Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

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

PubMed

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

2015-07-07

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

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.

A single EBV-based vector for stable episomal maintenance and expression of GFP in human embryonic stem cells.

PubMed

Thyagarajan, Bhaskar; Scheyhing, Kelly; Xue, Haipeng; Fontes, Andrew; Chesnut, Jon; Rao, Mahendra; Lakshmipathy, Uma

2009-03-01

Stable expression of transgenes in stem cells has been a challenge due to the nonavailability of efficient transfection methods and the inability of transgenes to support sustained gene expression. Several methods have been reported to stably modify both embryonic and adult stem cells. These methods rely on integration of the transgene into the genome of the host cell, which could result in an expression pattern dependent on the number of integrations and the genomic locus of integration. To overcome this issue, site-specific integration methods mediated by integrase, adeno-associated virus or via homologous recombination have been used to generate stable human embryonic stem cell (hESC) lines. In this study, we describe a vector that is maintained episomally in hESCs. The vector used in this study is based on components derived from the Epstein-Barr virus, containing the Epstein-Barr virus nuclear antigen 1 expression cassette and the OriP origin of replication. The vector also expresses the drug-resistance marker gene hygromycin, which allows for selection and long-term maintenance of cells harboring the plasmid. Using this vector system, we show sustained expression of green fluorescent protein in undifferentiated hESCs and their differentiating embryoid bodies. In addition, the stable hESC clones show comparable expression with and without drug selection. Consistent with this observation, bulk-transfected adipose tissue-derived mesenchymal stem cells showed persistent marker gene expression as they differentiate into adipocytes, osteoblasts and chondroblasts. Episomal vectors offer a fast and efficient method to create hESC reporter lines, which in turn allows one to test the effect of overexpression of various genes on stem cell growth, proliferation and differentiation.

Real Time Monitoring System of Pollution Waste on Musi River Using Support Vector Machine (SVM) Method

NASA Astrophysics Data System (ADS)

Fachrurrozi, Muhammad; Saparudin; Erwin

2017-04-01

Real-time Monitoring and early detection system which measures the quality standard of waste in Musi River, Palembang, Indonesia is a system for determining air and water pollution level. This system was designed in order to create an integrated monitoring system and provide real time information that can be read. It is designed to measure acidity and water turbidity polluted by industrial waste, as well as to show and provide conditional data integrated in one system. This system consists of inputting and processing the data, and giving output based on processed data. Turbidity, substances, and pH sensor is used as a detector that produce analog electrical direct current voltage (DC). Early detection system works by determining the value of the ammonia threshold, acidity, and turbidity level of water in Musi River. The results is then presented based on the level group pollution by the Support Vector Machine classification method.

Design of 2D time-varying vector fields.

PubMed

Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D; Zhang, Eugene

2012-10-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects.

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

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.

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

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

PubMed Central

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

2012-01-01

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

Technological and cross-border mixture value chain of science and engineering of multi-integrative mechatronics-integronics-adaptronics

NASA Astrophysics Data System (ADS)

Gheorghe, Gh. Ion; Popan, Gheorghe

2013-10-01

This scientific paper presents in national premiere and in original concept of the author, the scientific national and the author's original concept, the technological and cross-border mixture value chain of science and engineering of multi-integrative Mechatronics-Integronics-Adaptronics, as high-tech vector support development, for viability and sustainability of a new intelligent and competitive labour market.

Speech sound classification and detection of articulation disorders with support vector machines and wavelets.

PubMed

Georgoulas, George; Georgopoulos, Voula C; Stylios, Chrysostomos D

2006-01-01

This paper proposes a novel integrated methodology to extract features and classify speech sounds with intent to detect the possible existence of a speech articulation disorder in a speaker. Articulation, in effect, is the specific and characteristic way that an individual produces the speech sounds. A methodology to process the speech signal, extract features and finally classify the signal and detect articulation problems in a speaker is presented. The use of support vector machines (SVMs), for the classification of speech sounds and detection of articulation disorders is introduced. The proposed method is implemented on a data set where different sets of features and different schemes of SVMs are tested leading to satisfactory performance.

Chromosomal integration of adenoviral vector DNA in vivo.

PubMed

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

2010-10-01

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

Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

PubMed

Zhang, Jinshui; Yuan, Zhoumiqi; Shuai, Guanyuan; Pan, Yaozhong; Zhu, Xiufang

2017-04-26

This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient ( C ) and kernel width ( s ), in mapping homogeneous specific land cover.

An improved exact inversion formula for solenoidal fields in cone beam vector tomography

NASA Astrophysics Data System (ADS)

Katsevich, Alexander; Rothermel, Dimitri; Schuster, Thomas

2017-06-01

In this paper we present an improved inversion formula for the 3D cone beam transform of vector fields supported in the unit ball which is exact for solenoidal fields. It is well known that only the solenoidal part of a vector field can be determined from the longitudinal ray transform of a vector field in cone beam geometry. The inversion formula, as it was developed in Katsevich and Schuster (2013 An exact inversion formula for cone beam vector tomography Inverse Problems 29 065013), consists of two parts. The first part is of the filtered backprojection type, whereas the second part is a costly 4D integration and very inefficient. In this article we tackle this second term and obtain an improved formula, which is easy to implement and saves one order of integration. We also show that the first part contains all information about the curl of the field, whereas the second part has information about the boundary values. More precisely, the second part vanishes if the solenoidal part of the original field is tangential at the boundary. A number of numerical tests presented in the paper confirm the theoretical results and the exactness of the formula. Also, we obtain an inversion algorithm that works for general convex domains.

Stable integration and expression of heterologous genes in several lactobacilli using an integration vector constructed from the integrase and attP sequences of phage ΦAT3 isolated from Lactobacillus casei ATCC 393.

PubMed

Lin, Chao-Fen; Lo, Ta-Chun; Kuo, Yang-Cheng; Lin, Thy-Hou

2013-04-01

An integration vector capable of stably integrating and maintaining in the chromosomes of several lactobacilli over hundreds of generations has been constructed. The major integration machinery used is based on the ΦAT3 integrase (int) and attP sequences determined previously. A novel core sequence located at the 3' end of the tRNA(leu) gene is identified in Lactobacillus fermentum ATCC 14931 as the integration target by the integration vector though most of such sequences found in other lactobacilli are similar to that determined previously. Due to the lack of an appropriate attB site in Lactococcus lactis MG1363, the integration vector is found to be unable to integrate into the chromosome of the strain. However, such integration can be successfully restored by cotransforming the integration vector with a replicative one harboring both attB and erythromycin resistance sequences into the strain. Furthermore, the integration vector constructed carries a promoter region of placT from the chromosome of Lactobacillus rhamnosus TCELL-1 which is used to express green fluorescence and luminance protein genes in the lactobacilli studied.

LANDMARK-BASED SPEECH RECOGNITION: REPORT OF THE 2004 JOHNS HOPKINS SUMMER WORKSHOP.

PubMed

Hasegawa-Johnson, Mark; Baker, James; Borys, Sarah; Chen, Ken; Coogan, Emily; Greenberg, Steven; Juneja, Amit; Kirchhoff, Katrin; Livescu, Karen; Mohan, Srividya; Muller, Jennifer; Sonmez, Kemal; Wang, Tianyu

2005-01-01

Three research prototype speech recognition systems are described, all of which use recently developed methods from artificial intelligence (specifically support vector machines, dynamic Bayesian networks, and maximum entropy classification) in order to implement, in the form of an automatic speech recognizer, current theories of human speech perception and phonology (specifically landmark-based speech perception, nonlinear phonology, and articulatory phonology). All three systems begin with a high-dimensional multiframe acoustic-to-distinctive feature transformation, implemented using support vector machines trained to detect and classify acoustic phonetic landmarks. Distinctive feature probabilities estimated by the support vector machines are then integrated using one of three pronunciation models: a dynamic programming algorithm that assumes canonical pronunciation of each word, a dynamic Bayesian network implementation of articulatory phonology, or a discriminative pronunciation model trained using the methods of maximum entropy classification. Log probability scores computed by these models are then combined, using log-linear combination, with other word scores available in the lattice output of a first-pass recognizer, and the resulting combination score is used to compute a second-pass speech recognition output.

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

PubMed

Chen, Zhiru; Hong, Wenxue

2016-02-01

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

Integration Profile and Safety of an Adenovirus Hybrid-Vector Utilizing Hyperactive Sleeping Beauty Transposase for Somatic Integration

PubMed Central

Zhang, Wenli; Muck-Hausl, Martin; Wang, Jichang; Sun, Chuanbo; Gebbing, Maren; Miskey, Csaba; Ivics, Zoltan; Izsvak, Zsuzsanna; Ehrhardt, Anja

2013-01-01

We recently developed adenovirus/transposase hybrid-vectors utilizing the previously described hyperactive Sleeping Beauty (SB) transposase HSB5 for somatic integration and we could show stabilized transgene expression in mice and a canine model for hemophilia B. However, the safety profile of these hybrid-vectors with respect to vector dose and genotoxicity remains to be investigated. Herein, we evaluated this hybrid-vector system in C57Bl/6 mice with escalating vector dose settings. We found that in all mice which received the hyperactive SB transposase, transgene expression levels were stabilized in a dose-dependent manner and that the highest vector dose was accompanied by fatalities in mice. To analyze potential genotoxic side-effects due to somatic integration into host chromosomes, we performed a genome-wide integration site analysis using linker-mediated PCR (LM-PCR) and linear amplification-mediated PCR (LAM-PCR). Analysis of genomic DNA samples obtained from HSB5 treated female and male mice revealed a total of 1327 unique transposition events. Overall the chromosomal distribution pattern was close-to-random and we observed a random integration profile with respect to integration into gene and non-gene areas. Notably, when using the LM-PCR protocol, 27 extra-chromosomal integration events were identified, most likely caused by transposon excision and subsequent transposition into the delivered adenoviral vector genome. In total, this study provides a careful evaluation of the safety profile of adenovirus/Sleeping Beauty transposase hybrid-vectors. The obtained information will be useful when designing future preclinical studies utilizing hybrid-vectors in small and large animal models. PMID:24124483

Intranuclear DNA release is a determinant of transfection activity for a non-viral vector: biocleavable polyrotaxane as a supramolecularly dissociative condenser for efficient intranuclear DNA release.

PubMed

Yamada, Yuma; Nomura, Taku; Harashima, Hideyoshi; Yamashita, Atsushi; Katoono, Ryo; Yui, Nobuhiko

2010-01-01

It has been believed that nuclear gene delivery is the most important process for gene expression, and various non-viral vectors are currently being developed with this assumption. However, some of our earlier studies revealed a surprising difference in transfection activity between viral and non-viral vectors: this difference is largely due to the result of the intranuclear disposition of DNA rather than its delivery to the nucleus (Hama S. et al. (2006), Quantitative comparison of intracellular trafficking and nuclear transcription between adenoviral and lipoplex systems. Mol. Ther., 13, 786-794). Here, we report on some direct evidence that demonstrates the importance of the release of intranuclear DNA on transfection activity. The data show that transfection activity can be substantially enhanced by integrating a multifunctional envelope-type nano device (MEND) and a biocleavable polyrotaxane (DMAE-SS-PRX) as an artificial condenser. Our integration system showed significantly higher transfection activity compared to conventional gene delivery system. Moreover, this system provides a strong support for our hypothesis that intranuclear DNA disposition plays a critical role in gene expression for non-viral vectors.

Which coordinate system for modelling path integration?

PubMed

Vickerstaff, Robert J; Cheung, Allen

2010-03-21

Path integration is a navigation strategy widely observed in nature where an animal maintains a running estimate, called the home vector, of its location during an excursion. Evidence suggests it is both ancient and ubiquitous in nature, and has been studied for over a century. In that time, canonical and neural network models have flourished, based on a wide range of assumptions, justifications and supporting data. Despite the importance of the phenomenon, consensus and unifying principles appear lacking. A fundamental issue is the neural representation of space needed for biological path integration. This paper presents a scheme to classify path integration systems on the basis of the way the home vector records and updates the spatial relationship between the animal and its home location. Four extended classes of coordinate systems are used to unify and review both canonical and neural network models of path integration, from the arthropod and mammalian literature. This scheme demonstrates analytical equivalence between models which may otherwise appear unrelated, and distinguishes between models which may superficially appear similar. A thorough analysis is carried out of the equational forms of important facets of path integration including updating, steering, searching and systematic errors, using each of the four coordinate systems. The type of available directional cue, namely allothetic or idiothetic, is also considered. It is shown that on balance, the class of home vectors which includes the geocentric Cartesian coordinate system, appears to be the most robust for biological systems. A key conclusion is that deducing computational structure from behavioural data alone will be difficult or impossible, at least in the absence of an analysis of random errors. Consequently it is likely that further theoretical insights into path integration will require an in-depth study of the effect of noise on the four classes of home vectors. Copyright 2009 Elsevier Ltd. All rights reserved.

Clustering, climate and dengue transmission.

PubMed

Junxiong, Pang; Yee-Sin, Leo

2015-06-01

Dengue is currently the most rapidly spreading vector-borne disease, with an increasing burden over recent decades. Currently, neither a licensed vaccine nor an effective anti-viral therapy is available, and treatment largely remains supportive. Current vector control strategies to prevent and reduce dengue transmission are neither efficient nor sustainable as long-term interventions. Increased globalization and climate change have been reported to influence dengue transmission. In this article, we reviewed the non-climatic and climatic risk factors which facilitate dengue transmission. Sustainable and effective interventions to reduce the increasing threat from dengue would require the integration of these risk factors into current and future prevention strategies, including dengue vaccination, as well as the continuous support and commitment from the political and environmental stakeholders.

Assessing the potential for AAV vector genotoxicity in a murine model

PubMed Central

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

2011-01-01

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

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

PubMed

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

2017-09-20

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

Hybrid Adeno-Associated Viral Vectors Utilizing Transposase-Mediated Somatic Integration for Stable Transgene Expression in Human Cells

PubMed Central

Zhang, Wenli; Solanki, Manish; Müther, Nadine; Ebel, Melanie; Wang, Jichang; Sun, Chuanbo; Izsvak, Zsuzsanna; Ehrhardt, Anja

2013-01-01

Recombinant adeno-associated viral (AAV) vectors have been shown to be one of the most promising vectors for therapeutic gene delivery because they can induce efficient and long-term transduction in non-dividing cells with negligible side-effects. However, as AAV vectors mostly remain episomal, vector genomes and transgene expression are lost in dividing cells. Therefore, to stably transduce cells, we developed a novel AAV/transposase hybrid-vector. To facilitate SB-mediated transposition from the rAAV genome, we established a system in which one AAV vector contains the transposon with the gene of interest and the second vector delivers the hyperactive Sleeping Beauty (SB) transposase SB100X. Human cells were infected with the AAV-transposon vector and the transposase was provided in trans either by transient and stable plasmid transfection or by AAV vector transduction. We found that groups which received the hyperactive transposase SB100X showed significantly increased colony forming numbers indicating enhanced integration efficiencies. Furthermore, we found that transgene copy numbers in transduced cells were dose-dependent and that predominantly SB transposase-mediated transposition contributed to stabilization of the transgene. Based on a plasmid rescue strategy and a linear-amplification mediated PCR (LAM-PCR) protocol we analysed the SB100X-mediated integration profile after transposition from the AAV vector. A total of 1840 integration events were identified which revealed a close to random integration profile. In summary, we show for the first time that AAV vectors can serve as template for SB transposase mediated somatic integration. We developed the first prototype of this hybrid-vector system which with further improvements may be explored for treatment of diseases which originate from rapidly dividing cells. PMID:24116154

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.

Viral Determinants of Integration Site Preferences of Simian Immunodeficiency Virus-Based Vectors

PubMed Central

Monse, Hella; Laufs, Stephanie; Kuate, Seraphin; Zeller, W. Jens; Fruehauf, Stefan; Überla, Klaus

2006-01-01

Preferential integration into transcriptionally active regions of genomes has been observed for retroviral vectors based on gamma-retroviruses and lentiviruses. However, differences in the integration site preferences were detected, which might be explained by differences in viral components of the preintegration complexes. Viral determinants of integration site preferences have not been defined. Therefore, integration sites of simian immunodeficiency virus (SIV)-based vectors produced in the absence of accessory genes or lacking promoter and enhancer elements were compared. Similar integration patterns for the different SIV vectors indicate that vif, vpr, vpx, nef, env, and promoter or enhancer elements are not required for preferential integration of SIV into transcriptionally active regions of genomes. PMID:16873270

A novel Streptomyces spp. integration vector derived from the S. venezuelae phage, SV1.

PubMed

Fayed, Bahgat; Younger, Ellen; Taylor, Gabrielle; Smith, Margaret C M

2014-05-30

Integrating vectors based on the int/attP loci of temperate phages are convenient and used widely, particularly for cloning genes in Streptomyces spp. We have constructed and tested a novel integrating vector based on g27, encoding integrase, and attP site from the phage, SV1. This plasmid, pBF3 integrates efficiently in S. coelicolor and S. lividans but surprisingly fails to generate stable integrants in S. venezuelae, the natural host for phage SV1. pBF3 promises to be a useful addition to the range of integrating vectors currently available for Streptomyces molecular genetics.

