ferroelastic domain wall in a tetragonal system with a spontaneous strain, c/a - 1 of 0.10, in excellent agreement with the lattice parameters derived from x-ray diffraction. Contrast seen in forescatter images is attributed to variations in the direction of the electrical polarization vector, providing images of ferroelectric domain patterns.

Combination of complementary data mining methods for geographical characterization of extra virgin olive oils based on mineral composition.

PubMed

Sayago, Ana; González-Domínguez, Raúl; Beltrán, Rafael; Fernández-Recamales, Ángeles

2018-09-30

This work explores the potential of multi-element fingerprinting in combination with advanced data mining strategies to assess the geographical origin of extra virgin olive oil samples. For this purpose, the concentrations of 55 elements were determined in 125 oil samples from multiple Spanish geographic areas. Several unsupervised and supervised multivariate statistical techniques were used to build classification models and investigate the relationship between mineral composition of olive oils and their provenance. Results showed that Spanish extra virgin olive oils exhibit characteristic element profiles, which can be differentiated on the basis of their origin in accordance with three geographical areas: Atlantic coast (Huelva province), Mediterranean coast and inland regions. Furthermore, statistical modelling yielded high sensitivity and specificity, principally when random forest and support vector machines were employed, thus demonstrating the utility of these techniques in food traceability and authenticity research. Copyright © 2018 Elsevier Ltd. All rights reserved.

A New Unified Analysis of Estimate Errors by Model-Matching Phase-Estimation Methods for Sensorless Drive of Permanent-Magnet Synchronous Motors and New Trajectory-Oriented Vector Control, Part II

NASA Astrophysics Data System (ADS)

Shinnaka, Shinji

This paper presents a new unified analysis of estimate errors by model-matching extended-back-EMF estimation methods for sensorless drive of permanent-magnet synchronous motors. Analytical solutions about estimate errors, whose validity is confirmed by numerical experiments, are rich in universality and applicability. As an example of universality and applicability, a new trajectory-oriented vector control method is proposed, which can realize directly quasi-optimal strategy minimizing total losses with no additional computational loads by simply orienting one of vector-control coordinates to the associated quasi-optimal trajectory. The coordinate orientation rule, which is analytically derived, is surprisingly simple. Consequently the trajectory-oriented vector control method can be applied to a number of conventional vector control systems using model-matching extended-back-EMF estimation methods.

A new method for the prediction of chatter stability lobes based on dynamic cutting force simulation model and support vector machine

NASA Astrophysics Data System (ADS)

Peng, Chong; Wang, Lun; Liao, T. Warren

2015-10-01

Currently, chatter has become the critical factor in hindering machining quality and productivity in machining processes. To avoid cutting chatter, a new method based on dynamic cutting force simulation model and support vector machine (SVM) is presented for the prediction of chatter stability lobes. The cutting force is selected as the monitoring signal, and the wavelet energy entropy theory is used to extract the feature vectors. A support vector machine is constructed using the MATLAB LIBSVM toolbox for pattern classification based on the feature vectors derived from the experimental cutting data. Then combining with the dynamic cutting force simulation model, the stability lobes diagram (SLD) can be estimated. Finally, the predicted results are compared with existing methods such as zero-order analytical (ZOA) and semi-discretization (SD) method as well as actual cutting experimental results to confirm the validity of this new method.

B-decay anomalies in a composite leptoquark model

DOE PAGES

Barbieri, Riccardo; Murphy, Christopher W.; Senia, Fabrizio

2016-12-30

Here, the collection of a few anomalies in semileptonic B-decays, especially in b → cτmore » $$\\overline{v}$$, invites speculation about the emergence of some striking new phenomena, perhaps interpretable in terms of a weakly broken U(2) n flavor symmetry and of leptoquark mediators. We aim at a partial UV completion of this interpretation by generalizing the minimal composite Higgs model to include a composite vector leptoquark as well.« less

αAMG based on Weighted Matching for Systems of Elliptic PDEs Arising From Displacement and Mixed Methods

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

D'Ambra, P.; Vassilevski, P. S.

2014-05-30

Adaptive Algebraic Multigrid (or Multilevel) Methods (αAMG) are introduced to improve robustness and efficiency of classical algebraic multigrid methods in dealing with problems where no a-priori knowledge or assumptions on the near-null kernel of the underlined matrix are available. Recently we proposed an adaptive (bootstrap) AMG method, αAMG, aimed to obtain a composite solver with a desired convergence rate. Each new multigrid component relies on a current (general) smooth vector and exploits pairwise aggregation based on weighted matching in a matrix graph to define a new automatic, general-purpose coarsening process, which we refer to as “the compatible weighted matching”. Inmore » this work, we present results that broaden the applicability of our method to different finite element discretizations of elliptic PDEs. In particular, we consider systems arising from displacement methods in linear elasticity problems and saddle-point systems that appear in the application of the mixed method to Darcy problems.« less

Method for introducing unidirectional nested deletions

DOEpatents

Dunn, John J.; Quesada, Mark A.; Randesi, Matthew

2001-01-01

Disclosed is a method for the introduction of unidirectional deletions in a cloned DNA segment in the context of a cloning vector which contains an f1 endonuclease recognition sequence adjacent to the insertion site of the DNA segment. Also disclosed is a method for producing single-stranded DNA probes utilizing the same cloning vector. An optimal vector, PZIP is described. Methods for introducing unidirectional deletions into a terminal location of a cloned DNA sequence which is inserted into the vector of the present invention are also disclosed. These methods are useful for introducing deletions into either or both ends of a cloned DNA insert, for high throughput sequencing of any DNA of interest.

Ecological determinants of avian malaria infections: An integrative analysis at landscape, mosquito and vertebrate community levels.

PubMed

Ferraguti, Martina; Martínez-de la Puente, Josué; Bensch, Staffan; Roiz, David; Ruiz, Santigo; Viana, Duarte S; Soriguer, Ramón C; Figuerola, Jordi

2018-05-01

Vector and host communities, as well as habitat characteristics, may have important but different impacts on the prevalence, richness and evenness of vector-borne parasites. We investigated the relative importance of (1) the mosquito community composition, (2) the vertebrate community composition and (3) landscape characteristics on the prevalence, richness and evenness of avian Plasmodium. We hypothesized that parasite prevalence will be more affected by vector-related parameters, while host parameters should be also important to explain Plasmodium richness and evenness. We sampled 2,588 wild house sparrows (Passer domesticus) and 340,829 mosquitoes, and we performed vertebrate censuses at 45 localities in the Southwest of Spain. These localities included urban, rural and natural landscapes that were characterized by several habitat variables. Twelve Plasmodium lineages were identified in house sparrows corresponding to three major clades. Variation partitioning showed that landscape characteristics explained the highest fraction of variation in all response variables (21.0%-44.8%). Plasmodium prevalence was in addition explained by vector-related variables (5.4%) and its interaction with landscape (10.2%). Parasite richness and evenness were mostly explained by vertebrate community-related variables. The structuring role of landscape characteristics in vector and host communities was a key factor in determining parasite prevalence, richness and evenness, although the role of each factor differed according to the parasite parameters studied. These results show that the biotic and abiotic contexts are important to explain the transmission dynamics of mosquito-borne pathogens in the wild. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

A method to determine fault vectors in 4H-SiC from stacking sequences observed on high resolution transmission electron microscopy images

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

Wu, Fangzhen; Wang, Huanhuan; Raghothamachar, Balaji

A new method has been developed to determine the fault vectors associated with stacking faults in 4H-SiC from their stacking sequences observed on high resolution TEM images. This method, analogous to the Burgers circuit technique for determination of dislocation Burgers vector, involves determination of the vectors required in the projection of the perfect lattice to correct the deviated path constructed in the faulted material. Results for several different stacking faults were compared with fault vectors determined from X-ray topographic contrast analysis and were found to be consistent. This technique is expected to applicable to all structures comprising corner shared tetrahedra.

A Two-Layer Least Squares Support Vector Machine Approach to Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Liu, Jingli; Li, Jianping; Xu, Weixuan; Shi, Yong

Least squares support vector machine (LS-SVM) is a revised version of support vector machine (SVM) and has been proved to be a useful tool for pattern recognition. LS-SVM had excellent generalization performance and low computational cost. In this paper, we propose a new method called two-layer least squares support vector machine which combines kernel principle component analysis (KPCA) and linear programming form of least square support vector machine. With this method sparseness and robustness is obtained while solving large dimensional and large scale database. A U.S. commercial credit card database is used to test the efficiency of our method and the result proved to be a satisfactory one.

Singer product apertures-A coded aperture system with a fast decoding algorithm

NASA Astrophysics Data System (ADS)

Byard, Kevin; Shutler, Paul M. E.

2017-06-01

A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.

Methods for determining remanent and total magnetisations of magnetic sources - a review

NASA Astrophysics Data System (ADS)

Clark, David A.

2014-07-01

Assuming without evidence that magnetic sources are magnetised parallel to the geomagnetic field can seriously mislead interpretation and can result in drill holes missing their targets. This article reviews methods that are available for estimating, directly or indirectly, the natural remanent magnetisation (NRM) and total magnetisation of magnetic sources, noting the strengths and weaknesses of each approach. These methods are: (i) magnetic property measurements of samples; (ii) borehole magnetic measurements; (iii) inference of properties from petrographic/petrological information, supplemented by palaeomagnetic databases; (iv) constrained modelling/inversion of magnetic sources; (v) direct inversions of measured or calculated vector and gradient tensor data for simple sources; (vi) retrospective inference of magnetisation of a mined deposit by comparing magnetic data acquired pre- and post-mining; (vii) combined analysis of magnetic and gravity anomalies using Poisson's theorem; (viii) using a controlled magnetic source to probe the susceptibility distribution of the subsurface; (ix) Helbig-type analysis of gridded vector components, gradient tensor elements, and tensor invariants; (x) methods based on reduction to the pole and related transforms; and (xi) remote in situ determination of NRM direction, total magnetisation direction and Koenigsberger ratio by deploying dual vector magnetometers or a single combined gradiometer/magnetometer to monitor local perturbation of natural geomagnetic variations, operating in base station mode within a magnetic anomaly of interest. Characterising the total and remanent magnetisations of sources is important for several reasons. Knowledge of total magnetisation is often critical for accurate determination of source geometry and position. Knowledge of magnetic properties such as magnetisation intensity and Koenigsberger ratio constrains the likely magnetic mineralogy (composition and grain size) of a source, which gives an indication of its geological nature. Determining the direction of a stable ancient remanence gives an indication of the age of magnetisation, which provides useful information about the geological history of the source and its environs.

Segmentation of discrete vector fields.

PubMed

Li, Hongyu; Chen, Wenbin; Shen, I-Fan

2006-01-01

In this paper, we propose an approach for 2D discrete vector field segmentation based on the Green function and normalized cut. The method is inspired by discrete Hodge Decomposition such that a discrete vector field can be broken down into three simpler components, namely, curl-free, divergence-free, and harmonic components. We show that the Green Function Method (GFM) can be used to approximate the curl-free and the divergence-free components to achieve our goal of the vector field segmentation. The final segmentation curves that represent the boundaries of the influence region of singularities are obtained from the optimal vector field segmentations. These curves are composed of piecewise smooth contours or streamlines. Our method is applicable to both linear and nonlinear discrete vector fields. Experiments show that the segmentations obtained using our approach essentially agree with human perceptual judgement.

Fast Quaternion Attitude Estimation from Two Vector Measurements

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

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.

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 solution of 2D-vector tomography problem using the method of approximate inverse

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

Svetov, Ivan; Maltseva, Svetlana; Polyakova, Anna

2016-08-10

We propose a numerical solution of reconstruction problem of a two-dimensional vector field in a unit disk from the known values of the longitudinal and transverse ray transforms. The algorithm is based on the method of approximate inverse. Numerical simulations confirm that the proposed method yields good results of reconstruction of vector fields.

Alignment-free genetic sequence comparisons: a review of recent approaches by word analysis.

PubMed

Bonham-Carter, Oliver; Steele, Joe; Bastola, Dhundy

2014-11-01

Modern sequencing and genome assembly technologies have provided a wealth of data, which will soon require an analysis by comparison for discovery. Sequence alignment, a fundamental task in bioinformatics research, may be used but with some caveats. Seminal techniques and methods from dynamic programming are proving ineffective for this work owing to their inherent computational expense when processing large amounts of sequence data. These methods are prone to giving misleading information because of genetic recombination, genetic shuffling and other inherent biological events. New approaches from information theory, frequency analysis and data compression are available and provide powerful alternatives to dynamic programming. These new methods are often preferred, as their algorithms are simpler and are not affected by synteny-related problems. In this review, we provide a detailed discussion of computational tools, which stem from alignment-free methods based on statistical analysis from word frequencies. We provide several clear examples to demonstrate applications and the interpretations over several different areas of alignment-free analysis such as base-base correlations, feature frequency profiles, compositional vectors, an improved string composition and the D2 statistic metric. Additionally, we provide detailed discussion and an example of analysis by Lempel-Ziv techniques from data compression. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Assimilation of GMS-5 satellite winds using nudging method with MM5

NASA Astrophysics Data System (ADS)

Gao, Shanhong; Wu, Zengmao; Yang, Bo

2006-09-01

With the aid of Meteorological Information Composite and Processing System (MICAPS), satellite wind vectors derived from the Geostationary Meteorological Statellite-5 (GMS-5) and retrieved by National Satellite Meteorology Center of China (NSMC) can be obtained. Based on the nudging method built in the fifth-generation Mesoscale Model (MM5) of Pennsylvania State University and National Center for Atmospheric Research, a data preprocessor is developed to convert these satellite wind vectors to those with specified format required in MM5. To examine the data preprocessor and evaluate the impact of satellite winds from GMS-5 on MM5 simulations, a series of numerical experimental forecasts consisting of four typhoon cases in 2002 are designed and implemented. The results show that the preprocessor can process satellite winds smoothly and MM5 model runs successfully with a little extra computational load during ingesting these winds, and that assimilation of satellite winds by MM5 nudging method can obviously improve typhoon track forecast but contributes a little to typhoon intensity forecast. The impact of the satellite winds depends heavily upon whether the typhoon bogussing scheme in MM5 was turned on or not. The data preprocessor developed in this paper not only can treat GMS-5 satellite winds but also has capability with little modification to process derived winds from other geostationary satellites.

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

PubMed

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

2017-05-01

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

All-fiber polarization locked vector soliton laser using carbon nanotubes.

PubMed

Mou, C; Sergeyev, S; Rozhin, A; Turistyn, S

2011-10-01

We report an all-fiber mode-locked erbium-doped fiber laser (EDFL) employing carbon nanotube (CNT) polymer composite film. By using only standard telecom grade components, without any complex polarization control elements in the laser cavity, we have demonstrated polarization locked vector solitons generation with duration of ~583 fs, average power of ~3 mW (pulse energy of 118 pJ) at the repetition rate of ~25.7 MHz. © 2011 Optical Society of America

Multiclass Reduced-Set Support Vector Machines

NASA Technical Reports Server (NTRS)

Tang, Benyang; Mazzoni, Dominic

2006-01-01

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

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.

Sparse Method for Direction of Arrival Estimation Using Denoised Fourth-Order Cumulants Vector.

PubMed

Fan, Yangyu; Wang, Jianshu; Du, Rui; Lv, Guoyun

2018-06-04

Fourth-order cumulants (FOCs) vector-based direction of arrival (DOA) estimation methods of non-Gaussian sources may suffer from poor performance for limited snapshots or difficulty in setting parameters. In this paper, a novel FOCs vector-based sparse DOA estimation method is proposed. Firstly, by utilizing the concept of a fourth-order difference co-array (FODCA), an advanced FOCs vector denoising or dimension reduction procedure is presented for arbitrary array geometries. Then, a novel single measurement vector (SMV) model is established by the denoised FOCs vector, and efficiently solved by an off-grid sparse Bayesian inference (OGSBI) method. The estimation errors of FOCs are integrated in the SMV model, and are approximately estimated in a simple way. A necessary condition regarding the number of identifiable sources of our method is presented that, in order to uniquely identify all sources, the number of sources K must fulfill K ≤ ( M 4 - 2 M 3 + 7 M 2 - 6 M ) / 8 . The proposed method suits any geometry, does not need prior knowledge of the number of sources, is insensitive to associated parameters, and has maximum identifiability O ( M 4 ) , where M is the number of sensors in the array. Numerical simulations illustrate the superior performance of the proposed method.

Evaluation of a Machine-Learning Classifier for Keratoconus Detection Based on Scheimpflug Tomography.

PubMed

Ruiz Hidalgo, Irene; Rodriguez, Pablo; Rozema, Jos J; Ní Dhubhghaill, Sorcha; Zakaria, Nadia; Tassignon, Marie-José; Koppen, Carina

2016-06-01

To evaluate the performance of a support vector machine algorithm that automatically and objectively identifies corneal patterns based on a combination of 22 parameters obtained from Pentacam measurements and to compare this method with other known keratoconus (KC) classification methods. Pentacam data from 860 eyes were included in the study and divided into 5 groups: 454 KC, 67 forme fruste (FF), 28 astigmatic, 117 after refractive surgery (PR), and 194 normal eyes (N). Twenty-two parameters were used for classification using a support vector machine algorithm developed in Weka, a machine-learning computer software. The cross-validation accuracy for 3 different classification tasks (KC vs. N, FF vs. N and all 5 groups) was calculated and compared with other known classification methods. The accuracy achieved in the KC versus N discrimination task was 98.9%, with 99.1% sensitivity and 98.5% specificity for KC detection. The accuracy in the FF versus N task was 93.1%, with 79.1% sensitivity and 97.9% specificity for the FF discrimination. Finally, for the 5-groups classification, the accuracy was 88.8%, with a weighted average sensitivity of 89.0% and specificity of 95.2%. Despite using the strictest definition for FF KC, the present study obtained comparable or better results than the single-parameter methods and indices reported in the literature. In some cases, direct comparisons with the literature were not possible because of differences in the compositions and definitions of the study groups, especially the FF KC.

Employing the Components of the Human Development Index to Drive Resources to Educational Policies

ERIC Educational Resources Information Center

Sant'Anna, Annibal Parracho; de Araujo Ribeiro, Rodrigo Otavio; Dutt-Ross, Steven

2011-01-01

A new form of composition of the indicators employed to generate the United Nations Human Development Index (HDI) is presented here. This form of composition is based on the assumption that random errors affect the measurement of each indicator. This assumption allows for replacing the vector of evaluations according to each indicator by vectors…

Acoustic vector tomography and its application to magnetoacoustic tomography with magnetic induction (MAT-MI).

PubMed

Li, Xu; Xia, Rongmin; He, Bin

2008-01-01

A new tomographic algorithm for reconstructing a curl-free vector field, whose divergence serves as acoustic source is proposed. It is shown that under certain conditions, the scalar acoustic measurements obtained from a surface enclosing the source area can be vectorized according to the known measurement geometry and then be used to reconstruct the vector field. The proposed method is validated by numerical experiments. This method can be easily applied to magnetoacoustic tomography with magnetic induction (MAT-MI). A simulation study of applying this method to MAT-MI shows that compared to existing methods, the proposed method can give an accurate estimation of the induced current distribution and a better reconstruction of electrical conductivity within an object.

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

NASA Technical Reports Server (NTRS)

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

1975-01-01

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

System and method for extracting dominant orientations from a scene

DOEpatents

Straub, Julian; Rosman, Guy; Freifeld, Oren; Leonard, John J.; Fisher, III; , John W.

2017-05-30

In one embodiment, a method of identifying the dominant orientations of a scene comprises representing a scene as a plurality of directional vectors. The scene may comprise a three-dimensional representation of a scene, and the plurality of directional vectors may comprise a plurality of surface normals. The method further comprises determining, based on the plurality of directional vectors, a plurality of orientations describing the scene. The determined plurality of orientations explains the directionality of the plurality of directional vectors. In certain embodiments, the plurality of orientations may have independent axes of rotation. The plurality of orientations may be determined by representing the plurality of directional vectors as lying on a mathematical representation of a sphere, and inferring the parameters of a statistical model to adapt the plurality of orientations to explain the positioning of the plurality of directional vectors lying on the mathematical representation of the sphere.

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...

Phenomenology of flavorful composite vector bosons in light of B anomalies

NASA Astrophysics Data System (ADS)

Matsuzaki, Shinya; Nishiwaki, Kenji; Watanabe, Ryoutaro

2017-08-01

We analyze the flavor structure of composite vector bosons arising in a model of vectorlike technicolor — often called hypercolor (HC) — with eight flavors that form a one-family content of HC fermions. Dynamics of the composite vector bosons, referred to as HC ρ in this paper, are formulated together with HC pions by the hidden local symmetry (HLS), in a way analogous to QCD vector mesons. Then coupling properties to the standard model (SM) fermions, which respect the HLS gauge symmetry, are described in a way that couplings of the HC ρs to the left-handed SM quarks and leptons are given by a well-defined setup as taking the flavor mixing structures into account. Under the present scenario, we discuss significant bounds on the model from electroweak precision tests, flavor physics, and collider physics. We also try to address B anomalies in processes such as B → K (∗) μ + μ - and B\\to {D}^{(\\ast )}τ\\overline{ν} , recently reported by LHCb, Belle, (ATLAS, and CMS in part). Then we find that the present model can account for the anomaly in B → K (∗) μ + μ - consistently with the other constraints while it predicts no significant deviations in B\\to {D}^{(\\ast )}τ\\overline{ν} ν from the SM, which can be examined in the future Belle II experiment. The former is archived with the form C 9 = - C 10 of the Wilson coefficients for effective operators of b → sμ + μ -, which has been favored by the recent experimental data. We also investigate current and future experimental limits at the Large Hadron Collider (LHC) and see that possible collider signals come from dijet and ditau, or dimuon resonant searches for the present scenario with TeV mass range. To conclude, the present b → sμ + μ - anomaly is likely to imply discovery of new vector bosons in the ditau or dimuon channel in the context of the HC ρ model. Our model can be considered as a UV completion of conventional U(1)' models.

Bacterial diversity of the American sand fly Lutzomyia intermedia using high-throughput metagenomic sequencing.

PubMed

Monteiro, Carolina Cunha; Villegas, Luis Eduardo Martinez; Campolina, Thais Bonifácio; Pires, Ana Clara Machado Araújo; Miranda, Jose Carlos; Pimenta, Paulo Filemon Paolucci; Secundino, Nagila Francinete Costa

2016-08-31

Parasites of the genus Leishmania cause a broad spectrum of diseases, collectively known as leishmaniasis, in humans worldwide. American cutaneous leishmaniasis is a neglected disease transmitted by sand fly vectors including Lutzomyia intermedia, a proven vector. The female sand fly can acquire or deliver Leishmania spp. parasites while feeding on a blood meal, which is required for nutrition, egg development and survival. The microbiota composition and abundance varies by food source, life stages and physiological conditions. The sand fly microbiota can affect parasite life-cycle in the vector. We performed a metagenomic analysis for microbiota composition and abundance in Lu. intermedia, from an endemic area in Brazil. The adult insects were collected using CDC light traps, morphologically identified, carefully sterilized, dissected under a microscope and the females separated into groups according to their physiological condition: (i) absence of blood meal (unfed = UN); (ii) presence of blood meal (blood-fed = BF); and (iii) presence of developed ovaries (gravid = GR). Then, they were processed for metagenomics with Illumina Hiseq Sequencing in order to be sequence analyzed and to obtain the taxonomic profiles of the microbiota. Bacterial metagenomic analysis revealed differences in microbiota composition based upon the distinct physiological stages of the adult insect. Sequence identification revealed two phyla (Proteobacteria and Actinobacteria), 11 families and 15 genera; 87 % of the bacteria were Gram-negative, while only one family and two genera were identified as Gram-positive. The genera Ochrobactrum, Bradyrhizobium and Pseudomonas were found across all of the groups. The metagenomic analysis revealed that the microbiota of the Lu. intermedia female sand flies are distinct under specific physiological conditions and consist of 15 bacterial genera. The Ochrobactrum, Bradyrhizobium and Pseudomonas were the common genera. Our results detailing the constituents of Lu. intermedia native microbiota contribute to the knowledge regarding the bacterial community in an important sand fly vector and allow for further studies to better understand how the microbiota interacts with vectors of human parasites and to develop tools for biological control.

Determination of the viscous acoustic field for liquid drop positioning/forcing in an acoustic levitation chamber in microgravity

NASA Technical Reports Server (NTRS)

Lyell, Margaret J.

1992-01-01

The development of acoustic levitation systems has provided a technology with which to undertake droplet studies as well as do containerless processing experiments in a microgravity environment. Acoustic levitation chambers utilize radiation pressure forces to position/manipulate the drop. Oscillations can be induced via frequency modulation of the acoustic wave, with the modulated acoustic radiation vector acting as the driving force. To account for tangential as well as radial forcing, it is necessary that the viscous effects be included in the acoustic field. The method of composite expansions is employed in the determination of the acoustic field with viscous effects.

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.

Low scale composite Higgs model and 1.8 ˜2 TeV diboson excess

NASA Astrophysics Data System (ADS)

Bian, Ligong; Liu, Da; Shu, Jing

2018-04-01

We consider a simple solution to explain the recent diboson excess observed by ATLAS and CMS Collaborations in models with custodial symmetry SU(2)L × SU(2)R → SU(2)c. The SU(2)L triplet vector boson ρ with mass range of 1.8 ˜ 2 TeV would be produced through the Drell-Yan process with sizable diboson decay branching to account for the excess. The other SU(2)L × SU(2)R bidoublet axial vector boson a would cancel all deviations of electroweak obervables induced by ρ even if the SM fermions mix with some heavy vector-like (composite) fermions which couple to ρ (“nonuniversally partially composite”), therefore allows arbitrary couplings between each SM fermion and ρ. We present our model in the “General Composite Higgs” framework with SO(5) × U(1)X → SO(4) × U(1)X breaking at scale f and demand the first Weinberg sum rule and positive gauge boson form factors as the theoretical constraints. We find that our model can fit the diboson excess very well if the left-handed SM light quarks, charged leptons and tops have zero, zero/moderately small and moderate/large composite components for reasonable values of gρ and f. The correlation between tree level S parameter and the h → Zγ suggest a large a contribution to h → Zγ and it is indeed a 𝒪(1) effect in our parameter space which provides a strong hint for our scenario if this diboson excess is confirmed by the 13 ˜ 14 TeV LHC Run II.

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

PubMed

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

2009-01-01

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

A Kalman Filter for SINS Self-Alignment Based on Vector Observation.

PubMed

Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Tong, Jinwu

2017-01-29

In this paper, a self-alignment method for strapdown inertial navigation systems based on the q -method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate.

A Kalman Filter for SINS Self-Alignment Based on Vector Observation

PubMed Central

Xu, Xiang; Xu, Xiaosu; Zhang, Tao; Li, Yao; Tong, Jinwu

2017-01-01

In this paper, a self-alignment method for strapdown inertial navigation systems based on the q-method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate. PMID:28146059

Lexicon generation methods, lexicon generation devices, and lexicon generation articles of manufacture

DOEpatents

Carter, Richard J [Richland, WA; McCall, Jonathon D [West Richland, WA; Whitney, Paul D [Richland, WA; Gregory, Michelle L [Richland, WA; Turner, Alan E [Kennewick, WA; Hetzler, Elizabeth G [Kennewick, WA; White, Amanda M [Kennewick, WA; Posse, Christian [Seattle, WA; Nakamura, Grant C [Kennewick, WA

2010-10-26

Lexicon generation methods, computer implemented lexicon editing methods, lexicon generation devices, lexicon editors, and articles of manufacture are described according to some aspects. In one aspect, a lexicon generation method includes providing a seed vector indicative of occurrences of a plurality of seed terms within a plurality of text items, providing a plurality of content vectors indicative of occurrences of respective ones of a plurality of content terms within the text items, comparing individual ones of the content vectors with respect to the seed vector, and responsive to the comparing, selecting at least one of the content terms as a term of a lexicon usable in sentiment analysis of text.

The magnetofection method: using magnetic force to enhance gene delivery.

PubMed

Plank, Christian; Schillinger, Ulrike; Scherer, Franz; Bergemann, Christian; Rémy, Jean-Serge; Krötz, Florian; Anton, Martina; Lausier, Jim; Rosenecker, Joseph

2003-05-01

In order to enhance and target gene delivery we have previously established a novel method, termed magnetofection, which uses magnetic force acting on gene vectors that are associated with magnetic particles. Here we review the benefits, the mechanism and the potential of the method with regard to overcoming physical limitations to gene delivery. Magnetic particle chemistry and physics are discussed, followed by a detailed presentation of vector formulation and optimization work. While magnetofection does not necessarily improve the overall performance of any given standard gene transfer method in vitro, its major potential lies in the extraordinarily rapid and efficient transfection at low vector doses and the possibility of remotely controlled vector targeting in vivo.

Searching for transcription factor binding sites in vector spaces

PubMed Central

2012-01-01

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

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.

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.

Direct Volume Rendering with Shading via Three-Dimensional Textures

NASA Technical Reports Server (NTRS)

VanGelder, Allen; Kim, Kwansik

1996-01-01

A new and easy-to-implement method for direct volume rendering that uses 3D texture maps for acceleration, and incorporates directional lighting, is described. The implementation, called Voltx, produces high-quality images at nearly interactive speeds on workstations with hardware support for three-dimensional texture maps. Previously reported methods did not incorporate a light model, and did not address issues of multiple texture maps for large volumes. Our research shows that these extensions impact performance by about a factor of ten. Voltx supports orthographic, perspective, and stereo views. This paper describes the theory and implementation of this technique, and compares it to the shear-warp factorization approach. A rectilinear data set is converted into a three-dimensional texture map containing color and opacity information. Quantized normal vectors and a lookup table provide efficiency. A new tesselation of the sphere is described, which serves as the basis for normal-vector quantization. A new gradient-based shading criterion is described, in which the gradient magnitude is interpreted in the context of the field-data value and the material classification parameters, and not in isolation. In the rendering phase, the texture map is applied to a stack of parallel planes, which effectively cut the texture into many slabs. The slabs are composited to form an image.

Novel positioning method using Gaussian mixture model for a monolithic scintillator-based detector in positron emission tomography

NASA Astrophysics Data System (ADS)

Bae, Seungbin; Lee, Kisung; Seo, Changwoo; Kim, Jungmin; Joo, Sung-Kwan; Joung, Jinhun

2011-09-01

We developed a high precision position decoding method for a positron emission tomography (PET) detector that consists of a thick slab scintillator coupled with a multichannel photomultiplier tube (PMT). The DETECT2000 simulation package was used to validate light response characteristics for a 48.8 mm×48.8 mm×10 mm slab of lutetium oxyorthosilicate coupled to a 64 channel PMT. The data are then combined to produce light collection histograms. We employed a Gaussian mixture model (GMM) to parameterize the composite light response with multiple Gaussian mixtures. In the training step, light photons acquired by N PMT channels was used as an N-dimensional feature vector and were fed into a GMM training model to generate optimal parameters for M mixtures. In the positioning step, we decoded the spatial locations of incident photons by evaluating a sample feature vector with respect to the trained mixture parameters. The average spatial resolutions after positioning with four mixtures were 1.1 mm full width at half maximum (FWHM) at the corner and 1.0 mm FWHM at the center section. This indicates that the proposed algorithm achieved high performance in both spatial resolution and positioning bias, especially at the corner section of the detector.

A New Unified Analysis of Estimate Errors by Model-Matching Phase-Estimation Methods for Sensorless Drive of Permanent-Magnet Synchronous Motors and New Trajectory-Oriented Vector Control, Part I

NASA Astrophysics Data System (ADS)

Shinnaka, Shinji; Sano, Kousuke

This paper presents a new unified analysis of estimate errors by model-matching phase-estimation methods such as rotor-flux state-observers, back EMF state-observers, and back EMF disturbance-observers, for sensorless drive of permanent-magnet synchronous motors. Analytical solutions about estimate errors, whose validity is confirmed by numerical experiments, are rich in universality and applicability. As an example of universality and applicability, a new trajectory-oriented vector control method is proposed, which can realize directly quasi-optimal strategy minimizing total losses with no additional computational loads by simply orienting one of vector-control coordinates to the associated quasi-optimal trajectory. The coordinate orientation rule, which is analytically derived, is surprisingly simple. Consequently the trajectory-oriented vector control method can be applied to a number of conventional vector control systems using one of the model-matching phase-estimation methods.

Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs.

PubMed

Ahmadi, Hamed; Rodehutscord, Markus

2017-01-01

In the nutrition literature, there are several reports on the use of artificial neural network (ANN) and multiple linear regression (MLR) approaches for predicting feed composition and nutritive value, while the use of support vector machines (SVM) method as a new alternative approach to MLR and ANN models is still not fully investigated. The MLR, ANN, and SVM models were developed to predict metabolizable energy (ME) content of compound feeds for pigs based on the German energy evaluation system from analyzed contents of crude protein (CP), ether extract (EE), crude fiber (CF), and starch. A total of 290 datasets from standardized digestibility studies with compound feeds was provided from several institutions and published papers, and ME was calculated thereon. Accuracy and precision of developed models were evaluated, given their produced prediction values. The results revealed that the developed ANN [ R 2  = 0.95; root mean square error (RMSE) = 0.19 MJ/kg of dry matter] and SVM ( R 2  = 0.95; RMSE = 0.21 MJ/kg of dry matter) models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR ( R 2  = 0.89; RMSE = 0.27 MJ/kg of dry matter). The developed ANN and SVM models produced better prediction values in estimating ME in compound feed than those produced by conventional MLR; however, there were not obvious differences between performance of ANN and SVM models. Thus, SVM model may also be considered as a promising tool for modeling the relationship between chemical composition and ME of compound feeds for pigs. To provide the readers and nutritionist with the easy and rapid tool, an Excel ® calculator, namely, SVM_ME_pig, was created to predict the metabolizable energy values in compound feeds for pigs using developed support vector machine model.

TargetM6A: Identifying N6-Methyladenosine Sites From RNA Sequences via Position-Specific Nucleotide Propensities and a Support Vector Machine.

PubMed

Li, Guang-Qing; Liu, Zi; Shen, Hong-Bin; Yu, Dong-Jun

2016-10-01

As one of the most ubiquitous post-transcriptional modifications of RNA, N 6 -methyladenosine ( [Formula: see text]) plays an essential role in many vital biological processes. The identification of [Formula: see text] sites in RNAs is significantly important for both basic biomedical research and practical drug development. In this study, we designed a computational-based method, called TargetM6A, to rapidly and accurately target [Formula: see text] sites solely from the primary RNA sequences. Two new features, i.e., position-specific nucleotide/dinucleotide propensities (PSNP/PSDP), are introduced and combined with the traditional nucleotide composition (NC) feature to formulate RNA sequences. The extracted features are further optimized to obtain a much more compact and discriminative feature subset by applying an incremental feature selection (IFS) procedure. Based on the optimized feature subset, we trained TargetM6A on the training dataset with a support vector machine (SVM) as the prediction engine. We compared the proposed TargetM6A method with existing methods for predicting [Formula: see text] sites by performing stringent jackknife tests and independent validation tests on benchmark datasets. The experimental results show that the proposed TargetM6A method outperformed the existing methods for predicting [Formula: see text] sites and remarkably improved the prediction performances, with MCC = 0.526 and AUC = 0.818. We also provided a user-friendly web server for TargetM6A, which is publicly accessible for academic use at http://csbio.njust.edu.cn/bioinf/TargetM6A.

Compositional Verification with Abstraction, Learning, and SAT Solving

DTIC Science & Technology

2015-05-01

arithmetic, and bit-vectors (currently, via bit-blasting). The front-end is based on an existing tool called UFO [8] which converts C programs to the Horn...supports propositional logic, linear arithmetic, and bit-vectors (via bit-blasting). The front-end is based on the tool UFO [8]. It encodes safety of...tool UFO [8]. The encoding in Horn-SMT only uses the theory of Linear Rational Arithmetic. All experiments were carried out on an Intel R© CoreTM2 Quad

Using trees to compute approximate solutions to ordinary differential equations exactly

NASA Technical Reports Server (NTRS)

Grossman, Robert

1991-01-01

Some recent work is reviewed which relates families of trees to symbolic algorithms for the exact computation of series which approximate solutions of ordinary differential equations. It turns out that the vector space whose basis is the set of finite, rooted trees carries a natural multiplication related to the composition of differential operators, making the space of trees an algebra. This algebraic structure can be exploited to yield a variety of algorithms for manipulating vector fields and the series and algebras they generate.

Evaluation of Commercial and Field-Expedient Baited Traps for House Flies, Musca domestica L. (Diptera: Muscidae)

DTIC Science & Technology

2009-01-09

Vector Ecology 34 (1): 99-103. 2009. Keyword Index : House fly, Musca domestica, trapping. INTRODUCTION Traps have been a mainstay of house fly (Musca...attract synanthropic flies. Proc. Pap. 46th Ann. Conf. Calif. Mosq. Vector Contr. Assoc. pp. 70-73. Pickens, L. G. and R. W. Miller. 1987. Techniques...1139: 279- 284. SAS Institute. 1992. SAS users guide: statistics. SAS Institute, Cary, NC. Warner, W. B. 1991. Attractant composition for synanthropic

FIDEP2 User Manual to Micromechanical Models for Thermoviscoplastic Behavior of Metal Matrix Composites

DTIC Science & Technology

1998-09-01

1 .AND. ICOUNT .GT. ISTRAIN )GOTO 55 Add additional terms in equations for interface nodes If radial loading is applied, add term BMAT (NTOT-1) = SR...term in bmat Using Bmat , and the L-U decomposition of Amat determine XSOL, the vector of radial and hoop stresses CALL LUBKSB(AMAT,NRA,LDA,IPVT... BMAT ,XSOL) Compute stresses from the XSOL solution vector Use Boundary conditions S(1,NTOT2) = SR S(2,1) = S(1,1) Compute total axial

Reconstruction of Vectorial Acoustic Sources in Time-Domain Tomography

PubMed Central

Xia, Rongmin; Li, Xu; He, Bin

2009-01-01

A new theory is proposed for the reconstruction of curl-free vector field, whose divergence serves as acoustic source. The theory is applied to reconstruct vector acoustic sources from the scalar acoustic signals measured on a surface enclosing the source area. It is shown that, under certain conditions, the scalar acoustic measurements can be vectorized according to the known measurement geometry and subsequently be used to reconstruct the original vector field. Theoretically, this method extends the application domain of the existing acoustic reciprocity principle from a scalar field to a vector field, indicating that the stimulating vectorial source and the transmitted acoustic pressure vector (acoustic pressure vectorized according to certain measurement geometry) are interchangeable. Computer simulation studies were conducted to evaluate the proposed theory, and the numerical results suggest that reconstruction of a vector field using the proposed theory is not sensitive to variation in the detecting distance. The present theory may be applied to magnetoacoustic tomography with magnetic induction (MAT-MI) for reconstructing current distribution from acoustic measurements. A simulation on MAT-MI shows that, compared to existing methods, the present method can give an accurate estimation on the source current distribution and a better conductivity reconstruction. PMID:19211344

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

PubMed

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

2016-02-01

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

A new implementation of the CMRH method for solving dense linear systems

NASA Astrophysics Data System (ADS)

Heyouni, M.; Sadok, H.

2008-04-01

The CMRH method [H. Sadok, Methodes de projections pour les systemes lineaires et non lineaires, Habilitation thesis, University of Lille1, Lille, France, 1994; H. Sadok, CMRH: A new method for solving nonsymmetric linear systems based on the Hessenberg reduction algorithm, Numer. Algorithms 20 (1999) 303-321] is an algorithm for solving nonsymmetric linear systems in which the Arnoldi component of GMRES is replaced by the Hessenberg process, which generates Krylov basis vectors which are orthogonal to standard unit basis vectors rather than mutually orthogonal. The iterate is formed from these vectors by solving a small least squares problem involving a Hessenberg matrix. Like GMRES, this method requires one matrix-vector product per iteration. However, it can be implemented to require half as much arithmetic work and less storage. Moreover, numerical experiments show that this method performs accurately and reduces the residual about as fast as GMRES. With this new implementation, we show that the CMRH method is the only method with long-term recurrence which requires not storing at the same time the entire Krylov vectors basis and the original matrix as in the GMRES algorithmE A comparison with Gaussian elimination is provided.

The Gut Microbiome of the Vector Lutzomyia longipalpis Is Essential for Survival of Leishmania infantum.

PubMed

Kelly, Patrick H; Bahr, Sarah M; Serafim, Tiago D; Ajami, Nadim J; Petrosino, Joseph F; Meneses, Claudio; Kirby, John R; Valenzuela, Jesus G; Kamhawi, Shaden; Wilson, Mary E

2017-01-17

The vector-borne disease leishmaniasis, caused by Leishmania species protozoa, is transmitted to humans by phlebotomine sand flies. Development of Leishmania to infective metacyclic promastigotes in the insect gut, a process termed metacyclogenesis, is an essential prerequisite for transmission. Based on the hypothesis that vector gut microbiota influence the development of virulent parasites, we sequenced midgut microbiomes in the sand fly Lutzomyia longipalpis with or without Leishmania infantum infection. Sucrose-fed sand flies contained a highly diverse, stable midgut microbiome. Blood feeding caused a decrease in microbial richness that eventually recovered. However, bacterial richness progressively decreased in L. infantum-infected sand flies. Acetobacteraceae spp. became dominant and numbers of Pseudomonadaceae spp. diminished coordinately as the parasite underwent metacyclogenesis and parasite numbers increased. Importantly, antibiotic-mediated perturbation of the midgut microbiome rendered sand flies unable to support parasite growth and metacyclogenesis. Together, these data suggest that the sand fly midgut microbiome is a critical factor for Leishmania growth and differentiation to its infective state prior to disease transmission. Leishmania infantum, a parasitic protozoan causing fatal visceral leishmaniasis, is transmitted to humans through the bite of the sand fly Lutzomyia longipalpis Development of the parasite to its virulent metacyclic state occurs in the sand fly gut. In this study, the microbiota within the Lu. longipalpis midgut was delineated by 16S ribosomal DNA (rDNA) sequencing, revealing a highly diverse community composition that lost diversity as parasites developed to their metacyclic state and increased in abundance in infected flies. Perturbing sand fly gut microbiota with an antibiotic cocktail, which alone had no effect on either the parasite or the fly, arrested both the development of virulent parasites and parasite expansion. These findings indicate the importance of bacterial commensals within the insect vector for the development of virulent pathogens, and raise the possibility that impairing the microbial composition within the vector might represent a novel approach to control of vector-borne diseases. Copyright © 2017 Kelly et al.

Storage and computationally efficient permutations of factorized covariance and square-root information matrices

NASA Technical Reports Server (NTRS)

Muellerschoen, R. J.

1988-01-01

A unified method to permute vector-stored upper-triangular diagonal factorized covariance (UD) and vector stored upper-triangular square-root information filter (SRIF) arrays is presented. The method involves cyclical permutation of the rows and columns of the arrays and retriangularization with appropriate square-root-free fast Givens rotations or elementary slow Givens reflections. A minimal amount of computation is performed and only one scratch vector of size N is required, where N is the column dimension of the arrays. To make the method efficient for large SRIF arrays on a virtual memory machine, three additional scratch vectors each of size N are used to avoid expensive paging faults. The method discussed is compared with the methods and routines of Bierman's Estimation Subroutine Library (ESL).

Plant centromere compositions

DOEpatents

Mach, Jennifer M [Chicago, IL; Zieler, Helge [Del Mar, CA; Jin, RongGuan [Chesterfield, MO; Keith, Kevin [Three Forks, MT; Copenhaver, Gregory P [Chapel Hill, NC; Preuss, Daphne [Chicago, IL

2011-08-02

The present invention provides for the nucleic acid sequences of plant centromeres. This will permit construction of stably inherited recombinant DNA constructs and minichromosomes which can serve as vectors for the construction of transgenic plant and animal cells.

Plant centromere compositions

DOEpatents

Mach,; Jennifer M. , Zieler; Helge, Jin [Del Mar, CA; RongGuan, Keith [Chesterfield, MO; Kevin, Copenhaver [Three Forks, MT; Gregory P. , Preuss; Daphne, [Chicago, IL

2011-11-22

The present invention provides for the nucleic acid sequences of plant centromeres. This will permit construction of stably inherited recombinant DNA constructs and minichromosomes which can serve as vectors for the construction of transgenic plant and animal cells.

Plant centromere compositions

DOEpatents

Keith, Kevin; Copenhaver, Gregory; Preuss, Daphne

2006-10-10

The present invention provides for the nucleic acid sequences of plant centromeres. This will permit construction of stably inherited recombinant DNA constructs and minichromosomes which can serve as vectors for the construction of transgenic plant and animal cells.

Plant centromere compositions

DOEpatents

Mach, Jennifer [Chicago, IL; Zieler, Helge [Chicago, IL; Jin, James [Chicago, IL; Keith, Kevin [Chicago, IL; Copenhaver, Gregory [Chapel Hill, NC; Preuss, Daphne [Chicago, IL

2006-06-26

The present invention provides for the nucleic acid sequences of plant centromeres. This will permit construction of stably inherited recombinant DNA constructs and minichromosomes which can serve as vectors for the construction of transgenic plant and animal cells.

Plant centromere compositions

DOEpatents

Mach, Jennifer [Chicago, IL; Zieler, Helge [Chicago, IL; Jin, RongGuan [Chicago, IL; Keith, Kevin [Chicago, IL; Copenhaver, Gregory [Chapel Hill, NC; Preuss, Daphne [Chicago, IL

2007-06-05

The present invention provides for the nucleic acid sequences of plant centromeres. This will permit construction of stably inherited recombinant DNA constructs and minichromosomes which can serve as vectors for the construction of transgenic plant and animal cells.

Using support vector machine to predict beta- and gamma-turns in proteins.

PubMed

Hu, Xiuzhen; Li, Qianzhong

2008-09-01

By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting beta- and gamma-turns in the proteins is proposed. The 426 and 320 nonhomologous protein chains described by Guruprasad and Rajkumar (Guruprasad and Rajkumar J. Biosci 2000, 25,143) are used for training and testing the predictive model of the beta- and gamma-turns, respectively. The overall prediction accuracy and the Matthews correlation coefficient in 7-fold cross-validation are 79.8% and 0.47, respectively, for the beta-turns. The overall prediction accuracy in 5-fold cross-validation is 61.0% for the gamma-turns. These results are significantly higher than the other algorithms in the prediction of beta- and gamma-turns using the same datasets. In addition, the 547 and 823 nonhomologous protein chains described by Fuchs and Alix (Fuchs and Alix Proteins: Struct Funct Bioinform 2005, 59, 828) are used for training and testing the predictive model of the beta- and gamma-turns, and better results are obtained. This algorithm may be helpful to improve the performance of protein turns' prediction. To ensure the ability of the SVM method to correctly classify beta-turn and non-beta-turn (gamma-turn and non-gamma-turn), the receiver operating characteristic threshold independent measure curves are provided. (c) 2008 Wiley Periodicals, Inc.

Field Evaluation of a Push-Pull System to Reduce Malaria Transmission

PubMed Central

Menger, David J.; Omusula, Philemon; Holdinga, Maarten; Homan, Tobias; Carreira, Ana S.; Vandendaele, Patrice; Derycke, Jean-Luc; Mweresa, Collins K.; Mukabana, Wolfgang Richard; van Loon, Joop J. A.; Takken, Willem

2015-01-01

Malaria continues to place a disease burden on millions of people throughout the tropics, especially in sub-Saharan Africa. Although efforts to control mosquito populations and reduce human-vector contact, such as long-lasting insecticidal nets and indoor residual spraying, have led to significant decreases in malaria incidence, further progress is now threatened by the widespread development of physiological and behavioural insecticide-resistance as well as changes in the composition of vector populations. A mosquito-directed push-pull system based on the simultaneous use of attractive and repellent volatiles offers a complementary tool to existing vector-control methods. In this study, the combination of a trap baited with a five-compound attractant and a strip of net-fabric impregnated with micro-encapsulated repellent and placed in the eaves of houses, was tested in a malaria-endemic village in western Kenya. Using the repellent delta-undecalactone, mosquito house entry was reduced by more than 50%, while the traps caught high numbers of outdoor flying mosquitoes. Model simulations predict that, assuming area-wide coverage, the addition of such a push-pull system to existing prevention efforts will result in up to 20-fold reductions in the entomological inoculation rate. Reductions of such magnitude are also predicted when mosquitoes exhibit a high resistance against insecticides. We conclude that a push-pull system based on non-toxic volatiles provides an important addition to existing strategies for malaria prevention. PMID:25923114

Compositional Bias in Naïve and Chemically-modified Phage-Displayed Libraries uncovered by Paired-end Deep Sequencing.

PubMed

He, Bifang; Tjhung, Katrina F; Bennett, Nicholas J; Chou, Ying; Rau, Andrea; Huang, Jian; Derda, Ratmir

2018-01-19

Understanding the composition of a genetically-encoded (GE) library is instrumental to the success of ligand discovery. In this manuscript, we investigate the bias in GE-libraries of linear, macrocyclic and chemically post-translationally modified (cPTM) tetrapeptides displayed on the M13KE platform, which are produced via trinucleotide cassette synthesis (19 codons) and NNK-randomized codon. Differential enrichment of synthetic DNA {S}, ligated vector {L} (extension and ligation of synthetic DNA into the vector), naïve libraries {N} (transformation of the ligated vector into the bacteria followed by expression of the library for 4.5 hours to yield a "naïve" library), and libraries chemically modified by aldehyde ligation and cysteine macrocyclization {M} characterized by paired-end deep sequencing, detected a significant drop in diversity in {L} → {N}, but only a minor compositional difference in {S} → {L} and {N} → {M}. Libraries expressed at the N-terminus of phage protein pIII censored positively charged amino acids Arg and Lys; libraries expressed between pIII domains N1 and N2 overcame Arg/Lys-censorship but introduced new bias towards Gly and Ser. Interrogation of biases arising from cPTM by aldehyde ligation and cysteine macrocyclization unveiled censorship of sequences with Ser/Phe. Analogous analysis can be used to explore library diversity in new display platforms and optimize cPTM of these libraries.

Bioinspired Star-Shaped Poly(l-lysine) Polypeptides: Efficient Polymeric Nanocarriers for the Delivery of DNA to Mesenchymal Stem Cells.

PubMed

Walsh, David P; Murphy, Robert D; Panarella, Angela; Raftery, Rosanne M; Cavanagh, Brenton; Simpson, Jeremy C; O'Brien, Fergal J; Heise, Andreas; Cryan, Sally-Ann

2018-05-07

The field of tissue engineering is increasingly recognizing that gene therapy can be employed for modulating in vivo cellular response thereby guiding tissue regeneration. However, the field lacks a versatile and biocompatible gene delivery platform capable of efficiently delivering transgenes to mesenchymal stem cells (MSCs), a cell type often refractory to transfection. Herein, we describe the extensive and systematic exploration of three architectural variations of star-shaped poly(l-lysine) polypeptide (star-PLL) with varying number and length of poly(l-lysine) arms as potential nonviral gene delivery vectors for MSCs. We demonstrate that star-PLL vectors are capable of self-assembling with pDNA to form stable, cationic nanomedicines. Utilizing high content screening, live cell imaging, and mechanistic uptake studies we confirm the intracellular delivery of pDNA by star-PLLs to MSCs is a rapid process, which likely proceeds via a clathrin-independent mechanism. We identify a star-PLL composition with 64 poly(l-lysine) arms and five l-lysine subunits per arm as a particularly efficient vector that is capable of delivering both reporter genes and the therapeutic transgenes bone morphogenetic protein-2 and vascular endothelial growth factor to MSCs. This composition facilitated a 1000-fold increase in transgene expression in MSCs compared to its linear analogue, linear poly(l-lysine). Furthermore, it demonstrated comparable transgene expression to the widely used vector polyethylenimine using a lower pDNA dose with significantly less cytotoxicity. Overall, this study illustrates the ability of the star-PLL vectors to facilitate efficient, nontoxic nucleic acid delivery to MSCs thereby functioning as an innovative nanomedicine platform for tissue engineering applications.

Mosquito communities and disease risk influenced by land use change and seasonality in the Australian tropics.

PubMed

Meyer Steiger, Dagmar B; Ritchie, Scott A; Laurance, Susan G W

2016-07-07

Anthropogenic land use changes have contributed considerably to the rise of emerging and re-emerging mosquito-borne diseases. These diseases appear to be increasing as a result of the novel juxtapositions of habitats and species that can result in new interchanges of vectors, diseases and hosts. We studied whether the mosquito community structure varied between habitats and seasons and whether known disease vectors displayed habitat preferences in tropical Australia. Using CDC model 512 traps, adult mosquitoes were sampled across an anthropogenic disturbance gradient of grassland, rainforest edge and rainforest interior habitats, in both the wet and dry seasons. Nonmetric multidimensional scaling (NMS) ordinations were applied to examine major gradients in the composition of mosquito and vector communities. We captured ~13,000 mosquitoes from 288 trap nights across four study sites. A community analysis identified 29 species from 7 genera. Even though mosquito abundance and richness were similar between the three habitats, the community composition varied significantly in response to habitat type. The mosquito community in rainforest interiors was distinctly different to the community in grasslands, whereas forest edges acted as an ecotone with shared communities from both forest interiors and grasslands. We found two community patterns that will influence disease risk at out study sites, first, that disease vectoring mosquito species occurred all year round. Secondly, that anthropogenic grasslands adjacent to rainforests may increase the probability of novel disease transmission through changes to the vector community on rainforest edges, as most disease transmitting species predominantly occurred in grasslands. Our results indicate that the strong influence of anthropogenic land use change on mosquito communities could have potential implications for pathogen transmission to humans and wildlife.

Physical-geometric optics method for large size faceted particles.

PubMed

Sun, Bingqiang; Yang, Ping; Kattawar, George W; Zhang, Xiaodong

2017-10-02

A new physical-geometric optics method is developed to compute the single-scattering properties of faceted particles. It incorporates a general absorption vector to accurately account for inhomogeneous wave effects, and subsequently yields the relevant analytical formulas effective and computationally efficient for absorptive scattering particles. A bundle of rays incident on a certain facet can be traced as a single beam. For a beam incident on multiple facets, a systematic beam-splitting technique based on computer graphics is used to split the original beam into several sub-beams so that each sub-beam is incident only on an individual facet. The new beam-splitting technique significantly reduces the computational burden. The present physical-geometric optics method can be generalized to arbitrary faceted particles with either convex or concave shapes and with a homogeneous or an inhomogeneous (e.g., a particle with a core) composition. The single-scattering properties of irregular convex homogeneous and inhomogeneous hexahedra are simulated and compared to their counterparts from two other methods including a numerically rigorous method.