Integral transformation solution of free-space cylindrical vector beams and prediction of modified Bessel-Gaussian vector beams.

PubMed

Li, Chun-Fang

2007-12-15

A unified description of free-space cylindrical vector beams is presented that is an integral transformation solution to the vector Helmholtz equation and the transversality condition. In the paraxial condition, this solution not only includes the known J(1) Bessel-Gaussian vector beam and the axisymmetric Laguerre-Gaussian vector beam that were obtained by solving the paraxial wave equations but also predicts two kinds of vector beam, called a modified Bessel-Gaussian vector beam.

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Sequential cloning of chromosomes

DOEpatents

Lacks, Sanford A.

1995-07-18

A method for sequential cloning of chromosomal DNA of a target organism is disclosed. A first DNA segment homologous to the chromosomal DNA to be sequentially cloned is isolated. The first segment has a first restriction enzyme site on either side. A first vector product is formed by ligating the homologous segment into a suitably designed vector. The first vector product is circularly integrated into the target organism's chromosomal DNA. The resulting integrated chromosomal DNA segment includes the homologous DNA segment at either end of the integrated vector segment. The integrated chromosomal DNA is cleaved with a second restriction enzyme and ligated to form a vector-containing plasmid, which is replicated in a host organism. The replicated plasmid is then cleaved with the first restriction enzyme. Next, a DNA segment containing the vector and a segment of DNA homologous to a distal portion of the previously isolated DNA segment is isolated. This segment is then ligated to form a plasmid which is replicated within a suitable host. This plasmid is then circularly integrated into the target chromosomal DNA. The chromosomal DNA containing the circularly integrated vector is treated with a third, retrorestriction (class IIS) enzyme. The cleaved DNA is ligated to give a plasmid that is used to transform a host permissive for replication of its vector. The sequential cloning process continues by repeated cycles of circular integration and excision. The excision is carried out alternately with the second and third enzymes.

Gene therapy using retrovirus vectors: vector development and biosafety at clinical trials.

PubMed

Doi, Knayo; Takeuchi, Yasuhiro

2015-01-01

Retrovirus vectors (gammaretroviral and lentiviral vectors) have been considered as promising tools to transfer therapeutic genes into patient cells because they can permanently integrate into host cellular genome. To treat monogenic, inherited diseases, retroviral vectors have been used to add correct genes into patient cells. Conventional gammaretroviral vectors achieved successful results in clinical trials: treated patients had therapeutic gene expression in target cells and had improved symptoms of diseases. However, serious side-effects of leukemia occurred, caused by retroviral insertional mutagenesis (IM). These incidences stressed the importance of monitoring vector integration sites in patient cells as well as of re-consideration on safer vectors. More recently lentiviral vectors which can deliver genes into non-dividing cells started to be used in clinical trials including neurological disorders, showing their efficacy. Vector integration site analysis revealed that lentiviruses integrate less likely to near promoter regions of oncogenes than gammaretroviruses and no adverse events have been reported in lentiviral vector-mediated gene therapy clinical trials. Therefore lentiviral vectors have promises to be applied to a wide range of common diseases in near future. For example, T cells from cancer patients were transduced to express chimeric T cell receptors recognizing their tumour cells enhancing patients' anti-cancer immunity.

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

PubMed Central

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

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

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

PubMed

Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

2017-01-01

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

Using an object-based grid system to evaluate a newly developed EP approach to formulate SVMs as applied to the classification of organophosphate nerve agents

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Lewis, Michael; Sadik, Omowunmi; Wong, Lut; Wanekaya, Adam; Gonzalez, Richard J.; Balan, Arun

2004-04-01

This paper extends the classification approaches described in reference [1] in the following way: (1.) developing and evaluating a new method for evolving organophosphate nerve agent Support Vector Machine (SVM) classifiers using Evolutionary Programming, (2.) conducting research experiments using a larger database of organophosphate nerve agents, and (3.) upgrading the architecture to an object-based grid system for evaluating the classification of EP derived SVMs. Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. This paper reports the integration of multi-array sensors with Support Vector Machines (SVMs) for the detection of organophosphates nerve agents using a grid computing system called Legion. Grid computing is the use of large collections of heterogeneous, distributed resources (including machines, databases, devices, and users) to support large-scale computations and wide-area data access. Finally, preliminary results using EP derived support vector machines designed to operate on distributed systems have provided accurate classification results. In addition, distributed training time architectures are 50 times faster when compared to standard iterative training time methods.

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Ribosomal DNA Integrating rAAV-rDNA Vectors Allow for Stable Transgene Expression

PubMed Central

Lisowski, Leszek; Lau, Ashley; Wang, Zhongya; Zhang, Yue; Zhang, Feijie; Grompe, Markus; Kay, Mark A

2012-01-01

Although recombinant adeno-associated virus (rAAV) vectors are proving to be efficacious in clinical trials, the episomal character of the delivered transgene restricts their effectiveness to use in quiescent tissues, and may not provide lifelong expression. In contrast, integrating vectors enhance the risk of insertional mutagenesis. In an attempt to overcome both of these limitations, we created new rAAV-rDNA vectors, with an expression cassette flanked by ribosomal DNA (rDNA) sequences capable of homologous recombination into genomic rDNA. We show that after in vivo delivery the rAAV-rDNA vectors integrated into the genomic rDNA locus 8–13 times more frequently than control vectors, providing an estimate that 23–39% of the integrations were specific to the rDNA locus. Moreover, a rAAV-rDNA vector containing a human factor IX (hFIX) expression cassette resulted in sustained therapeutic levels of serum hFIX even after repeated manipulations to induce liver regeneration. Because of the relative safety of integration in the rDNA locus, these vectors expand the usage of rAAV for therapeutics requiring long-term gene transfer into dividing cells. PMID:22990671

Aeroelastic analysis of a troposkien-type wind turbine blade

NASA Technical Reports Server (NTRS)

Nitzsche, F.

1981-01-01

The linear aeroelastic equations for one curved blade of a vertical axis wind turbine in state vector form are presented. The method is based on a simple integrating matrix scheme together with the transfer matrix idea. The method is proposed as a convenient way of solving the associated eigenvalue problem for general support conditions.

Adeno-associated virus Rep-mediated targeting of integrase-defective retroviral vector DNA circles into human chromosome 19

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

Huang, Shuohao; Kawabe, Yoshinori; Ito, Akira

2012-01-06

Highlights: Black-Right-Pointing-Pointer Adeno-associated virus (AAV) is capable of targeted integration in human cells. Black-Right-Pointing-Pointer Integrase-defective retroviral vector (IDRV) enables a circular DNA delivery. Black-Right-Pointing-Pointer A targeted integration system of IDRV DNA using the AAV integration mechanism. Black-Right-Pointing-Pointer Targeted IDRV integration ameliorates the safety concerns for retroviral vectors. -- Abstract: Retroviral vectors have been employed in clinical trials for gene therapy owing to their relative large packaging capacity, alterable cell tropism, and chromosomal integration for stable transgene expression. However, uncontrollable integrations of transgenes are likely to cause safety issues, such as insertional mutagenesis. A targeted transgene integration system for retroviral vectors,more » therefore, is a straightforward way to address the insertional mutagenesis issue. Adeno-associated virus (AAV) is the only known virus capable of targeted integration in human cells. In the presence of AAV Rep proteins, plasmids possessing the p5 integration efficiency element (p5IEE) can be integrated into the AAV integration site (AAVS1) in the human genome. In this report, we describe a system that can target the circular DNA derived from non-integrating retroviral vectors to the AAVS1 site by utilizing the Rep/p5IEE integration mechanism. Our results showed that after G418 selection 30% of collected clones had retroviral DNA targeted at the AAVS1 site.« less

Generalized Case ``Van Kampen theory for electromagnetic oscillations in a magnetized plasma

NASA Astrophysics Data System (ADS)

Bairaktaris, F.; Hizanidis, K.; Ram, A. K.

2017-10-01

The Case-Van Kampen theory is set up to describe electrostatic oscillations in an unmagnetized plasma. Our generalization to electromagnetic oscillations in magnetized plasma is formulated in the relativistic position-momentum phase space of the particles. The relativistic Vlasov equation includes the ambient, homogeneous, magnetic field, and space-time dependent electromagnetic fields that satisfy Maxwell's equations. The standard linearization technique leads to an equation for the perturbed distribution function in terms of the electromagnetic fields. The eigenvalues and eigenfunctions are obtained from three integrals `` each integral being over two different components of the momentum vector. Results connecting phase velocity, frequency, and wave vector will be presented. Supported in part by the Hellenic National Programme on Controlled Thermonuclear Fusion associated with the EUROfusion Consortium, and by DoE Grant DE-FG02-91ER-54109.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Sequential cloning of chromosomes

DOEpatents

Lacks, S.A.

1995-07-18

A method for sequential cloning of chromosomal DNA of a target organism is disclosed. A first DNA segment homologous to the chromosomal DNA to be sequentially cloned is isolated. The first segment has a first restriction enzyme site on either side. A first vector product is formed by ligating the homologous segment into a suitably designed vector. The first vector product is circularly integrated into the target organism`s chromosomal DNA. The resulting integrated chromosomal DNA segment includes the homologous DNA segment at either end of the integrated vector segment. The integrated chromosomal DNA is cleaved with a second restriction enzyme and ligated to form a vector-containing plasmid, which is replicated in a host organism. The replicated plasmid is then cleaved with the first restriction enzyme. Next, a DNA segment containing the vector and a segment of DNA homologous to a distal portion of the previously isolated DNA segment is isolated. This segment is then ligated to form a plasmid which is replicated within a suitable host. This plasmid is then circularly integrated into the target chromosomal DNA. The chromosomal DNA containing the circularly integrated vector is treated with a third, retrorestriction (class IIS) enzyme. The cleaved DNA is ligated to give a plasmid that is used to transform a host permissive for replication of its vector. The sequential cloning process continues by repeated cycles of circular integration and excision. The excision is carried out alternately with the second and third enzymes. 9 figs.

Will integrated surveillance systems for vectors and vector-borne diseases be the future of controlling vector-borne diseases? A practical example from China.

PubMed

Wu, Y; Ling, F; Hou, J; Guo, S; Wang, J; Gong, Z

2016-07-01

Vector-borne diseases are one of the world's major public health threats and annually responsible for 30-50% of deaths reported to the national notifiable disease system in China. To control vector-borne diseases, a unified, effective and economic surveillance system is urgently needed; all of the current surveillance systems in China waste resources and/or information. Here, we review some current surveillance systems and present a concept for an integrated surveillance system combining existing vector and vector-borne disease monitoring systems. The integrated surveillance system has been tested in pilot programmes in China and led to a 21·6% cost saving in rodent-borne disease surveillance. We share some experiences gained from these programmes.

Foundation Mathematics for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-03-01

1. Arithmetic and geometry; 2. Preliminary algebra; 3. Differential calculus; 4. Integral calculus; 5. Complex numbers and hyperbolic functions; 6. Series and limits; 7. Partial differentiation; 8. Multiple integrals; 9. Vector algebra; 10. Matrices and vector spaces; 11. Vector calculus; 12. Line, surface and volume integrals; 13. Laplace transforms; 14. Ordinary differential equations; 15. Elementary probability; Appendices; Index.

Student Solution Manual for Foundation Mathematics for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-03-01

1. Arithmetic and geometry; 2. Preliminary algebra; 3. Differential calculus; 4. Integral calculus; 5. Complex numbers and hyperbolic functions; 6. Series and limits; 7. Partial differentiation; 8. Multiple integrals; 9. Vector algebra; 10. Matrices and vector spaces; 11. Vector calculus; 12. Line, surface and volume integrals; 13. Laplace transforms; 14. Ordinary differential equations; 15. Elementary probability; Appendix.

Combining information from 3 anatomic regions in the diagnosis of glaucoma with time-domain optical coherence tomography.

PubMed

Wang, Mingwu; Lu, Ake Tzu-Hui; Varma, Rohit; Schuman, Joel S; Greenfield, David S; Huang, David

2014-03-01

To improve the diagnosis of glaucoma by combining time-domain optical coherence tomography (TD-OCT) measurements of the optic disc, circumpapillary retinal nerve fiber layer (RNFL), and macular retinal thickness. Ninety-six age-matched normal and 96 perimetric glaucoma participants were included in this observational, cross-sectional study. Or-logic, support vector machine, relevance vector machine, and linear discrimination function were used to analyze the performances of combined TD-OCT diagnostic variables. The area under the receiver-operating curve (AROC) was used to evaluate the diagnostic accuracy and to compare the diagnostic performance of single and combined anatomic variables. The best RNFL thickness variables were the inferior (AROC=0.900), overall (AROC=0.892), and superior quadrants (AROC=0.850). The best optic disc variables were horizontal integrated rim width (AROC=0.909), vertical integrated rim area (AROC=0.908), and cup/disc vertical ratio (AROC=0.890). All macular retinal thickness variables had AROCs of 0.829 or less. Combining the top 3 RNFL and optic disc variables in optimizing glaucoma diagnosis, support vector machine had the highest AROC, 0.954, followed by or-logic (AROC=0.946), linear discrimination function (AROC=0.946), and relevance vector machine (AROC=0.943). All combination diagnostic variables had significantly larger AROCs than any single diagnostic variable. There are no significant differences among the combination diagnostic indices. With TD-OCT, RNFL and optic disc variables had better diagnostic accuracy than macular retinal variables. Combining top RNFL and optic disc variables significantly improved diagnostic performance. Clinically, or-logic classification was the most practical analytical tool with sufficient accuracy to diagnose early glaucoma.

Enhancers Are Major Targets for Murine Leukemia Virus Vector Integration

PubMed Central

De Ravin, Suk See; Su, Ling; Theobald, Narda; Choi, Uimook; Macpherson, Janet L.; Poidinger, Michael; Symonds, Geoff; Pond, Susan M.; Ferris, Andrea L.; Hughes, Stephen H.

2014-01-01

ABSTRACT Retroviral vectors have been used in successful gene therapies. However, in some patients, insertional mutagenesis led to leukemia or myelodysplasia. Both the strong promoter/enhancer elements in the long terminal repeats (LTRs) of murine leukemia virus (MLV)-based vectors and the vector-specific integration site preferences played an important role in these adverse clinical events. MLV integration is known to prefer regions in or near transcription start sites (TSS). Recently, BET family proteins were shown to be the major cellular proteins responsible for targeting MLV integration. Although MLV integration sites are significantly enriched at TSS, only a small fraction of the MLV integration sites (<15%) occur in this region. To resolve this apparent discrepancy, we created a high-resolution genome-wide integration map of more than one million integration sites from CD34+ hematopoietic stem cells transduced with a clinically relevant MLV-based vector. The integration sites form ∼60,000 tight clusters. These clusters comprise ∼1.9% of the genome. The vast majority (87%) of the integration sites are located within histone H3K4me1 islands, a hallmark of enhancers. The majority of these clusters also have H3K27ac histone modifications, which mark active enhancers. The enhancers of some oncogenes, including LMO2, are highly preferred targets for integration without in vivo selection. IMPORTANCE We show that active enhancer regions are the major targets for MLV integration; this means that MLV preferentially integrates in regions that are favorable for viral gene expression in a variety of cell types. The results provide insights for MLV integration target site selection and also explain the high risk of insertional mutagenesis that is associated with gene therapy trials using MLV vectors. PMID:24501411

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.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Mouse mammary tumor virus-based vector transduces non-dividing cells, enters the nucleus via a TNPO3-independent pathway and integrates in a less biased fashion than other retroviruses.

PubMed

Konstantoulas, Constantine James; Indik, Stanislav

2014-04-30

Mouse mammary tumor virus (MMTV) is a complex, milk-born betaretrovirus, which preferentially infects dendritic cells (DC) in the gastrointestinal tract and then spreads to T and B lymphocytes and finally to the mammary gland. It is not clear how the prototypic betaretrovirus infects mucosal DCs and naïve lymphocytes as these cells are considered to be non-proliferative. Studies of MMTV biology have been hampered by the difficulty of obtaining sufficient virus/vector titers after transfection of a molecular clone in cultured cells. To surmount this barrier we developed a novel MMTV-based vector system with a split genome design containing potent posttranscriptional regulatory functions. Using this system, vector particles were produced to markedly greater titers (>1000-fold) than those obtained previously. The titers (>106 transduction units /ml) were comparable to those achieved with lentiviral or gammaretroviral vectors. Importantly, the vector transduced the enhanced green fluorescence protein gene into the chromosomes of non-dividing cells, such as cells arrested at the G2/M phase of the cell cycle and unstimulated hematopoietic progenitor cells, at an efficiency similar to that obtained with the HIV-1-based vector. In contrast to HIV-1, MMTV transductions were not affected by knocking down the expression of a factor involved in nuclear import of the HIV-1 pre-integration complexes, TNPO3. In contrast to HIV-1, the MMTV-based vector did not preferentially integrate in transcription units. Additionally, no preference for integration near transcription start sites, the regions preferentially targeted by gammaretroviral vectors, was observed. The vector derived from MMTV exhibits a random integration pattern. Overall, the betaretroviral vector system should facilitate molecular virology studies of the prototypic betaretrovirus as well as studies attempting to elucidate fundamental cellular processes such as nuclear import pathways. Random integration in cycling and non-cycling cells may be applicable in unbiased gene delivery.