The Seepage Simulation of Single Hole and Composite Gas Drainage Based on LB Method

NASA Astrophysics Data System (ADS)

Chen, Yanhao; Zhong, Qiu; Gong, Zhenzhao

2018-01-01

Gas drainage is the most effective method to prevent and solve coal mine gas power disasters. It is very important to study the seepage flow law of gas in fissure coal gas. The LB method is a simplified computational model based on micro-scale, especially for the study of seepage problem. Based on fracture seepage mathematical model on the basis of single coal gas drainage, using the LB method during coal gas drainage of gas flow numerical simulation, this paper maps the single-hole drainage gas, symmetric slot and asymmetric slot, the different width of the slot combined drainage area gas flow under working condition of gas cloud of gas pressure, flow path diagram and flow velocity vector diagram, and analyses the influence on gas seepage field under various working conditions, and also discusses effective drainage method of the center hole slot on both sides, and preliminary exploration that is related to the combination of gas drainage has been carried on as well.

TA-GC cloning: A new simple and versatile technique for the directional cloning of PCR products for recombinant protein expression.

PubMed

Niarchos, Athanasios; Siora, Anastasia; Konstantinou, Evangelia; Kalampoki, Vasiliki; Lagoumintzis, George; Poulas, Konstantinos

2017-01-01

During the last few decades, the recombinant protein expression finds more and more applications. The cloning of protein-coding genes into expression vectors is required to be directional for proper expression, and versatile in order to facilitate gene insertion in multiple different vectors for expression tests. In this study, the TA-GC cloning method is proposed, as a new, simple and efficient method for the directional cloning of protein-coding genes in expression vectors. The presented method features several advantages over existing methods, which tend to be relatively more labour intensive, inflexible or expensive. The proposed method relies on the complementarity between single A- and G-overhangs of the protein-coding gene, obtained after a short incubation with T4 DNA polymerase, and T and C overhangs of the novel vector pET-BccI, created after digestion with the restriction endonuclease BccI. The novel protein-expression vector pET-BccI also facilitates the screening of transformed colonies for recombinant transformants. Evaluation experiments of the proposed TA-GC cloning method showed that 81% of the transformed colonies contained recombinant pET-BccI plasmids, and 98% of the recombinant colonies expressed the desired protein. This demonstrates that TA-GC cloning could be a valuable method for cloning protein-coding genes in expression vectors.

TA-GC cloning: A new simple and versatile technique for the directional cloning of PCR products for recombinant protein expression

PubMed Central

Niarchos, Athanasios; Siora, Anastasia; Konstantinou, Evangelia; Kalampoki, Vasiliki; Poulas, Konstantinos

2017-01-01

During the last few decades, the recombinant protein expression finds more and more applications. The cloning of protein-coding genes into expression vectors is required to be directional for proper expression, and versatile in order to facilitate gene insertion in multiple different vectors for expression tests. In this study, the TA-GC cloning method is proposed, as a new, simple and efficient method for the directional cloning of protein-coding genes in expression vectors. The presented method features several advantages over existing methods, which tend to be relatively more labour intensive, inflexible or expensive. The proposed method relies on the complementarity between single A- and G-overhangs of the protein-coding gene, obtained after a short incubation with T4 DNA polymerase, and T and C overhangs of the novel vector pET-BccI, created after digestion with the restriction endonuclease BccI. The novel protein-expression vector pET-BccI also facilitates the screening of transformed colonies for recombinant transformants. Evaluation experiments of the proposed TA-GC cloning method showed that 81% of the transformed colonies contained recombinant pET-BccI plasmids, and 98% of the recombinant colonies expressed the desired protein. This demonstrates that TA-GC cloning could be a valuable method for cloning protein-coding genes in expression vectors. PMID:29091919

Chemical Compositions of the Peel Essential Oil of Citrus aurantium and Its Natural Larvicidal Activity against the Malaria Vector Anopheles stephensi (Diptera: Culicidae) in Comparison with Citrus paradisi.

PubMed

Sanei-Dehkordi, Alireza; Sedaghat, Mohammad Mehdi; Vatandoost, Hassan; Abai, Mohammad Reza

2016-12-01

Recently, essential oils and extracts derived from plants have received much interest as potential bio-active agents against mosquito vectors. The essential oils extract from fresh peel of ripe fruit of Citrus aurantium and Citrus paradisi were tested against mosquito vector Anopheles stephensi (Diptera: Culicidae) under laboratory condition. Then chemical composition of the essential oil of C. aurantium was analyzed using gas chromatography-mass spectrometry (GC-MS). The essential oils obtained from C. aurantium , and C. paradisi showed good larviciding effect against An. stephensi with LC 50 values 31.20 ppm and 35.71 ppm respectively. Clear dose response relationships were established with the highest dose of 80 ppm plant extract evoking almost 100% mortality. Twenty-one (98.62%) constituents in the leaf oil were identified. The main constituent of the leaf oil was Dl-limonene (94.81). The results obtained from this study suggest that the limonene of peel essential oil of C. aurantium is promising as larvicide against An. stephensi larvae and could be useful in the search for new natural larvicidal compounds.

Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

PubMed

Carvalho, B M; Rangel, E F; Vale, M M

2017-08-01

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

Construction and Characterization of an in-vivo Linear Covalently Closed DNA Vector Production System

PubMed Central

2012-01-01

Background While safer than their viral counterparts, conventional non-viral gene delivery DNA vectors offer a limited safety profile. They often result in the delivery of unwanted prokaryotic sequences, antibiotic resistance genes, and the bacterial origins of replication to the target, which may lead to the stimulation of unwanted immunological responses due to their chimeric DNA composition. Such vectors may also impart the potential for chromosomal integration, thus potentiating oncogenesis. We sought to engineer an in vivo system for the quick and simple production of safer DNA vector alternatives that were devoid of non-transgene bacterial sequences and would lethally disrupt the host chromosome in the event of an unwanted vector integration event. Results We constructed a parent eukaryotic expression vector possessing a specialized manufactured multi-target site called “Super Sequence”, and engineered E. coli cells (R-cell) that conditionally produce phage-derived recombinase Tel (PY54), TelN (N15), or Cre (P1). Passage of the parent plasmid vector through R-cells under optimized conditions, resulted in rapid, efficient, and one step in vivo generation of mini lcc—linear covalently closed (Tel/TelN-cell), or mini ccc—circular covalently closed (Cre-cell), DNA constructs, separated from the backbone plasmid DNA. Site-specific integration of lcc plasmids into the host chromosome resulted in chromosomal disruption and 105 fold lower viability than that seen with the ccc counterpart. Conclusion We offer a high efficiency mini DNA vector production system that confers simple, rapid and scalable in vivo production of mini lcc DNA vectors that possess all the benefits of “minicircle” DNA vectors and virtually eliminate the potential for undesirable vector integration events. PMID:23216697

Construction and characterization of an in-vivo linear covalently closed DNA vector production system.

PubMed

Nafissi, Nafiseh; Slavcev, Roderick

2012-12-06

While safer than their viral counterparts, conventional non-viral gene delivery DNA vectors offer a limited safety profile. They often result in the delivery of unwanted prokaryotic sequences, antibiotic resistance genes, and the bacterial origins of replication to the target, which may lead to the stimulation of unwanted immunological responses due to their chimeric DNA composition. Such vectors may also impart the potential for chromosomal integration, thus potentiating oncogenesis. We sought to engineer an in vivo system for the quick and simple production of safer DNA vector alternatives that were devoid of non-transgene bacterial sequences and would lethally disrupt the host chromosome in the event of an unwanted vector integration event. We constructed a parent eukaryotic expression vector possessing a specialized manufactured multi-target site called "Super Sequence", and engineered E. coli cells (R-cell) that conditionally produce phage-derived recombinase Tel (PY54), TelN (N15), or Cre (P1). Passage of the parent plasmid vector through R-cells under optimized conditions, resulted in rapid, efficient, and one step in vivo generation of mini lcc--linear covalently closed (Tel/TelN-cell), or mini ccc--circular covalently closed (Cre-cell), DNA constructs, separated from the backbone plasmid DNA. Site-specific integration of lcc plasmids into the host chromosome resulted in chromosomal disruption and 10(5) fold lower viability than that seen with the ccc counterpart. We offer a high efficiency mini DNA vector production system that confers simple, rapid and scalable in vivo production of mini lcc DNA vectors that possess all the benefits of "minicircle" DNA vectors and virtually eliminate the potential for undesirable vector integration events.

Classification of diesel pool refinery streams through near infrared spectroscopy and support vector machines using C-SVC and ν-SVC.

PubMed

Alves, Julio Cesar L; Henriques, Claudete B; Poppi, Ronei J

2014-01-03

The use of near infrared (NIR) spectroscopy combined with chemometric methods have been widely used in petroleum and petrochemical industry and provides suitable methods for process control and quality control. The algorithm support vector machines (SVM) has demonstrated to be a powerful chemometric tool for development of classification models due to its ability to nonlinear modeling and with high generalization capability and these characteristics can be especially important for treating near infrared (NIR) spectroscopy data of complex mixtures such as petroleum refinery streams. In this work, a study on the performance of the support vector machines algorithm for classification was carried out, using C-SVC and ν-SVC, applied to near infrared (NIR) spectroscopy data of different types of streams that make up the diesel pool in a petroleum refinery: light gas oil, heavy gas oil, hydrotreated diesel, kerosene, heavy naphtha and external diesel. In addition to these six streams, the diesel final blend produced in the refinery was added to complete the data set. C-SVC and ν-SVC classification models with 2, 4, 6 and 7 classes were developed for comparison between its results and also for comparison with the soft independent modeling of class analogy (SIMCA) models results. It is demonstrated the superior performance of SVC models especially using ν-SVC for development of classification models for 6 and 7 classes leading to an improvement of sensitivity on validation sample sets of 24% and 15%, respectively, when compared to SIMCA models, providing better identification of chemical compositions of different diesel pool refinery streams. Copyright © 2013 Elsevier B.V. All rights reserved.

Method for predicting peptide detection in mass spectrometry

DOEpatents

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

2010-07-13

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

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...

A Simple Method to Increase the Transduction Efficiency of Single-Stranded Adeno-Associated Virus Vectors In Vitro and In Vivo

PubMed Central

Ma, Wenqin; Li, Baozheng; Ling, Chen; Jayandharan, Giridhara R.; Byrne, Barry J.

2011-01-01

Abstract We have recently shown that co-administration of conventional single-stranded adeno-associated virus 2 (ssAAV2) vectors with self-complementary (sc) AAV2-protein phosphatase 5 (PP5) vectors leads to a significant increase in the transduction efficiency of ssAAV2 vectors in human cells in vitro as well as in murine hepatocytes in vivo. In the present study, this strategy has been further optimized by generating a mixed population of ssAAV2-EGFP and scAAV2-PP5 vectors at a 10:1 ratio to achieve enhanced green fluorescent protein (EGFP) transgene expression at approximately 5- to 10-fold higher efficiency, both in vitro and in vivo. This simple coproduction method should be adaptable to any ssAAV serotype vector containing transgene cassettes that are too large to be encapsidated in scAAV vectors. PMID:21219084

Measuring magnetic field vector by stimulated Raman transitions

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

Wang, Wenli; Wei, Rong, E-mail: weirong@siom.ac.cn; Lin, Jinda

2016-03-21

We present a method for measuring the magnetic field vector in an atomic fountain by probing the line strength of stimulated Raman transitions. The relative line strength for a Λ-type level system with an existing magnetic field is theoretically analyzed. The magnetic field vector measured by our proposed method is consistent well with that by the traditional bias magnetic field method with an axial resolution of 6.1 mrad and a radial resolution of 0.16 rad. Dependences of the Raman transitions on laser polarization schemes are also analyzed. Our method offers the potential advantages for magnetic field measurement without requiring additional bias fields,more » beyond the limitation of magnetic field intensity, and extending the spatial measurement range. The proposed method can be widely used for measuring magnetic field vector in other precision measurement fields.« less

Estimation of chaotic coupled map lattices using symbolic vector dynamics

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

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

PubMed

Illés, Tamás; Somoskeöy, Szabolcs

2013-06-01

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

Analytical Approach to the Fuel Optimal Impulsive Transfer Problem Using Primer Vector Method

NASA Astrophysics Data System (ADS)

Fitrianingsih, E.; Armellin, R.

2018-04-01

One of the objectives of mission design is selecting an optimum orbital transfer which often translated as a transfer which requires minimum propellant consumption. In order to assure the selected trajectory meets the requirement, the optimality of transfer should first be analyzed either by directly calculating the ΔV of the candidate trajectories and select the one that gives a minimum value or by evaluating the trajectory according to certain criteria of optimality. The second method is performed by analyzing the profile of the modulus of the thrust direction vector which is known as primer vector. Both methods come with their own advantages and disadvantages. However, it is possible to use the primer vector method to verify if the result from the direct method is truly optimal or if the ΔV can be reduced further by implementing correction maneuver to the reference trajectory. In addition to its capability to evaluate the transfer optimality without the need to calculate the transfer ΔV, primer vector also enables us to identify the time and position to apply correction maneuver in order to optimize a non-optimum transfer. This paper will present the analytical approach to the fuel optimal impulsive transfer using primer vector method. The validity of the method is confirmed by comparing the result to those from the numerical method. The investigation of the optimality of direct transfer is used to give an example of the application of the method. The case under study is the prograde elliptic transfers from Earth to Mars. The study enables us to identify the optimality of all the possible transfers.

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach

PubMed Central

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-01-01

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. PMID:28629202

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.

Detection of a sudden change of the field time series based on the Lorenz system.

PubMed

Da, ChaoJiu; Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series.

Reconstruction of fetal vector electrocardiogram from maternal abdominal signals under fetus body rotations.

PubMed

Nabeshima, Yuji; Kimura, Yoshitaka; Ito, Takuro; Ohwada, Kazunari; Karashima, Akihiro; Katayama, Norihiro; Nakao, Mitsuyuki

2013-01-01

Fetal electrocardiogram (fECG) and its vector form (fVECG) could provide significant clinical information concerning physiological conditions of a fetus. So far various independent component analysis (ICA)-based methods for extracting fECG from maternal abdominal signals have been proposed. Because full extraction of component waves such as P, Q, R, S, and T, is difficult to be realized under noisy and nonstationary situations, the fVECG is further hard to be reconstructed, where different projections of the fetal heart vector are required. In order to reconstruct fVECG, we proposed a novel method for synthesizing different projections of the heart vector, making good use of the fetus movement. This method consists of ICA, estimation of rotation angles of fetus, and synthesis of projections of the heart vector. Through applications to the synthetic and actual data, our method is shown to precisely estimate rotation angle of the fetus and to successfully reconstruct the fVECG.

Method and system of filtering and recommending documents

DOEpatents

Patton, Robert M.; Potok, Thomas E.

2016-02-09

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

Extrapolation methods for vector sequences

NASA Technical Reports Server (NTRS)

Smith, David A.; Ford, William F.; Sidi, Avram

1987-01-01

This paper derives, describes, and compares five extrapolation methods for accelerating convergence of vector sequences or transforming divergent vector sequences to convergent ones. These methods are the scalar epsilon algorithm (SEA), vector epsilon algorithm (VEA), topological epsilon algorithm (TEA), minimal polynomial extrapolation (MPE), and reduced rank extrapolation (RRE). MPE and RRE are first derived and proven to give the exact solution for the right 'essential degree' k. Then, Brezinski's (1975) generalization of the Shanks-Schmidt transform is presented; the generalized form leads from systems of equations to TEA. The necessary connections are then made with SEA and VEA. The algorithms are extended to the nonlinear case by cycling, the error analysis for MPE and VEA is sketched, and the theoretical support for quadratic convergence is discussed. Strategies for practical implementation of the methods are considered.

Genetic shifting: a novel approach for controlling vector-borne diseases.

PubMed

Powell, Jeffrey R; Tabachnick, Walter J

2014-06-01

Rendering populations of vectors of diseases incapable of transmitting pathogens through genetic methods has long been a goal of vector geneticists. We outline a method to achieve this goal that does not involve the introduction of any new genetic variants to the target population. Rather we propose that shifting the frequencies of naturally occurring alleles that confer refractoriness to transmission can reduce transmission below a sustainable level. The program employs methods successfully used in plant and animal breeding. Because no artificially constructed genetically modified organisms (GMOs) are introduced into the environment, the method is minimally controversial. We use Aedes aegypti and dengue virus (DENV) for illustrative purposes but point out that the proposed program is generally applicable to vector-borne disease control. Copyright © 2014 Elsevier Ltd. All rights reserved.

A simple method for construction of artificial microRNA vector in plant.

PubMed

Li, Yang; Li, Yang; Zhao, Sunping; Zhong, Sheng; Wang, Zhaohai; Ding, Bo; Li, Yangsheng

2014-10-01

Artificial microRNA (amiRNA) is a powerful tool for silencing genes in many plant species. Here we provide an easy method to construct amiRNA vectors that reinvents the Golden Gate cloning approach and features a novel system called top speed amiRNA construction (TAC). This speedy approach accomplishes one restriction-ligation step in only 5 min, allowing easy and high-throughput vector construction. Three primers were annealed to be a specific adaptor, then digested and ligated on our novel vector pTAC. Importantly, this method allows the recombined amiRNA constructs to maintain the precursor of osa-miR528 with exception of the desired amiRNA/amiRNA* sequences. Using this method, our results showed the expected decrease of targeted genes in Nicotiana benthamiana and Oryza sativa.

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

NASA Astrophysics Data System (ADS)

Hus, Jean-Christophe; Bruschweiler, Rafael

2002-07-01

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

Efficient production of recombinant adeno-associated viral vector, serotype DJ/8, carrying the GFP gene.

PubMed

Hashimoto, Haruo; Mizushima, Tomoko; Chijiwa, Tsuyoshi; Nakamura, Masato; Suemizu, Hiroshi

2017-06-15

The purpose of this study was to establish an efficient method for the preparation of an adeno-associated viral (AAV), serotype DJ/8, carrying the GFP gene (AAV-DJ/8-GFP). We compared the yields of AAV-DJ/8 vector, which were produced by three different combination methods, consisting of two plasmid DNA transfection methods (lipofectamine and calcium phosphate co-precipitation; CaPi) and two virus DNA purification methods (iodixanol and cesium chloride; CsCl). The results showed that the highest yield of AAV-DJ/8-GFP vector was accomplished with the combination method of lipofectamine transfection and iodixanol purification. The viral protein expression levels and the transduction efficacy in HEK293 and CHO cells were not different among four different combination methods for AAV-DJ/8-GFP vectors. We confirmed that the AAV-DJ/8-GFP vector could transduce to human and murine hepatocyte-derived cell lines. These results show that AAV-DJ/8-GFP, purified by the combination of lipofectamine and iodixanol, produces an efficient yield without altering the characteristics of protein expression and AAV gene transduction. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantum dot coating of baculoviral vectors enables visualization of transduced cells and tissues

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

Zhao, Ying; Lo, Seong Loong; Zheng, Yuangang

2013-04-26

Highlights: •The use of quantum dot (QD)-labeled viral vectors for in vivo imaging is not well investigated. •A new method to label enveloped baculovirus with glutathione-capped CdTe QDs is developed. •The labeling enables the identification of transduced, cultured cells based on fluorescence. •The labeling also allows evaluation of viral transduction in a real-time manner in living mice. •The method has the potential to assess viral vector-based gene therapy protocols in future. -- Abstract: Imaging of transduced cells and tissues is valuable in developing gene transfer vectors and evaluating gene therapy efficacy. We report here a simple method to use brightmore » and photostable quantum dots to label baculovirus, an emerging gene therapy vector. The labeling was achieved through the non-covalent interaction of glutathione-capped CdTe quantum dots with the virus envelope, without the use of chemical conjugation. The quantum dot labeling was nondestructive to viral transduction function and enabled the identification of baculoviral vector-transduced, living cells based on red fluorescence. When the labeled baculoviral vectors were injected intravenously or intraventricularly for in vivo delivery of a transgene into mice, quantum dot fluorescence signals allow us monitor whether or not the injected tissues were transduced. More importantly, using a dual-color whole-body imaging technology, we demonstrated that in vivo viral transduction could be evaluated in a real-time manner in living mice. Thus, our method of labeling a read-to-use gene delivery vector with quantum dots could be useful towards the improvement of vector design and will have the potential to assess baculovirus-based gene therapy protocols in future.« less

Classification of pulmonary nodules in lung CT images using shape and texture features

NASA Astrophysics Data System (ADS)

Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan; Kumar, Prafulla

2016-03-01

Differentiation of malignant and benign pulmonary nodules is important for prognosis of lung cancer. In this paper, benign and malignant nodules are classified using support vector machine. Several shape-based and texture-based features are used to represent the pulmonary nodules in the feature space. A semi-automated technique is used for nodule segmentation. Relevant features are selected for efficient representation of nodules in the feature space. The proposed scheme and the competing technique are evaluated on a data set of 542 nodules of Lung Image Database Consortium and Image Database Resource Initiative. The nodules with composite rank of malignancy "1","2" are considered as benign and "4","5" are considered as malignant. Area under the receiver operating characteristics curve is 0:9465 for the proposed method. The proposed method outperforms the competing technique.

Ribosomal targets for antibiotic drug discovery

DOEpatents

Blanchard, Scott C.; Feldman, Michael Brian; Wang, Leyi; Doudna Cate, James H.; Pulk, Arto; Altman, Roger B.; Wasserman, Michael R

2016-09-13

The present invention relates to methods to identify molecules that binds in the neomycin binding pocket of a bacterial ribosome using structures of an intact bacterial ribosome that reveal how the ribosome binds tRNA in two functionally distinct states, determined by x-ray crystallography. One state positions tRNA in the peptidyl-tRNA binding site. The second, a fully rotated state, is stabilized by ribosome recycling factor (RRF) and binds tRNA in a highly bent conformation in a hybrid peptidyl/exit (P/E) site. Additionally, the invention relates to various assays, including single-molecule assay for ribosome recycling, and methods to identify compounds that interfere with ribosomal function by detecting newly identified intermediate FRET states using known and novel FRET pairs on the ribosome. The invention also provides vectors and compositions with an N-terminally tagged S13 protein.

State-vector formalism and the Legendre polynomial solution for modelling guided waves in anisotropic plates

NASA Astrophysics Data System (ADS)

Zheng, Mingfang; He, Cunfu; Lu, Yan; Wu, Bin

2018-01-01

We presented a numerical method to solve phase dispersion curve in general anisotropic plates. This approach involves an exact solution to the problem in the form of the Legendre polynomial of multiple integrals, which we substituted into the state-vector formalism. In order to improve the efficiency of the proposed method, we made a special effort to demonstrate the analytical methodology. Furthermore, we analyzed the algebraic symmetries of the matrices in the state-vector formalism for anisotropic plates. The basic feature of the proposed method was the expansion of field quantities by Legendre polynomials. The Legendre polynomial method avoid to solve the transcendental dispersion equation, which can only be solved numerically. This state-vector formalism combined with Legendre polynomial expansion distinguished the adjacent dispersion mode clearly, even when the modes were very close. We then illustrated the theoretical solutions of the dispersion curves by this method for isotropic and anisotropic plates. Finally, we compared the proposed method with the global matrix method (GMM), which shows excellent agreement.

A hybrid method for accurate star tracking using star sensor and gyros.

PubMed

Lu, Jiazhen; Yang, Lie; Zhang, Hao

2017-10-01

Star tracking is the primary operating mode of star sensors. To improve tracking accuracy and efficiency, a hybrid method using a star sensor and gyroscopes is proposed in this study. In this method, the dynamic conditions of an aircraft are determined first by the estimated angular acceleration. Under low dynamic conditions, the star sensor is used to measure the star vector and the vector difference method is adopted to estimate the current angular velocity. Under high dynamic conditions, the angular velocity is obtained by the calibrated gyros. The star position is predicted based on the estimated angular velocity and calibrated gyros using the star vector measurements. The results of the semi-physical experiment show that this hybrid method is accurate and feasible. In contrast with the star vector difference and gyro-assisted methods, the star position prediction result of the hybrid method is verified to be more accurate in two different cases under the given random noise of the star centroid.

Top partner-resonance interplay in a composite Higgs framework

NASA Astrophysics Data System (ADS)

Yepes, Juan; Zerwekh, Alfonso

2018-04-01

Guided us by the scenario of weak scale naturalness and the possible existence of exotic resonances, we have explored in a SO(5) Composite Higgs setup the interplay among three matter sectors: elementary, top partners and vector resonances. We parametrize it through explicit interactions of spin-1 SO(4)-resonances, coupled to the SO(5)-invariant fermionic currents and tensors presented in this work. Such invariants are built upon the Standard Model fermion sector as well as top partners sourced by the unbroken SO(4). The mass scales entailed by the top partner and vector resonance sectors will control the low energy effects emerging from our interplaying model. Its phenomenological impact and parameter spaces have been considered via flavor-dijet processes and electric dipole moments bounds. Finally, the strength of the Nambu-Goldstone symmetry breaking and the extra couplings implied by the top partner mass scales are measured in accordance with expected estimations.

Distribution of Potential Hydrothermally Altered Rocks in Central Colorado Derived From Landsat Thematic Mapper Data: A Geographic Information System Data Set

USGS Publications Warehouse

Knepper, Daniel H.

2010-01-01

As part of the Central Colorado Mineral Resource Assessment Project, the digital image data for four Landsat Thematic Mapper scenes covering central Colorado between Wyoming and New Mexico were acquired and band ratios were calculated after masking pixels dominated by vegetation, snow, and terrain shadows. Ratio values were visually enhanced by contrast stretching, revealing only those areas with strong responses (high ratio values). A color-ratio composite mosaic was prepared for the four scenes so that the distribution of potentially hydrothermally altered rocks could be visually evaluated. To provide a more useful input to a Geographic Information System-based mineral resource assessment, the information contained in the color-ratio composite raster image mosaic was converted to vector-based polygons after thresholding to isolate the strongest ratio responses and spatial filtering to reduce vector complexity and isolate the largest occurrences of potentially hydrothermally altered rocks.

Rapid construction of a Bacterial Artificial Chromosomal (BAC) expression vector using designer DNA fragments.

PubMed

Chen, Chao; Zhao, Xinqing; Jin, Yingyu; Zhao, Zongbao Kent; Suh, Joo-Won

2014-11-01

Bacterial artificial chromosomal (BAC) vectors are increasingly being used in cloning large DNA fragments containing complex biosynthetic pathways to facilitate heterologous production of microbial metabolites for drug development. To express inserted genes using Streptomyces species as the production hosts, an integration expression cassette is required to be inserted into the BAC vector, which includes genetic elements encoding a phage-specific attachment site, an integrase, an origin of transfer, a selection marker and a promoter. Due to the large sizes of DNA inserted into the BAC vectors, it is normally inefficient and time-consuming to assemble these fragments by routine PCR amplifications and restriction-ligations. Here we present a rapid method to insert fragments to construct BAC-based expression vectors. A DNA fragment of about 130 bp was designed, which contains upstream and downstream homologous sequences of both BAC vector and pIB139 plasmid carrying the whole integration expression cassette. In-Fusion cloning was performed using the designer DNA fragment to modify pIB139, followed by λ-RED-mediated recombination to obtain the BAC-based expression vector. We demonstrated the effectiveness of this method by rapid construction of a BAC-based expression vector with an insert of about 120 kb that contains the entire gene cluster for biosynthesis of immunosuppressant FK506. The empty BAC-based expression vector constructed in this study can be conveniently used for construction of BAC libraries using either microbial pure culture or environmental DNA, and the selected BAC clones can be directly used for heterologous expression. Alternatively, if a BAC library has already been constructed using a commercial BAC vector, the selected BAC vectors can be manipulated using the method described here to get the BAC-based expression vectors with desired gene clusters for heterologous expression. The rapid construction of a BAC-based expression vector facilitates heterologous expression of large gene clusters for drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Skoglöv, E.; Erikson, A.

2002-11-01

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

An Alignment-Free Algorithm in Comparing the Similarity of Protein Sequences Based on Pseudo-Markov Transition Probabilities among Amino Acids

PubMed Central

Li, Yushuang; Yang, Jiasheng; Zhang, Yi

2016-01-01

In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. We first encode a protein sequence into a 440 dimensional feature vector consisting of a 400 dimensional Pseudo-Markov transition probability vector among the 20 amino acids, a 20 dimensional content ratio vector, and a 20 dimensional position ratio vector of the amino acids in the sequence. By evaluating the Euclidean distances among the representing vectors, we compare the similarity of protein sequences. We then apply this method into the ND5 dataset consisting of the ND5 protein sequences of 9 species, and the F10 and G11 datasets representing two of the xylanases containing glycoside hydrolase families, i.e., families 10 and 11. As a result, our method achieves a correlation coefficient of 0.962 with the canonical protein sequence aligner ClustalW in the ND5 dataset, much higher than those of other 5 popular alignment-free methods. In addition, we successfully separate the xylanases sequences in the F10 family and the G11 family and illustrate that the F10 family is more heat stable than the G11 family, consistent with a few previous studies. Moreover, we prove mathematically an identity equation involving the Pseudo-Markov transition probability vector and the amino acids content ratio vector. PMID:27918587

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

PubMed

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

2016-10-15

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

Characterization of Sr-substituted W-type hexagonal ferrites synthesized by sol-gel autocombustion method

NASA Astrophysics Data System (ADS)

Ahmad, Mukhtar; Grössinger, R.; Kriegisch, M.; Kubel, F.; Rana, M. U.

2013-04-01

The magnetic and microwave characterization of single phase hexaferrites of entirely new composition Ba1-xSrxCo2AlFe15O27 (x=0.2-1.0) for application in a microwave absorber, have been reported. The samples synthesized by sol-gel method were investigated by differential thermal analyzer, Fourier transform infrared spectroscope, X-ray diffractometer, field emission gun scanning electron microscope, vibrating sample magnetometer and vector network analyzer. Platelet grains exhibit well defined hexagonal shape which is a better shape for microwave absorption. M-H loops for a selected sample were measured for a temperature range of 4.2-400 K. Moreover M-H loops for all Sr-substituted samples were also measured at room temperature up to a maximum applied field of 9 T. Saturation magnetization values were calculated by the law of approach to saturation. The room temperature coercivity for all the samples is found to be a few hundred oersteds which is necessary for electromagnetic materials and makes these ferrites ideal for microwave devices, security, switching and sensing applications. The complex permittivity, permeability and reflection losses of a selected ferrite-epoxy composite were also investigated over a frequency range of 0.5-13 GHz.

Harmonic reduction of Direct Torque Control of six-phase induction motor.

PubMed

Taheri, A

2016-07-01

In this paper, a new switching method in Direct Torque Control (DTC) of a six-phase induction machine for reduction of current harmonics is introduced. Selecting a suitable vector in each sampling period is an ordinal method in the ST-DTC drive of a six-phase induction machine. The six-phase induction machine has 64 voltage vectors and divided further into four groups. In the proposed DTC method, the suitable voltage vectors are selected from two vector groups. By a suitable selection of two vectors in each sampling period, the harmonic amplitude is decreased more, in and various comparison to that of the ST-DTC drive. The harmonics loss is greater reduced, while the electromechanical energy is decreased with switching loss showing a little increase. Spectrum analysis of the phase current in the standard and new switching table DTC of the six-phase induction machine and determination for the amplitude of each harmonics is proposed in this paper. The proposed method has a less sampling time in comparison to the ordinary method. The Harmonic analyses of the current in the low and high speed shows the performance of the presented method. The simplicity of the proposed method and its implementation without any extra hardware is other advantages of the proposed method. The simulation and experimental results show the preference of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

New perspectives in tracing vector-borne interaction networks.

PubMed

Gómez-Díaz, Elena; Figuerola, Jordi

2010-10-01

Disentangling trophic interaction networks in vector-borne systems has important implications in epidemiological and evolutionary studies. Molecular methods based on bloodmeal typing in vectors have been increasingly used to identify hosts. Although most molecular approaches benefit from good specificity and sensitivity, their temporal resolution is limited by the often rapid digestion of blood, and mixed bloodmeals still remain a challenge for bloodmeal identification in multi-host vector systems. Stable isotope analyses represent a novel complementary tool that can overcome some of these problems. The utility of these methods using examples from different vector-borne systems are discussed and the extents to which they are complementary and versatile are highlighted. There are excellent opportunities for progress in the study of vector-borne transmission networks resulting from the integration of both molecular and stable isotope approaches. Copyright © 2010 Elsevier Ltd. All rights reserved.

Reprogramming Methods Do Not Affect Gene Expression Profile of Human Induced Pluripotent Stem Cells.

PubMed

Trevisan, Marta; Desole, Giovanna; Costanzi, Giulia; Lavezzo, Enrico; Palù, Giorgio; Barzon, Luisa

2017-01-20

Induced pluripotent stem cells (iPSCs) are pluripotent cells derived from adult somatic cells. After the pioneering work by Yamanaka, who first generated iPSCs by retroviral transduction of four reprogramming factors, several alternative methods to obtain iPSCs have been developed in order to increase the yield and safety of the process. However, the question remains open on whether the different reprogramming methods can influence the pluripotency features of the derived lines. In this study, three different strategies, based on retroviral vectors, episomal vectors, and Sendai virus vectors, were applied to derive iPSCs from human fibroblasts. The reprogramming efficiency of the methods based on episomal and Sendai virus vectors was higher than that of the retroviral vector-based approach. All human iPSC clones derived with the different methods showed the typical features of pluripotent stem cells, including the expression of alkaline phosphatase and stemness maker genes, and could give rise to the three germ layer derivatives upon embryoid bodies assay. Microarray analysis confirmed the presence of typical stem cell gene expression profiles in all iPSC clones and did not identify any significant difference among reprogramming methods. In conclusion, the use of different reprogramming methods is equivalent and does not affect gene expression profile of the derived human iPSCs.

Malaria vector control: from past to future.

PubMed

Raghavendra, Kamaraju; Barik, Tapan K; Reddy, B P Niranjan; Sharma, Poonam; Dash, Aditya P

2011-04-01

Malaria is one of the most common vector-borne diseases widespread in the tropical and subtropical regions. Despite considerable success of malaria control programs in the past, malaria still continues as a major public health problem in several countries. Vector control is an essential part for reducing malaria transmission and became less effective in recent years, due to many technical and administrative reasons, including poor or no adoption of alternative tools. Of the different strategies available for vector control, the most successful are indoor residual spraying and insecticide-treated nets (ITNs), including long-lasting ITNs and materials. Earlier DDT spray has shown spectacular success in decimating disease vectors but resulted in development of insecticide resistance, and to control the resistant mosquitoes, organophosphates, carbamates, and synthetic pyrethroids were introduced in indoor residual spraying with needed success but subsequently resulted in the development of widespread multiple insecticide resistance in vectors. Vector control in many countries still use insecticides in the absence of viable alternatives. Few developments for vector control, using ovitraps, space spray, biological control agents, etc., were encouraging when used in limited scale. Likewise, recent introduction of safer vector control agents, such as insect growth regulators, biocontrol agents, and natural plant products have yet to gain the needed scale of utility for vector control. Bacterial pesticides are promising and are effective in many countries. Environmental management has shown sufficient promise for vector control and disease management but still needs advocacy for inter-sectoral coordination and sometimes are very work-intensive. The more recent genetic manipulation and sterile insect techniques are under development and consideration for use in routine vector control and for these, standardized procedures and methods are available but need thorough understanding of biology, ethical considerations, and sufficiently trained manpower for implementation being technically intensive methods. All the methods mentioned in the review that are being implemented or proposed for implementation needs effective inter-sectoral coordination and community participation. The latest strategy is evolution-proof insecticides that include fungal biopesticides, Wolbachia, and Denso virus that essentially manipulate the life cycle of the mosquitoes were found effective but needs more research. However, for effective vector control, integrated vector management methods, involving use of combination of effective tools, is needed and is also suggested by Global Malaria Control Strategy. This review article raises issues associated with the present-day vector control strategies and state opportunities with a focus on ongoing research and recent advances to enable to sustain the gains achieved so far.

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

PubMed

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

2017-09-07

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

Hybrid Decompositional Verification for Discovering Failures in Adaptive Flight Control Systems

NASA Technical Reports Server (NTRS)

Thompson, Sarah; Davies, Misty D.; Gundy-Burlet, Karen

2010-01-01

Adaptive flight control systems hold tremendous promise for maintaining the safety of a damaged aircraft and its passengers. However, most currently proposed adaptive control methodologies rely on online learning neural networks (OLNNs), which necessarily have the property that the controller is changing during the flight. These changes tend to be highly nonlinear, and difficult or impossible to analyze using standard techniques. In this paper, we approach the problem with a variant of compositional verification. The overall system is broken into components. Undesirable behavior is fed backwards through the system. Components which can be solved using formal methods techniques explicitly for the ranges of safe and unsafe input bounds are treated as white box components. The remaining black box components are analyzed with heuristic techniques that try to predict a range of component inputs that may lead to unsafe behavior. The composition of these component inputs throughout the system leads to overall system test vectors that may elucidate the undesirable behavior

Automatic Generation of Caricatures with Multiple Expressions Using Transformative Approach

NASA Astrophysics Data System (ADS)

Liao, Wen-Hung; Lai, Chien-An

The proliferation of digital cameras has changed the way we create and share photos. Novel forms of photo composition and reproduction have surfaced in recent years. In this paper, we present an automatic caricature generation system using transformative approaches. By combing facial feature detection, image segmentation and image warping/morphing techniques, the system is able to generate stylized caricature using only one reference image. When more than one reference sample are available, the system can either choose the best fit based on shape matching, or synthesize a composite style using polymorph technique. The system can also produce multiple expressions by controlling a subset of MPEG-4 facial animation parameters (FAP). Finally, to enable flexible manipulation of the synthetic caricature, we also investigate issues such as color quantization and raster-to-vector conversion. A major strength of our method is that the synthesized caricature bears a higher degree of resemblance to the real person than traditional component-based approaches.

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

NASA Technical Reports Server (NTRS)

Carney, Kelly Scott

1997-01-01

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

Polytopic vector analysis in igneous petrology: Application to lunar petrogenesis

NASA Technical Reports Server (NTRS)

Shervais, John W.; Ehrlich, R.

1993-01-01

Lunar samples represent a heterogeneous assemblage of rocks with complex inter-relationships that are difficult to decipher using standard petrogenetic approaches. These inter-relationships reflect several distinct petrogenetic trends as well as thermomechanical mixing of distinct components. Additional complications arise from the unequal quality of chemical analyses and from the fact that many samples (e.g., breccia clasts) are too small to be representative of the system from which they derived. Polytopic vector analysis (PVA) is a multi-variate procedure used as a tool for exploratory data analysis. PVA allows the analyst to classify samples and clarifies relationships among heterogenous samples with complex petrogenetic histories. It differs from orthogonal factor analysis in that it uses non-orthogonal multivariate sample vectors to extract sample endmember compositions. The output from a Q-mode (sample based) factor analysis is the initial step in PVA. The Q-mode analysis, using criteria established by Miesch and Klovan and Miesch, is used to determine the number of endmembers in the data system. The second step involves determination of endmembers and mixing proportions with all output expressed in the same geochemical variable as the input. The composition of endmembers is derived by analysis of the variability of the data set. Endmembers need not be present in the data set, nor is it necessary for their composition to be known a priori. A set of any endmembers defines a 'polytope' or classification figure (triangle for a three component system, tetrahedron for a four component system, a 'five-tope' in four dimensions for five component system, et cetera).

Mathematical modelling of vector-borne diseases and insecticide resistance evolution.

PubMed

Gabriel Kuniyoshi, Maria Laura; Pio Dos Santos, Fernando Luiz

2017-01-01

Vector-borne diseases are important public health issues and, consequently, in silico models that simulate them can be useful. The susceptible-infected-recovered (SIR) model simulates the population dynamics of an epidemic and can be easily adapted to vector-borne diseases, whereas the Hardy-Weinberg model simulates allele frequencies and can be used to study insecticide resistance evolution. The aim of the present study is to develop a coupled system that unifies both models, therefore enabling the analysis of the effects of vector population genetics on the population dynamics of an epidemic. Our model consists of an ordinary differential equation system. We considered the populations of susceptible, infected and recovered humans, as well as susceptible and infected vectors. Concerning these vectors, we considered a pair of alleles, with complete dominance interaction that determined the rate of mortality induced by insecticides. Thus, we were able to separate the vectors according to the genotype. We performed three numerical simulations of the model. In simulation one, both alleles conferred the same mortality rate values, therefore there was no resistant strain. In simulations two and three, the recessive and dominant alleles, respectively, conferred a lower mortality. Our numerical results show that the genetic composition of the vector population affects the dynamics of human diseases. We found that the absolute number of vectors and the proportion of infected vectors are smaller when there is no resistant strain, whilst the ratio of infected people is larger in the presence of insecticide-resistant vectors. The dynamics observed for infected humans in all simulations has a very similar shape to real epidemiological data. The population genetics of vectors can affect epidemiological dynamics, and the presence of insecticide-resistant strains can increase the number of infected people. Based on the present results, the model is a basis for development of other models and for investigating population dynamics.

[A research on real-time ventricular QRS classification methods for single-chip-microcomputers].

PubMed

Peng, L; Yang, Z; Li, L; Chen, H; Chen, E; Lin, J

1997-05-01

Ventricular QRS classification is key technique of ventricular arrhythmias detection in single-chip-microcomputer based dynamic electrocardiogram real-time analyser. This paper adopts morphological feature vector including QRS amplitude, interval information to reveal QRS morphology. After studying the distribution of QRS morphology feature vector of MIT/BIH DB ventricular arrhythmia files, we use morphological feature vector cluster to classify multi-morphology QRS. Based on the method, morphological feature parameters changing method which is suitable to catch occasional ventricular arrhythmias is presented. Clinical experiments verify missed ventricular arrhythmia is less than 1% by this method.

Novel method of finding extreme edges in a convex set of N-dimension vectors

NASA Astrophysics Data System (ADS)

Hu, Chia-Lun J.

2001-11-01

As we published in the last few years, for a binary neural network pattern recognition system to learn a given mapping {Um mapped to Vm, m=1 to M} where um is an N- dimension analog (pattern) vector, Vm is a P-bit binary (classification) vector, the if-and-only-if (IFF) condition that this network can learn this mapping is that each i-set in {Ymi, m=1 to M} (where Ymithere existsVmiUm and Vmi=+1 or -1, is the i-th bit of VR-m).)(i=1 to P and there are P sets included here.) Is POSITIVELY, LINEARLY, INDEPENDENT or PLI. We have shown that this PLI condition is MORE GENERAL than the convexity condition applied to a set of N-vectors. In the design of old learning machines, we know that if a set of N-dimension analog vectors form a convex set, and if the machine can learn the boundary vectors (or extreme edges) of this set, then it can definitely learn the inside vectors contained in this POLYHEDRON CONE. This paper reports a new method and new algorithm to find the boundary vectors of a convex set of ND analog vectors.

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.

Complex codon usage pattern and compositional features of retroviruses.

PubMed

RoyChoudhury, Sourav; Mukherjee, Debaprasad

2013-01-01

Retroviruses infect a wide range of organisms including humans. Among them, HIV-1, which causes AIDS, has now become a major threat for world health. Some of these viruses are also potential gene transfer vectors. In this study, the patterns of synonymous codon usage in retroviruses have been studied through multivariate statistical methods on ORFs sequences from the available 56 retroviruses. The principal determinant for evolution of the codon usage pattern in retroviruses seemed to be the compositional constraints, while selection for translation of the viral genes plays a secondary role. This was further supported by multivariate analysis on relative synonymous codon usage. Thus, it seems that mutational bias might have dominated role over translational selection in shaping the codon usage of retroviruses. Codon adaptation index was used to identify translationally optimal codons among genes from retroviruses. The comparative analysis of the preferred and optimal codons among different retroviral groups revealed that four codons GAA, AAA, AGA, and GGA were significantly more frequent in most of the retroviral genes inspite of some differences. Cluster analysis also revealed that phylogenetically related groups of retroviruses have probably evolved their codon usage in a concerted manner under the influence of their nucleotide composition.

Introducing the Filtered Park's and Filtered Extended Park's Vector Approach to detect broken rotor bars in induction motors independently from the rotor slots number

NASA Astrophysics Data System (ADS)

Gyftakis, Konstantinos N.; Marques Cardoso, Antonio J.; Antonino-Daviu, Jose A.

2017-09-01

The Park's Vector Approach (PVA), together with its variations, has been one of the most widespread diagnostic methods for electrical machines and drives. Regarding the broken rotor bars fault diagnosis in induction motors, the common practice is to rely on the width increase of the Park's Vector (PV) ring and then apply some more sophisticated signal processing methods. It is shown in this paper that this method can be unreliable and is strongly dependent on the magnetic poles and rotor slot numbers. To overcome this constraint, the novel Filtered Park's/Extended Park's Vector Approach (FPVA/FEPVA) is introduced. The investigation is carried out with FEM simulations and experimental testing. The results prove to satisfyingly coincide, whereas the proposed advanced FPVA method is desirably reliable.

Detection of a sudden change of the field time series based on the Lorenz system

PubMed Central

Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series. PMID:28141832

Finding a Hadamard matrix by simulated annealing of spin vectors

NASA Astrophysics Data System (ADS)

Bayu Suksmono, Andriyan

2017-05-01

Reformulation of a combinatorial problem into optimization of a statistical-mechanics system enables finding a better solution using heuristics derived from a physical process, such as by the simulated annealing (SA). In this paper, we present a Hadamard matrix (H-matrix) searching method based on the SA on an Ising model. By equivalence, an H-matrix can be converted into a seminormalized Hadamard (SH) matrix, whose first column is unit vector and the rest ones are vectors with equal number of -1 and +1 called SH-vectors. We define SH spin vectors as representation of the SH vectors, which play a similar role as the spins on Ising model. The topology of the lattice is generalized into a graph, whose edges represent orthogonality relationship among the SH spin vectors. Starting from a randomly generated quasi H-matrix Q, which is a matrix similar to the SH-matrix without imposing orthogonality, we perform the SA. The transitions of Q are conducted by random exchange of {+, -} spin-pair within the SH-spin vectors that follow the Metropolis update rule. Upon transition toward zeroth energy, the Q-matrix is evolved following a Markov chain toward an orthogonal matrix, at which the H-matrix is said to be found. We demonstrate the capability of the proposed method to find some low-order H-matrices, including the ones that cannot trivially be constructed by the Sylvester method.

Non-overlapped P- and S-wave Poynting vectors and their solution by the grid method

NASA Astrophysics Data System (ADS)

Lu, Yongming; Liu, Qiancheng

2018-06-01

The Poynting vector represents the local directional energy flux density of seismic waves in geophysics. It is widely used in elastic reverse time migration to analyze source illumination, suppress low-wavenumber noise, correct for image polarity and extract angle-domain common-image gathers. However, the P- and S-waves are mixed together during wavefield propagation so that the P and S energy fluxes are not clean everywhere, especially at the overlapped points. In this paper, we use a modified elastic-wave equation in which the P and S vector wavefields are naturally separated. Then, we develop an efficient method to evaluate the separable P and S Poynting vectors, respectively, based on the view that the group velocity and phase velocity have the same direction in isotropic elastic media. We furthermore formulate our method using an unstructured mesh-based modeling method named the grid method. Finally, we verify our method using two numerical examples.

Deduction of two-dimensional blood flow vector by dual angle diverging waves from a cardiac sector probe

NASA Astrophysics Data System (ADS)

Maeda, Moe; Nagaoka, Ryo; Ikeda, Hayato; Yaegashi, So; Saijo, Yoshifumi

2018-07-01

Color Doppler method is widely used for noninvasive diagnosis of heart diseases. However, the method can measure one-dimensional (1D) blood flow velocity only along an ultrasonic beam. In this study, diverging waves with two different angles were irradiated from a cardiac sector probe to estimate a two-dimensional (2D) blood flow vector from each velocity measured with the angles. The feasibility of the proposed method was evaluated in experiments using flow poly(vinyl alcohol) (PVA) gel phantoms. The 2D velocity vectors obtained with the proposed method were compared with the flow vectors obtained with the particle image velocimetry (PIV) method. Root mean square errors of the axial and lateral components were 11.3 and 29.5 mm/s, respectively. The proposed method was also applied to echo data from the left ventricle of the heart. The inflow from the mitral valve in diastole and the ejection flow concentrating in the aorta in systole were visualized.

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

Attitude Determination Using Two Vector Measurements

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1998-01-01

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

Methods, systems and apparatus for controlling third harmonic voltage when operating a multi-space machine in an overmodulation region

DOEpatents

Perisic, Milun; Kinoshita, Michael H; Ranson, Ray M; Gallegos-Lopez, Gabriel

2014-06-03

Methods, system and apparatus are provided for controlling third harmonic voltages when operating a multi-phase machine in an overmodulation region. The multi-phase machine can be, for example, a five-phase machine in a vector controlled motor drive system that includes a five-phase PWM controlled inverter module that drives the five-phase machine. Techniques for overmodulating a reference voltage vector are provided. For example, when the reference voltage vector is determined to be within the overmodulation region, an angle of the reference voltage vector can be modified to generate a reference voltage overmodulation control angle, and a magnitude of the reference voltage vector can be modified, based on the reference voltage overmodulation control angle, to generate a modified magnitude of the reference voltage vector. By modifying the reference voltage vector, voltage command signals that control a five-phase inverter module can be optimized to increase output voltages generated by the five-phase inverter module.

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

Viability of strongly coupled scenarios with a light Higgs-like boson.

PubMed

Pich, Antonio; Rosell, Ignasi; Sanz-Cillero, Juan José

2013-05-03

We present a one-loop calculation of the oblique S and T parameters within strongly coupled models of electroweak symmetry breaking with a light Higgs-like boson. We use a general effective Lagrangian, implementing the chiral symmetry breaking SU(2)(L) [Symbol: see text]SU(2)(R) → SU(2)(L+R) with Goldstone bosons, gauge bosons, the Higgs-like scalar, and one multiplet of vector and axial-vector massive resonance states. Using a dispersive representation and imposing a proper ultraviolet behavior, we obtain S and T at the next-to-leading order in terms of a few resonance parameters. The experimentally allowed range forces the vector and axial-vector states to be heavy, with masses above the TeV scale, and suggests that the Higgs-like scalar should have a WW coupling close to the standard model one. Our conclusions are generic and apply to more specific scenarios such as the minimal SO(5)/SO(4) composite Higgs model.

New Multigrid Method Including Elimination Algolithm Based on High-Order Vector Finite Elements in Three Dimensional Magnetostatic Field Analysis

NASA Astrophysics Data System (ADS)

Hano, Mitsuo; Hotta, Masashi

A new multigrid method based on high-order vector finite elements is proposed in this paper. Low level discretizations in this method are obtained by using low-order vector finite elements for the same mesh. Gauss-Seidel method is used as a smoother, and a linear equation of lowest level is solved by ICCG method. But it is often found that multigrid solutions do not converge into ICCG solutions. An elimination algolithm of constant term using a null space of the coefficient matrix is also described. In three dimensional magnetostatic field analysis, convergence time and number of iteration of this multigrid method are discussed with the convectional ICCG method.

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

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

PubMed Central

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

2012-01-01

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

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

PubMed

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

2012-01-01

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

Modelling soil water retention using support vector machines with genetic algorithm optimisation.

PubMed

Lamorski, Krzysztof; Sławiński, Cezary; Moreno, Felix; Barna, Gyöngyi; Skierucha, Wojciech; Arrue, José L

2014-01-01

This work presents point pedotransfer function (PTF) models of the soil water retention curve. The developed models allowed for estimation of the soil water content for the specified soil water potentials: -0.98, -3.10, -9.81, -31.02, -491.66, and -1554.78 kPa, based on the following soil characteristics: soil granulometric composition, total porosity, and bulk density. Support Vector Machines (SVM) methodology was used for model development. A new methodology for elaboration of retention function models is proposed. Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models' parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. This new aim function avoids overestimation of models which is typically encountered when root mean squared error is used as an aim function. Elaborated models showed good agreement with measured soil water retention data. Achieved coefficients of determination values were in the range 0.67-0.92. Studies demonstrated usability of ν-SVM methodology together with genetic algorithm optimisation for retention modelling which gave better performing models than other tested approaches.

Epirubicin-loaded superparamagnetic iron-oxide nanoparticles for transdermal delivery: cancer therapy by circumventing the skin barrier.

PubMed

Rao, Yue-feng; Chen, Wei; Liang, Xing-guang; Huang, Yong-zhuo; Miao, Jing; Liu, Lin; Lou, Yan; Zhang, Xing-guo; Wang, Ben; Tang, Rui-kang; Chen, Zhong; Lu, Xiao-yang

2015-01-14

The transdermal administration of chemotherapeutic agents is a persistent challenge for tumor treatments. A model anticancer agent, epirubicin (EPI), is attached to functionalized superparamagnetic iron-oxide nanoparticles (SPION). The covalent modification of the SPION results in EPI-SPION, a potential drug delivery vector that uses magnetism for the targeted transdermal chemotherapy of skin tumors. The spherical EPI-SPION composite exhibits excellent magnetic responsiveness with a saturation magnetization intensity of 77.8 emu g(-1) . They feature specific pH-sensitive drug release, targeting the acidic microenvironment typical in common tumor tissues or endosomes/lysosomes. Cellular uptake studies using human keratinocyte HaCaT cells and melanoma WM266 cells demonstrate that SPION have good biocompatibility. After conjugation with EPI, the nanoparticles can inhibit WM266 cell proliferation; its inhibitory effect on tumor proliferation is determined to be dose-dependent. In vitro transdermal studies demonstrate that the EPI-SPION composites can penetrate deep inside the skin driven by an external magnetic field. The magnetic-field-assisted SPION transdermal vector can circumvent the stratum corneum via follicular pathways. The study indicates the potential of a SPION-based vector for feasible transdermal therapy of skin cancer. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Vertical oviposition activity of mosquitoes in the Atlantic Forest of Brazil with emphasis on the sylvan vector, Haemagogus leucocelaenus (Diptera: Culicidae).