Closed-form integrator for the quaternion (euler angle) kinematics equations

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A. (Inventor)

2000-01-01

The invention is embodied in a method of integrating kinematics equations for updating a set of vehicle attitude angles of a vehicle using 3-dimensional angular velocities of the vehicle, which includes computing an integrating factor matrix from quantities corresponding to the 3-dimensional angular velocities, computing a total integrated angular rate from the quantities corresponding to a 3-dimensional angular velocities, computing a state transition matrix as a sum of (a) a first complementary function of the total integrated angular rate and (b) the integrating factor matrix multiplied by a second complementary function of the total integrated angular rate, and updating the set of vehicle attitude angles using the state transition matrix. Preferably, the method further includes computing a quanternion vector from the quantities corresponding to the 3-dimensional angular velocities, in which case the updating of the set of vehicle attitude angles using the state transition matrix is carried out by (a) updating the quanternion vector by multiplying the quanternion vector by the state transition matrix to produce an updated quanternion vector and (b) computing an updated set of vehicle attitude angles from the updated quanternion vector. The first and second trigonometric functions are complementary, such as a sine and a cosine. The quantities corresponding to the 3-dimensional angular velocities include respective averages of the 3-dimensional angular velocities over plural time frames. The updating of the quanternion vector preserves the norm of the vector, whereby the updated set of vehicle attitude angles are virtually error-free.

Sleeping Beauty-baculovirus hybrid vectors for long-term gene expression in the eye.

PubMed

Turunen, Tytteli Anni Kaarina; Laakkonen, Johanna Päivikki; Alasaarela, Laura; Airenne, Kari Juhani; Ylä-Herttuala, Seppo

2014-01-01

A baculovirus vector is capable of efficiently transducing many nondiving and diving cell types. However, the potential of baculovirus is restricted for many gene delivery applications as a result of the transient gene expression that it mediates. The plasmid-based Sleeping Beauty (SB) transposon system integrates transgenes into target cell genome efficiently with a genomic integration pattern that is generally considered safer than the integration of many other integrating vectors; yet efficient delivery of therapeutic genes into cells of target tissues in vivo is a major challenge for nonviral gene therapy. In the present study, SB was introduced into baculovirus to obtain novel hybrid vectors that would combine the best features of the two vector systems (i.e. effective gene delivery and efficient integration into the genome), thus circumventing the major limitations of these vectors. We constructed and optimized SB-baculovirus hybrid vectors that bear either SB100x transposase or SB transposon in the forward or reverse orientations with respect to the viral backbone The functionality of the novel hybrid vectors was investigated in cell cultures and in a proof-of-concept study in the mouse eye. The hybrid vectors showed high and sustained transgene expression that remained stable and demonstrated no signs of decline during the 2 months follow-up in vitro. These results were verified in the mouse eye where persistent transgene expression was detected two months after intravitreal injection. Our results confirm that (i) SB-baculovirus hybrid vectors mediate long-term gene expression in vitro and in vivo, and (ii) the hybrid vectors are potential new tools for the treatment of ocular diseases. Copyright © 2014 John Wiley & Sons, Ltd.

Stable integration of recombinant adeno-associated virus vector genomes after transduction of murine hematopoietic stem cells.

PubMed

Han, Zongchao; Zhong, Li; Maina, Njeri; Hu, Zhongbo; Li, Xiaomiao; Chouthai, Nitin S; Bischof, Daniela; Weigel-Van Aken, Kirsten A; Slayton, William B; Yoder, Mervin C; Srivastava, Arun

2008-03-01

We previously reported that among single-stranded adeno-associated virus (ssAAV) vectors, serotypes 1 through 5, ssAAV1 is the most efficient in transducing murine hematopoietic stem cells (HSCs), but viral second-strand DNA synthesis remains a rate-limiting step. Subsequently, using double-stranded, self-complementary AAV (scAAV) vectors, serotypes 7 through 10, we observed that scAAV7 vectors also transduce murine HSCs efficiently. In the present study, we used scAAV1 and scAAV7 shuttle vectors to transduce HSCs in a murine bone marrow serial transplant model in vivo, which allowed examination of the AAV proviral integration pattern in the mouse genome, as well as recovery and nucleotide sequence analyses of AAV-HSC DNA junction fragments. The proviral genomes were stably integrated, and integration sites were localized to different mouse chromosomes. None of the integration sites was found to be in a transcribed gene, or near a cellular oncogene. None of the animals, monitored for up to 1 year, exhibited pathological abnormalities. Thus, AAV proviral integration-induced risk of oncogenesis was not found in our study, which provides functional confirmation of stable transduction of self-renewing multipotential HSCs by scAAV vectors as well as promise for the use of these vectors in the potential treatment of disorders of the hematopoietic system.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Wheel speed management control system for spacecraft

NASA Technical Reports Server (NTRS)

Goodzeit, Neil E. (Inventor); Linder, David M. (Inventor)

1991-01-01

A spacecraft attitude control system uses at least four reaction wheels. In order to minimize reaction wheel speed and therefore power, a wheel speed management system is provided. The management system monitors the wheel speeds and generates a wheel speed error vector. The error vector is integrated, and the error vector and its integral are combined to form a correction vector. The correction vector is summed with the attitude control torque command signals for driving the reaction wheels.

Construction of a New Phage Integration Vector pFIV-Val for Use in Different Francisella Species

PubMed Central

Tlapák, Hana; Köppen, Kristin; Rydzewski, Kerstin; Grunow, Roland; Heuner, Klaus

2018-01-01

We recently identified and described a putative prophage on the genomic island FhaGI-1 located within the genome of Francisella hispaniensis AS02-814 (F. tularensis subsp. novicida-like 3523). In this study, we constructed two variants of a Francisella phage integration vector, called pFIV1-Val and pFIV2-Val (Francisella Integration Vector-tRNAVal-specific), using the attL/R-sites and the site-specific integrase (FN3523_1033) of FhaGI-1, a chloramphenicol resistance cassette and a sacB gene for counter selection of transformants against the vector backbone. We inserted the respective sites and genes into vector pUC57-Kana to allow for propagation in Escherichia coli. The constructs generated a circular episomal form in E. coli which could be used to transform Francisella spp. where FIV-Val stably integrated site specifically into the tRNAVal gene of the genome, whereas pUC57-Kana is lost due to counter selection. Functionality of the new vector was demonstrated by the successfully complementation of a Francisella mutant strain. The vectors were stable in vitro and during host-cell infection without selective pressure. Thus, the vectors can be applied as a further genetic tool in Francisella research, expanding the present genetic tools by an integrative element. This new element is suitable to perform long-term experiments with different Francisella species. PMID:29594068

Construction of a New Phage Integration Vector pFIV-Val for Use in Different Francisella Species.

PubMed

Tlapák, Hana; Köppen, Kristin; Rydzewski, Kerstin; Grunow, Roland; Heuner, Klaus

2018-01-01

We recently identified and described a putative prophage on the genomic island FhaGI-1 located within the genome of Francisella hispaniensis AS02-814 ( F. tularensis subsp. novicida -like 3523). In this study, we constructed two variants of a Francisella phage integration vector, called pFIV1-Val and pFIV2-Val ( Francisella Integration Vector-tRNA Val -specific), using the attL/R- sites and the site-specific integrase (FN3523_1033) of FhaGI-1, a chloramphenicol resistance cassette and a sacB gene for counter selection of transformants against the vector backbone. We inserted the respective sites and genes into vector pUC57-Kana to allow for propagation in Escherichia coli . The constructs generated a circular episomal form in E. coli which could be used to transform Francisella spp . where FIV-Val stably integrated site specifically into the tRNA Val gene of the genome, whereas pUC57-Kana is lost due to counter selection. Functionality of the new vector was demonstrated by the successfully complementation of a Francisella mutant strain. The vectors were stable in vitro and during host-cell infection without selective pressure. Thus, the vectors can be applied as a further genetic tool in Francisella research, expanding the present genetic tools by an integrative element. This new element is suitable to perform long-term experiments with different Francisella species.

Decision support system for diabetic retinopathy using discrete wavelet transform.

PubMed

Noronha, K; Acharya, U R; Nayak, K P; Kamath, S; Bhandary, S V

2013-03-01

Prolonged duration of the diabetes may affect the tiny blood vessels of the retina causing diabetic retinopathy. Routine eye screening of patients with diabetes helps to detect diabetic retinopathy at the early stage. It is very laborious and time-consuming for the doctors to go through many fundus images continuously. Therefore, decision support system for diabetic retinopathy detection can reduce the burden of the ophthalmologists. In this work, we have used discrete wavelet transform and support vector machine classifier for automated detection of normal and diabetic retinopathy classes. The wavelet-based decomposition was performed up to the second level, and eight energy features were extracted. Two energy features from the approximation coefficients of two levels and six energy values from the details in three orientations (horizontal, vertical and diagonal) were evaluated. These features were fed to the support vector machine classifier with various kernel functions (linear, radial basis function, polynomial of orders 2 and 3) to evaluate the highest classification accuracy. We obtained the highest average classification accuracy, sensitivity and specificity of more than 99% with support vector machine classifier (polynomial kernel of order 3) using three discrete wavelet transform features. We have also proposed an integrated index called Diabetic Retinopathy Risk Index using clinically significant wavelet energy features to identify normal and diabetic retinopathy classes using just one number. We believe that this (Diabetic Retinopathy Risk Index) can be used as an adjunct tool by the doctors during the eye screening to cross-check their diagnosis.

Lefschetz thimbles in fermionic effective models with repulsive vector-field

NASA Astrophysics Data System (ADS)

Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira

2018-06-01

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

Applying different independent component analysis algorithms and support vector regression for IT chain store sales forecasting.

PubMed

Dai, Wensheng; Wu, Jui-Yu; Lu, Chi-Jie

2014-01-01

Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.

Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting

PubMed Central

Dai, Wensheng

2014-01-01

Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches. Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme. Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems. But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem. In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store. Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error. The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting. PMID:25165740

jsPhyloSVG: a javascript library for visualizing interactive and vector-based phylogenetic trees on the web.

PubMed

Smits, Samuel A; Ouverney, Cleber C

2010-08-18

Many software packages have been developed to address the need for generating phylogenetic trees intended for print. With an increased use of the web to disseminate scientific literature, there is a need for phylogenetic trees to be viewable across many types of devices and feature some of the interactive elements that are integral to the browsing experience. We propose a novel approach for publishing interactive phylogenetic trees. We present a javascript library, jsPhyloSVG, which facilitates constructing interactive phylogenetic trees from raw Newick or phyloXML formats directly within the browser in Scalable Vector Graphics (SVG) format. It is designed to work across all major browsers and renders an alternative format for those browsers that do not support SVG. The library provides tools for building rectangular and circular phylograms with integrated charting. Interactive features may be integrated and made to respond to events such as clicks on any element of the tree, including labels. jsPhyloSVG is an open-source solution for rendering dynamic phylogenetic trees. It is capable of generating complex and interactive phylogenetic trees across all major browsers without the need for plugins. It is novel in supporting the ability to interpret the tree inference formats directly, exposing the underlying markup to data-mining services. The library source code, extensive documentation and live examples are freely accessible at www.jsphylosvg.com.

Genetic stability of gene targeted immunoglobulin loci. I. Heavy chain isotype exchange induced by a universal gene replacement vector.

PubMed Central

Kardinal, C; Selmayr, M; Mocikat, R

1996-01-01

Gene targeting at the immunoglobulin loci of B cells is an efficient tool for studying immunoglobulin expression or generating chimeric antibodies. We have shown that vector integration induced by human immunoglobulin G1 (IgG1) insertion vectors results in subsequent vector excision mediated by the duplicated target sequence, whereas replacement events which could be induced by the same constructs remain stable. We could demonstrate that the distribution of the vector homology strongly influences the genetic stability obtained. To this end we developed a novel type of a heavy chain replacement vector making use of the heavy chain class switch recombination sequence. Despite the presence of a two-sided homology this construct is universally applicable irrespective of the constant gene region utilized by the B cell. In comparison to an integration vector the frequency of stable incorporation was strongly increased, but we still observed vector excision, although at a markedly reduced rate. The latter events even occurred with circular constructs. Linearization of the construct at various sites and the comparison with an integration vector that carries the identical homology sequence, but differs in the distribution of homology, revealed the following features of homologous recombination of immunoglobulin genes: (i) the integration frequency is only determined by the length of the homology flank where the cross-over takes place; (ii) a 5' flank that does not meet the minimum requirement of homology length cannot be complemented by a sufficient 3' flank; (iii) free vector ends play a role for integration as well as for replacement targeting; (iv) truncating recombination events are suppressed in the presence of two flanks. Furthermore, we show that the switch region that was used as 3' flank is non-functional in an inverted orientation. Images Figure 2 PMID:8958041

Genetic stability of gene targeted immunoglobulin loci. I. Heavy chain isotype exchange induced by a universal gene replacement vector.

PubMed

Kardinal, C; Selmayr, M; Mocikat, R

1996-11-01

Gene targeting at the immunoglobulin loci of B cells is an efficient tool for studying immunoglobulin expression or generating chimeric antibodies. We have shown that vector integration induced by human immunoglobulin G1 (IgG1) insertion vectors results in subsequent vector excision mediated by the duplicated target sequence, whereas replacement events which could be induced by the same constructs remain stable. We could demonstrate that the distribution of the vector homology strongly influences the genetic stability obtained. To this end we developed a novel type of a heavy chain replacement vector making use of the heavy chain class switch recombination sequence. Despite the presence of a two-sided homology this construct is universally applicable irrespective of the constant gene region utilized by the B cell. In comparison to an integration vector the frequency of stable incorporation was strongly increased, but we still observed vector excision, although at a markedly reduced rate. The latter events even occurred with circular constructs. Linearization of the construct at various sites and the comparison with an integration vector that carries the identical homology sequence, but differs in the distribution of homology, revealed the following features of homologous recombination of immunoglobulin genes: (i) the integration frequency is only determined by the length of the homology flank where the cross-over takes place; (ii) a 5' flank that does not meet the minimum requirement of homology length cannot be complemented by a sufficient 3' flank; (iii) free vector ends play a role for integration as well as for replacement targeting; (iv) truncating recombination events are suppressed in the presence of two flanks. Furthermore, we show that the switch region that was used as 3' flank is non-functional in an inverted orientation.

Homologous and heterologous recombination between adenovirus vector DNA and chromosomal DNA.

PubMed

Stephen, Sam Laurel; Sivanandam, Vijayshankar Ganesh; Kochanek, Stefan

2008-11-01

Adenovirus vector DNA is perceived to remain as episome following gene transfer. We quantitatively and qualitatively analysed recombination between high capacity adenoviral vector (HC-AdV) and chromosomal DNA following gene transfer in vitro. We studied homologous and heterologous recombination with a single HC-AdV carrying (i) a large genomic HPRT fragment with the HPRT CHICAGO mutation causing translational stop upon homologous recombination with the HPRT locus and (ii) a selection marker to allow for clonal selection in the event of heterologous recombination. We analysed the sequences at the junctions between vector and chromosomal DNA. In primary cells and in cell lines, the frequency of homologous recombination ranged from 2 x 10(-5) to 1.6 x 10(-6). Heterologous recombination occurred at rates between 5.5 x 10(-3) and 1.1 x 10(-4). HC-AdV DNA integrated via the termini mostly as intact molecules. Analysis of the junction sequences indicated vector integration in a relatively random manner without an obvious preference for particular chromosomal regions, but with a preference for integration into genes. Integration into protooncogenes or tumor suppressor genes was not observed. Patchy homologies between vector termini and chromosomal DNA were found at the site of integration. Although the majority of integrations had occurred without causing mutations in the chromosomal DNA, cases of nucleotide substitutions and insertions were observed. In several cases, deletions of even relative large chromosomal regions were likely. These results extend previous information on the integration patterns of adenovirus vector DNA and contribute to a risk-benefit assessment of adenovirus-mediated gene transfer.

Specific insertions of zinc finger domains into Gag-Pol yield engineered retroviral vectors with selective integration properties

PubMed Central

Lim, Kwang-il; Klimczak, Ryan; Yu, Julie H.; Schaffer, David V.