PubMed

Alencar, Jeronimo; de Mello, Cecilia Ferreira; Gil-Santana, Hélcio R; Guimarães, Anthony Érico; de Almeida, Sergio Antonio Silva; Gleiser, Raquel M

2016-06-01

This study aimed to assess the vertical patterns of oviposition and temporal changes in the distribution of mosquito species in an area of the Atlantic Forest in Rio de Janeiro State, Brazil, and in particular, the behavior and oviposition of potential yellow fever virus vectors. Mosquito samples were collected from the Ecological Reserve Guapiaçu (REGUA, Brazil), which includes a somewhat disturbed forest, with a large diversity of plants and animals. In all, 5,458 specimens (ten species from seven genera) were collected. Haemagogus leucocelaenus was the most frequently captured species, representing 73% of the specimens collected. Species richness and diversity were the highest in the samples collected from the ground-level ovitraps and decreased with height. Species composition also differed significantly among heights. The largest species differences were detected between ovitraps set at the ground level and those set at 7 m and 9 m; Hg. leucocelaenus, Limatus durhamii, and Limatus paraensis contributed most to these differences. Sampling month and climatic variables had significant effects on species richness and diversity. Species diversity and richness decreased with height, suggesting that the conditions for mosquito breeding are more favorable closer to the ground. Species composition also showed vertical differences. © 2016 The Society for Vector Ecology.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

An implementation of the QMR method based on coupled two-term recurrences

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noeel M.

1992-01-01

The authors have proposed a new Krylov subspace iteration, the quasi-minimal residual algorithm (QMR), for solving non-Hermitian linear systems. In the original implementation of the QMR method, the Lanczos process with look-ahead is used to generate basis vectors for the underlying Krylov subspaces. In the Lanczos algorithm, these basis vectors are computed by means of three-term recurrences. It has been observed that, in finite precision arithmetic, vector iterations based on three-term recursions are usually less robust than mathematically equivalent coupled two-term vector recurrences. This paper presents a look-ahead algorithm that constructs the Lanczos basis vectors by means of coupled two-term recursions. Implementation details are given, and the look-ahead strategy is described. A new implementation of the QMR method, based on this coupled two-term algorithm, is described. A simplified version of the QMR algorithm without look-ahead is also presented, and the special case of QMR for complex symmetric linear systems is considered. Results of numerical experiments comparing the original and the new implementations of the QMR method are reported.

A new method for distortion magnetic field compensation of a geomagnetic vector measurement system

NASA Astrophysics Data System (ADS)

Liu, Zhongyan; Pan, Mengchun; Tang, Ying; Zhang, Qi; Geng, Yunling; Wan, Chengbiao; Chen, Dixiang; Tian, Wugang

2016-12-01

The geomagnetic vector measurement system mainly consists of three-axis magnetometer and an INS (inertial navigation system), which have many ferromagnetic parts on them. The magnetometer is always distorted by ferromagnetic parts and other electric equipments such as INS and power circuit module within the system, which can lead to geomagnetic vector measurement error of thousands of nT. Thus, the geomagnetic vector measurement system has to be compensated in order to guarantee the measurement accuracy. In this paper, a new distortion magnetic field compensation method is proposed, in which a permanent magnet with different relative positions is used to change the ambient magnetic field to construct equations of the error model parameters, and the parameters can be accurately estimated by solving linear equations. In order to verify effectiveness of the proposed method, the experiment is conducted, and the results demonstrate that, after compensation, the components errors of measured geomagnetic field are reduced significantly. It demonstrates that the proposed method can effectively improve the accuracy of the geomagnetic vector measurement system.

Composition and Genetic Diversity of Mosquitoes (Diptera: Culicidae) on Islands and Mainland Shores of Kenya’s Lakes Victoria and Baringo

PubMed Central

Ajamma, Yvonne Ukamaka; Villinger, Jandouwe; Omondi, David; Salifu, Daisy; Onchuru, Thomas Ogao; Njoroge, Laban; Muigai, Anne W. T.; Masiga, Daniel K.

2016-01-01

The Lake Baringo and Lake Victoria regions of Kenya are associated with high seroprevalence of mosquito-transmitted arboviruses. However, molecular identification of potential mosquito vector species, including morphologically identified ones, remains scarce. To estimate the diversity, abundance, and distribution of mosquito vectors on the mainland shores and adjacent inhabited islands in these regions, we collected and morphologically identified adult and immature mosquitoes and obtained the corresponding sequence variation at cytochrome c oxidase 1 (COI) and internal transcribed spacer region 2 (ITS2) gene regions. A total of 63 species (including five subspecies) were collected from both study areas, 47 of which have previously been implicated as disease vectors. Fourteen species were found only on island sites, which are rarely included in mosquito diversity surveys. We collected more mosquitoes, yet with lower species composition, at Lake Baringo (40,229 mosquitoes, 32 species) than at Lake Victoria (22,393 mosquitoes, 54 species). Phylogenetic analysis of COI gene sequences revealed Culex perexiguus and Cx. tenagius that could not be distinguished morphologically. Most Culex species clustered into a heterogeneous clade with closely related sequences, while Culex pipiens clustered into two distinct COI and ITS2 clades. These data suggest limitations in current morphological identification keys. This is the first DNA barcode report of Kenyan mosquitoes. To improve mosquito species identification, morphological identifications should be supported by their molecular data, while diversity surveys should target both adults and immatures. The diversity of native mosquito disease vectors identified in this study impacts disease transmission risks to humans and livestock. PMID:27402888

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

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.

Video-rate terahertz electric-field vector imaging

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

Takai, Mayuko; Takeda, Masatoshi; Sasaki, Manabu

We present an experimental setup to dramatically reduce a measurement time for obtaining spatial distributions of terahertz electric-field (E-field) vectors. The method utilizes the electro-optic sampling, and we use a charge-coupled device to detect a spatial distribution of the probe beam polarization rotation by the E-field-induced Pockels effect in a 〈110〉-oriented ZnTe crystal. A quick rotation of the ZnTe crystal allows analyzing the terahertz E-field direction at each image position, and the terahertz E-field vector mapping at a fixed position of an optical delay line is achieved within 21 ms. Video-rate mapping of terahertz E-field vectors is likely to bemore » useful for achieving real-time sensing of terahertz vector beams, vector vortices, and surface topography. The method is also useful for a fast polarization analysis of terahertz beams.« less

Impact of insecticide-treated bed nets on malaria transmission indices on the south coast of Kenya

PubMed Central

2011-01-01

Background Besides significantly reducing malaria vector densities, prolonged usage of bed nets has been linked to decline of Anopheles gambiae s.s. relative to Anopheles arabiensis, changes in host feeding preference of malaria vectors, and behavioural shifts to exophagy (outdoor biting) for the two important malaria vectors in Africa, An. gambiae s.l. and Anopheles funestus. In southern coastal Kenya, bed net use was negligible in 1997-1998 when Anopheles funestus and An. gambiae s.s. were the primary malaria vectors, with An. arabiensis and Anopheles merus playing a secondary role. Since 2001, bed net use has increased progressively and reached high levels by 2009-2010 with corresponding decline in malaria transmission. Methods To evaluate the impact of the substantial increase in household bed net use within this area on vector density, vector composition, and human-vector contact, indoor and outdoor resting mosquitoes were collected in the same region during 2009-2010 using pyrethrum spray catches and clay pots for indoor and outdoor collections respectively. Information on bed net use per sleeping spaces and factors influencing mosquito density were determined in the same houses using Poisson regression analysis. Species distribution was determined, and number of mosquitoes per house, human-biting rates (HBR), and entomological inoculation rate (EIR) were compared to those reported for the same area during 1997-1998, when bed net coverage had been minimal. Results Compared to 1997-1998, a significant decline in the relative proportion of An. gambiae s.s. among collected mosquitoes was noted, coupled with a proportionate increase of An. arabiensis. Following > 5 years of 60-86% coverage with bed nets, the density, human biting rate and EIR of indoor resting mosquitoes were reduced by more than 92% for An. funestus and by 75% for An. gambiae s.l. In addition, the host feeding choice of both vectors shifted more toward non-human vertebrates. Besides bed net use, malaria vector abundance was also influenced by type of house construction and according to whether one sleeps on a bed or a mat (both of these are associated with household wealth). Mosquito density was positively associated with presence of domestic animals. Conclusions These entomological indices indicate a much reduced human biting rate and a diminishing role of An. gambiae s.s. in malaria transmission following high bed net coverage. While increasing bed net coverage beyond the current levels may not significantly reduce the transmission potential of An. arabiensis, it is anticipated that increasing or at least sustaining high bed net coverage will result in a diminished role for An. funestus in malaria transmission. PMID:22165904

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

NASA Astrophysics Data System (ADS)

Chang, Ching-Yuan; Ma, Chien-Ching

2017-08-01

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

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes.

PubMed

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-10-03

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.

Chromosome preference of disease genes and vectorization for the prediction of non-coding disease genes

PubMed Central

Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan

2017-01-01

Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes. PMID:29108274

Vectorization on the star computer of several numerical methods for a fluid flow problem

NASA Technical Reports Server (NTRS)

Lambiotte, J. J., Jr.; Howser, L. M.

1974-01-01

A reexamination of some numerical methods is considered in light of the new class of computers which use vector streaming to achieve high computation rates. A study has been made of the effect on the relative efficiency of several numerical methods applied to a particular fluid flow problem when they are implemented on a vector computer. The method of Brailovskaya, the alternating direction implicit method, a fully implicit method, and a new method called partial implicitization have been applied to the problem of determining the steady state solution of the two-dimensional flow of a viscous imcompressible fluid in a square cavity driven by a sliding wall. Results are obtained for three mesh sizes and a comparison is made of the methods for serial computation.

DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins.

PubMed

Meher, Prabina Kumar; Sahu, Tanmaya Kumar; Banchariya, Anjali; Rao, Atmakuri Ramakrishna

2017-03-24

Insecticide resistance is a major challenge for the control program of insect pests in the fields of crop protection, human and animal health etc. Resistance to different insecticides is conferred by the proteins encoded from certain class of genes of the insects. To distinguish the insecticide resistant proteins from non-resistant proteins, no computational tool is available till date. Thus, development of such a computational tool will be helpful in predicting the insecticide resistant proteins, which can be targeted for developing appropriate insecticides. Five different sets of feature viz., amino acid composition (AAC), di-peptide composition (DPC), pseudo amino acid composition (PAAC), composition-transition-distribution (CTD) and auto-correlation function (ACF) were used to map the protein sequences into numeric feature vectors. The encoded numeric vectors were then used as input in support vector machine (SVM) for classification of insecticide resistant and non-resistant proteins. Higher accuracies were obtained under RBF kernel than that of other kernels. Further, accuracies were observed to be higher for DPC feature set as compared to others. The proposed approach achieved an overall accuracy of >90% in discriminating resistant from non-resistant proteins. Further, the two classes of resistant proteins i.e., detoxification-based and target-based were discriminated from non-resistant proteins with >95% accuracy. Besides, >95% accuracy was also observed for discrimination of proteins involved in detoxification- and target-based resistance mechanisms. The proposed approach not only outperformed Blastp, PSI-Blast and Delta-Blast algorithms, but also achieved >92% accuracy while assessed using an independent dataset of 75 insecticide resistant proteins. This paper presents the first computational approach for discriminating the insecticide resistant proteins from non-resistant proteins. Based on the proposed approach, an online prediction server DIRProt has also been developed for computational prediction of insecticide resistant proteins, which is accessible at http://cabgrid.res.in:8080/dirprot/ . The proposed approach is believed to supplement the efforts needed to develop dynamic insecticides in wet-lab by targeting the insecticide resistant proteins.

[Bioimpedance vector analysis for body composition in Mexican population].

PubMed

Espinosa-Cuevas, Maria de los Angeles; Rivas-Rodríguez, Lucía; González-Medina, Enna Cristal; Atilano-Carsi, Ximena; Miranda-Alatriste, Paola; Correa-Rotter, Ricardo

2007-01-01

To construct bivariate tolerance ellipses from impedance values normalized for height, which can be used in Mexican population for the assessment of body composition and compare them with others made in different populations. Body composition was assessed by bioelectrical impedance analysis (BIA) in 439 subjects (204 men and 235 women), 18 to 82 years old, with a BMI between 18-31, using an impedanciometer Quadscan 4000. Resistance, reactance and phase angle were used to calculate bioelectrical impedance vectors and construct bivariate tolerance ellipses. Mean age in men was 47.1 +/- 16 years and 42.4 +/- 13 for women, mean weight (73.4 + 9 vs. 60.1 + 8 kg) and height (1.68 vs. 1.55 m) were significant greater in men than in women (p < 0.002). Women in comparison with men, had greater values of impedance (622.96 +/- 66.16 S2 vs. 523.59 +/- 56.56 D) and resistance (618.96 +/- 66.10 Q 61.97 vs. 521.73 +/- 61.97 2), as well as of resistance and reactance standardized by height (398.24 +/-46.30 S2/m vs. 308.66 +/- 38.44) (44.32 +/- 7.14 i/m vs. 39.75 +/-6.29) respectively, with a significant difference in all of them (p < 0.0001). Similarly, the reactance was greater in females, nevertheless this difference did not reach statistical significance (68.96 +/- 11.17 vs. 67.18 +/- 10.3; p = 0.0861). The phase angle was greater in men than in women, with a statistically significant difference (7.330 +/- 0.88 vs. 6.360 +/- 0.97; p < 0.0001). Bivariate tolerance ellipses (50%, 75% and 95%) derived from Mexican subjects showed a significant upward deviation (p < 0.05) from previously published references from Mexican American and Italian populations. New ellipses of tolerance were therefore constructed for the Mexican population. Bioimpedance vectors in Mexican subjects are significantly different from the existing ones, supporting the need of population specific bivariate tolerance ellipses for the evaluation of body composition.

Visualizing vector field topology in fluid flows

NASA Technical Reports Server (NTRS)

Helman, James L.; Hesselink, Lambertus

1991-01-01

Methods of automating the analysis and display of vector field topology in general and flow topology in particular are discussed. Two-dimensional vector field topology is reviewed as the basis for the examination of topology in three-dimensional separated flows. The use of tangent surfaces and clipping in visualizing vector field topology in fluid flows is addressed.

Spectroscopy of SU(4) composite Higgs theory with two distinct fermion representations

NASA Astrophysics Data System (ADS)

Ayyar, Venkitesh; DeGrand, Thomas; Golterman, Maarten; Hackett, Daniel C.; Jay, William I.; Neil, Ethan T.; Shamir, Yigal; Svetitsky, Benjamin

2018-04-01

We have simulated the SU(4) lattice gauge theory coupled to dynamical fermions in the fundamental and two-index antisymmetric (sextet) representations simultaneously. Such theories arise naturally in the context of composite Higgs models that include a partially composite top quark. We describe the low-lying meson spectrum of the theory and fit the pseudoscalar masses and decay constants to chiral perturbation theory. We infer as well the mass and decay constant of the Goldstone boson corresponding to the nonanomalous U(1) symmetry of the model. Our results are broadly consistent with large-Nc scaling and vector-meson dominance.

Helper-Free Foamy Virus Vectors

PubMed Central

TROBRIDGE, GRANT D.; RUSSELL, DAVID W.

2010-01-01

Retroviral vectors based on human foamy virus (HFV) have been developed and show promise as gene therapy vehicles. Here we describe a method for the production of HFV vector stocks free of detectable helper virus. The helper and vector plasmid constructs used both lack the HFV bel genes, so recombination between these constructs cannot create a wild-type virus. A fusion promoter that combines portions of the cytomegalovirus (CMV) immediate-early and HFV long terminal repeat (LTR) promoters was used to drive expression of both the helper and vector constructs. The CMV–LTR fusion promoter allows for HFV vector production in the absence of the Bel-1 trans-activator protein, which would otherwise be necessary for efficient transcription from the HFV LTR. Vector stocks containing either neomycin phosphotransferase or alkaline phosphatase reporter genes were produced by transient transfection at titers greater than 105 transducing units/ml. G418-resistant BHK-21 cells obtained by transduction with neo vectors contained randomly integrated HFV vector proviruses without detectable deletions or rearrangements. The vector stocks generated were free of replication-competent retrovirus (RCR), as determined by assays for LTR trans-activation and a marker rescue assay developed here for the detection of Bel-independent RCR. OVERVIEW SUMMARY Vectors based on human foamy virus have been developed but low titers and the presence of replication-competent retrovirus (RCR) in vector stocks have prevented their use in preclinical animal experiments. We have developed a transient transfection method that can be used to produce replication-incompetent HFV vector stocks at titers greater than 105/ml, and that does not produce contaminating RCR. The use of CMV-HFV LTR fusion promoters in the helper and vector constructs has circumvented the requirement for the HFV Bel-1 trans-activator protein. Consequently, the potential for generating wild-type HFV by recombination between helper and vector constructs during vector production has been eliminated. Here we describe HFV vector production using this Bel-independent system. PMID:9853518

[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.

[Construction and eukaryotic expression of PVAX1-hPV58mE6E7fcGB composite gene vaccine].

PubMed

Wang, He; Yu, Jiyun; Li, Li

2013-10-01

To construct and express a composite gene vaccine for human papillomavirus 58(HPV58)-associated cervical cancer, we inserted HPV58mE6E7 fusion gene into pCI-Fc-GPI eukaryotic expression vector, constructing a recombinant plasmid named pCI-sig-HPV58mE6E7-Fc-GPI. Then we further inserted fragment of sig-HPV58mE6E7Fc-GPI into the novel vaccine vector PVAX1-IRES-GM/B7, constructing PVAX1-HPV58mE6E7FcGB composite gene vaccine. PVAX1-HPV58mE6E7FcGB vaccine was successfully constructed and identified by restriction endonuclease and sequencing analysis. Eukaryotic expression of fusion antigen sig-HPV58mE6E7-Fc-GPI and molecular ad-juvant GM-CSF and B7. 1 were proved to be realized at the same time by flow cytometry and immunofluorescence. So PVAX1-HPV58mE6E7FcGB can be taken as a candidate of therapeutic vaccine for HPV58-associated tumors and their precancerous transformations.

Land cover variation and West Nile virus prevalence: Patterns, processes, and implications for disease control

USGS Publications Warehouse

Ezenwa, V.O.; Milheim, L.E.; Coffey, M.F.; Godsey, M.S.; King, R.J.; Guptill, S.C.

2007-01-01

Identifying links between environmental variables and infectious disease risk is essential to understanding how human-induced environmental changes will effect the dynamics of human and wildlife diseases. Although land cover change has often been tied to spatial variation in disease occurrence, the underlying factors driving the correlations are often unknown, limiting the applicability of these results for disease prevention and control. In this study, we described associations between land cover composition and West Nile virus (WNV) infection prevalence, and investigated three potential processes accounting for observed patterns: (1) variation in vector density; (2) variation in amplification host abundance; and (3) variation in host community composition. Interestingly, we found that WNV infection rates among Culex mosquitoes declined with increasing wetland cover, but wetland area was not significantly associated with either vector density or amplification host abundance. By contrast, wetland area was strongly correlated with host community composition, and model comparisons suggested that this factor accounted, at least partially, for the observed effect of wetland area on WNV infection risk. Our results suggest that preserving large wetland areas, and by extension, intact wetland bird communities, may represent a valuable ecosystem-based approach for controlling WNV outbreaks. ?? Mary Ann Liebert, Inc.

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

PubMed

Zhang, Jianguang; Jiang, Jianmin

2018-02-01

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

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Vectorized and multitasked solution of the few-group neutron diffusion equations

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

Zee, S.K.; Turinsky, P.J.; Shayer, Z.

1989-03-01

A numerical algorithm with parallelism was used to solve the two-group, multidimensional neutron diffusion equations on computers characterized by shared memory, vector pipeline, and multi-CPU architecture features. Specifically, solutions were obtained on the Cray X/MP-48, the IBM-3090 with vector facilities, and the FPS-164. The material-centered mesh finite difference method approximation and outer-inner iteration method were employed. Parallelism was introduced in the inner iterations using the cyclic line successive overrelaxation iterative method and solving in parallel across lines. The outer iterations were completed using the Chebyshev semi-iterative method that allows parallelism to be introduced in both space and energy groups. Formore » the three-dimensional model, power, soluble boron, and transient fission product feedbacks were included. Concentrating on the pressurized water reactor (PWR), the thermal-hydraulic calculation of moderator density assumed single-phase flow and a closed flow channel, allowing parallelism to be introduced in the solution across the radial plane. Using a pinwise detail, quarter-core model of a typical PWR in cycle 1, for the two-dimensional model without feedback the measured million floating point operations per second (MFLOPS)/vector speedups were 83/11.7. 18/2.2, and 2.4/5.6 on the Cray, IBM, and FPS without multitasking, respectively. Lower performance was observed with a coarser mesh, i.e., shorter vector length, due to vector pipeline start-up. For an 18 x 18 x 30 (x-y-z) three-dimensional model with feedback of the same core, MFLOPS/vector speedups of --61/6.7 and an execution time of 0.8 CPU seconds on the Cray without multitasking were measured. Finally, using two CPUs and the vector pipelines of the Cray, a multitasking efficiency of 81% was noted for the three-dimensional model.« less

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

PubMed

Xia, Wenjun; Mita, Yoshio; Shibata, Tadashi

2016-05-01

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

Improving semi-text-independent method of writer verification using difference vector

NASA Astrophysics Data System (ADS)

Li, Xin; Ding, Xiaoqing

2009-01-01

The semi-text-independent method of writer verification based on the linear framework is a method that can use all characters of two handwritings to discriminate the writers in the condition of knowing the text contents. The handwritings are allowed to just have small numbers of even totally different characters. This fills the vacancy of the classical text-dependent methods and the text-independent methods of writer verification. Moreover, the information, what every character is, is used for the semi-text-independent method in this paper. Two types of standard templates, generated from many writer-unknown handwritten samples and printed samples of each character, are introduced to represent the content information of each character. The difference vectors of the character samples are gotten by subtracting the standard templates from the original feature vectors and used to replace the original vectors in the process of writer verification. By removing a large amount of content information and remaining the style information, the verification accuracy of the semi-text-independent method is improved. On a handwriting database involving 30 writers, when the query handwriting and the reference handwriting are composed of 30 distinct characters respectively, the average equal error rate (EER) of writer verification reaches 9.96%. And when the handwritings contain 50 characters, the average EER falls to 6.34%, which is 23.9% lower than the EER of not using the difference vectors.

A Power Transformers Fault Diagnosis Model Based on Three DGA Ratios and PSO Optimization SVM

NASA Astrophysics Data System (ADS)

Ma, Hongzhe; Zhang, Wei; Wu, Rongrong; Yang, Chunyan

2018-03-01

In order to make up for the shortcomings of existing transformer fault diagnosis methods in dissolved gas-in-oil analysis (DGA) feature selection and parameter optimization, a transformer fault diagnosis model based on the three DGA ratios and particle swarm optimization (PSO) optimize support vector machine (SVM) is proposed. Using transforming support vector machine to the nonlinear and multi-classification SVM, establishing the particle swarm optimization to optimize the SVM multi classification model, and conducting transformer fault diagnosis combined with the cross validation principle. The fault diagnosis results show that the average accuracy of test method is better than the standard support vector machine and genetic algorithm support vector machine, and the proposed method can effectively improve the accuracy of transformer fault diagnosis is proved.

A novel, easy and rapid method for constructing yeast two-hybrid vectors using In-Fusion technology.

PubMed

Yu, Deshui; Liao, Libing; Zhang, Ju; Zhang, Yi; Xu, Kedong; Liu, Kun; Li, Xiaoli; Tan, Guangxuan; Chen, Ran; Wang, Yulu; Liu, Xia; Zhang, Xuan; Han, Xiaomeng; Wei, Zhangkun; Li, Chengwei

2018-05-01

Yeast two-hybrid systems are powerful tools for analyzing interactions between proteins. Vector construction is an essential step in yeast two-hybrid experiments, which require bait and prey plasmids. In this study, we modified the multiple cloning site sequence of the yeast plasmid pGADT7 by site-directed mutagenesis PCR to generate the pGADT7-In vector, which resulted in an easy and rapid method for constructing yeast two-hybrid vectors using the In-Fusion cloning technique. This method has three key advantages: only one pair of primers and one round of PCR are needed to generate bait and prey plasmids for each gene, it is restriction endonuclease- and ligase-independent, and it is fast and easily performed.

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

DOEpatents

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

2014-06-17

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

Improved dense trajectories for action recognition based on random projection and Fisher vectors

NASA Astrophysics Data System (ADS)

Ai, Shihui; Lu, Tongwei; Xiong, Yudian

2018-03-01

As an important application of intelligent monitoring system, the action recognition in video has become a very important research area of computer vision. In order to improve the accuracy rate of the action recognition in video with improved dense trajectories, one advanced vector method is introduced. Improved dense trajectories combine Fisher Vector with Random Projection. The method realizes the reduction of the characteristic trajectory though projecting the high-dimensional trajectory descriptor into the low-dimensional subspace based on defining and analyzing Gaussian mixture model by Random Projection. And a GMM-FV hybrid model is introduced to encode the trajectory feature vector and reduce dimension. The computational complexity is reduced by Random Projection which can drop Fisher coding vector. Finally, a Linear SVM is used to classifier to predict labels. We tested the algorithm in UCF101 dataset and KTH dataset. Compared with existed some others algorithm, the result showed that the method not only reduce the computational complexity but also improved the accuracy of action recognition.

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.

Ultra-low background DNA cloning system.

PubMed

Goto, Kenta; Nagano, Yukio

2013-01-01

Yeast-based in vivo cloning is useful for cloning DNA fragments into plasmid vectors and is based on the ability of yeast to recombine the DNA fragments by homologous recombination. Although this method is efficient, it produces some by-products. We have developed an "ultra-low background DNA cloning system" on the basis of yeast-based in vivo cloning, by almost completely eliminating the generation of by-products and applying the method to commonly used Escherichia coli vectors, particularly those lacking yeast replication origins and carrying an ampicillin resistance gene (Amp(r)). First, we constructed a conversion cassette containing the DNA sequences in the following order: an Amp(r) 5' UTR (untranslated region) and coding region, an autonomous replication sequence and a centromere sequence from yeast, a TRP1 yeast selectable marker, and an Amp(r) 3' UTR. This cassette allowed conversion of the Amp(r)-containing vector into the yeast/E. coli shuttle vector through use of the Amp(r) sequence by homologous recombination. Furthermore, simultaneous transformation of the desired DNA fragment into yeast allowed cloning of this DNA fragment into the same vector. We rescued the plasmid vectors from all yeast transformants, and by-products containing the E. coli replication origin disappeared. Next, the rescued vectors were transformed into E. coli and the by-products containing the yeast replication origin disappeared. Thus, our method used yeast- and E. coli-specific "origins of replication" to eliminate the generation of by-products. Finally, we successfully cloned the DNA fragment into the vector with almost 100% efficiency.

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 feature selection approach towards progressive vector transmission over the Internet

NASA Astrophysics Data System (ADS)

Miao, Ru; Song, Jia; Feng, Min

2017-09-01

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

Exploiting the potential of vector control for disease prevention.

PubMed

Townson, H; Nathan, M B; Zaim, M; Guillet, P; Manga, L; Bos, R; Kindhauser, M

2005-12-01

Although vector control has proven highly effective in preventing disease transmission, it is not being used to its full potential, thereby depriving disadvantaged populations of the benefits of well tried and tested methods. Following the discovery of synthetic residual insecticides in the 1940s, large-scale programmes succeeded in bringing many of the important vector-borne diseases under control. By the late 1960s, most vector-borne diseases--with the exception of malaria in Africa--were no longer considered to be of primary public health importance. The result was that control programmes lapsed, resources dwindled, and specialists in vector control disappeared from public health units. Within two decades, many important vector-borne diseases had re-emerged or spread to new areas. The time has come to restore vector control to its key role in the prevention of disease transmission, albeit with an increased emphasis on multiple measures, whether pesticide-based or involving environmental modification, and with a strengthened managerial and operational capacity. Integrated vector management provides a sound conceptual framework for deployment of cost-effective and sustainable methods of vector control. This approach allows for full consideration of the complex determinants of disease transmission, including local disease ecology, the role of human activity in increasing risks of disease transmission, and the socioeconomic conditions of affected communities.

Exploiting the potential of vector control for disease prevention.

PubMed Central

Townson, H.; Nathan, M. B.; Zaim, M.; Guillet, P.; Manga, L.; Bos, R.; Kindhauser, M.

2005-01-01

Although vector control has proven highly effective in preventing disease transmission, it is not being used to its full potential, thereby depriving disadvantaged populations of the benefits of well tried and tested methods. Following the discovery of synthetic residual insecticides in the 1940s, large-scale programmes succeeded in bringing many of the important vector-borne diseases under control. By the late 1960s, most vector-borne diseases--with the exception of malaria in Africa--were no longer considered to be of primary public health importance. The result was that control programmes lapsed, resources dwindled, and specialists in vector control disappeared from public health units. Within two decades, many important vector-borne diseases had re-emerged or spread to new areas. The time has come to restore vector control to its key role in the prevention of disease transmission, albeit with an increased emphasis on multiple measures, whether pesticide-based or involving environmental modification, and with a strengthened managerial and operational capacity. Integrated vector management provides a sound conceptual framework for deployment of cost-effective and sustainable methods of vector control. This approach allows for full consideration of the complex determinants of disease transmission, including local disease ecology, the role of human activity in increasing risks of disease transmission, and the socioeconomic conditions of affected communities. PMID:16462987

Overcoming the challenges of mosquito (Diptera: Culicidae) sampling in remote localities: a comparison of CO2 attractants on mosquito communities in three tropical forest habitats.

PubMed

Steiger, D B Meyer; Ritchie, S A; Laurance, S G W

2014-01-01

Emerging infectious diseases are on the rise with future outbreaks predicted to occur in frontier regions of tropical countries. Disease surveillance in these hotspots is challenging because sampling techniques often rely on vector attractants that are either unavailable in remote localities or difficult to transport. We examined whether a novel method for producing CO2 from yeast and sugar produces similar mosquito species captures compared with a standard attractant such as dry ice. Across three different vegetation communities, we found traps baited with dry ice frequently captured more mosquitoes than yeast-baited traps; however, there was little effect on mosquito community composition. Based on our preliminary experiments, we find that this method of producing CO2 is a realistic alternative to dry ice and would be highly suitable for remote field work.

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

NASA Astrophysics Data System (ADS)

Xie, Tian; Grossman, Jeffrey C.

2018-04-01

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights. Here, we develop a crystal graph convolutional neural networks framework to directly learn material properties from the connection of atoms in the crystal, providing a universal and interpretable representation of crystalline materials. Our method provides a highly accurate prediction of density functional theory calculated properties for eight different properties of crystals with various structure types and compositions after being trained with 1 04 data points. Further, our framework is interpretable because one can extract the contributions from local chemical environments to global properties. Using an example of perovskites, we show how this information can be utilized to discover empirical rules for materials design.

Schools as Potential Risk Sites for Vector-Borne Disease Transmission: Mosquito Vectors in Rural Schools in Two Municipalities in Colombia.

PubMed

Olano, Víctor Alberto; Matiz, María Inés; Lenhart, Audrey; Cabezas, Laura; Vargas, Sandra Lucía; Jaramillo, Juan Felipe; Sarmiento, Diana; Alexander, Neal; Stenström, Thor Axel; Overgaard, Hans J

2015-09-01

Dengue and other vector-borne diseases are of great public health importance in Colombia. Vector surveillance and control activities are often focused at the household level. Little is known about the importance of nonhousehold sites, including schools, in maintaining vector-borne disease transmission. The objectives of this paper were to determine the mosquito species composition in rural schools in 2 municipalities in Colombia and to assess the potential risk of vector-borne disease transmission in school settings. Entomological surveys were carried out in rural schools during the dry and rainy seasons of 2011. A total of 12 mosquito species were found: Aedes aegypti, Anopheles pseudopunctipennis, Culex coronator, Cx. quinquefasciatus, and Limatus durhamii in both immature and adult forms; Ae. fluviatilis, Cx. nigripalpus, Cx. corniger, and Psorophora ferox in immature forms only; and Ae. angustivittatus, Haemagogus equinus, and Trichoprosopon lampropus in adult forms only. The most common mosquito species was Cx. quinquefasciatus. Classrooms contained the greatest abundance of adult female Ae. aegypti and Cx. quinquefasciatus. The most common Ae. aegypti breeding sites were containers classified as "others" (e.g., cans), followed by containers used for water storage. A high level of Ae. aegypti infestation was found during the wet season. Our results suggest that rural schools are potentially important foci for the transmission of dengue and other mosquito-borne diseases. We propose that public health programs should be implemented in rural schools to prevent vector-borne diseases.

Gene silencing in Escherichia coli using antisense RNAs expressed from doxycycline-inducible vectors.

PubMed

Nakashima, N; Tamura, T

2013-06-01

Here, we report on the construction of doxycycline (tetracycline analogue)-inducible vectors that express antisense RNAs in Escherichia coli. Using these vectors, the expression of genes of interest can be silenced conditionally. The expression of antisense RNAs from the vectors was more tightly regulated than the previously constructed isopropyl-β-D-galactopyranoside-inducible vectors. Furthermore, expression levels of antisense RNAs were enhanced by combining the doxycycline-inducible promoter with the T7 promoter-T7 RNA polymerase system; the T7 RNA polymerase gene, under control of the doxycycline-inducible promoter, was integrated into the lacZ locus of the genome without leaving any antibiotic marker. These vectors are useful for investigating gene functions or altering cell phenotypes for biotechnological and industrial applications. A gene silencing method using antisense RNAs in Escherichia coli is described, which facilitates the investigation of bacterial gene function. In particular, the method is suitable for comprehensive analyses or phenotypic analyses of genes essential for growth. Here, we describe expansion of vector variations for expressing antisense RNAs, allowing choice of a vector appropriate for the target genes or experimental purpose. © 2013 The Society for Applied Microbiology.

A recursive technique for adaptive vector quantization

NASA Technical Reports Server (NTRS)

Lindsay, Robert A.

1989-01-01

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

A search for leptoquarks and squarks at HERA

NASA Astrophysics Data System (ADS)

Ahmed, T.; Aid, S.; Andreev, V.; Andrieu, B.; Appuhn, R.-D.; Arpagaus, M.; Babaev, A.; Baehr, J.; Bán, J.; Baranov, P.; Barrelet, E.; Bartel, W.; Barth, M.; Bassler, U.; Beck, H. P.; Behrend, H.-J.; Belousov, A.; Berger, Ch.; Bergstein, H.; Bernardi, G.; Bernet, R.; Bertrand-Coremans, G.; Besançon, M.; Beyer, R.; Biddulph, P.; Bizot, J. C.; Blobel, V.; Borras, K.; Botterweck, F.; Boudry, V.; Braemer, A.; Brasse, F.; Braunschweig, W.; Brisson, V.; Bruncko, D.; Brune, C.; Buchholz, R.; Büngener, L.; Bürger, J.; Büsser, F. W.; Buniatian, A.; Burke, S.; Buschhorn, G.; Campbell, A. J.; Carli, T.; Charles, F.; Clarke, D.; Clegg, A. B.; Colombo, M.; Contreras, J. G.; Coughlan, J. A.; Courau, A.; Coutures, Ch.; Cozzika, G.; Criegee, L.; Cussans, D. G.; Cvach, J.; Dagoret, S.; Dainton, J. B.; Danilov, M.; Dau, W. D.; Daum, K.; David, M.; Deffur, E.; Delcourt, B.; Del Buono, L.; de Roeck, A.; de Wolf, E. A.; di Nezza, P.; Dollfus, C.; Dowell, J. D.; Dreis, H. B.; Duboc, J.; Düllmann, D.; Dünger, O.; Duhm, H.; Ebert, J.; Ebert, T. R.; Eckerlin, G.; Efremenko, V.; Egli, S.; Ehrlichmann, H.; Eichenberger, S.; Eichler, R.; Eisele, F.; Eisenhandler, E.; Ellison, R. J.; Elsen, E.; Erdmann, M.; Erdmann, W.; Evrard, E.; Favart, L.; Fedotov, A.; Feeken, D.; Felst, R.; Feltesse, J.; Ferencei, J.; Ferrarotto, F.; Flamm, K.; Fleischer, M.; Flieser, M.; Flügge, G.; Fomenko, A.; Fominykh, B.; Forbush, M.; Formánek, J.; Foster, J. M.; Franke, G.; Fretwurst, E.; Gabathuler, E.; Gabathuler, K.; Gamerdinger, K.; Garvey, J.; Gayler, J.; Gebauer, M.; Gellrich, A.; Genzel, H.; Gerhards, R.; Goerlach, U.; Goerlich, L.; Gogitidze, N.; Goldberg, M.; Goldner, D.; Gonzalez-Pineiro, B.; Goodall, A. M.; Gorelov, I.; Goritchev, P.; Grab, C.; Grässler, H.; Grässler, R.; Greenshaw, T.; Grindhammer, G.; Gruber, A.; Gruber, C.; Haack, J.; Haidt, D.; Hajduk, L.; Hamon, O.; Hampel, M.; Hanlon, E. M.; Hapke, M.; Haynes, W. J.; Heatherington, J.; Hedberg, V.; Heinzelmann, G.; Henderson, R. C. W.; Henschel, H.; Herma, R.; Herynek, I.; Hess, M. F.; Hildesheim, W.; Hill, P.; Hiller, K. H.; Hilton, C. D.; Hladký, J.; Hoeger, K. C.; Höppner, M.; Horisberger, R.; Huet, Ph.; Hufnagel, H.; Ibbotson, M.; Itterbeck, H.; Jabiol, M.-A.; Jacholkowska, A.; Jacobsson, C.; Jaffre, M.; Janoth, J.; Jansen, T.; Jönsson, L.; Johannsen, K.; Johnson, D. P.; Johnson, L.; Jung, H.; Kalmus, P. I. P.; Kant, D.; Kaschowitz, R.; Kasselmann, P.; Kathage, U.; Kaufmann, H. H.; Kazarian, S.; Kenyon, I. R.; Kermiche, S.; Keuker, C.; Kiesling, C.; Klein, M.; Kleinwort, C.; Knies, G.; Ko, W.; Köhler, T.; Kolanoski, H.; Kole, F.; Kolya, S. D.; Korbel, V.; Korn, M.; Kostka, P.; Kotelnikov, S. K.; Krasny, M. W.; Krehbiel, H.; Krücker, D.; Krüger, U.; Krüner-Marquis, U.; Kubenka, J. P.; Küster, H.; Kuhlen, M.; Kurča, T.; Kurzhöfer, J.; Kuznik, B.; Lacour, D.; Lamarche, F.; Lander, R.; Landon, M. P. J.; Lange, W.; Lanius, P.; Laporte, J.-F.; Lebedev, A.; Leverenz, C.; Levonian, S.; Ley, Ch.; Lindner, A.; Lindström, G.; Linsel, F.; Lipinski, J.; List, B.; Loch, P.; Lohmander, H.; Lopez, G. C.; Lüke, D.; Magnussen, N.; Malinovski, E.; Mani, S.; Maraček, R.; Marage, P.; Marks, J.; Marshall, R.; Martens, J.; Martin, R.; Martyn, H.-U.; Martyniak, J.; Masson, S.; Mavroidis, T.; Maxfield, S. J.; McMahon, S. J.; Mehta, A.; Meier, K.; Mercer, D.; Merz, T.; Meyer, C. A.; Meyer, H.; Meyer, J.; Mikocki, S.; Milstead, D.; Moreau, F.; Morris, J. V.; Müller, G.; Müller, K.; Murín, P.; Nagovizin, V.; Nahnhauer, R.; Naroska, B.; Naumann, Th.; Newman, P. R.; Newton, D.; Neyret, D.; Nguyen, H. K.; Niebergall, F.; Niebuhr, C.; Nisius, R.; Nowak, G.; Noyes, G. W.; Nyberg-Werther, M.; Oberlack, H.; Obrock, U.; Olsson, J. E.; Panaro, E.; Panitch, A.; Pascaud, C.; Patel, G. D.; Peppel, E.; Perez, E.; Phillips, J. P.; Pichler, Ch.; Pitzl, D.; Pope, G.; Prell, S.; Prosi, R.; Rädel, G.; Raupach, F.; Reimer, P.; Reinshagen, S.; Ribarics, P.; Riech, V.; Riedlberger, J.; Riess, S.; Rietz, M.; Robertson, S. M.; Robmann, P.; Roloff, H. E.; Roosen, R.; Rosenbauer, K.; Rostovtsev, A.; Rouse, F.; Royon, C.; Rüter, K.; Rusakov, S.; Rybicki, K.; Rylko, R.; Sahlmann, N.; Sanchez, E.; Sankey, D. P. C.; Savitsky, M.; Schacht, P.; Schiek, S.; Schleper, P.; von Schlippe, W.; Schmidt, C.; Schmidt, D.; Schmidt, G.; Schöning, A.; Schröder, V.; Schuhmann, E.; Schwab, B.; Schwind, A.; Seehausen, U.; Sefkow, F.; Seidel, M.; Sell, R.; Semenov, A.; Shekelyan, V.; Sheviakov, I.; Shooshtari, H.; Shtarkov, L. N.; Siegmon, G.; Siewert, U.; Sirois, Y.; Skillicorn, I. O.; Smirnov, P.; Smith, J. R.; Soloviev, Y.; Spitzer, H.; Starosta, R.; Steenbock, M.; Steffen, P.; Steinberg, R.; Stella, B.; Stephens, K.; Stier, J.; Stiewe, J.; Stösslein, U.; Strachota, J.; Straumann, U.; Struczinski, W.; Sutton, J. P.; Tapprogge, S.; Taylor, R. E.; Tchernyshov, V.; Thiebaux, C.; Thompson, G.; Tichomirov, I.; Truöl, P.; Turnau, J.; Tutas, J.; Uelkes, P.; Usik, A.; Valkár, S.; Valkárová, A.; Vallée, C.; van Esch, P.; van Mechelen, P.; Vartapetian, A.; Vazdik, Y.; Vecko, M.; Verrecchia, P.; Villet, G.; Wacker, K.; Wagener, A.; Wagener, M.; Walker, I. W.; Walther, A.; Weber, G.; Weber, M.; Wegener, D.; Wegner, A.; Wellisch, H. P.; West, L. R.; Willard, S.; Winde, M.; Winter, G.-G.; Wright, A. E.; Wünsch, E.; Wulff, N.; Yiou, T. P.; Žáček, J.; Zarbock, D.; Zhang, Z.; Zimmer, M.; Zimmermann, W.; Zomer, F.; Zuber, K.

1994-12-01

A search in the H1 experiment at HERA for scalar and vector leptoquarks, leptogluons and squarks coupling to first generation fermions is presented in a data sample corresponding to an integrated luminosity of 425 nb-1. For masses ranging up to ˜275 GeV, no significant evidence for the direct production of such particles is found in various possible decay channels. At high masses and beyond the centre of mass energy of 296 GeV a contact interaction analysis is used to further constrain the couplings and masses of new vector leptoquarks and to set lower limits on compositeness scales.

[Adeno-associated viral vectors: methods for production and purification for gene therapy applications].

PubMed

Mena-Enriquez, Mayra; Flores-Contreras, Lucia; Armendáriz-Borunda, Juan

2012-01-01

Viral vectors based on adeno-associated virus (AAV) are widely used in gene therapy protocols, because they have characteristics that make them valuable for the treatment of genetic and chronic degenerative diseases. AAV2 serotype had been the best characterized to date. However, the AAV vectors developed from other serotypes is of special interest, since they have organ-specific tropism which increases their potential for transgene delivery to target cells for performing their therapeutic effects. This article summarizes AAV generalities, methods for their production and purification. It also discusses the use of these vectors in vitro, in vivo and their application in gene therapy clinical trials.

Method and system for efficiently searching an encoded vector index

DOEpatents

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

2001-09-04

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

repRNA: a web server for generating various feature vectors of RNA sequences.

PubMed

Liu, Bin; Liu, Fule; Fang, Longyun; Wang, Xiaolong; Chou, Kuo-Chen

2016-02-01

With the rapid growth of RNA sequences generated in the postgenomic age, it is highly desired to develop a flexible method that can generate various kinds of vectors to represent these sequences by focusing on their different features. This is because nearly all the existing machine-learning methods, such as SVM (support vector machine) and KNN (k-nearest neighbor), can only handle vectors but not sequences. To meet the increasing demands and speed up the genome analyses, we have developed a new web server, called "representations of RNA sequences" (repRNA). Compared with the existing methods, repRNA is much more comprehensive, flexible and powerful, as reflected by the following facts: (1) it can generate 11 different modes of feature vectors for users to choose according to their investigation purposes; (2) it allows users to select the features from 22 built-in physicochemical properties and even those defined by users' own; (3) the resultant feature vectors and the secondary structures of the corresponding RNA sequences can be visualized. The repRNA web server is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repRNA/ .

[Construction and characterization of liposomal magnetofection system in pig kidney cells].

PubMed

Chen, Wenjie; Cui, Haixin; Zhao, Xiang; Cui, Jinhui; Wang, Yan; Sun, Changjiao

2014-06-01

Magnetic nano gene vector is one of the non-viral gene vectors, modified by functional group to bind cationic transfect reagents. Coupling magnetofection with the universal lipofection we developed a novel somatic cell transfection method as the so-called liposomal magnetofection (LMF). This approach is potential to provide somatic cell cloning with stable genetic cell lines to cultivate transgenic animals. In order to construct such liposomal magnetic gene vectors complexes system, we used nano magnetic gene vector to combine with liposomal cationic transfect reagents by molecular self-assembly. This vectors system successfully carried exogenous gene and then transfected animal somatic cells. Here, we conducted atomic force microscopy (AFM), zeta potential-diameter analysis and other characterization experiments to investegate the size distribution and morphology of magnetic nanoparticles, the way of the vectors to load and concentrate DNA molecules. Our data reveal that, the LMF of Pig Kidney cells exhibited higher transfection efficiency comparing with the transfection mediated by the commercial lipofectamine2000. Moreover, LMF method overcomes the constraint of transient expression mediated by lipofection. Meanwhile, MTT assay showed low cytotoxicity of LMF. Hence, LMF is a feasible, low cytotoxic and effective method of cell transfection.

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

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

PubMed

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

2016-01-01

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

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.

Correlation between polar values and vector analysis.

PubMed

Naeser, K; Behrens, J K

1997-01-01

To evaluate the possible correlation between polar value and vector analysis assessment of surgically induced astigmatism. Department of Ophthalmology, Aalborg Sygehus Syd, Denmark. The correlation between polar values and vector analysis was evaluated by simple mathematical and optical methods using accepted principles of trigonometry and first-order optics. Vector analysis and polar values report different aspects of surgically induced astigmatism. Vector analysis describes the total astigmatic change, characterized by both astigmatic magnitude and direction, while the polar value method produces a single, reduced figure that reports flattening or steepening in preselected directions, usually the plane of the surgical meridian. There is a simple Pythagorean correlation between vector analysis and two polar values separated by an arch of 45 degrees. The polar value calculated in the surgical meridian indicates the power or the efficacy of the surgical procedure. The polar value calculated in a plane inclined 45 degrees to the surgical meridian indicates the degree of cylinder rotation induced by surgery. These two polar values can be used to obtain other relevant data such as magnitude, direction, and sphere of an induced cylinder. Consistent use of these methods will enable surgeons to control and in many cases reduce preoperative astigmatism.

Human Immunodeficiency Virus type 1 group M consensus and mosaic envelope glycoproteins

DOEpatents

Korber, Bette T.; Fischer, William; Liao, Hua-Xin; Haynes, Barton F.; Letvin, Norman; Hahn, Beatrice H.

2017-11-21

The disclosure relates to nucleic acids mosaic clade M HIV-1 Env polypeptides and to compositions and vectors comprising same. The nucleic acids are suitable for use in inducing an immune response to HIV-1 in a human.

CSM research: Methods and application studies

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.

1989-01-01

Computational mechanics is that discipline of applied science and engineering devoted to the study of physical phenomena by means of computational methods based on mathematical modeling and simulation, utilizing digital computers. The discipline combines theoretical and applied mechanics, approximation theory, numerical analysis, and computer science. Computational mechanics has had a major impact on engineering analysis and design. When applied to structural mechanics, the discipline is referred to herein as computational structural mechanics. Complex structures being considered by NASA for the 1990's include composite primary aircraft structures and the space station. These structures will be much more difficult to analyze than today's structures and necessitate a major upgrade in computerized structural analysis technology. NASA has initiated a research activity in structural analysis called Computational Structural Mechanics (CSM). The broad objective of the CSM activity is to develop advanced structural analysis technology that will exploit modern and emerging computers, such as those with vector and/or parallel processing capabilities. Here, the current research directions for the Methods and Application Studies Team of the Langley CSM activity are described.

A machine learning approach to the potential-field method for implicit modeling of geological structures

NASA Astrophysics Data System (ADS)

Gonçalves, Ítalo Gomes; Kumaira, Sissa; Guadagnin, Felipe

2017-06-01

Implicit modeling has experienced a rise in popularity over the last decade due to its advantages in terms of speed and reproducibility in comparison with manual digitization of geological structures. The potential-field method consists in interpolating a scalar function that indicates to which side of a geological boundary a given point belongs to, based on cokriging of point data and structural orientations. This work proposes a vector potential-field solution from a machine learning perspective, recasting the problem as multi-class classification, which alleviates some of the original method's assumptions. The potentials related to each geological class are interpreted in a compositional data framework. Variogram modeling is avoided through the use of maximum likelihood to train the model, and an uncertainty measure is introduced. The methodology was applied to the modeling of a sample dataset provided with the software Move™. The calculations were implemented in the R language and 3D visualizations were prepared with the rgl package.

Protein location prediction using atomic composition and global features of the amino acid sequence

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

Cherian, Betsy Sheena, E-mail: betsy.skb@gmail.com; Nair, Achuthsankar S.

2010-01-22

Subcellular location of protein is constructive information in determining its function, screening for drug candidates, vaccine design, annotation of gene products and in selecting relevant proteins for further studies. Computational prediction of subcellular localization deals with predicting the location of a protein from its amino acid sequence. For a computational localization prediction method to be more accurate, it should exploit all possible relevant biological features that contribute to the subcellular localization. In this work, we extracted the biological features from the full length protein sequence to incorporate more biological information. A new biological feature, distribution of atomic composition is effectivelymore » used with, multiple physiochemical properties, amino acid composition, three part amino acid composition, and sequence similarity for predicting the subcellular location of the protein. Support Vector Machines are designed for four modules and prediction is made by a weighted voting system. Our system makes prediction with an accuracy of 100, 82.47, 88.81 for self-consistency test, jackknife test and independent data test respectively. Our results provide evidence that the prediction based on the biological features derived from the full length amino acid sequence gives better accuracy than those derived from N-terminal alone. Considering the features as a distribution within the entire sequence will bring out underlying property distribution to a greater detail to enhance the prediction accuracy.« less

Study on preparation and microwave absorption property of the core-nanoshell composite materials doped with La.

PubMed

Wei, Liqiu; Che, Ruxin; Jiang, Yijun; Yu, Bing

2013-12-01

Microwave absorbing material plays a great role in electromagnetic pollution controlling, electromagnetic interference shielding and stealth technology, etc. The core-nanoshell composite materials doped with La were prepared by a solid-state reaction method, which is applied to the electromagnetic wave absorption. The core is magnetic fly-ash hollow cenosphere, and the shell is the nanosized ferrite doped with La. The thermal decomposition process of the sample was investigated by thermogravimetry and differential thermal analysis. The morphology and components of the composite materials were investigated by the X-ray diffraction analysis, the microstructure was observed by scanning electron microscope and transmission electron microscope. The results of vibrating sample magnetometer analysis indicated that the exchange-coupling interaction happens between ferrite of magnetic fly-ash hollow cenosphere and nanosized ferrite coating, which caused outstanding magnetic properties. The microwave absorbing property of the sample was measured by reflectivity far field radar cross section of radar microwave absorbing material with vector network analyzer. The results indicated that the exchange-coupling interaction enhanced magnetic loss of composite materials. Therefore, in the frequency of 5 GHz, the reflection coefficient can achieve -24 dB. It is better than single material and is consistent with requirements of the microwave absorbing material at the low-frequency absorption. Copyright © 2013 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

Carbon Nano Tube Composites with Chemically Functionalized Plant Oils

NASA Astrophysics Data System (ADS)

Thielemans, Wim; Wool, Richard P.; Blau, Werner; Barron, Valerie

2003-03-01

Carbon Nano Tube Composites with Chemically Functionalized Plant Oil Wim Thielemans, R., P. Wool, V. Barron and W. Blau Multi-Wall Carbon Nano Tubes (MWCNT) made by the Kratchmer-Huffman CCVD process were found to interact and solubilize by slow mechanical stirring, with chemically functionalized plant oils, such as acrylated, epoxidized and maleinated triglycerides (TG) derived from plant oils. The chemical functionality on the TG imparted amphiphilic properties to the oils which allows them to self-assemble on the nanotubes, promoting both dissolution and the ability to make nanocomposites with unusual properties. Once in solution, the MWCT can be processed in a variety of methods, in particular to make composites with enhanced mechanical, fracture and thermal properties. Since the tensile modulus of MWs is about 1 TPa and a vector percolation analysis indicated tensile strengths of 50-100 GPa, we obtain significantly improved properties with even small amounts (1-3the glass transition temperature of the composite by about 20 oC, and the tensile modulus by about 11significant effects on the fracture stress can be obtained due to the both the influence of the strength and length of the MWNT at the crack tip. The ability of the oils to self-assemble on the carbon nanotube surfaces also makes them ideal candidates for self-healing materials. The properties with different functionalized oils will be reported. Supported by EPA, DoE and ISF

Extracellular secretion of recombinant proteins

DOEpatents

Linger, Jeffrey G.; Darzins, Aldis

2014-07-22

Nucleic acids encoding secretion signals, expression vectors containing the nucleic acids, and host cells containing the expression vectors are disclosed. Also disclosed are polypeptides that contain the secretion signals and methods of producing polypeptides, including methods of directing the extracellular secretion of the polypeptides. Exemplary embodiments include cellulase proteins fused to secretion signals, methods to produce and isolate these polypeptides, and methods to degrade lignocellulosic biomass.

A New Microwave Shield Preparation for Super High Frequency Range: Occupational Approach to Radiation Protection.