2010-01-01

Retroviral vectors offer benefits of efficient delivery and stable gene expression; however, their clinical use raises the concerns of insertional mutagenesis and potential oncogenesis due to genomic integration preferences in transcriptional start sites (TSS). We have shifted the integration preferences of retroviral vectors by generating a library of viral variants with a DNA-binding domain inserted at random positions throughout murine leukemia virus Gag-Pol, then selecting for variants that are viable and exhibit altered integration properties. We found seven permissive zinc finger domain (ZFD) insertion sites throughout Gag-Pol, including within p12, reverse transcriptase, and integrase. Comprehensive genome integration analysis showed that several ZFD insertions yielded retroviral vector variants with shifted integration patterns that did not favor TSS. Furthermore, integration site analysis revealed selective integration for numerous mutants. For example, two retroviral variants with a given ZFD at appropriate positions in Gag-Pol strikingly integrated primarily into four common sites out of 3.1 × 109 possible human genome locations (P = 4.6 × 10-29). Our findings demonstrate that insertion of DNA-binding motifs into multiple locations in Gag-Pol can make considerable progress toward engineering safer retroviral vectors that integrate into a significantly narrowed pool of sites on human genome and overcome the preference for TSS. PMID:20616052

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

PubMed Central

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

2016-01-01

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

A Method for Extracting Important Segments from Documents Using Support Vector Machines

NASA Astrophysics Data System (ADS)

Suzuki, Daisuke; Utsumi, Akira

In this paper we propose an extraction-based method for automatic summarization. The proposed method consists of two processes: important segment extraction and sentence compaction. The process of important segment extraction classifies each segment in a document as important or not by Support Vector Machines (SVMs). The process of sentence compaction then determines grammatically appropriate portions of a sentence for a summary according to its dependency structure and the classification result by SVMs. To test the performance of our method, we conducted an evaluation experiment using the Text Summarization Challenge (TSC-1) corpus of human-prepared summaries. The result was that our method achieved better performance than a segment-extraction-only method and the Lead method, especially for sentences only a part of which was included in human summaries. Further analysis of the experimental results suggests that a hybrid method that integrates sentence extraction with segment extraction may generate better summaries.

Ub-ISAP: a streamlined UNIX pipeline for mining unique viral vector integration sites from next generation sequencing data.

PubMed

Kamboj, Atul; Hallwirth, Claus V; Alexander, Ian E; McCowage, Geoffrey B; Kramer, Belinda

2017-06-17

The analysis of viral vector genomic integration sites is an important component in assessing the safety and efficiency of patient treatment using gene therapy. Alongside this clinical application, integration site identification is a key step in the genetic mapping of viral elements in mutagenesis screens that aim to elucidate gene function. We have developed a UNIX-based vector integration site analysis pipeline (Ub-ISAP) that utilises a UNIX-based workflow for automated integration site identification and annotation of both single and paired-end sequencing reads. Reads that contain viral sequences of interest are selected and aligned to the host genome, and unique integration sites are then classified as transcription start site-proximal, intragenic or intergenic. Ub-ISAP provides a reliable and efficient pipeline to generate large datasets for assessing the safety and efficiency of integrating vectors in clinical settings, with broader applications in cancer research. Ub-ISAP is available as an open source software package at https://sourceforge.net/projects/ub-isap/ .

New ΦBT1 site-specific integrative vectors with neutral phenotype in Streptomyces.

PubMed

Gonzalez-Quiñonez, Nathaly; López-García, María Teresa; Yagüe, Paula; Rioseras, Beatriz; Pisciotta, Annalisa; Alduina, Rosa; Manteca, Ángel

2016-03-01

Integrative plasmids are one of the best options to introduce genes in low copy and in a stable form into bacteria. The ΦC31-derived plasmids constitute the most common integrative vectors used in Streptomyces. They integrate at different positions (attB and pseudo-attB sites) generating different mutations. The less common ΦBT1-derived vectors integrate at the unique attB site localized in the SCO4848 gene (S. coelicolor genome) or their orthologues in other streptomycetes. This work demonstrates that disruption of SCO4848 generates a delay in spore germination. SCO4848 is co-transcribed with SCO4849, and the spore germination phenotype is complemented by SCO4849. Plasmids pNG1-4 were created by modifying the ΦBT1 integrative vector pMS82 by introducing a copy of SCO4849 under the control of the promoter region of SCO4848. pNG2 and pNG4 also included a copy of the P ermE * in order to facilitate gene overexpression. pNG3 and pNG4 harboured a copy of the bla gene (ampicillin resistance) to facilitate selection in E. coli. pNG1-4 are the only integrative vectors designed to produce a neutral phenotype when they are integrated into the Streptomyces genome. The experimental approach developed in this work can be applied to create phenotypically neutral integrative plasmids in other bacteria.

Integrating natural and social sciences to manage sustainably vectors of change in the marine environment: Dogger Bank transnational case study

NASA Astrophysics Data System (ADS)

Burdon, Daryl; Boyes, Suzanne J.; Elliott, Michael; Smyth, Katie; Atkins, Jonathan P.; Barnes, Richard A.; Wurzel, Rüdiger K.

2018-02-01

The management of marine resources is a complex process driven by the dynamics of the natural system and the influence of stakeholders including policy-makers. An integration of natural and social sciences research is required by policy-makers to better understand, and manage sustainably, natural changes and anthropogenic activities within particular marine systems. Given the uncertain development of activities in the marine environment, future scenarios assessments can be used to investigate whether marine policy measures are robust and sustainable. This paper develops an interdisciplinary framework, which incorporates future scenarios assessments, and identifies four main types of evaluation needed to integrate natural and social sciences research to support the integrated management of the marine environment: environmental policy and governance assessments; ecosystem services, indicators and valuation; modelling tools for management evaluations, and risk assessment and risk management. The importance of stakeholder engagement within each evaluation method is highlighted. The paper focuses on the transnational spatial marine management of the Dogger Bank, in the central North Sea, a site which is very important ecologically, economically and politically. Current management practices are reviewed, and research tools to support future management decisions are applied and discussed in relation to two main vectors of change affecting the Dogger Bank, namely commercial fisheries and offshore wind farm developments, and in relation to the need for nature conservation. The input of local knowledge through stakeholder engagement is highlighted as a necessary requirement to produce site-specific policy recommendations for the future management of the Dogger Bank. We present wider policy recommendations to integrate natural and social sciences in a global marine context.

Construction and applications of exon-trapping gene-targeting vectors with a novel strategy for negative selection.

PubMed

Saito, Shinta; Ura, Kiyoe; Kodama, Miho; Adachi, Noritaka

2015-06-30

Targeted gene modification by homologous recombination provides a powerful tool for studying gene function in cells and animals. In higher eukaryotes, non-homologous integration of targeting vectors occurs several orders of magnitude more frequently than does targeted integration, making the gene-targeting technology highly inefficient. For this reason, negative-selection strategies have been employed to reduce the number of drug-resistant clones associated with non-homologous vector integration, particularly when artificial nucleases to introduce a DNA break at the target site are unavailable or undesirable. As such, an exon-trap strategy using a promoterless drug-resistance marker gene provides an effective way to counterselect non-homologous integrants. However, constructing exon-trapping targeting vectors has been a time-consuming and complicated process. By virtue of highly efficient att-mediated recombination, we successfully developed a simple and rapid method to construct plasmid-based vectors that allow for exon-trapping gene targeting. These exon-trap vectors were useful in obtaining correctly targeted clones in mouse embryonic stem cells and human HT1080 cells. Most importantly, with the use of a conditionally cytotoxic gene, we further developed a novel strategy for negative selection, thereby enhancing the efficiency of counterselection for non-homologous integration of exon-trap vectors. Our methods will greatly facilitate exon-trapping gene-targeting technologies in mammalian cells, particularly when combined with the novel negative selection strategy.

Summer Study Program in Geophysical Fluid Dynamics - The Influence of Convection on Large-Scale Circulations - 1988

DTIC Science & Technology

1989-07-01

the vector of the body force." lo., ,P /’P l> 16 __ __ _ __ ___P . 19 U In the first lecture we define the buoyancy force, develop a simplified...force and l’is a unit vector along the motion vector . Integrating Bernoulli’s law over a closed loop one gets: I also [ C by integrating along the...convection. It is conveiient to write these equations as evolution equations for a atate vector U(x, z, t) where x is the horizontal coordinate vector

Condition Assessment of Foundation Piles and Utility Poles Based on Guided Wave Propagation Using a Network of Tactile Transducers and Support Vector Machines

PubMed Central

Yu, Yang; Niederleithinger, Ernst; Li, Jianchun; Wiggenhauser, Herbert

2017-01-01

This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%. PMID:29258274

A vectorized algorithm for 3D dynamics of a tethered satellite

NASA Technical Reports Server (NTRS)

Wilson, Howard B.

1989-01-01

Equations of motion characterizing the three dimensional motion of a tethered satellite during the retrieval phase are studied. The mathematical model involves an arbitrary number of point masses connected by weightless cords. Motion occurs in a gravity gradient field. The formulation presented accounts for general functions describing support point motion, rate of tether retrieval, and arbitrary forces applied to the point masses. The matrix oriented program language MATLAB is used to produce an efficient vectorized formulation for computing natural frequencies and mode shapes for small oscillations about the static equilibrium configuration; and for integrating the nonlinear differential equations governing large amplitude motions. An example of time response pertaining to the skip rope effect is investigated.

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.

Tissue multifractality and hidden Markov model based integrated framework for optimum precancer detection

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sabyasachi; Das, Nandan K.; Kurmi, Indrajit; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2017-10-01

We report the application of a hidden Markov model (HMM) on multifractal tissue optical properties derived via the Born approximation-based inverse light scattering method for effective discrimination of precancerous human cervical tissue sites from the normal ones. Two global fractal parameters, generalized Hurst exponent and the corresponding singularity spectrum width, computed by multifractal detrended fluctuation analysis (MFDFA), are used here as potential biomarkers. We develop a methodology that makes use of these multifractal parameters by integrating with different statistical classifiers like the HMM and support vector machine (SVM). It is shown that the MFDFA-HMM integrated model achieves significantly better discrimination between normal and different grades of cancer as compared to the MFDFA-SVM integrated model.

Integration of adeno-associated virus vectors in CD34+ human hematopoietic progenitor cells after transduction.

PubMed

Fisher-Adams, G; Wong, K K; Podsakoff, G; Forman, S J; Chatterjee, S

1996-07-15

Gene transfer vectors based on adeno-associated virus (AAV) appear promising because of their high transduction frequencies regardless of cell cycle status and ability to integrate into chromosomal DNA. We tested AAV-mediated gene transfer into a panel of human bone marrow or umbilical cord-derived CD34+ hematopoietic progenitor cells, using vectors encoding several transgenes under the control of viral and cellular promoters. Gene transfer was evaluated by (1) chromosomal integration of vector sequences and (2) analysis of transgene expression. Southern hybridization and fluorescence in situ hybridization analysis of transduced CD34 genomic DNA showed the presence of integrated vector sequences in chromosomal DNA in a portion of transduced cells and showed that integrated vector sequences were replicated along with cellular DNA during mitosis. Transgene expression in transduced CD34 cells in suspension cultures and in myeloid colonies differentiating in vitro from transduced CD34 cells approximated that predicted by the multiplicity of transduction. This was true in CD34 cells from different donors, regardless of the transgene or selective pressure. Comparisons of CD34 cell transduction either before or after cytokine stimulation showed similar gene transfer frequencies. Our findings suggest that AAV transduction of CD34+ hematopoietic progenitor cells is efficient, can lead to stable integration in a population of transduced cells, and may therefore provide the basis for safe and efficient ex vivo gene therapy of the hematopoietic system.

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

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Optimal distribution of integration time for intensity measurements in Stokes polarimetry.

PubMed

Li, Xiaobo; Liu, Tiegen; Huang, Bingjing; Song, Zhanjie; Hu, Haofeng

2015-10-19

We consider the typical Stokes polarimetry system, which performs four intensity measurements to estimate a Stokes vector. We show that if the total integration time of intensity measurements is fixed, the variance of the Stokes vector estimator depends on the distribution of the integration time at four intensity measurements. Therefore, by optimizing the distribution of integration time, the variance of the Stokes vector estimator can be decreased. In this paper, we obtain the closed-form solution of the optimal distribution of integration time by employing Lagrange multiplier method. According to the theoretical analysis and real-world experiment, it is shown that the total variance of the Stokes vector estimator can be significantly decreased about 40% in the case discussed in this paper. The method proposed in this paper can effectively decrease the measurement variance and thus statistically improves the measurement accuracy of the polarimetric system.

Horizontal vectorization of electron repulsion integrals.

PubMed

Pritchard, Benjamin P; Chow, Edmond

2016-10-30

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

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.

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.

Towards the Development of an Automated Learning Assistant for Vector Calculus: Integration over Planar Regions

ERIC Educational Resources Information Center

Yaacob, Yuzita; Wester, Michael; Steinberg, Stanly

2010-01-01

This paper presents a prototype of a computer learning assistant ILMEV (Interactive Learning-Mathematica Enhanced Vector calculus) package with the purpose of helping students to understand the theory and applications of integration in vector calculus. The main problem for students using Mathematica is to convert a textbook description of a…

VectorBase: a home for invertebrate vectors of human pathogens

PubMed Central

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

2007-01-01

VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever. PMID:17145709

Optimizing Performance of Combustion Chemistry Solvers on Intel's Many Integrated Core (MIC) Architectures

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

Sitaraman, Hariswaran; Grout, Ray W

This work investigates novel algorithm designs and optimization techniques for restructuring chemistry integrators in zero and multidimensional combustion solvers, which can then be effectively used on the emerging generation of Intel's Many Integrated Core/Xeon Phi processors. These processors offer increased computing performance via large number of lightweight cores at relatively lower clock speeds compared to traditional processors (e.g. Intel Sandybridge/Ivybridge) used in current supercomputers. This style of processor can be productively used for chemistry integrators that form a costly part of computational combustion codes, in spite of their relatively lower clock speeds. Performance commensurate with traditional processors is achieved heremore » through the combination of careful memory layout, exposing multiple levels of fine grain parallelism and through extensive use of vendor supported libraries (Cilk Plus and Math Kernel Libraries). Important optimization techniques for efficient memory usage and vectorization have been identified and quantified. These optimizations resulted in a factor of ~ 3 speed-up using Intel 2013 compiler and ~ 1.5 using Intel 2017 compiler for large chemical mechanisms compared to the unoptimized version on the Intel Xeon Phi. The strategies, especially with respect to memory usage and vectorization, should also be beneficial for general purpose computational fluid dynamics codes.« less

Global Status of DDT and Its Alternatives for Use in Vector Control to Prevent Disease

PubMed Central

van den Berg, Henk

2009-01-01

Objective I review the status of dichlorodiphenyltrichloroethane (DDT), used for disease vector control, along with current evidence on its benefits and risks in relation to the available alternatives. Data sources and extraction Contemporary data on DDT use were largely obtained from questionnaires and reports. I also conducted a Scopus search to retrieve published articles. Data synthesis DDT has been recommended as part of the arsenal of insecticides available for indoor residual spraying until suitable alternatives are available. Approximately 14 countries use DDT for disease control, and several countries are preparing to reintroduce DDT. The effectiveness of DDT depends on local settings and merits close consideration in relation to the alternatives. Concerns about the continued use of DDT are fueled by recent reports of high levels of human exposure associated with indoor spraying amid accumulating evidence on chronic health effects. There are signs that more malaria vectors are becoming resistant to the toxic action of DDT, and that resistance is spreading to new countries. A comprehensive cost assessment of DDT versus its alternatives that takes side effects into account is missing. Effective chemical methods are available as immediate alternatives to DDT, but the choice of insecticide class is limited, and in certain areas the development of resistance is undermining the efficacy of insecticidal tools. New insecticides are not expected in the short term. Nonchemical methods are potentially important, but their effectiveness at program level needs urgent study. Conclusions To reduce reliance on DDT, support is needed for integrated and multipartner strategies of vector control and for the continued development of new technologies. Integrated vector management provides a framework for developing and implementing effective technologies and strategies as sustainable alternatives to reliance on DDT. PMID:20049114

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.

A generalized nonlocal vector calculus

NASA Astrophysics Data System (ADS)

Alali, Bacim; Liu, Kuo; Gunzburger, Max

2015-10-01

A nonlocal vector calculus was introduced in Du et al. (Math Model Meth Appl Sci 23:493-540, 2013) that has proved useful for the analysis of the peridynamics model of nonlocal mechanics and nonlocal diffusion models. A formulation is developed that provides a more general setting for the nonlocal vector calculus that is independent of particular nonlocal models. It is shown that general nonlocal calculus operators are integral operators with specific integral kernels. General nonlocal calculus properties are developed, including nonlocal integration by parts formula and Green's identities. The nonlocal vector calculus introduced in Du et al. (Math Model Meth Appl Sci 23:493-540, 2013) is shown to be recoverable from the general formulation as a special example. This special nonlocal vector calculus is used to reformulate the peridynamics equation of motion in terms of the nonlocal gradient operator and its adjoint. A new example of nonlocal vector calculus operators is introduced, which shows the potential use of the general formulation for general nonlocal models.

Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators

PubMed Central

Alwee, Razana; Hj Shamsuddin, Siti Mariyam; Sallehuddin, Roselina

2013-01-01

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models. PMID:23766729

Hybrid support vector regression and autoregressive integrated moving average models improved by particle swarm optimization for property crime rates forecasting with economic indicators.

PubMed

Alwee, Razana; Shamsuddin, Siti Mariyam Hj; Sallehuddin, Roselina

2013-01-01

Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.

Integrating an infectious disease programme into the primary health care service: a retrospective analysis of Chagas disease community-based surveillance in Honduras.