PubMed

Zaroushani, Vida; Khavanin, Ali; Jonidi Jafari, Ahmad; Mortazavi, Seyed Bagher

2016-01-01

Widespread use of X-band frequency (a part of the super high frequency microwave) in the various workplaces would contribute to occupational exposure with potential of adverse health effects.  According to limited study on microwave shielding for the workplace, this study tried to prepare a new microwave shielding for this purpose. We used EI-403 epoxy thermosetting resin as a matrix and nickel oxide nanoparticle with the diameter of 15-35 nm as filler. The Epoxy/ Nickel oxide composites with 5, 7, 9 and 11 wt% were made in three different thicknesses (2, 4 and 6 mm). According to transmission / reflection method, shielding effectiveness (SE) in the X-band frequency range (8-12.5 GHz) was measured by scattering parameters directly given by the 2-port Vector Network Analyzer. The fabricated composites characterized by X-ray Diffraction and Field Emission Scanning Electron Microscope. The best average of shielding effectiveness in each thickness of fabricated composites obtained by 11%-2 mm, 7%-4 mm and 7%-6 mm composites with SE values of 46.80%, 66.72% and 64.52%, respectively. In addition, the 11%-6 mm, 5%-6 mm and 11%-4 mm-fabricated composites were able to attenuate extremely the incident microwave energy at 8.01, 8.51 and 8.53 GHz by SE of 84.14%, 83.57 and 81.30%, respectively. The 7%-4mm composite could be introduced as a suitable alternative microwave shield in radiation protection topics in order to its proper SE and other preferable properties such as low cost and weight, resistance to corrosion etc. It is necessary to develop and investigate the efficacy of the fabricated composites in the fields by future studies.

Methods of treating Parkinson's disease using viral vectors

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

Bankiewicz, Krystof; Cunningham, Janet

Methods of delivering viral vectors, particularly recombinant adeno-associated virus (rAAV) virions, to the central nervous system (CNS) using convection enhanced delivery (CED) are provided. The rAAV virions include a nucleic acid sequence encoding a therapeutic polypeptide. The methods can be used for treating CNS disorders such as for treating Parkinson's Disease.

Vector potential methods

NASA Technical Reports Server (NTRS)

Hafez, M.

1989-01-01

Vector potential and related methods, for the simulation of both inviscid and viscous flows over aerodynamic configurations, are briefly reviewed. The advantages and disadvantages of several formulations are discussed and alternate strategies are recommended. Scalar potential, modified potential, alternate formulations of Euler equations, least-squares formulation, variational principles, iterative techniques and related methods, and viscous flow simulation are discussed.

The composite structure of mixed τ-(Ag, Cu)xV2O5 bronzes—Evidence for T dependant guest-species ordering and mobility

NASA Astrophysics Data System (ADS)

Hermes, Wilfred; Dollé, Mickaël; Rozier, Patrick; Lidin, Sven

2013-03-01

The complex structural behavior of τ-[AgCu]˜0.92V4O10 has been elucidated by single crystal X-ray diffraction and thermal analysis. The τ-phase region is apparently composed of several distinct phases and this study identifies at least three: τ1rt, τ2rt and τlt. τ1rt and τ2rt have slightly different compositions and crystal habits. Both phases transform to τlt at low temperature. The room temperature modification τ1rt crystallizes in an incommensurately modulated structure with monoclinic symmetry C2(0β1/2) [equivalent to no 5.4, B2(01/2γ) in the Intnl. Tables for Crystallography, Volume C] and the cell parameters a=11.757(4) Å, b=3.6942(5) Å c=9.463(2) Å β=114.62(2)° and the q-vector (0 0.92 1/2), but it is more convenient to transform this to a setting with a non-standard centering X=(1/2 1/2 0 0; 0 0 1/2 1/2; 1/2 1/2 1/2 1/2;) and an axial q vector (0 0.92 0). The structure features a vanadate host lattice with Cu and Ag guests forming an incommensurate composite. The structural data indicates perfect Ag/Cu ordering. At low temperature this modification is replaced by a triclinic phase characterized by two independent q-vectors. The τ2rt phase is similar to the low temperature modification τlt but the satellite reflections are generally more diffuse.

LHC vector resonance searches in the t\\overline{t}Z final state

NASA Astrophysics Data System (ADS)

Backović, Mihailo; Flacke, Thomas; Jain, Bithika; Lee, Seung J.

2017-03-01

LHC searches for BSM resonances in l + l - , jj, t\\overline{t} , γγ and VV final states have so far not resulted in discovery of new physics. Current results set lower limits on mass scales of new physics resonances well into the O(1) TeV range, assuming that the new resonance decays dominantly to a pair of Standard Model particles. While the SM pair searches are a vital probe of possible new physics, it is important to re-examine the scope of new physics scenarios probed with such final states. Scenarios where new resonances decay dominantly to final states other than SM pairs, even though well theoretically motivated, lie beyond the scope of SM pair searches. In this paper we argue that LHC searches for (vector) resonances beyond two particle final states would be useful complementary probes of new physics scenarios. As an example, we consider a class of composite Higgs models, and identify specific model parameter points where the color singlet, electrically neutral vector resonance ρ0 decays dominantly not to a pair of SM particles, but to a fermionic top partner T f1 and a top quark, with T f1 → tZ. We show that dominant decays of ρ 0 → T f1 t in the context of Composite Higgs models are possible even when the decay channel to a pair of T f1 is kinematically open. Our analysis deals with scenarios where both m ρ and {m}_T{{}{_f}}{_1} are of O(1) TeV, leading to highly boosted t\\overline{t}Z final state topologies. We show that the particular composite Higgs scenario we consider is discoverable at the LHC13 with as little as 30 fb-1, while being allowed by other existing experimental constraints.

The covariance matrix for the solution vector of an equality-constrained least-squares problem

NASA Technical Reports Server (NTRS)

Lawson, C. L.

1976-01-01

Methods are given for computing the covariance matrix for the solution vector of an equality-constrained least squares problem. The methods are matched to the solution algorithms given in the book, 'Solving Least Squares Problems.'

Stokes vector based interpolation method to improve the efficiency of bio-inspired polarization-difference imaging in turbid media

NASA Astrophysics Data System (ADS)

Guan, Jinge; Ren, Wei; Cheng, Yaoyu

2018-04-01

We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.

Vector method for strain estimation in phase-sensitive optical coherence elastography

NASA Astrophysics Data System (ADS)

Matveyev, A. L.; Matveev, L. A.; Sovetsky, A. A.; Gelikonov, G. V.; Moiseev, A. A.; Zaitsev, V. Y.

2018-06-01

A noise-tolerant approach to strain estimation in phase-sensitive optical coherence elastography, robust to decorrelation distortions, is discussed. The method is based on evaluation of interframe phase-variation gradient, but its main feature is that the phase is singled out at the very last step of the gradient estimation. All intermediate steps operate with complex-valued optical coherence tomography (OCT) signals represented as vectors in the complex plane (hence, we call this approach the ‘vector’ method). In comparison with such a popular method as least-square fitting of the phase-difference slope over a selected region (even in the improved variant with amplitude weighting for suppressing small-amplitude noisy pixels), the vector approach demonstrates superior tolerance to both additive noise in the receiving system and speckle-decorrelation caused by tissue straining. Another advantage of the vector approach is that it obviates the usual necessity of error-prone phase unwrapping. Here, special attention is paid to modifications of the vector method that make it especially suitable for processing deformations with significant lateral inhomogeneity, which often occur in real situations. The method’s advantages are demonstrated using both simulated and real OCT scans obtained during reshaping of a collagenous tissue sample irradiated by an IR laser beam producing complex spatially inhomogeneous deformations.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

A combined vector potential-scalar potential method for FE computation of 3D magnetic fields in electrical devices with iron cores

NASA Technical Reports Server (NTRS)

Wang, R.; Demerdash, N. A.

1991-01-01

A method of combined use of magnetic vector potential based finite-element (FE) formulations and magnetic scalar potential (MSP) based formulations for computation of three-dimensional magnetostatic fields is introduced. In this method, the curl-component of the magnetic field intensity is computed by a reduced magnetic vector potential. This field intensity forms the basic of a forcing function for a global magnetic scalar potential solution over the entire volume of the region. This method allows one to include iron portions sandwiched in between conductors within partitioned current-carrying subregions. The method is most suited for large-scale global-type 3-D magnetostatic field computations in electrical devices, and in particular rotating electric machinery.

Cloud field classification based upon high spatial resolution textural features. II - Simplified vector approaches

NASA Technical Reports Server (NTRS)

Chen, D. W.; Sengupta, S. K.; Welch, R. M.

1989-01-01

This paper compares the results of cloud-field classification derived from two simplified vector approaches, the Sum and Difference Histogram (SADH) and the Gray Level Difference Vector (GLDV), with the results produced by the Gray Level Cooccurrence Matrix (GLCM) approach described by Welch et al. (1988). It is shown that the SADH method produces accuracies equivalent to those obtained using the GLCM method, while the GLDV method fails to resolve error clusters. Compared to the GLCM method, the SADH method leads to a 31 percent saving in run time and a 50 percent saving in storage requirements, while the GLVD approach leads to a 40 percent saving in run time and an 87 percent saving in storage requirements.

Acceleration of convergence of vector sequences

NASA Technical Reports Server (NTRS)

Sidi, A.; Ford, W. F.; Smith, D. A.

1983-01-01

A general approach to the construction of convergence acceleration methods for vector sequence is proposed. Using this approach, one can generate some known methods, such as the minimal polynomial extrapolation, the reduced rank extrapolation, and the topological epsilon algorithm, and also some new ones. Some of the new methods are easier to implement than the known methods and are observed to have similar numerical properties. The convergence analysis of these new methods is carried out, and it is shown that they are especially suitable for accelerating the convergence of vector sequences that are obtained when one solves linear systems of equations iteratively. A stability analysis is also given, and numerical examples are provided. The convergence and stability properties of the topological epsilon algorithm are likewise given.

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

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.

A review of the vector management methods to prevent and control outbreaks of West Nile virus infection and the challenge for Europe

PubMed Central

2014-01-01

West Nile virus infection is a growing concern in Europe. Vector management is often the primary option to prevent and control outbreaks of the disease. Its implementation is, however, complex and needs to be supported by integrated multidisciplinary surveillance systems and to be organized within the framework of predefined response plans. The impact of the vector control measures depends on multiple factors and the identification of the best combination of vector control methods is therefore not always straightforward. Therefore, this contribution aims at critically reviewing the existing vector control methods to prevent and control outbreaks of West Nile virus infection and to present the challenges for Europe. Most West Nile virus vector control experiences have been recently developed in the US, where ecological conditions are different from the EU and vector control is organized under a different regulatory frame. The extrapolation of information produced in North America to Europe might be limited because of the seemingly different epidemiology in the European region. Therefore, there is an urgent need to analyse the European experiences of the prevention and control of outbreaks of West Nile virus infection and to perform robust cost-benefit analysis that can guide the implementation of the appropriate control measures. Furthermore, to be effective, vector control programs require a strong organisational backbone relying on a previously defined plan, skilled technicians and operators, appropriate equipment, and sufficient financial resources. A decision making guide scheme is proposed which may assist in the process of implementation of vector control measures tailored on specific areas and considering the available information and possible scenarios. PMID:25015004

Modified conjugate gradient method for diagonalizing large matrices.

PubMed

Jie, Quanlin; Liu, Dunhuan

2003-11-01

We present an iterative method to diagonalize large matrices. The basic idea is the same as the conjugate gradient (CG) method, i.e, minimizing the Rayleigh quotient via its gradient and avoiding reintroducing errors to the directions of previous gradients. Each iteration step is to find lowest eigenvector of the matrix in a subspace spanned by the current trial vector and the corresponding gradient of the Rayleigh quotient, as well as some previous trial vectors. The gradient, together with the previous trial vectors, play a similar role as the conjugate gradient of the original CG algorithm. Our numeric tests indicate that this method converges significantly faster than the original CG method. And the computational cost of one iteration step is about the same as the original CG method. It is suitable for first principle calculations.

Adeno-associated virus vectors can be efficiently produced without helper virus.

PubMed

Matsushita, T; Elliger, S; Elliger, C; Podsakoff, G; Villarreal, L; Kurtzman, G J; Iwaki, Y; Colosi, P

1998-07-01

The purpose of this work was to develop an efficient method for the production of adeno-associated virus (AAV) vectors in the absence of helper virus. The adenovirus regions that mediate AAV vector replication were identified and assembled into a helper plasmid. These included the VA, E2A and E4 regions. When this helper plasmid was cotransfected into 293 cells, along with plasmids encoding the AAV vector, and rep and cap genes, AAV vector was produced as efficiently as when using adenovirus infection as a source of help. CMV-driven constructs expressing the E4orf6 and the 72-M(r), E2A proteins were able to functionally replace the E4 and E2A regions, respectively. Therefore the minimum set of genes required to produce AAV helper activity equivalent to that provided by adenovirus infection consists of, or is a subset of, the following genes: the E4orf6 gene, the 72-M(r), E2A protein gene, the VA RNA genes and the E1 region. AAV vector preparations made with adenovirus and by the helper virus-free method were essentially indistinguishable with respect to particle density, particle to infectivity ratio, capsimer ratio and efficiency of muscle transduction in vivo. Only AAV vector preparations made by the helper virus-free method were not reactive with anti-adenovirus sera.

Quantum and electromagnetic propagation with the conjugate symmetric Lanczos method.

PubMed

Acevedo, Ramiro; Lombardini, Richard; Turner, Matthew A; Kinsey, James L; Johnson, Bruce R

2008-02-14

The conjugate symmetric Lanczos (CSL) method is introduced for the solution of the time-dependent Schrodinger equation. This remarkably simple and efficient time-domain algorithm is a low-order polynomial expansion of the quantum propagator for time-independent Hamiltonians and derives from the time-reversal symmetry of the Schrodinger equation. The CSL algorithm gives forward solutions by simply complex conjugating backward polynomial expansion coefficients. Interestingly, the expansion coefficients are the same for each uniform time step, a fact that is only spoiled by basis incompleteness and finite precision. This is true for the Krylov basis and, with further investigation, is also found to be true for the Lanczos basis, important for efficient orthogonal projection-based algorithms. The CSL method errors roughly track those of the short iterative Lanczos method while requiring fewer matrix-vector products than the Chebyshev method. With the CSL method, only a few vectors need to be stored at a time, there is no need to estimate the Hamiltonian spectral range, and only matrix-vector and vector-vector products are required. Applications using localized wavelet bases are made to harmonic oscillator and anharmonic Morse oscillator systems as well as electrodynamic pulse propagation using the Hamiltonian form of Maxwell's equations. For gold with a Drude dielectric function, the latter is non-Hermitian, requiring consideration of corrections to the CSL algorithm.

Malaria-induced changes in host odors enhance mosquito attraction

PubMed Central

De Moraes, Consuelo M.; Stanczyk, Nina M.; Betz, Heike S.; Pulido, Hannier; Sim, Derek G.; Read, Andrew F.; Mescher, Mark C.

2014-01-01

Vector-borne pathogens may alter traits of their primary hosts in ways that influence the frequency and nature of interactions between hosts and vectors. Previous work has reported enhanced mosquito attraction to host organisms infected with malaria parasites but did not address the mechanisms underlying such effects. Here we document malaria-induced changes in the odor profiles of infected mice (relative to healthy individuals) over the course of infection, as well as effects on the attractiveness of infected hosts to mosquito vectors. We observed enhanced mosquito attraction to infected mice during a key period after the subsidence of acute malaria symptoms, but during which mice remained highly infectious. This attraction corresponded to an overall elevation in the volatile emissions of infected mice observed during this period. Furthermore, data analyses—using discriminant analysis of principal components and random forest approaches—revealed clear differences in the composition of the volatile blends of infected and healthy individuals. Experimental manipulation of individual compounds that exhibited altered emission levels during the period when differential vector attraction was observed also elicited enhanced mosquito attraction, indicating that compounds being influenced by malaria infection status also mediate vector host-seeking behavior. These findings provide important insights into the cues that mediate vector attraction to hosts infected with transmissible stages of malaria parasites, as well as documenting characteristic changes in the odors of infected individuals that may have potential value as diagnostic biomarkers of infection. PMID:24982164

Malaria-induced changes in host odors enhance mosquito attraction.

PubMed

De Moraes, Consuelo M; Stanczyk, Nina M; Betz, Heike S; Pulido, Hannier; Sim, Derek G; Read, Andrew F; Mescher, Mark C

2014-07-29

Vector-borne pathogens may alter traits of their primary hosts in ways that influence the frequency and nature of interactions between hosts and vectors. Previous work has reported enhanced mosquito attraction to host organisms infected with malaria parasites but did not address the mechanisms underlying such effects. Here we document malaria-induced changes in the odor profiles of infected mice (relative to healthy individuals) over the course of infection, as well as effects on the attractiveness of infected hosts to mosquito vectors. We observed enhanced mosquito attraction to infected mice during a key period after the subsidence of acute malaria symptoms, but during which mice remained highly infectious. This attraction corresponded to an overall elevation in the volatile emissions of infected mice observed during this period. Furthermore, data analyses--using discriminant analysis of principal components and random forest approaches--revealed clear differences in the composition of the volatile blends of infected and healthy individuals. Experimental manipulation of individual compounds that exhibited altered emission levels during the period when differential vector attraction was observed also elicited enhanced mosquito attraction, indicating that compounds being influenced by malaria infection status also mediate vector host-seeking behavior. These findings provide important insights into the cues that mediate vector attraction to hosts infected with transmissible stages of malaria parasites, as well as documenting characteristic changes in the odors of infected individuals that may have potential value as diagnostic biomarkers of infection.

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.

Diaphorina citri (Hemiptera: Liviidae) Vector Competence for the Citrus Greening Pathogen 'Candidatus Liberibacter Asiaticus'.

PubMed

Tabachnick, Walter J

2015-06-01

Characterizing the vector competence of Diaphorina citri Kuwayama for 'Candidatus Liberibacter asiaticus,' the pathogen causing citrus greening, is essential for understanding the epidemiology of this disease that is threatening the U.S. citrus industry. Vector competence studies have been difficult because of the biology of D. citri, the inability to culture the pathogen, and the available diagnostic methods used to detect the bacteria in plant and insect tissues. The methods employed in many studies of D. citri vector competence may have overestimated amounts of live 'Ca. L. asiaticus' in both plant and insect tissues, and it is possible that the amounts of phloem ingested by psyllids may not contain sufficient detectable pathogen using current diagnostic methods. As a result of the difficulty in characterizing D. citri vector competence, the several daunting challenges for providing D. citri that are unable to inoculate 'Ca. L. asiaticus', as a novel method to control greening are discussed. Suggestions to overcome some of these challenges are provided. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effective Clipart Image Vectorization through Direct Optimization of Bezigons.

PubMed

Yang, Ming; Chao, Hongyang; Zhang, Chi; Guo, Jun; Yuan, Lu; Sun, Jian

2016-02-01

Bezigons, i.e., closed paths composed of Bézier curves, have been widely employed to describe shapes in image vectorization results. However, most existing vectorization techniques infer the bezigons by simply approximating an intermediate vector representation (such as polygons). Consequently, the resultant bezigons are sometimes imperfect due to accumulated errors, fitting ambiguities, and a lack of curve priors, especially for low-resolution images. In this paper, we describe a novel method for vectorizing clipart images. In contrast to previous methods, we directly optimize the bezigons rather than using other intermediate representations; therefore, the resultant bezigons are not only of higher fidelity compared with the original raster image but also more reasonable because they were traced by a proficient expert. To enable such optimization, we have overcome several challenges and have devised a differentiable data energy as well as several curve-based prior terms. To improve the efficiency of the optimization, we also take advantage of the local control property of bezigons and adopt an overlapped piecewise optimization strategy. The experimental results show that our method outperforms both the current state-of-the-art method and commonly used commercial software in terms of bezigon quality.

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

NASA Astrophysics Data System (ADS)

Chou, Chien-Ming; Wang, Ru-Yih

2004-04-01

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

Cloud Detection of Optical Satellite Images Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.

Classical reconstruction of interference patterns of position-wave-vector-entangled photon pairs by the time-reversal method

NASA Astrophysics Data System (ADS)

Ogawa, Kazuhisa; Kobayashi, Hirokazu; Tomita, Akihisa

2018-02-01

The quantum interference of entangled photons forms a key phenomenon underlying various quantum-optical technologies. It is known that the quantum interference patterns of entangled photon pairs can be reconstructed classically by the time-reversal method; however, the time-reversal method has been applied only to time-frequency-entangled two-photon systems in previous experiments. Here, we apply the time-reversal method to the position-wave-vector-entangled two-photon systems: the two-photon Young interferometer and the two-photon beam focusing system. We experimentally demonstrate that the time-reversed systems classically reconstruct the same interference patterns as the position-wave-vector-entangled two-photon systems.

Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar

PubMed Central

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing

2015-01-01

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri–Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method. PMID:26569241

Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar.

PubMed

Wang, Xianpeng; Wang, Wei; Li, Xin; Liu, Jing

2015-11-10

In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri-Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method.

Gimbal-Angle Vectors of the Nonredundant CMG Cluster

NASA Astrophysics Data System (ADS)

Lee, Donghun; Bang, Hyochoong

2018-05-01

This paper deals with the method using the preferred gimbal angles of a control moment gyro (CMG) cluster for controlling spacecraft attitude. To apply the method to the nonredundant CMG cluster, analytical gimbal-angle solutions for the zero angular momentum state are derived, and the gimbal-angle vectors for the nonzero angular momentum states are studied by a numerical method. It will be shown that the number of the gimbal-angle vectors is determined from the given skew angle and the angular momentum state of the CMG cluster. Through numerical examples, it is shown that the method using the preferred gimbal-angle is an efficient approach to avoid internal singularities for the nonredundant CMG cluster.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Piezoelectrically forced vibrations of electroded doubly rotated quartz plates by state space method

NASA Technical Reports Server (NTRS)

Chander, R.

1990-01-01

The purpose of this investigation is to develop an analytical method to study the vibration characteristics of piezoelectrically forced quartz plates. The procedure can be summarized as follows. The three dimensional governing equations of piezoelectricity, the constitutive equations and the strain-displacement relationships are used in deriving the final equations. For this purpose, a state vector consisting of stresses and displacements are chosen and the above equations are manipulated to obtain the projection of the derivative of the state vector with respect to the thickness coordinate on to the state vector itself. The solution to the state vector at any plane is then easily obtained in a closed form in terms of the state vector quantities at a reference plane. To simplify the analysis, simple thickness mode and plane strain approximations are used.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

Discontinuous finite element method for vector radiative transfer

NASA Astrophysics Data System (ADS)

Wang, Cun-Hai; Yi, Hong-Liang; Tan, He-Ping

2017-03-01

The discontinuous finite element method (DFEM) is applied to solve the vector radiative transfer in participating media. The derivation in a discrete form of the vector radiation governing equations is presented, in which the angular space is discretized by the discrete-ordinates approach with a local refined modification, and the spatial domain is discretized into finite non-overlapped discontinuous elements. The elements in the whole solution domain are connected by modelling the boundary numerical flux between adjacent elements, which makes the DFEM numerically stable for solving radiative transfer equations. Several various problems of vector radiative transfer are tested to verify the performance of the developed DFEM, including vector radiative transfer in a one-dimensional parallel slab containing a Mie/Rayleigh/strong forward scattering medium and a two-dimensional square medium. The fact that DFEM results agree very well with the benchmark solutions in published references shows that the developed DFEM in this paper is accurate and effective for solving vector radiative transfer problems.

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.

Theoretical and Numerical Approaches for Determining the Reflection and Transmission Coefficients of OPEFB-PCL Composites at X-Band Frequencies

PubMed Central

Ahmad, Ahmad F.; Abbas, Zulkifly; Obaiys, Suzan J.; Ibrahim, Norazowa; Hashim, Mansor; Khaleel, Haider

2015-01-01

Bio-composites of oil palm empty fruit bunch (OPEFB) fibres and polycaprolactones (PCL) with a thickness of 1 mm were prepared and characterized. The composites produced from these materials are low in density, inexpensive, environmentally friendly, and possess good dielectric characteristics. The magnitudes of the reflection and transmission coefficients of OPEFB fibre-reinforced PCL composites with different percentages of filler were measured using a rectangular waveguide in conjunction with a microwave vector network analyzer (VNA) in the X-band frequency range. In contrast to the effective medium theory, which states that polymer-based composites with a high dielectric constant can be obtained by doping a filler with a high dielectric constant into a host material with a low dielectric constant, this paper demonstrates that the use of a low filler percentage (12.2%OPEFB) and a high matrix percentage (87.8%PCL) provides excellent results for the dielectric constant and loss factor, whereas 63.8% filler material with 36.2% host material results in lower values for both the dielectric constant and loss factor. The open-ended probe technique (OEC), connected with the Agilent vector network analyzer (VNA), is used to determine the dielectric properties of the materials under investigation. The comparative approach indicates that the mean relative error of FEM is smaller than that of NRW in terms of the corresponding S21 magnitude. The present calculation of the matrix/filler percentages endorses the exact amounts of substrate utilized in various physics applications. PMID:26474301

Characterization of the Asian citrus psyllid transcriptome

USDA-ARS?s Scientific Manuscript database

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

Turbine Engine Component Analysis: Cantilevered Composite Flat Plate Analysis

DTIC Science & Technology

1989-11-01

4/5 element which translates into the ADIN. shell element (Type 7) with thickness correction. PATADI automatically generates midsurface normal vectors...for each node referenced by a shell element. Using thickness correction, the element thickness will be oriented along the midsurface direction. If no

BIOELECTRICAL IMPEDANCE VECTOR ANALYSIS IDENTIFIES SARCOPENIA IN NURSING HOME RESIDENTS

USDA-ARS?s Scientific Manuscript database

Loss of muscle mass and water shifts between body compartments are contributing factors to frailty in the elderly. The body composition changes are especially pronounced in institutionalized elderly. We investigated the ability of single-frequency bioelectrical impedance analysis (BIA) to identify b...

Quantization, Frobenius and Bi algebras from the Categorical Framework of Quantum Mechanics to Natural Language Semantics

NASA Astrophysics Data System (ADS)

Sadrzadeh, Mehrnoosh

2017-07-01

Compact Closed categories and Frobenius and Bi algebras have been applied to model and reason about Quantum protocols. The same constructions have also been applied to reason about natural language semantics under the name: ``categorical distributional compositional'' semantics, or in short, the ``DisCoCat'' model. This model combines the statistical vector models of word meaning with the compositional models of grammatical structure. It has been applied to natural language tasks such as disambiguation, paraphrasing and entailment of phrases and sentences. The passage from the grammatical structure to vectors is provided by a functor, similar to the Quantization functor of Quantum Field Theory. The original DisCoCat model only used compact closed categories. Later, Frobenius algebras were added to it to model long distance dependancies such as relative pronouns. Recently, bialgebras have been added to the pack to reason about quantifiers. This paper reviews these constructions and their application to natural language semantics. We go over the theory and present some of the core experimental results.

Systematic measurements of ion-proton differential streaming in the solar wind.

PubMed

Berger, L; Wimmer-Schweingruber, R F; Gloeckler, G

2011-04-15

The small amount of heavy ions in the highly rarefied solar wind are sensitive tracers for plasma-physics processes, which are usually not accessible in the laboratory. We have analyzed differential streaming between heavy ions and protons in the solar wind at 1 AU. 3D velocity vector and magnetic field measurements from the Solar Wind Electron Proton Alpha Monitor and the Magnetometer aboard the Advanced Composition Explorer were used to reconstruct the ion-proton difference vector v(ip) = v(i) - v(p) from the 12 min 1D Solar Wind Ion Composition Spectrometer observations. We find that all 44 analyzed heavy ions flow along the interplanetary magnetic field at velocities which are smaller than, but comparable to, the local Alfvén speed C(A). The flow speeds of 35 of the 44 ion species lie within the range of ±0.15C(A) around 0.55C(A), the flow speed of He(2+).

Host influence in the genomic composition of flaviviruses: A multivariate approach.