PubMed

Hashimoto, Ken; Zúniga, Concepción; Nakamura, Jiro; Hanada, Kyo

2015-03-24

Integration of disease-specific programmes into the primary health care (PHC) service has been attempted mostly in clinically oriented disease control such as HIV/AIDS and tuberculosis but rarely in vector control. Chagas disease is controlled principally by interventions against the triatomine vector. In Honduras, after successful reduction of household infestation by vertical approach, the Ministry of Health implemented community-based vector surveillance at the PHC services (health centres) to prevent the resurgence of infection. This paper retrospectively analyses the effects and process of integrating a Chagas disease vector surveillance system into health centres. We evaluated the effects of integration at six pilot sites in western Honduras during 2008-2011 on; surveillance performance; knowledge, attitude and practice in schoolchildren; reports of triatomine bug infestation and institutional response; and seroprevalence among children under 15 years of age. The process of integration of the surveillance system was analysed using the PRECEDE-PROCEED model for health programme planning. The model was employed to systematically determine influential and interactive factors which facilitated the integration process at different levels of the Ministry of Health and the community. Overall surveillance performance improved from 46 to 84 on a 100 point-scale. Schoolchildren's attitude (risk awareness) score significantly increased from 77 to 83 points. Seroprevalence declined from 3.4% to 0.4%. Health centres responded to the community bug reports by insecticide spraying. As key factors, the health centres had potential management capacity and influence over the inhabitants' behaviours and living environment directly and through community health volunteers. The National Chagas Programme played an essential role in facilitating changes with adequate distribution of responsibilities, participatory modelling, training and, evaluation and advocacy. We found that Chagas disease vector surveillance can be integrated into the PHC service. Health centres demonstrated capacity to manage vector surveillance and improve performance, children's awareness, vector report-response and seroprevalence, once tasks were simplified to be performed by trained non-specialists and distributed among the stakeholders. Health systems integration requires health workers to perform beyond their usual responsibilities and acquire management skills. Integration of vector control is feasible and can contribute to strengthening the preventive capacity of the PHC service.

Site-specific integration of Streptomyces PhiC31 integrase-based vectors in the chromosome of Rhodococcus equi.

PubMed

Hong, Yang; Hondalus, Mary K

2008-10-01

Streptomyces PhiC31-based site-specific integration was used to transform the facultative intracellular pathogen Rhodococcus equi. The transformation efficiency of vectors incorporating the PhiC31 integrase and attP sites was comparable to that of replication plasmids using the same electroporation procedure. A single attB integration site was identified within an ORF encoding a pirin-like protein, which deviates slightly from the consensus sequence of Streptomyces attB sites. Vector integration was stably maintained in the R. equi chromosome for as many as 100 generations during unselected passage in vitro. In addition, integration does not appear to affect the replication of bacteria inside macrophages. Finally, this integration system was also used to successfully complement an R. equi mutant.

Integrated vector management for malaria control

PubMed Central

Beier, John C; Keating, Joseph; Githure, John I; Macdonald, Michael B; Impoinvil, Daniel E; Novak, Robert J

2008-01-01

Integrated vector management (IVM) is defined as "a rational decision-making process for the optimal use of resources for vector control" and includes five key elements: 1) evidence-based decision-making, 2) integrated approaches 3), collaboration within the health sector and with other sectors, 4) advocacy, social mobilization, and legislation, and 5) capacity-building. In 2004, the WHO adopted IVM globally for the control of all vector-borne diseases. Important recent progress has been made in developing and promoting IVM for national malaria control programmes in Africa at a time when successful malaria control programmes are scaling-up with insecticide-treated nets (ITN) and/or indoor residual spraying (IRS) coverage. While interventions using only ITNs and/or IRS successfully reduce transmission intensity and the burden of malaria in many situations, it is not clear if these interventions alone will achieve those critical low levels that result in malaria elimination. Despite the successful employment of comprehensive integrated malaria control programmes, further strengthening of vector control components through IVM is relevant, especially during the "end-game" where control is successful and further efforts are required to go from low transmission situations to sustained local and country-wide malaria elimination. To meet this need and to ensure sustainability of control efforts, malaria control programmes should strengthen their capacity to use data for decision-making with respect to evaluation of current vector control programmes, employment of additional vector control tools in conjunction with ITN/IRS tactics, case-detection and treatment strategies, and determine how much and what types of vector control and interdisciplinary input are required to achieve malaria elimination. Similarly, on a global scale, there is a need for continued research to identify and evaluate new tools for vector control that can be integrated with existing biomedical strategies within national malaria control programmes. This review provides an overview of how IVM programmes are being implemented, and provides recommendations for further development of IVM to meet the goals of national malaria control programmes in Africa. PMID:19091038

Artificial Lighting as a Vector Attractant and Cause of Disease Diffusion

PubMed Central

Barghini, Alessandro; de Medeiros, Bruno A. S.

2010-01-01

Background Traditionally, epidemiologists have considered electrification to be a positive factor. In fact, electrification and plumbing are typical initiatives that represent the integration of an isolated population into modern society, ensuring the control of pathogens and promoting public health. Nonetheless, electrification is always accompanied by night lighting that attracts insect vectors and changes people’s behavior. Although this may lead to new modes of infection and increased transmission of insect-borne diseases, epidemiologists rarely consider the role of night lighting in their surveys. Objective We reviewed the epidemiological evidence concerning the role of lighting in the spread of vector-borne diseases to encourage other researchers to consider it in future studies. Discussion We present three infectious vector-borne diseases—Chagas, leishmaniasis, and malaria—and discuss evidence that suggests that the use of artificial lighting results in behavioral changes among human populations and changes in the prevalence of vector species and in the modes of transmission. Conclusion Despite a surprising lack of studies, existing evidence supports our hypothesis that artificial lighting leads to a higher risk of infection from vector-borne diseases. We believe that this is related not only to the simple attraction of traditional vectors to light sources but also to changes in the behavior of both humans and insects that result in new modes of disease transmission. Considering the ongoing expansion of night lighting in developing countries, additional research on this subject is urgently needed. PMID:20675268

Proper Conformal Killing Vectors in Kantowski-Sachs Metric

NASA Astrophysics Data System (ADS)

Hussain, Tahir; Farhan, Muhammad

2018-04-01

This paper deals with the existence of proper conformal Killing vectors (CKVs) in Kantowski-Sachs metric. Subject to some integrability conditions, the general form of vector filed generating CKVs and the conformal factor is presented. The integrability conditions are solved generally as well as in some particular cases to show that the non-conformally flat Kantowski-Sachs metric admits two proper CKVs, while it admits a 15-dimensional Lie algebra of CKVs in the case when it becomes conformally flat. The inheriting conformal Killing vectors (ICKVs), which map fluid lines conformally, are also investigated.

Robust support vector regression networks for function approximation with outliers.

PubMed

Chuang, Chen-Chia; Su, Shun-Feng; Jeng, Jin-Tsong; Hsiao, Chih-Ching

2002-01-01

Support vector regression (SVR) employs the support vector machine (SVM) to tackle problems of function approximation and regression estimation. SVR has been shown to have good robust properties against noise. When the parameters used in SVR are improperly selected, overfitting phenomena may still occur. However, the selection of various parameters is not straightforward. Besides, in SVR, outliers may also possibly be taken as support vectors. Such an inclusion of outliers in support vectors may lead to seriously overfitting phenomena. In this paper, a novel regression approach, termed as the robust support vector regression (RSVR) network, is proposed to enhance the robust capability of SVR. In the approach, traditional robust learning approaches are employed to improve the learning performance for any selected parameters. From the simulation results, our RSVR can always improve the performance of the learned systems for all cases. Besides, it can be found that even the training lasted for a long period, the testing errors would not go up. In other words, the overfitting phenomenon is indeed suppressed.

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

PubMed

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

2013-01-01

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

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.

Fluorescent tagged episomals for stoichiometric induced pluripotent stem cell reprogramming.

PubMed

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

2017-06-05

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

A hybrid least squares support vector machines and GMDH approach for river flow forecasting

NASA Astrophysics Data System (ADS)

Samsudin, R.; Saad, P.; Shabri, A.

2010-06-01

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

Distributed support vector machine in master-slave mode.

PubMed

Chen, Qingguo; Cao, Feilong

2018-05-01

It is well known that the support vector machine (SVM) is an effective learning algorithm. The alternating direction method of multipliers (ADMM) algorithm has emerged as a powerful technique for solving distributed optimisation models. This paper proposes a distributed SVM algorithm in a master-slave mode (MS-DSVM), which integrates a distributed SVM and ADMM acting in a master-slave configuration where the master node and slave nodes are connected, meaning the results can be broadcasted. The distributed SVM is regarded as a regularised optimisation problem and modelled as a series of convex optimisation sub-problems that are solved by ADMM. Additionally, the over-relaxation technique is utilised to accelerate the convergence rate of the proposed MS-DSVM. Our theoretical analysis demonstrates that the proposed MS-DSVM has linear convergence, meaning it possesses the fastest convergence rate among existing standard distributed ADMM algorithms. Numerical examples demonstrate that the convergence and accuracy of the proposed MS-DSVM are superior to those of existing methods under the ADMM framework. Copyright © 2018 Elsevier Ltd. All rights reserved.

Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm.

PubMed

Mao, Yong; Zhou, Xiao-Bo; Pi, Dao-Ying; Sun, You-Xian; Wong, Stephen T C

2005-10-01

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear statistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two representative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method performs well in selecting genes and achieves high classification accuracies with these genes.

Dissociable cognitive mechanisms underlying human path integration.

PubMed

Wiener, Jan M; Berthoz, Alain; Wolbers, Thomas

2011-01-01

Path integration is a fundamental mechanism of spatial navigation. In non-human species, it is assumed to be an online process in which a homing vector is updated continuously during an outward journey. In contrast, human path integration has been conceptualized as a configural process in which travelers store working memory representations of path segments, with the computation of a homing vector only occurring when required. To resolve this apparent discrepancy, we tested whether humans can employ different path integration strategies in the same task. Using a triangle completion paradigm, participants were instructed either to continuously update the start position during locomotion (continuous strategy) or to remember the shape of the outbound path and to calculate home vectors on basis of this representation (configural strategy). While overall homing accuracy was superior in the configural condition, participants were quicker to respond during continuous updating, strongly suggesting that homing vectors were computed online. Corroborating these findings, we observed reliable differences in head orientation during the outbound path: when participants applied the continuous updating strategy, the head deviated significantly from straight ahead in direction of the start place, which can be interpreted as a continuous motor expression of the homing vector. Head orientation-a novel online measure for path integration-can thus inform about the underlying updating mechanism already during locomotion. In addition to demonstrating that humans can employ different cognitive strategies during path integration, our two-systems view helps to resolve recent controversies regarding the role of the medial temporal lobe in human path integration.

Lentiviral Vector Induced Insertional Haploinsufficiency of Ebf1 Causes Murine Leukemia

PubMed Central

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

2012-01-01

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

KISTI at TREC 2014 Clinical Decision Support Track: Concept-based Document Re-ranking to Biomedical Information Retrieval

DTIC Science & Technology

2014-11-01

sematic type. Injury or Poisoning inpo T037 Anatomical Abnormality anab T190 Given a document D, a concept vector = {1, 2, … , ...integrating biomedical terminology . Nucleic acids research 32, Database issue (2004), 267–270. 5. Chapman, W.W., Hillert, D., Velupillai, S., et...Conference (TREC), (2011). 9. Koopman, B. and Zuccon, G. Understanding negation and family history to improve clinical information retrieval. Proceedings

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

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

Koulouri, Alexandra, E-mail: koulouri@uni-muenster.de; Department of Electrical and Electronic Engineering, Imperial College London, Exhibition Road, London SW7 2BT; Brookes, Mike

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

Cost-effectiveness of environmental management for vector control in resource development projects.

PubMed

Bos, R

1991-01-01

Vector control methods are traditionally divided in chemical, biological and environmental management approaches, and this distinction also reflected in certain financial and economic aspects. This is particularly true for environmental modification, usually engineering or other structural works. It is highly capital intensive, as opposed to chemical and biological control which require recurrent expenditures, and discount rates are therefore a prominent consideration in deciding for one or the other approach. Environmental manipulation requires recurrent action, but can often be carried out with the community participation, which raises the issue of opportunity costs. The incorporation of environmental management in resource projects is generally impeded by economic considerations. The Internal Rate of Return continues to be a crucial criterion for funding agencies and development banks to support new projects; at the same time Governments of debt-riden countries in the Third World will do their best to avoid additional loans on such frills as environmental and health safeguards. Two approaches can be recommended to nevertheless ensure the incorporation of environmental management measures in resource projects in an affordable way. First, there are several examples of cases where environmental management measures either have a dual benefit (increasing both agricultural production and reducing vector-borne disease transmission) or can be implemented at zero costs. Second, the additional costs involved in structural modifications can be separated from the project development costs considered in the calculations of the Internal Rate of Return, and financial support can be sought from bilateral technical cooperation agencies particularly interested in environmental and health issues. There is a dearth of information in the cost-effectiveness of alternative vector control strategies in the developing country context. The process of integrating vector control in the general health services will make it even more difficult to gain a clear insight in the matter.

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

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

PubMed

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

2007-07-01

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

TWSVR: Regression via Twin Support Vector Machine.

PubMed

Khemchandani, Reshma; Goyal, Keshav; Chandra, Suresh

2016-02-01

Taking motivation from Twin Support Vector Machine (TWSVM) formulation, Peng (2010) attempted to propose Twin Support Vector Regression (TSVR) where the regressor is obtained via solving a pair of quadratic programming problems (QPPs). In this paper we argue that TSVR formulation is not in the true spirit of TWSVM. Further, taking motivation from Bi and Bennett (2003), we propose an alternative approach to find a formulation for Twin Support Vector Regression (TWSVR) which is in the true spirit of TWSVM. We show that our proposed TWSVR can be derived from TWSVM for an appropriately constructed classification problem. To check the efficacy of our proposed TWSVR we compare its performance with TSVR and classical Support Vector Regression(SVR) on various regression datasets. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

Human Induced Pluripotent Stem Cells Free of Vector and Transgene Sequences

PubMed Central

Yu, Junying; Hu, Kejin; Smuga-Otto, Kim; Tian, Shulan; Stewart, Ron; Slukvin, Igor I.; Thomson, James A.

2009-01-01

Reprogramming differentiated human cells to induced pluripotent stem (iPS) cells has applications in basic biology, drug development, and transplantation. Human iPS cell derivation previously required vectors that integrate into the genome, which can create mutations and limit the utility of the cells in both research and clinical applications. Here we describe the derivation of human iPS cells using non-integrating episomal vectors. After removal of the episome, iPS cells completely free of vector and transgene sequences are derived that are similar to human embryonic stem (ES) cells in proliferative and developmental potential. These results demonstrate that reprogramming human somatic cells does not require genomic integration or the continued presence of exogenous reprogramming factors, and removes one obstacle to the clinical application of human iPS cells. PMID:19325077

Cytokine-independent growth and clonal expansion of a primary human CD8+ T-cell clone following retroviral transduction with the IL-15 gene

PubMed Central

Hsu, Cary; Jones, Stephanie A.; Cohen, Cyrille J.; Zheng, Zhili; Kerstann, Keith; Zhou, Juhua; Robbins, Paul F.; Peng, Peter D.; Shen, Xinglei; Gomes, Theotonius J.; Dunbar, Cynthia E.; Munroe, David J.; Stewart, Claudia; Cornetta, Kenneth; Wangsa, Danny; Ried, Thomas; Rosenberg, Steven A.

2007-01-01

Malignancies arising from retrovirally transduced hematopoietic stem cells have been reported in animal models and human gene therapy trials. Whether mature lymphocytes are susceptible to insertional mutagenesis is unknown. We have characterized a primary human CD8+ T-cell clone, which exhibited logarithmic ex vivo growth in the absence of exogenous cytokine support for more than 1 year after transduction with a murine leukemia virus–based vector encoding the T-cell growth factor IL-15. Phenotypically, the clone was CD28−, CD45RA−, CD45RO+, and CD62L−, a profile consistent with effector memory T lymphocytes. After gene transfer with tumor-antigen–specific T-cell receptors, the clone secreted IFN-γ upon encountering tumor targets, providing further evidence that they derived from mature lymphocytes. Gene-expression analyses revealed no evidence of insertional activation of genes flanking the retroviral insertion sites. The clone exhibited constitutive telomerase activity, and the presence of autocrine loop was suggested by impaired cell proliferation following knockdown of IL-15Rα expression. The generation of this cell line suggests that nonphysiologic expression of IL-15 can result in the long-term in vitro growth of mature human T lymphocytes. The cytokine-independent growth of this line was a rare event that has not been observed in other IL-15 vector transduction experiments or with any other integrating vector system. It does not appear that the retroviral vector integration sites played a role in the continuous growth of this cell clone, but this remains under investigation. PMID:17353346

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks

PubMed Central

Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-01-01

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network. PMID:29267252

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

PubMed

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

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

NASA Astrophysics Data System (ADS)

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

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

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.