PubMed

Simón, Diego; Fajardo, Alvaro; Sóñora, Martín; Delfraro, Adriana; Musto, Héctor

2017-10-28

Flaviviruses present substantial differences in their host range and transmissibility. We studied the evolution of base composition, dinucleotide biases, codon usage and amino acid frequencies in the genus Flavivirus within a phylogenetic framework by principal components analysis. There is a mutual interplay between the evolutionary history of flaviviruses and their respective vectors and/or hosts. Hosts associated to distinct phylogenetic groups may be driving flaviviruses at different pace and through various sequence landscapes, as can be seen for viruses associated with Aedes or Culex spp., although phylogenetic inertia cannot be ruled out. In some cases, viruses face even opposite forces. For instance, in tick-borne flaviviruses, while vertebrate hosts exert pressure to deplete their CpG, tick vectors drive them to exhibit GC-rich codons. Within a vertebrate environment, natural selection appears to be acting on the viral genome to overcome the immune system. On the other side, within an arthropod environment, mutational biases seem to be the dominant forces. Copyright © 2017 Elsevier Inc. All rights reserved.

Color deconvolution. Optimizing handling of 3D unitary optical density vectors with polar coordinates.

PubMed

Bigras, Gilbert

2012-06-01

Color deconvolution relies on determination of unitary optical density vectors (OD(3D)) derived from pure constituent stains initially defined as intensity vectors in RGB space. OD(3D) can be defined in polar coordinates (phi, theta, radius); always being equal to one, radius can be ignored. Easier handling of unitary optical density 2D vectors (OD(2D)) is shown. OD(2D) pure stains used in anatomical pathology were assessed as centroid values (phi, theta) with a measure of variance: inertia based on arc lengths between centroid value and sampled points. These variables were plotted on a stereographic projection plane. In order to assess pure stains OD(2D), different methods of sampling RGB pixels were tested and compared: (2) direct sampling of nuclei from preparations using (a) composite H&E and (b) hematoxylin only and (2) for any pure stain RGB image, different associated 8-bit masks (saturation, brightness and RGB average) were used for sampling and compared. Behaviors of phi, theta and inertia were obtained by moving threshold in 8-bit mask histograms. Phi and theta stability were tested against variable light intensity during image acquisition and by using 2 different image acquisition systems. The more saturated RGB pixels are, the more stable phi, theta and inertia values are obtained. Different commercial hematoxylins have distinct OD(2D) characteristics. UltraView DAB stain shows high inertia and is angularly closer to usual counterstains than ultraView Red stain, which also has a lower inertia. Superior accuracy is expected from the latter stain. Phi and theta OD(2D) values are sensitive to light intensity variation, to the used imaging system and to the used objectives. An ImageJ plugin was designed to plot and interactively modify OD(2D) values with instant update of color deconvolution allowing heuristic segmentation. Utilization of polar OD(2D) eases statistical characterization of OD(3D) vectors: conditions of optimal sampling were demonstrated and various factors influencing OD(2D) stability were explored. Stereographic projection plane allows intuitive visualization of OD(3D) vectors as well as heuristic vectorial modification. All findings are not restricted to anatomical pathology but can be applied to bright field microscopy and subtractive color applications in general.

A regularization approach to hydrofacies delineation

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

Wohlberg, Brendt; Tartakovsky, Daniel

2009-01-01

We consider an inverse problem of identifying complex internal structures of composite (geological) materials from sparse measurements of system parameters and system states. Two conceptual frameworks for identifying internal boundaries between constitutive materials in a composite are considered. A sequential approach relies on support vector machines, nearest neighbor classifiers, or geostatistics to reconstruct boundaries from measurements of system parameters and then uses system states data to refine the reconstruction. A joint approach inverts the two data sets simultaneously by employing a regularization approach.

A Damage-Dependent Finite Element Analysis for Fiber-Reinforced Composite Laminates

NASA Technical Reports Server (NTRS)

Coats, Timothy W.; Harris, Charles E.

1998-01-01

A progressive damage methodology has been developed to predict damage growth and residual strength of fiber-reinforced composite structure with through penetrations such as a slit. The methodology consists of a damage-dependent constitutive relationship based on continuum damage mechanics. Damage is modeled using volume averaged strain-like quantities known as internal state variables and is represented in the equilibrium equations as damage induced force vectors instead of the usual degradation and modification of the global stiffness matrix.

Eddy current modeling in linear and nonlinear multifilamentary composite materials

NASA Astrophysics Data System (ADS)

Menana, Hocine; Farhat, Mohamad; Hinaje, Melika; Berger, Kevin; Douine, Bruno; Lévêque, Jean

2018-04-01

In this work, a numerical model is developed for a rapid computation of eddy currents in composite materials, adaptable for both carbon fiber reinforced polymers (CFRPs) for NDT applications and multifilamentary high temperature superconductive (HTS) tapes for AC loss evaluation. The proposed model is based on an integro-differential formulation in terms of the electric vector potential in the frequency domain. The high anisotropy and the nonlinearity of the considered materials are easily handled in the frequency domain.

Computing the Sensitivity Kernels for 2.5-D Seismic Waveform Inversion in Heterogeneous, Anisotropic Media

NASA Astrophysics Data System (ADS)

Zhou, Bing; Greenhalgh, S. A.

2011-10-01

2.5-D modeling and inversion techniques are much closer to reality than the simple and traditional 2-D seismic wave modeling and inversion. The sensitivity kernels required in full waveform seismic tomographic inversion are the Fréchet derivatives of the displacement vector with respect to the independent anisotropic model parameters of the subsurface. They give the sensitivity of the seismograms to changes in the model parameters. This paper applies two methods, called `the perturbation method' and `the matrix method', to derive the sensitivity kernels for 2.5-D seismic waveform inversion. We show that the two methods yield the same explicit expressions for the Fréchet derivatives using a constant-block model parameterization, and are available for both the line-source (2-D) and the point-source (2.5-D) cases. The method involves two Green's function vectors and their gradients, as well as the derivatives of the elastic modulus tensor with respect to the independent model parameters. The two Green's function vectors are the responses of the displacement vector to the two directed unit vectors located at the source and geophone positions, respectively; they can be generally obtained by numerical methods. The gradients of the Green's function vectors may be approximated in the same manner as the differential computations in the forward modeling. The derivatives of the elastic modulus tensor with respect to the independent model parameters can be obtained analytically, dependent on the class of medium anisotropy. Explicit expressions are given for two special cases—isotropic and tilted transversely isotropic (TTI) media. Numerical examples are given for the latter case, which involves five independent elastic moduli (or Thomsen parameters) plus one angle defining the symmetry axis.

Towards a Phylogenetic Approach to the Composition of Species Complexes in the North and Central American Triatoma, Vectors of Chagas Disease

PubMed Central

de la Rúa, Nicholas M.; Bustamante, Dulce M.; Menes, Marianela; Stevens, Lori; Monroy, Carlota; Kilpatrick, William; Rizzo, Donna; Klotz, Stephen A.; Schmidt, Justin; Axen, Heather J.; Dorn, Patricia L.

2014-01-01

Phylogenetic relationships of insect vectors of parasitic diseases are important for understanding the evolution of epidemiologically relevant traits, and may be useful in vector control. The subfamily Triatominae (Hemiptera:Reduviidae) includes ~140 extant species arranged in five tribes comprised of 15 genera. The genus Triatoma is the most species-rich and contains important vectors of Trypanosoma cruzi, the causative agent of Chagas disease. Triatoma species were grouped into complexes originally by morphology and more recently with the addition of information from molecular phylogenetics (the four-complex hypothesis); however, without a strict adherence to monophyly. To date, the validity of proposed species complexes has not been tested by statistical tests of topology. The goal of this study was to clarify the systematics of 19 Triatoma species from North and Central America. We inferred their evolutionary relatedness using two independent data sets: the complete nuclear Internal Transcribed Spacer-2 ribosomal DNA (ITS-2 rDNA) and head morphometrics. In addition, we used the Shimodaira-Hasegawa statistical test of topology to assess the fit of the data to a set of competing systematic hypotheses (topologies). An unconstrained topology inferred from the ITS-2 data was compared to topologies constrained based on the four-complex hypothesis or one inferred from our morphometry results. The unconstrained topology represents a statistically significant better fit of the molecular data than either the four-complex or the morphometric topology. We propose an update to the composition of species complexes in the North and Central American Triatoma, based on a phylogeny inferred from ITS-2 as a first step towards updating the phylogeny of the complexes based on monophyly and statistical tests of topologies. PMID:24681261

Composition and Genetic Diversity of Mosquitoes (Diptera: Culicidae) on Islands and Mainland Shores of Kenya's Lakes Victoria and Baringo.

PubMed

Ajamma, Yvonne Ukamaka; Villinger, Jandouwe; Omondi, David; Salifu, Daisy; Onchuru, Thomas Ogao; Njoroge, Laban; Muigai, Anne W T; Masiga, Daniel K

2016-11-01

The Lake Baringo and Lake Victoria regions of Kenya are associated with high seroprevalence of mosquito-transmitted arboviruses. However, molecular identification of potential mosquito vector species, including morphologically identified ones, remains scarce. To estimate the diversity, abundance, and distribution of mosquito vectors on the mainland shores and adjacent inhabited islands in these regions, we collected and morphologically identified adult and immature mosquitoes and obtained the corresponding sequence variation at cytochrome c oxidase 1 (COI) and internal transcribed spacer region 2 (ITS2) gene regions. A total of 63 species (including five subspecies) were collected from both study areas, 47 of which have previously been implicated as disease vectors. Fourteen species were found only on island sites, which are rarely included in mosquito diversity surveys. We collected more mosquitoes, yet with lower species composition, at Lake Baringo (40,229 mosquitoes, 32 species) than at Lake Victoria (22,393 mosquitoes, 54 species). Phylogenetic analysis of COI gene sequences revealed Culex perexiguus and Cx tenagius that could not be distinguished morphologically. Most Culex species clustered into a heterogeneous clade with closely related sequences, while Culex pipiens clustered into two distinct COI and ITS2 clades. These data suggest limitations in current morphological identification keys. This is the first DNA barcode report of Kenyan mosquitoes. To improve mosquito species identification, morphological identifications should be supported by their molecular data, while diversity surveys should target both adults and immatures. The diversity of native mosquito disease vectors identified in this study impacts disease transmission risks to humans and livestock. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America.

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

PubMed

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

2017-12-06

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

Bioelectrical impedance vector analysis as a useful predictor of nutritional status in patients with short bowel syndrome.

PubMed

Fassini, Priscila Giacomo; Nicoletti, Carolina Ferreira; Pfrimer, Karina; Nonino, Carla Barbosa; Marchini, Júlio Sérgio; Ferriolli, Eduardo

2017-08-01

Short bowel syndrome (SBS) represents a serious intestinal absorption disorder. Therefore, patients with SBS may have severe malnutrition and excessive mineral and fluid losses. Once the assessment of nutritional status is important in their follow-up, body composition measurements and especially total body water (TBW) must be repeatedly evaluated for the assessment of changes in hydration and nutritional care. The aim of this study was to investigate if bioelectrical impedance vector analysis (BIVA) is a useful predictor of nutritional and hydration status in SBS patients. In this observational study, 22 participants (12 women), 11 with SBS and 11 gender, age and BMI-matched controls, were evaluated using the bioelectrical impedance measurements (BIA) and BIVA to assess nutritional and hydration status. Participants age was 53 ± 8 y (mean ± SD). Body water, fat mass and lean mass as assessed by BIA did not differ between the two groups. However, BIVA showed important differences between the groups regarding hydration and amount of soft tissue (p < 0.0001 for women and p = 0.0015 for men). The results also evidenced that women's vectors were related to cachexia, while men's vectors were divided into lean and cachexia quadrants. The use of BIVA analysis also evidenced hydration disturbance and losses of soft tissue. BIVA may represent a better predictor of nutritional status for analysis and interpretation of body composition in patients with short bowel syndrome. This trial was registered at ClinicalTrials.gov as NCT02113228. Copyright © 2016 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Methods for engineering polypeptide variants via somatic hypermutation and polypeptide made thereby

DOEpatents

Tsien, Roger Y; Wang, Lei

2015-01-13

Methods using somatic hypermutation (SHM) for producing polypeptide and nucleic acid variants, and nucleic acids encoding such polypeptide variants are disclosed. Such variants may have desired properties. Also disclosed are novel polypeptides, such as improved fluorescent proteins, produced by the novel methods, and nucleic acids, vectors, and host cells comprising such vectors.

Efficient construction of producer cell lines for a SIN lentiviral vector for SCID-X1 gene therapy by concatemeric array transfection

PubMed Central

Throm, Robert E.; Ouma, Annastasia A.; Zhou, Sheng; Chandrasekaran, Anantharaman; Lockey, Timothy; Greene, Michael; De Ravin, Suk See; Moayeri, Morvarid; Malech, Harry L.; Sorrentino, Brian P.

2009-01-01

Retroviral vectors containing internal promoters, chromatin insulators, and self-inactivating (SIN) long terminal repeats (LTRs) may have significantly reduced genotoxicity relative to the conventional retroviral vectors used in recent, otherwise successful clinical trials. Large-scale production of such vectors is problematic, however, as the introduction of SIN vectors into packaging cells cannot be accomplished with the traditional method of viral transduction. We have derived a set of packaging cell lines for HIV-based lentiviral vectors and developed a novel concatemeric array transfection technique for the introduction of SIN vector genomes devoid of enhancer and promoter sequences in the LTR. We used this method to derive a producer cell clone for a SIN lentiviral vector expressing green fluorescent protein, which when grown in a bioreactor generated more than 20 L of supernatant with titers above 107 transducing units (TU) per milliliter. Further refinement of our technique enabled the rapid generation of whole populations of stably transformed cells that produced similar titers. Finally, we describe the construction of an insulated, SIN lentiviral vector encoding the human interleukin 2 receptor common γ chain (IL2RG) gene and the efficient derivation of cloned producer cells that generate supernatants with titers greater than 5 × 107 TU/mL and that are suitable for use in a clinical trial for X-linked severe combined immunodeficiency (SCID-X1). PMID:19286997

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.

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

PubMed

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

2017-04-01

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

Portfolio Analysis for Vector Calculus

ERIC Educational Resources Information Center

Kaplan, Samuel R.

2015-01-01

Classic stock portfolio analysis provides an applied context for Lagrange multipliers that undergraduate students appreciate. Although modern methods of portfolio analysis are beyond the scope of vector calculus, classic methods reinforce the utility of this material. This paper discusses how to introduce classic stock portfolio analysis in a…

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

NASA Astrophysics Data System (ADS)

Tahaei, Marzieh S.; Reader, Andrew J.

2016-09-01

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

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.

LCD denoise and the vector mutual information method in the application of the gear fault diagnosis under different working conditions

NASA Astrophysics Data System (ADS)

Xiangfeng, Zhang; Hong, Jiang

2018-03-01

In this paper, the full vector LCD method is proposed to solve the misjudgment problem caused by the change of the working condition. First, the signal from different working condition is decomposed by LCD, to obtain the Intrinsic Scale Component (ISC)whose instantaneous frequency with physical significance. Then, calculate of the cross correlation coefficient between ISC and the original signal, signal denoising based on the principle of mutual information minimum. At last, calculate the sum of absolute Vector mutual information of the sample under different working condition and the denoised ISC as the characteristics to classify by use of Support vector machine (SVM). The wind turbines vibration platform gear box experiment proves that this method can identify fault characteristics under different working conditions. The advantage of this method is that it reduce dependence of man’s subjective experience, identify fault directly from the original data of vibration signal. It will has high engineering value.

Datum Feature Extraction and Deformation Analysis Method Based on Normal Vector of Point Cloud

NASA Astrophysics Data System (ADS)

Sun, W.; Wang, J.; Jin, F.; Liang, Z.; Yang, Y.

2018-04-01

In order to solve the problem lacking applicable analysis method in the application of three-dimensional laser scanning technology to the field of deformation monitoring, an efficient method extracting datum feature and analysing deformation based on normal vector of point cloud was proposed. Firstly, the kd-tree is used to establish the topological relation. Datum points are detected by tracking the normal vector of point cloud determined by the normal vector of local planar. Then, the cubic B-spline curve fitting is performed on the datum points. Finally, datum elevation and the inclination angle of the radial point are calculated according to the fitted curve and then the deformation information was analyzed. The proposed approach was verified on real large-scale tank data set captured with terrestrial laser scanner in a chemical plant. The results show that the method could obtain the entire information of the monitor object quickly and comprehensively, and reflect accurately the datum feature deformation.

iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition.

PubMed

Chen, Wei; Feng, Peng-Mian; Lin, Hao; Chou, Kuo-Chen

2014-01-01

In eukaryotic genes, exons are generally interrupted by introns. Accurately removing introns and joining exons together are essential processes in eukaryotic gene expression. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapid and effective detection of splice sites that play important roles in gene structure annotation and even in RNA splicing. Although a series of computational methods were proposed for splice site identification, most of them neglected the intrinsic local structural properties. In the present study, a predictor called "iSS-PseDNC" was developed for identifying splice sites. In the new predictor, the sequences were formulated by a novel feature-vector called "pseudo dinucleotide composition" (PseDNC) into which six DNA local structural properties were incorporated. It was observed by the rigorous cross-validation tests on two benchmark datasets that the overall success rates achieved by iSS-PseDNC in identifying splice donor site and splice acceptor site were 85.45% and 87.73%, respectively. It is anticipated that iSS-PseDNC may become a useful tool for identifying splice sites and that the six DNA local structural properties described in this paper may provide novel insights for in-depth investigations into the mechanism of RNA splicing.

Enhanced gene disruption by programmable nucleases delivered by a minicircle vector.

PubMed

Dad, A-B K; Ramakrishna, S; Song, M; Kim, H

2014-11-01

Targeted genetic modification using programmable nucleases such as zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) is of great value in biomedical research, medicine and biotechnology. Minicircle vectors, which lack extraneous bacterial sequences, have several advantages over conventional plasmids for transgene delivery. Here, for the first time, we delivered programmable nucleases into human cells using transient transfection of a minicircle vector and compared the results with those obtained using a conventional plasmid. Surrogate reporter assays and T7 endonuclease analyses revealed that cells in the minicircle vector group displayed significantly higher mutation frequencies at the target sites than those in the conventional plasmid group. Quantitative PCR and reverse transcription-PCR showed higher vector copy number and programmable nuclease transcript levels, respectively, in 293T cells after minicircle versus conventional plasmid vector transfection. In addition, tryphan blue staining and flow cytometry after annexin V and propidium iodide staining showed that cell viability was also significantly higher in the minicircle group than in the conventional plasmid group. Taken together, our results show that gene disruption using minicircle vector-mediated delivery of ZFNs and TALENs is a more efficient, safer and less toxic method than using a conventional plasmid, and indicate that the minicircle vector could serve as an advanced delivery method for programmable nucleases.

British Container Breeding Mosquitoes: The Impact of Urbanisation and Climate Change on Community Composition and Phenology

PubMed Central

Townroe, Susannah; Callaghan, Amanda

2014-01-01

The proliferation of artificial container habitats in urban areas has benefitted urban adaptable mosquito species globally. In areas where mosquitoes transmit viruses and parasites, it can promote vector population productivity and fuel mosquito-borne disease outbreaks. In Britain, storage of water in garden water butts is increasing, potentially expanding mosquito larval habitats and influencing population dynamics and mosquito-human contact. Here we show that the community composition, abundance and phenology of mosquitoes breeding in experimental water butt containers were influenced by urbanisation. Mosquitoes in urban containers were less species-rich but present in significantly higher densities (100.4±21.3) per container than those in rural containers (77.7±15.1). Urban containers were dominated by Culex pipiens (a potential vector of West Nile Virus [WNV]) and appear to be increasingly exploited by Anopheles plumbeus (a human-biting potential WNV and malaria vector). Culex phenology was influenced by urban land use type, with peaks in larval abundances occurring earlier in urban than rural containers. Among other factors, this was associated with an urban heat island effect which raised urban air and water temperatures by 0.9°C and 1.2°C respectively. Further increases in domestic water storage, particularly in urban areas, in combination with climate changes will likely alter mosquito population dynamics in the UK. PMID:24759617

British container breeding mosquitoes: the impact of urbanisation and climate change on community composition and phenology.

PubMed

Townroe, Susannah; Callaghan, Amanda

2014-01-01

The proliferation of artificial container habitats in urban areas has benefitted urban adaptable mosquito species globally. In areas where mosquitoes transmit viruses and parasites, it can promote vector population productivity and fuel mosquito-borne disease outbreaks. In Britain, storage of water in garden water butts is increasing, potentially expanding mosquito larval habitats and influencing population dynamics and mosquito-human contact. Here we show that the community composition, abundance and phenology of mosquitoes breeding in experimental water butt containers were influenced by urbanisation. Mosquitoes in urban containers were less species-rich but present in significantly higher densities (100.4±21.3) per container than those in rural containers (77.7±15.1). Urban containers were dominated by Culex pipiens (a potential vector of West Nile Virus [WNV]) and appear to be increasingly exploited by Anopheles plumbeus (a human-biting potential WNV and malaria vector). Culex phenology was influenced by urban land use type, with peaks in larval abundances occurring earlier in urban than rural containers. Among other factors, this was associated with an urban heat island effect which raised urban air and water temperatures by 0.9°C and 1.2°C respectively. Further increases in domestic water storage, particularly in urban areas, in combination with climate changes will likely alter mosquito population dynamics in the UK.

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

PubMed

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

2016-01-01

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

A study on locating the sonic source of sinusoidal magneto-acoustic signals using a vector method.

PubMed

Zhang, Shunqi; Zhou, Xiaoqing; Ma, Ren; Yin, Tao; Liu, Zhipeng

2015-01-01

Methods based on the magnetic-acoustic effect are of great significance in studying the electrical imaging properties of biological tissues and currents. The continuous wave method, which is commonly used, can only detect the current amplitude without the sound source position. Although the pulse mode adopted in magneto-acoustic imaging can locate the sonic source, the low measuring accuracy and low SNR has limited its application. In this study, a vector method was used to solve and analyze the magnetic-acoustic signal based on the continuous sine wave mode. This study includes theory modeling of the vector method, simulations to the line model, and experiments with wire samples to analyze magneto-acoustic (MA) signal characteristics. The results showed that the amplitude and phase of the MA signal contained the location information of the sonic source. The amplitude and phase obeyed the vector theory in the complex plane. This study sets a foundation for a new technique to locate sonic sources for biomedical imaging of tissue conductivity. It also aids in studying biological current detecting and reconstruction based on the magneto-acoustic effect.

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

NASA Astrophysics Data System (ADS)

Huttunen, Jani; Kokkola, Harri; Mielonen, Tero; Esa Juhani Mononen, Mika; Lipponen, Antti; Reunanen, Juha; Vilhelm Lindfors, Anders; Mikkonen, Santtu; Erkki Juhani Lehtinen, Kari; Kouremeti, Natalia; Bais, Alkiviadis; Niska, Harri; Arola, Antti

2016-07-01

In order to have a good estimate of the current forcing by anthropogenic aerosols, knowledge on past aerosol levels is needed. Aerosol optical depth (AOD) is a good measure for aerosol loading. However, dedicated measurements of AOD are only available from the 1990s onward. One option to lengthen the AOD time series beyond the 1990s is to retrieve AOD from surface solar radiation (SSR) measurements taken with pyranometers. In this work, we have evaluated several inversion methods designed for this task. We compared a look-up table method based on radiative transfer modelling, a non-linear regression method and four machine learning methods (Gaussian process, neural network, random forest and support vector machine) with AOD observations carried out with a sun photometer at an Aerosol Robotic Network (AERONET) site in Thessaloniki, Greece. Our results show that most of the machine learning methods produce AOD estimates comparable to the look-up table and non-linear regression methods. All of the applied methods produced AOD values that corresponded well to the AERONET observations with the lowest correlation coefficient value being 0.87 for the random forest method. While many of the methods tended to slightly overestimate low AODs and underestimate high AODs, neural network and support vector machine showed overall better correspondence for the whole AOD range. The differences in producing both ends of the AOD range seem to be caused by differences in the aerosol composition. High AODs were in most cases those with high water vapour content which might affect the aerosol single scattering albedo (SSA) through uptake of water into aerosols. Our study indicates that machine learning methods benefit from the fact that they do not constrain the aerosol SSA in the retrieval, whereas the LUT method assumes a constant value for it. This would also mean that machine learning methods could have potential in reproducing AOD from SSR even though SSA would have changed during the observation period.

Prediction task guided representation learning of medical codes in EHR.

PubMed

Cui, Liwen; Xie, Xiaolei; Shen, Zuojun

2018-06-18

There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental and crucial step in developing such models is to convert medical codes in EHR to feature vectors. These medical codes are used to represent diagnoses or procedures. Their vector representations have a tremendous impact on the performance of machine learning models. Recently, some researchers have utilized representation learning methods from Natural Language Processing (NLP) to learn vector representations of medical codes. However, most previous approaches are unsupervised, i.e. the generation of medical code vectors is independent from prediction tasks. Thus, the obtained feature vectors may be inappropriate for a specific prediction task. Moreover, unsupervised methods often require a lot of samples to obtain reliable results, but most practical problems have very limited patient samples. In this paper, we develop a new method called Prediction Task Guided Health Record Aggregation (PTGHRA), which aggregates health records guided by prediction tasks, to construct training corpus for various representation learning models. Compared with unsupervised approaches, representation learning models integrated with PTGHRA yield a significant improvement in predictive capability of generated medical code vectors, especially for limited training samples. Copyright © 2018. Published by Elsevier Inc.

Validation of a method to measure the vector fidelity of triaxial vector sensors

NASA Astrophysics Data System (ADS)

De Freitas, J. M.

2018-06-01

A method to measure the misalignment angles and vector fidelity of a mutually orthogonal arrangement of triaxial accelerometers has been validated by introducing known misalignments into the measurement procedure. The method is based on the excitation of all three accelerometers in equal measure and the determination of the second order responsivity tensor as a metric. The sensor axis misalignment angles measured using a sensor rotation technique as a reference were 1.49°  ±  0.05°, 0.63°  ±  0.02°, and 0.78°  ±  0.04°. The resolution of the new approach against the reference was 0.03° with an accuracy of 0.2° and maximum deviation of 0.4°. An ellipticity tensor β that characterises the extent to which a triaxial system preserves the input polarisation state purity was introduced. In a careful laboratory arrangement, up to 98% input polarisation state purity was shown to be maintained. It is recommended that documentation on commercial and research grade high-precision triaxial sensor systems should give the responsivity matrix . This technique will improve the range of vector fidelity measurement tools for triaxial accelerometers and other vector sensors such as magnetometers, gyroscopes and acoustic vector sensors.

Video data compression using artificial neural network differential vector quantization

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

A vector matching method for analysing logic Petri nets

NASA Astrophysics Data System (ADS)

Du, YuYue; Qi, Liang; Zhou, MengChu

2011-11-01

Batch processing function and passing value indeterminacy in cooperative systems can be described and analysed by logic Petri nets (LPNs). To directly analyse the properties of LPNs, the concept of transition enabling vector sets is presented and a vector matching method used to judge the enabling transitions is proposed in this article. The incidence matrix of LPNs is defined; an equation about marking change due to a transition's firing is given; and a reachable tree is constructed. The state space explosion is mitigated to a certain extent from directly analysing LPNs. Finally, the validity and reliability of the proposed method are illustrated by an example in electronic commerce.