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

PubMed Central

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

2014-01-01

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

Parallel/Vector Integration Methods for Dynamical Astronomy

NASA Astrophysics Data System (ADS)

Fukushima, T.

Progress of parallel/vector computers has driven us to develop suitable numerical integrators utilizing their computational power to the full extent while being independent on the size of system to be integrated. Unfortunately, the parallel version of Runge-Kutta type integrators are known to be not so efficient. Recently we developed a parallel version of the extrapolation method (Ito and Fukushima 1997), which allows variable timesteps and still gives an acceleration factor of 3-4 for general problems. While the vector-mode usage of Picard-Chebyshev method (Fukushima 1997a, 1997b) will lead the acceleration factor of order of 1000 for smooth problems such as planetary/satellites orbit integration. The success of multiple-correction PECE mode of time-symmetric implicit Hermitian integrator (Kokubo 1998) seems to enlighten Milankar's so-called "pipelined predictor corrector method", which is expected to lead an acceleration factor of 3-4. We will review these directions and discuss future prospects.

Integration of narrow-host-range vectors from Escherichia coli into the genomes of amino acid-producing corynebacteria after intergeneric conjugation.

PubMed

Mateos, L M; Schäfer, A; Kalinowski, J; Martin, J F; Pühler, A

1996-10-01

Conjugative transfer of mobilizable derivatives of the Escherichia coli narrow-host-range plasmids pBR322, pBR325, pACYC177, and pACYC184 from E. coli to species of the gram-positive genera Corynebacterium and Brevibacterium resulted in the integration of the plasmids into the genomes of the recipient bacteria. Transconjugants appeared at low frequencies and reproducibly with a delay of 2 to 3 days compared with matings with replicative vectors. Southern analysis of corynebacterial transconjugants and nucleotide sequences from insertion sites revealed that integration occurs at different locations and that different parts of the vector are involved in the process. Integration is not dependent on indigenous insertion sequence elements but results from recombination between very short homologous DNA segments (8 to 12 bp) present in the vector and in the host DNA. In the majority of the cases (90%), integration led to cointegrate formation, and in some cases, deletions or rearrangements occurred during the recombination event. Insertions were found to be quite stable even in the absence of selective pressure.

Integration of narrow-host-range vectors from Escherichia coli into the genomes of amino acid-producing corynebacteria after intergeneric conjugation.

PubMed Central

Mateos, L M; Schäfer, A; Kalinowski, J; Martin, J F; Pühler, A

1996-01-01

Conjugative transfer of mobilizable derivatives of the Escherichia coli narrow-host-range plasmids pBR322, pBR325, pACYC177, and pACYC184 from E. coli to species of the gram-positive genera Corynebacterium and Brevibacterium resulted in the integration of the plasmids into the genomes of the recipient bacteria. Transconjugants appeared at low frequencies and reproducibly with a delay of 2 to 3 days compared with matings with replicative vectors. Southern analysis of corynebacterial transconjugants and nucleotide sequences from insertion sites revealed that integration occurs at different locations and that different parts of the vector are involved in the process. Integration is not dependent on indigenous insertion sequence elements but results from recombination between very short homologous DNA segments (8 to 12 bp) present in the vector and in the host DNA. In the majority of the cases (90%), integration led to cointegrate formation, and in some cases, deletions or rearrangements occurred during the recombination event. Insertions were found to be quite stable even in the absence of selective pressure. PMID:8824624

Recognizing human activities using appearance metric feature and kinematics feature

NASA Astrophysics Data System (ADS)

Qian, Huimin; Zhou, Jun; Lu, Xinbiao; Wu, Xinye

2017-05-01

The problem of automatically recognizing human activities from videos through the fusion of the two most important cues, appearance metric feature and kinematics feature, is considered. And a system of two-dimensional (2-D) Poisson equations is introduced to extract the more discriminative appearance metric feature. Specifically, the moving human blobs are first detected out from the video by background subtraction technique to form a binary image sequence, from which the appearance feature designated as the motion accumulation image and the kinematics feature termed as centroid instantaneous velocity are extracted. Second, 2-D discrete Poisson equations are employed to reinterpret the motion accumulation image to produce a more differentiated Poisson silhouette image, from which the appearance feature vector is created through the dimension reduction technique called bidirectional 2-D principal component analysis, considering the balance between classification accuracy and time consumption. Finally, a cascaded classifier based on the nearest neighbor classifier and two directed acyclic graph support vector machine classifiers, integrated with the fusion of the appearance feature vector and centroid instantaneous velocity vector, is applied to recognize the human activities. Experimental results on the open databases and a homemade one confirm the recognition performance of the proposed algorithm.

Integrating vector control across diseases.

PubMed

Golding, Nick; Wilson, Anne L; Moyes, Catherine L; Cano, Jorge; Pigott, David M; Velayudhan, Raman; Brooker, Simon J; Smith, David L; Hay, Simon I; Lindsay, Steve W

2015-10-01

Vector-borne diseases cause a significant proportion of the overall burden of disease across the globe, accounting for over 10 % of the burden of infectious diseases. Despite the availability of effective interventions for many of these diseases, a lack of resources prevents their effective control. Many existing vector control interventions are known to be effective against multiple diseases, so combining vector control programmes to simultaneously tackle several diseases could offer more cost-effective and therefore sustainable disease reductions. The highly successful cross-disease integration of vaccine and mass drug administration programmes in low-resource settings acts a precedent for cross-disease vector control. Whilst deliberate implementation of vector control programmes across multiple diseases has yet to be trialled on a large scale, a number of examples of 'accidental' cross-disease vector control suggest the potential of such an approach. Combining contemporary high-resolution global maps of the major vector-borne pathogens enables us to quantify overlap in their distributions and to estimate the populations jointly at risk of multiple diseases. Such an analysis shows that over 80 % of the global population live in regions of the world at risk from one vector-borne disease, and more than half the world's population live in areas where at least two different vector-borne diseases pose a threat to health. Combining information on co-endemicity with an assessment of the overlap of vector control methods effective against these diseases allows us to highlight opportunities for such integration. Malaria, leishmaniasis, lymphatic filariasis, and dengue are prime candidates for combined vector control. All four of these diseases overlap considerably in their distributions and there is a growing body of evidence for the effectiveness of insecticide-treated nets, screens, and curtains for controlling all of their vectors. The real-world effectiveness of cross-disease vector control programmes can only be evaluated by large-scale trials, but there is clear evidence of the potential of such an approach to enable greater overall health benefit using the limited funds available.

High-efficiency Transduction of Rhesus Hematopoietic Repopulating Cells by a Modified HIV1-based Lentiviral Vector

PubMed Central

Uchida, Naoya; Hargrove, Phillip W.; Lap, Coen J.; Evans, Molly E.; Phang, Oswald; Bonifacino, Aylin C.; Krouse, Allen E.; Metzger, Mark E.; Nguyen, Anh-Dao; Hsieh, Matthew M.; Wolfsberg, Tyra G.; Donahue, Robert E.; Persons, Derek A.; Tisdale, John F.

2012-01-01

Human immunodeficiency virus type 1 (HIV1) vectors poorly transduce rhesus hematopoietic cells due to species-specific restriction factors, including the tripartite motif-containing 5 isoformα (TRIM5α) which targets the HIV1 capsid. We previously developed a chimeric HIV1 (χHIV) vector system wherein the vector genome is packaged with the simian immunodeficiency virus (SIV) capsid for efficient transduction of both rhesus and human CD34+ cells. To evaluate whether χHIV vectors could efficiently transduce rhesus hematopoietic repopulating cells, we performed a competitive repopulation assay in rhesus macaques, in which half of the CD34+ cells were transduced with standard SIV vectors and the other half with χHIV vectors. As compared with SIV vectors, χHIV vectors achieved higher vector integration, and the transgene expression rates were two- to threefold higher in granulocytes and red blood cells and equivalent in lymphocytes and platelets for 2 years. A recipient of χHIV vector-only transduced cells reached up to 40% of transgene expression rates in granulocytes and lymphocytes and 20% in red blood cells. Similar to HIV1 and SIV vectors, χHIV vector frequently integrated into gene regions, especially into introns. In summary, our χHIV vector demonstrated efficient transduction for rhesus long-term repopulating cells, comparable with SIV vectors. This χHIV vector should allow preclinical testing of HIV1-based therapeutic vectors in large animal models. PMID:22871664

Mathematical Methods for Physics and Engineering Third Edition Paperback Set

NASA Astrophysics Data System (ADS)

Riley, Ken F.; Hobson, Mike P.; Bence, Stephen J.

2006-06-01

Prefaces; 1. Preliminary algebra; 2. Preliminary calculus; 3. Complex numbers and hyperbolic functions; 4. Series and limits; 5. Partial differentiation; 6. Multiple integrals; 7. Vector algebra; 8. Matrices and vector spaces; 9. Normal modes; 10. Vector calculus; 11. Line, surface and volume integrals; 12. Fourier series; 13. Integral transforms; 14. First-order ordinary differential equations; 15. Higher-order ordinary differential equations; 16. Series solutions of ordinary differential equations; 17. Eigenfunction methods for differential equations; 18. Special functions; 19. Quantum operators; 20. Partial differential equations: general and particular; 21. Partial differential equations: separation of variables; 22. Calculus of variations; 23. Integral equations; 24. Complex variables; 25. Application of complex variables; 26. Tensors; 27. Numerical methods; 28. Group theory; 29. Representation theory; 30. Probability; 31. Statistics; Index.

Novel Hybrid of LS-SVM and Kalman Filter for GPS/INS Integration

NASA Astrophysics Data System (ADS)

Xu, Zhenkai; Li, Yong; Rizos, Chris; Xu, Xiaosu

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies can overcome the drawbacks of the individual systems. One of the advantages is that the integrated solution can provide continuous navigation capability even during GPS outages. However, bridging the GPS outages is still a challenge when Micro-Electro-Mechanical System (MEMS) inertial sensors are used. Methods being currently explored by the research community include applying vehicle motion constraints, optimal smoother, and artificial intelligence (AI) techniques. In the research area of AI, the neural network (NN) approach has been extensively utilised up to the present. In an NN-based integrated system, a Kalman filter (KF) estimates position, velocity and attitude errors, as well as the inertial sensor errors, to output navigation solutions while GPS signals are available. At the same time, an NN is trained to map the vehicle dynamics with corresponding KF states, and to correct INS measurements when GPS measurements are unavailable. To achieve good performance it is critical to select suitable quality and an optimal number of samples for the NN. This is sometimes too rigorous a requirement which limits real world application of NN-based methods.The support vector machine (SVM) approach is based on the structural risk minimisation principle, instead of the minimised empirical error principle that is commonly implemented in an NN. The SVM can avoid local minimisation and over-fitting problems in an NN, and therefore potentially can achieve a higher level of global performance. This paper focuses on the least squares support vector machine (LS-SVM), which can solve highly nonlinear and noisy black-box modelling problems. This paper explores the application of the LS-SVM to aid the GPS/INS integrated system, especially during GPS outages. The paper describes the principles of the LS-SVM and of the KF hybrid method, and introduces the LS-SVM regression algorithm. Field test data is processed to evaluate the performance of the proposed approach.

Signal detection using support vector machines in the presence of ultrasonic speckle

NASA Astrophysics Data System (ADS)

Kotropoulos, Constantine L.; Pitas, Ioannis

2002-04-01

Support Vector Machines are a general algorithm based on guaranteed risk bounds of statistical learning theory. They have found numerous applications, such as in classification of brain PET images, optical character recognition, object detection, face verification, text categorization and so on. In this paper we propose the use of support vector machines to segment lesions in ultrasound images and we assess thoroughly their lesion detection ability. We demonstrate that trained support vector machines with a Radial Basis Function kernel segment satisfactorily (unseen) ultrasound B-mode images as well as clinical ultrasonic images.

A hypothetical learning trajectory for conceptualizing matrices as linear transformations

NASA Astrophysics Data System (ADS)

Andrews-Larson, Christine; Wawro, Megan; Zandieh, Michelle

2017-08-01

In this paper, we present a hypothetical learning trajectory (HLT) aimed at supporting students in developing flexible ways of reasoning about matrices as linear transformations in the context of introductory linear algebra. In our HLT, we highlight the integral role of the instructor in this development. Our HLT is based on the 'Italicizing N' task sequence, in which students work to generate, compose, and invert matrices that correspond to geometric transformations specified within the problem context. In particular, we describe the ways in which the students develop local transformation views of matrix multiplication (focused on individual mappings of input vectors to output vectors) and extend these local views to more global views in which matrices are conceptualized in terms of how they transform a space in a coordinated way.

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

Dayman, Ken J; Ade, Brian J; Weber, Charles F

High-dimensional, nonlinear function estimation using large datasets is a current area of interest in the machine learning community, and applications may be found throughout the analytical sciences, where ever-growing datasets are making more information available to the analyst. In this paper, we leverage the existing relevance vector machine, a sparse Bayesian version of the well-studied support vector machine, and expand the method to include integrated feature selection and automatic function shaping. These innovations produce an algorithm that is able to distinguish variables that are useful for making predictions of a response from variables that are unrelated or confusing. We testmore » the technology using synthetic data, conduct initial performance studies, and develop a model capable of making position-independent predictions of the coreaveraged burnup using a single specimen drawn randomly from a nuclear reactor core.« less

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

NASA Astrophysics Data System (ADS)

Lohe, M. A.

2018-06-01

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

Integrated vector management: a critical strategy for combating vector-borne diseases in South Sudan.

PubMed

Chanda, Emmanuel; Govere, John M; Macdonald, Michael B; Lako, Richard L; Haque, Ubydul; Baba, Samson P; Mnzava, Abraham

2013-10-25

Integrated vector management (IVM) based vector control is encouraged by the World Health Organization (WHO). However, operational experience with the IVM strategy has mostly come from countries with relatively well-established health systems and with malaria control focused programmes. Little is known about deployment of IVM for combating multiple vector-borne diseases in post-emergency settings, where delivery structures are less developed or absent. This manuscript reports on the feasibility of operational IVM for combating vector-borne diseases in South Sudan. A methodical review of published and unpublished documents on vector-borne diseases for South Sudan was conducted via systematic literature search of online electronic databases, Google Scholar, PubMed and WHO, using a combination of search terms. Additional, non-peer reviewed literature was examined for information related to the subject. South Sudan is among the heartlands of vector-borne diseases in the world, characterized by enormous infrastructure, human and financial resource constraints and a weak health system against an increasing number of refugees, returnees and internally displaced people. The presence of a multiplicity of vector-borne diseases in this post-conflict situation presents a unique opportunity to explore the potential of a rational IVM strategy for multiple disease control and optimize limited resource utilization, while maximizing the benefits and providing a model for countries in a similar situation. The potential of integrating vector-borne disease control is enormous in South Sudan. However, strengthened coordination, intersectoral collaboration and institutional and technical capacity for entomological monitoring and evaluation, including enforcement of appropriate legislation are crucial.

Integrated vector management: a critical strategy for combating vector-borne diseases in South Sudan

PubMed Central

2013-01-01

Background Integrated vector management (IVM) based vector control is encouraged by the World Health Organization (WHO). However, operational experience with the IVM strategy has mostly come from countries with relatively well-established health systems and with malaria control focused programmes. Little is known about deployment of IVM for combating multiple vector-borne diseases in post-emergency settings, where delivery structures are less developed or absent. This manuscript reports on the feasibility of operational IVM for combating vector-borne diseases in South Sudan. Case description A methodical review of published and unpublished documents on vector-borne diseases for South Sudan was conducted via systematic literature search of online electronic databases, Google Scholar, PubMed and WHO, using a combination of search terms. Additional, non-peer reviewed literature was examined for information related to the subject. Discussion South Sudan is among the heartlands of vector-borne diseases in the world, characterized by enormous infrastructure, human and financial resource constraints and a weak health system against an increasing number of refugees, returnees and internally displaced people. The presence of a multiplicity of vector-borne diseases in this post-conflict situation presents a unique opportunity to explore the potential of a rational IVM strategy for multiple disease control and optimize limited resource utilization, while maximizing the benefits and providing a model for countries in a similar situation. Conclusion The potential of integrating vector-borne disease control is enormous in South Sudan. However, strengthened coordination, intersectoral collaboration and institutional and technical capacity for entomological monitoring and evaluation, including enforcement of appropriate legislation are crucial. PMID:24156749

The geometric approach to sets of ordinary differential equations and Hamiltonian dynamics

NASA Technical Reports Server (NTRS)

Estabrook, F. B.; Wahlquist, H. D.

1975-01-01

The calculus of differential forms is used to discuss the local integration theory of a general set of autonomous first order ordinary differential equations. Geometrically, such a set is a vector field V in the space of dependent variables. Integration consists of seeking associated geometric structures invariant along V: scalar fields, forms, vectors, and integrals over subspaces. It is shown that to any field V can be associated a Hamiltonian structure of forms if, when dealing with an odd number of dependent variables, an arbitrary equation of constraint is also added. Families of integral invariants are an immediate consequence. Poisson brackets are isomorphic to Lie products of associated CT-generating vector fields. Hamilton's variational principle follows from the fact that the maximal regular integral manifolds of a closed set of forms must include the characteristics of the set.

Integrated optic vector-matrix multiplier

DOEpatents

Watts, Michael R [Albuquerque, NM

2011-09-27

A vector-matrix multiplier is disclosed which uses N different wavelengths of light that are modulated with amplitudes representing elements of an N.times.1 vector and combined to form an input wavelength-division multiplexed (WDM) light stream. The input WDM light stream is split into N streamlets from which each wavelength of the light is individually coupled out and modulated for a second time using an input signal representing elements of an M.times.N matrix, and is then coupled into an output waveguide for each streamlet to form an output WDM light stream which is detected to generate a product of the vector and matrix. The vector-matrix multiplier can be formed as an integrated optical circuit using either waveguide amplitude modulators or ring resonator amplitude modulators.

Scalar products of Bethe vectors in models with {\\mathfrak{gl}}(2| 1) symmetry 1. Super-analog of Reshetikhin formula

NASA Astrophysics Data System (ADS)

Hutsalyuk, A.; Liashyk, A.; Pakuliak, S. Z.; Ragoucy, E.; Slavnov, N. A.

2016-11-01

We study the scalar products of Bethe vectors in integrable models solvable by the nested algebraic Bethe ansatz and possessing {gl}(2| 1) symmetry. Using explicit formulas of the monodromy matrix entries’ multiple actions onto Bethe vectors we obtain a representation for the scalar product in the most general case. This explicit representation appears to be a sum over partitions of the Bethe parameters. It can be used for the analysis of scalar products involving on-shell Bethe vectors. As a by-product, we obtain a determinant representation for the scalar products of generic Bethe vectors in integrable models with {gl}(1| 1) symmetry. Dedicated to the memory of Petr Petrovich Kulish.

Expanding integrated vector management to promote healthy environments

PubMed Central

Lizzi, Karina M.; Qualls, Whitney A.; Brown, Scott C.; Beier, John C.

2014-01-01

Integrated Vector Management (IVM) strategies are intended to protect communities from pathogen transmission by arthropods. These strategies target multiple vectors and different ecological and socioeconomic settings, but the aggregate benefits of IVM are limited by the narrow focus of its approach; IVM strategies only aim to control arthropod vectors. We argue that IVM should encompass environmental modifications at early stages, for instance, infrastructural development and sanitation services, to regulate not only vectors but also nuisance-biting arthropods. An additional focus on nuisance-biting arthropods will improve public health, quality of life, and minimize social disparity issues fostered by pests. Optimally, IVM could incorporate environmental awareness and promotion of control methods in order to proactively reduce threats of serious pest situations. PMID:25028090

Optimal cue integration in ants.

PubMed

Wystrach, Antoine; Mangan, Michael; Webb, Barbara

2015-10-07

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

Lentiviral vectors encoding shRNAs efficiently transduce and knockdown LINGO-1 but induce an interferon response and cytotoxicity in CNS neurons

PubMed Central

Hutson, Thomas H.; Foster, Edmund; Dawes, John M.; Hindges, Robert; Yáñez-Muñoz, Rafael J.; Moon, Lawrence D.F.

2017-01-01

Background Knocking down neuronal LINGO-1 using short hairpin RNAs (shRNAs) might enhance axon regeneration in the CNS. Integration-deficient lentiviral vectors have great potential as a therapeutic delivery system for CNS injuries. However, recent studies have revealed that shRNAs can induce an interferon response resulting in off-target effects and cytotoxicity. Methods CNS neurons were transduced with integration-deficient lentiviral vectors in vitro. The transcriptional effect of shRNA expression was analysed using qRT-PCR and northern blots were used to assess shRNA production. Results Integration-deficient lentiviral vectors efficiently transduced CNS neurons and knocked down LINGO-1 mRNA in vitro. However, an increase in cell death was observed when lentiviral vectors encoding an shRNA were applied or when high vector concentrations were used. We demonstrate that high doses of vector or the use of vectors encoding shRNAs can induce an up-regulation of interferon stimulated genes (OAS1 and PKR) and a down-regulation of off- target genes (including p75NTR and NgR1). Furthermore, the northern blot demonstrated that these negative consequences occur even when lentiviral vectors express low levels of shRNAs. Together, these results may explain why neurite outgrowth was not enhanced on an inhibitory substrate after transduction with lentiviral vectors encoding an shRNA targeting LINGO-1. Conclusions These findings highlight the importance of including appropriate controls to verify silencing specificity and the requirement to check for an interferon response when conducting RNA interference experiments. However, the potential benefits that RNA interference and viral vectors offer to gene-based therapies to CNS injuries cannot be overlooked and demand further investigation. PMID:22499506

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine

PubMed Central

Pettersson-Yeo, William; Benetti, Stefania; Marquand, Andre F.; Joules, Richard; Catani, Marco; Williams, Steve C. R.; Allen, Paul; McGuire, Philip; Mechelli, Andrea

2014-01-01

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions. Here, we describe four integrative approaches: (1) an un-weighted sum of kernels, (2) multi-kernel learning, (3) prediction averaging, and (4) majority voting, and compare their ability to enhance classification accuracy relative to the best single-modality classification accuracy. We achieve this by integrating structural, functional, and diffusion tensor magnetic resonance imaging data, in order to compare ultra-high risk (n = 19), first episode psychosis (n = 19) and healthy control subjects (n = 23). Our results show that (i) whilst integration can enhance classification accuracy by up to 13%, the frequency of such instances may be limited, (ii) where classification can be enhanced, simple methods may yield greater increases relative to more computationally complex alternatives, and, (iii) the potential for classification enhancement is highly influenced by the specific diagnostic comparison under consideration. In conclusion, our findings suggest that for moderately sized clinical neuroimaging datasets, combining different imaging modalities in a data-driven manner is no “magic bullet” for increasing classification accuracy. However, it remains possible that this conclusion is dependent on the use of neuroimaging modalities that had little, or no, complementary information to offer one another, and that the integration of more diverse types of data would have produced greater classification enhancement. We suggest that future studies ideally examine a greater variety of data types (e.g., genetic, cognitive, and neuroimaging) in order to identify the data types and combinations optimally suited to the classification of early stage psychosis. PMID:25076868

An empirical comparison of different approaches for combining multimodal neuroimaging data with support vector machine.

PubMed

Pettersson-Yeo, William; Benetti, Stefania; Marquand, Andre F; Joules, Richard; Catani, Marco; Williams, Steve C R; Allen, Paul; McGuire, Philip; Mechelli, Andrea

2014-01-01

In the pursuit of clinical utility, neuroimaging researchers of psychiatric and neurological illness are increasingly using analyses, such as support vector machine, that allow inference at the single-subject level. Recent studies employing single-modality data, however, suggest that classification accuracies must be improved for such utility to be realized. One possible solution is to integrate different data types to provide a single combined output classification; either by generating a single decision function based on an integrated kernel matrix, or, by creating an ensemble of multiple single modality classifiers and integrating their predictions. Here, we describe four integrative approaches: (1) an un-weighted sum of kernels, (2) multi-kernel learning, (3) prediction averaging, and (4) majority voting, and compare their ability to enhance classification accuracy relative to the best single-modality classification accuracy. We achieve this by integrating structural, functional, and diffusion tensor magnetic resonance imaging data, in order to compare ultra-high risk (n = 19), first episode psychosis (n = 19) and healthy control subjects (n = 23). Our results show that (i) whilst integration can enhance classification accuracy by up to 13%, the frequency of such instances may be limited, (ii) where classification can be enhanced, simple methods may yield greater increases relative to more computationally complex alternatives, and, (iii) the potential for classification enhancement is highly influenced by the specific diagnostic comparison under consideration. In conclusion, our findings suggest that for moderately sized clinical neuroimaging datasets, combining different imaging modalities in a data-driven manner is no "magic bullet" for increasing classification accuracy. However, it remains possible that this conclusion is dependent on the use of neuroimaging modalities that had little, or no, complementary information to offer one another, and that the integration of more diverse types of data would have produced greater classification enhancement. We suggest that future studies ideally examine a greater variety of data types (e.g., genetic, cognitive, and neuroimaging) in order to identify the data types and combinations optimally suited to the classification of early stage psychosis.

Comparison of HIV- and EIAV-based vectors on their efficiency in transducing murine and human hematopoietic repopulating cells.

PubMed

Siapati, Elena K; Bigger, Brian W; Miskin, James; Chipchase, Daniel; Parsley, Kathryn L; Mitrophanous, Kyriacos; Themis, Mike; Thrasher, Adrian J; Bonnet, Dominique

2005-09-01

The use of lentiviral vectors for gene transfer into hematopoietic stem cells has raised considerable interest as these vectors can permanently integrate their genome into quiescent cells. Vectors based on alternative lentiviruses would theoretically be safer than HIV-1-based vectors and could also be used in HIV-positive patients, minimizing the risk of generating replication-competent virus. Here we report the use of third-generation equine infectious anemia virus (EIAV)- and HIV-1-based vectors with minimal viral sequences and absence of accessory proteins. We have compared their efficiency in transducing mouse and human hematopoietic stem cells both in vitro and in vivo to that of a previously documented second-generation HIV-1 vector. The third-generation EIAV- and HIV-based vectors gave comparable levels of transduction and transgene expression in both mouse and human NOD/SCID repopulating cells but were less efficient than the second-generation HIV-1 vector in human HSCs. For the EIAV vector this is possibly a reflection of the lower protein expression levels achieved in human cells, as vector copy number analysis revealed that this vector exhibited a trend to integrate equally efficiently compared to the third-generation HIV-1 vector in both mouse and human HSCs. Interestingly, the presence or absence of Tat in viral preparations did not influence the transduction efficiency of HIV-1 vectors in human HSCs.

A novel, broad-range, CTXΦ-derived stable integrative expression vector for functional studies.

PubMed

Das, Bhabatosh; Kumari, Reena; Pant, Archana; Sen Gupta, Sourav; Saxena, Shruti; Mehta, Ojasvi; Nair, Gopinath Balakrish

2014-12-01

CTXΦ, a filamentous vibriophage encoding cholera toxin, uses a unique strategy for its lysogeny. The single-stranded phage genome forms intramolecular base-pairing interactions between two inversely oriented XerC and XerD binding sites (XBS) and generates a functional phage attachment site, attP(+), for integration. The attP(+) structure is recognized by the host-encoded tyrosine recombinases XerC and XerD (XerCD), which enables irreversible integration of CTXΦ into the chromosome dimer resolution site (dif) of Vibrio cholerae. The dif site and the XerCD recombinases are widely conserved in bacteria. We took advantage of these conserved attributes to develop a broad-host-range integrative expression vector that could irreversibly integrate into the host chromosome using XerCD recombinases without altering the function of any known open reading frame (ORF). In this study, we engineered two different arabinose-inducible expression vectors, pBD62 and pBD66, using XBS of CTXΦ. pBD62 replicates conditionally and integrates efficiently into the dif of the bacterial chromosome by site-specific recombination using host-encoded XerCD recombinases. The expression level of the gene of interest could be controlled through the PBAD promoter by modulating the functions of the vector-encoded transcriptional factor AraC. We validated the irreversible integration of pBD62 into a wide range of pathogenic and nonpathogenic bacteria, such as V. cholerae, Vibrio fluvialis, Vibrio parahaemolyticus, Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae. Gene expression from the PBAD promoter of integrated vectors was confirmed in V. cholerae using the well-studied reporter genes mCherry, eGFP, and lacZ. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Meta-analysis of studies on chemical, physical and biological agents in the control of Aedes aegypti.

PubMed

Lima, Estelita Pereira; Goulart, Marília Oliveira Fonseca; Rolim Neto, Modesto Leite

2015-09-04

Aedes aegypti is a vector of international concern because it can transmit to humans three important arboviral diseases: yellow fever, dengue and chikungunya. Epidemics that are repeated year after year in a variety of urban centers indicate that there are control failures, allowing the vector to continue expanding. To identify the most effective vector control strategies and the factors that contributed to the success or failure of each strategy, we carried out a systematic review with meta-analysis of articles published in 12 databases, from 1974 to the month of December 2013. We evaluated the association between the use of whatever chemical substance, mechanical agent, biological or integrated actions against A. aegypti and the control of the vector, as measured by 10 indicators. We found 2,791 articles, but after careful selection, only 26 studies remained for analysis related to control interventions implemented in 15 countries, with 5 biological, 5 chemical, 3 mechanical and 13 integrated strategies. The comparison among all of them, indicated that the control of A. aegypti is significantly associated with the type of strategy used, and that integrated interventions consist of the most effective method for controlling A. aegypti. The most effective control method was the integrated approach, considering the influence of eco-bio-social determinants in the virus-vector-man epidemiological chain, and community involvement, starting with community empowerment as active agents of vector control.

Proceedings of the Workshop on Directional Acoustic Sensors Held in Newport, Rhode Island on 17-18 April 2001

DTIC Science & Technology

2001-04-18

representation of the acoustic field, the first three terms of which represent the scalar, vector, and tensor (or dyadic ) components of the field, referred to by...encouragement and financial support. We also thank Ms. Kathy Stark of America House Communications , Newport, RI, for the planning and administration of this...Connectivity between warfighter and technical community • Technical competency for integrity of total warfighting system • Full access to our

An integrated fiber-optic probe combined with support vector regression for fast estimation of optical properties of turbid media.

PubMed

Zhou, Yang; Fu, Xiaping; Ying, Yibin; Fang, Zhenhuan

2015-06-23

A fiber-optic probe system was developed to estimate the optical properties of turbid media based on spatially resolved diffuse reflectance. Because of the limitations in numerical calculation of radiative transfer equation (RTE), diffusion approximation (DA) and Monte Carlo simulations (MC), support vector regression (SVR) was introduced to model the relationship between diffuse reflectance values and optical properties. The SVR models of four collection fibers were trained by phantoms in calibration set with a wide range of optical properties which represented products of different applications, then the optical properties of phantoms in prediction set were predicted after an optimal searching on SVR models. The results indicated that the SVR model was capable of describing the relationship with little deviation in forward validation. The correlation coefficient (R) of reduced scattering coefficient μ'(s) and absorption coefficient μ(a) in the prediction set were 0.9907 and 0.9980, respectively. The root mean square errors of prediction (RMSEP) of μ'(s) and μ(a) in inverse validation were 0.411 cm(-1) and 0.338 cm(-1), respectively. The results indicated that the integrated fiber-optic probe system combined with SVR model were suitable for fast and accurate estimation of optical properties of turbid media based on spatially resolved diffuse reflectance. Copyright © 2015 Elsevier B.V. All rights reserved.

A Study on Aircraft Engine Control Systems for Integrated Flight and Propulsion Control

NASA Astrophysics Data System (ADS)

Yamane, Hideaki; Matsunaga, Yasushi; Kusakawa, Takeshi; Yasui, Hisako

The Integrated Flight and Propulsion Control (IFPC) for a highly maneuverable aircraft and a fighter-class engine with pitch/yaw thrust vectoring is described. Of the two IFPC functions the aircraft maneuver control utilizes the thrust vectoring based on aerodynamic control surfaces/thrust vectoring control allocation specified by the Integrated Control Unit (ICU) of a FADEC (Full Authority Digital Electronic Control) system. On the other hand in the Performance Seeking Control (PSC) the ICU identifies engine's various characteristic changes, optimizes manipulated variables and finally adjusts engine control parameters in cooperation with the Engine Control Unit (ECU). It is shown by hardware-in-the-loop simulation that the thrust vectoring can enhance aircraft maneuverability/agility and that the PSC can improve engine performance parameters such as SFC (specific fuel consumption), thrust and gas temperature.

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

PubMed Central

Bockhorst, Tobias

2015-01-01

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

Student Solution Manual for Essential Mathematical Methods for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-02-01

1. Matrices and vector spaces; 2. Vector calculus; 3. Line, surface and volume integrals; 4. Fourier series; 5. Integral transforms; 6. Higher-order ODEs; 7. Series solutions of ODEs; 8. Eigenfunction methods; 9. Special functions; 10. Partial differential equations; 11. Solution methods for PDEs; 12. Calculus of variations; 13. Integral equations; 14. Complex variables; 15. Applications of complex variables; 16. Probability; 17. Statistics.

Essential Mathematical Methods for the Physical Sciences

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2011-02-01

1. Matrices and vector spaces; 2. Vector calculus; 3. Line, surface and volume integrals; 4. Fourier series; 5. Integral transforms; 6. Higher-order ODEs; 7. Series solutions of ODEs; 8. Eigenfunction methods; 9. Special functions; 10. Partial differential equations; 11. Solution methods for PDEs; 12. Calculus of variations; 13. Integral equations; 14. Complex variables; 15. Applications of complex variables; 16. Probability; 17. Statistics; Appendices; Index.

Support Vector Machines Model of Computed Tomography for Assessing Lymph Node Metastasis in Esophageal Cancer with Neoadjuvant Chemotherapy.

PubMed

Wang, Zhi-Long; Zhou, Zhi-Guo; Chen, Ying; Li, Xiao-Ting; Sun, Ying-Shi

The aim of this study was to diagnose lymph node metastasis of esophageal cancer by support vector machines model based on computed tomography. A total of 131 esophageal cancer patients with preoperative chemotherapy and radical surgery were included. Various indicators (tumor thickness, tumor length, tumor CT value, total number of lymph nodes, and long axis and short axis sizes of largest lymph node) on CT images before and after neoadjuvant chemotherapy were recorded. A support vector machines model based on these CT indicators was built to predict lymph node metastasis. Support vector machines model diagnosed lymph node metastasis better than preoperative short axis size of largest lymph node on CT. The area under the receiver operating characteristic curves were 0.887 and 0.705, respectively. The support vector machine model of CT images can help diagnose lymph node metastasis in esophageal cancer with preoperative chemotherapy.

Hybrid lentivirus-phiC31-int-NLS vector allows site-specific recombination in murine and human cells but induces DNA damage.

PubMed

Grandchamp, Nicolas; Altémir, Dorothée; Philippe, Stéphanie; Ursulet, Suzanna; Pilet, Héloïse; Serre, Marie-Claude; Lenain, Aude; Serguera, Che; Mallet, Jacques; Sarkis, Chamsy

2014-01-01

Gene transfer allows transient or permanent genetic modifications of cells for experimental or therapeutic purposes. Gene delivery by HIV-derived lentiviral vector (LV) is highly effective but the risk of insertional mutagenesis is important and the random/uncontrollable integration of the DNA vector can deregulate the cell transcriptional activity. Non Integrative Lentiviral Vectors (NILVs) solve this issue in non-dividing cells, but they do not allow long term expression in dividing cells. In this context, obtaining stable expression while avoiding the problems inherent to unpredictable DNA vector integration requires the ability to control the integration site. One possibility is to use the integrase of phage phiC31 (phiC31-int) which catalyzes efficient site-specific recombination between the attP site in the phage genome and the chromosomal attB site of its Streptomyces host. Previous studies showed that phiC31-int is active in many eukaryotic cells, such as murine or human cells, and directs the integration of a DNA substrate into pseudo attP sites (pattP) which are homologous to the native attP site. In this study, we combined the efficiency of NILV for gene delivery and the specificity of phiC31-int for DNA substrate integration to engineer a hybrid tool for gene transfer with the aim of allowing long term expression in dividing and non-dividing cells preventing genotoxicity. We demonstrated the feasibility to target NILV integration in human and murine pattP sites with a dual NILV vectors system: one which delivers phiC31-int, the other which constitute the substrate containing an attB site in its DNA sequence. These promising results are however alleviated by the occurrence of significant DNA damages. Further improvements are thus required to prevent chromosomal rearrangements for a therapeutic use of the system. However, its use as a tool for experimental applications such as transgenesis is already applicable.

Metabolic and structural integrity of magnetic nanoparticle-loaded primary endothelial cells for targeted cell therapy.

PubMed

Orynbayeva, Zulfiya; Sensenig, Richard; Polyak, Boris

2015-05-01

To successfully translate magnetically mediated cell targeting from bench to bedside, there is a need to systematically assess the potential adverse effects of magnetic nanoparticles (MNPs) interacting with 'therapeutic' cells. Here, we examined in detail the effects of internalized polymeric MNPs on primary rat endothelial cells' structural intactness, metabolic integrity and proliferation potential. The intactness of cytoskeleton and organelles was studied by fluorescent confocal microscopy, flow cytometry and high-resolution respirometry. MNP-loaded primary endothelial cells preserve intact cytoskeleton and organelles, maintain normal rate of proliferation, calcium signaling and mitochondria energy metabolism. This study provides supportive evidence that MNPs at doses necessary for targeting did not induce significant adverse effects on structural integrity and functionality of primary endothelial cells - potential cell therapy vectors.

How effective is integrated vector management against malaria and lymphatic filariasis where the diseases are transmitted by the same vector?

PubMed

Stone, Christopher M; Lindsay, Steve W; Chitnis, Nakul

2014-12-01

The opportunity to integrate vector management across multiple vector-borne diseases is particularly plausible for malaria and lymphatic filariasis (LF) control where both diseases are transmitted by the same vector. To date most examples of integrated control targeting these diseases have been unanticipated consequences of malaria vector control, rather than planned strategies that aim to maximize the efficacy and take the complex ecological and biological interactions between the two diseases into account. We developed a general model of malaria and LF transmission and derived expressions for the basic reproductive number (R0) for each disease. Transmission of both diseases was most sensitive to vector mortality and biting rate. Simulating different levels of coverage of long lasting-insecticidal nets (LLINs) and larval control confirms the effectiveness of these interventions for the control of both diseases. When LF was maintained near the critical density of mosquitoes, minor levels of vector control (8% coverage of LLINs or treatment of 20% of larval sites) were sufficient to eliminate the disease. Malaria had a far greater R0 and required a 90% population coverage of LLINs in order to eliminate it. When the mosquito density was doubled, 36% and 58% coverage of LLINs and larval control, respectively, were required for LF elimination; and malaria elimination was possible with a combined coverage of 78% of LLINs and larval control. Despite the low level of vector control required to eliminate LF, simulations suggest that prevalence of LF will decrease at a slower rate than malaria, even at high levels of coverage. If representative of field situations, integrated management should take into account not only how malaria control can facilitate filariasis elimination, but strike a balance between the high levels of coverage of (multiple) interventions required for malaria with the long duration predicted to be required for filariasis elimination.

Numerical computation of gravitational field of general extended body and its application to rotation curve study of galaxies

NASA Astrophysics Data System (ADS)

Fukushima, Toshio

2017-06-01

Reviewed are recently developed methods of the numerical integration of the gravitational field of general two- or three-dimensional bodies with arbitrary shape and mass density distribution: (i) an axisymmetric infinitely-thin disc (Fukushima 2016a, MNRAS, 456, 3702), (ii) a general infinitely-thin plate (Fukushima 2016b, MNRAS, 459, 3825), (iii) a plane-symmetric and axisymmetric ring-like object (Fukushima 2016c, AJ, 152, 35), (iv) an axisymmetric thick disc (Fukushima 2016d, MNRAS, 462, 2138), and (v) a general three-dimensional body (Fukushima 2016e, MNRAS, 463, 1500). The key techniques employed are (a) the split quadrature method using the double exponential rule (Takahashi and Mori, 1973, Numer. Math., 21, 206), (b) the precise and fast computation of complete elliptic integrals (Fukushima 2015, J. Comp. Appl. Math., 282, 71), (c) Ridder's algorithm of numerical differentiaion (Ridder 1982, Adv. Eng. Softw., 4, 75), (d) the recursive computation of the zonal toroidal harmonics, and (e) the integration variable transformation to the local spherical polar coordinates. These devices succesfully regularize the Newton kernel in the integrands so as to provide accurate integral values. For example, the general 3D potential is regularly integrated as Φ (\\vec{x}) = - G \\int_0^∞ ( \\int_{-1}^1 ( \\int_0^{2π} ρ (\\vec{x}+\\vec{q}) dψ ) dγ ) q dq, where \\vec{q} = q (√{1-γ^2} cos ψ, √{1-γ^2} sin ψ, γ), is the relative position vector referred to \\vec{x}, the position vector at which the potential is evaluated. As a result, the new methods can compute the potential and acceleration vector very accurately. In fact, the axisymmetric integration reproduces the Miyamoto-Nagai potential with 14 correct digits. The developed methods are applied to the gravitational field study of galaxies and protoplanetary discs. Among them, the investigation on the rotation curve of M33 supports a disc-like structure of the dark matter with a double-power-law surface mass density distribution. Fortran 90 subroutines to execute these methods and their test programs and sample outputs are available from the author's WEB site: https://www.researchgate.net/profile/Toshio_Fukushima/

Student Solution Manual for Mathematical Methods for Physics and Engineering Third Edition

NASA Astrophysics Data System (ADS)

Riley, K. F.; Hobson, M. P.

2006-03-01

Preface; 1. Preliminary algebra; 2. Preliminary calculus; 3. Complex numbers and hyperbolic functions; 4. Series and limits; 5. Partial differentiation; 6. Multiple integrals; 7. Vector algebra; 8. Matrices and vector spaces; 9. Normal modes; 10. Vector calculus; 11. Line, surface and volume integrals; 12. Fourier series; 13. Integral transforms; 14. First-order ordinary differential equations; 15. Higher-order ordinary differential equations; 16. Series solutions of ordinary differential equations; 17. Eigenfunction methods for differential equations; 18. Special functions; 19. Quantum operators; 20. Partial differential equations: general and particular; 21. Partial differential equations: separation of variables; 22. Calculus of variations; 23. Integral equations; 24. Complex variables; 25. Application of complex variables; 26. Tensors; 27. Numerical methods; 28. Group theory; 29. Representation theory; 30. Probability; 31. Statistics.

Vector-mediated chromosomal integration of the glutamate decarboxylase gene in streptococcus thermophilus

USDA-ARS?s Scientific Manuscript database

The integrative vector pINTRS was used to transfer glutamate decarboxylase (GAD) activity to Streptococcus thermophilus ST128, thus allowing for the production of '-aminobutyric acid (GABA). In pINTRS, the gene encoding glutamate decarboxylase, gadB, was flanked by DNA fragments homologous to a S. ...

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

PubMed

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

2011-01-01

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

Genotoxicity of retroviral hematopoietic stem cell gene therapy

PubMed Central

Trobridge, Grant D

2012-01-01

Introduction Retroviral vectors have been developed for hematopoietic stem cell (HSC) gene therapy and have successfully cured X-linked severe combined immunodeficiency (SCID-X1), adenosine deaminase deficiency (ADA-SCID), adrenoleukodystrophy, and Wiskott-Aldrich syndrome. However, in HSC gene therapy clinical trials, genotoxicity mediated by integrated vector proviruses has led to clonal expansion, and in some cases frank leukemia. Numerous studies have been performed to understand the molecular basis of vector-mediated genotoxicity with the aim of developing safer vectors and safer gene therapy protocols. These genotoxicity studies are critical to advancing HSC gene therapy. Areas covered This review provides an introduction to the mechanisms of retroviral vector genotoxicity. It also covers advances over the last 20 years in designing safer gene therapy vectors, and in integration site analysis in clinical trials and large animal models. Mechanisms of retroviral-mediated genotoxicity, and the risk factors that contribute to clonal expansion and leukemia in HSC gene therapy are introduced. Expert opinion Continued research on virus–host interactions and next-generation vectors should further improve the safety of future HSC gene therapy vectors and protocols. PMID:21375467

A Fast Vector Radiative Transfer Model for Atmospheric and Oceanic Remote Sensing

NASA Astrophysics Data System (ADS)

Ding, J.; Yang, P.; King, M. D.; Platnick, S. E.; Meyer, K.

2017-12-01

A fast vector radiative transfer model is developed in support of atmospheric and oceanic remote sensing. This model is capable of simulating the Stokes vector observed at the top of the atmosphere (TOA) and the terrestrial surface by considering absorption, scattering, and emission. The gas absorption is parameterized in terms of atmospheric gas concentrations, temperature, and pressure. The parameterization scheme combines a regression method and the correlated-K distribution method, and can easily integrate with multiple scattering computations. The approach is more than four orders of magnitude faster than a line-by-line radiative transfer model with errors less than 0.5% in terms of transmissivity. A two-component approach is utilized to solve the vector radiative transfer equation (VRTE). The VRTE solver separates the phase matrices of aerosol and cloud into forward and diffuse parts and thus the solution is also separated. The forward solution can be expressed by a semi-analytical equation based on the small-angle approximation, and serves as the source of the diffuse part. The diffuse part is solved by the adding-doubling method. The adding-doubling implementation is computationally efficient because the diffuse component needs much fewer spherical function expansion terms. The simulated Stokes vector at both the TOA and the surface have comparable accuracy compared with the counterparts based on numerically rigorous methods.

Harnessing Integrated Vector Management for Enhanced Disease Prevention.

PubMed

Chanda, Emmanuel; Ameneshewa, Birkinesh; Bagayoko, Magaran; Govere, John M; Macdonald, Michael B

2017-01-01

The increasing global threat of emerging and re-emerging vector-borne diseases (VBDs) poses a serious health problem. The World Health Organization (WHO) recommends integrated vector management (IVM) strategy for combating VBD transmission. An IVM approach requires entomological knowledge, technical and infrastructure capacity, and systems facilitating stakeholder collaboration. In sub-Saharan Africa, successful operational IVM experience comes from relatively few countries. This article provides an update on the extent to which IVM is official national policy, the degree of IVM implementation, the level of compliance with WHO guidelines, and concordance in the understanding of IVM, and it assesses the operational impact of IVM. The future outlook encompasses rational and sustainable use of effective vector control tools and inherent improved return for investment for disease vector control. Copyright © 2016 Elsevier Ltd. All rights reserved.

The LAM-PCR Method to Sequence LV Integration Sites.

PubMed

Wang, Wei; Bartholomae, Cynthia C; Gabriel, Richard; Deichmann, Annette; Schmidt, Manfred

2016-01-01

Integrating viral gene transfer vectors are commonly used gene delivery tools in clinical gene therapy trials providing stable integration and continuous gene expression of the transgene in the treated host cell. However, integration of the reverse-transcribed vector DNA into the host genome is a potentially mutagenic event that may directly contribute to unwanted side effects. A comprehensive and accurate analysis of the integration site (IS) repertoire is indispensable to study clonality in transduced cells obtained from patients undergoing gene therapy and to identify potential in vivo selection of affected cell clones. To date, next-generation sequencing (NGS) of vector-genome junctions allows sophisticated studies on the integration repertoire in vitro and in vivo. We have explored the use of the Illumina MiSeq Personal Sequencer platform to sequence vector ISs amplified by non-restrictive linear amplification-mediated PCR (nrLAM-PCR) and LAM-PCR. MiSeq-based high-quality IS sequence retrieval is accomplished by the introduction of a double-barcode strategy that substantially minimizes the frequency of IS sequence collisions compared to the conventionally used single-barcode protocol. Here, we present an updated protocol of (nr)LAM-PCR for the analysis of lentiviral IS using a double-barcode system and followed by deep sequencing using the MiSeq device.

Polarization-analyzing circuit on InP for integrated Stokes vector receiver.

PubMed

Ghosh, Samir; Kawabata, Yuto; Tanemura, Takuo; Nakano, Yoshiaki

2017-05-29

Stokes vector modulation and direct detection (SVM/DD) has immense potentiality to reduce the cost burden for the next-generation short-reach optical communication networks. In this paper, we propose and demonstrate an InGaAsP/InP waveguide-based polarization-analyzing circuit for an integrated Stokes vector (SV) receiver. By transforming the input state-of-polarization (SOP) and projecting its SV onto three different vectors on the Poincare sphere, we show that the actual SOP can be retrieved by simple calculation. We also reveal that this projection matrix has a flexibility and its deviation due to device imperfectness can be calibrated to a certain degree, so that the proposed device would be fundamentally robust against fabrication errors. A proof-of-concept photonic integrated circuit (PIC) is fabricated on InP by using half-ridge waveguides to successfully demonstrate detection of different SOPs scattered on the Poincare sphere.

Towards a Safer, More Randomized Lentiviral Vector Integration Profile Exploring Artificial LEDGF Chimeras

PubMed Central

Vranckx, Lenard S.; Demeulemeester, Jonas; Debyser, Zeger

2016-01-01

The capacity to integrate transgenes into the host cell genome makes retroviral vectors an interesting tool for gene therapy. Although stable insertion resulted in successful correction of several monogenic disorders, it also accounts for insertional mutagenesis, a major setback in otherwise successful clinical gene therapy trials due to leukemia development in a subset of treated patients. Despite improvements in vector design, their use is still not risk-free. Lentiviral vector (LV) integration is directed into active transcription units by LEDGF/p75, a host-cell protein co-opted by the viral integrase. We engineered LEDGF/p75-based hybrid tethers in an effort to elicit a more random integration pattern to increase biosafety, and potentially reduce proto-oncogene activation. We therefore truncated LEDGF/p75 by deleting the N-terminal chromatin-reading PWWP-domain, and replaced this domain with alternative pan-chromatin binding peptides. Expression of these LEDGF-hybrids in LEDGF-depleted cells efficiently rescued LV transduction and resulted in LV integrations that distributed more randomly throughout the host-cell genome. In addition, when considering safe harbor criteria, LV integration sites for these LEDGF-hybrids distributed more safely compared to LEDGF/p75-mediated integration in wild-type cells. This approach should be broadly applicable to introduce therapeutic or suicide genes for cell therapy, such as patient-specific iPS cells. PMID:27788138

Molecular taxonomy of the two Leishmania vectors Lutzomyia umbratilis and Lutzomyia anduzei (Diptera: Psychodidae) from the Brazilian Amazon

PubMed Central

2013-01-01

Background Lutzomyia umbratilis (a probable species complex) is the main vector of Leishmania guyanensis in the northern region of Brazil. Lutzomyia anduzei has been implicated as a secondary vector of this parasite. These species are closely related and exhibit high morphological similarity in the adult stage; therefore, they have been wrongly identified, both in the past and in the present. This shows the need for employing integrated taxonomy. Methods With the aim of gathering information on the molecular taxonomy and evolutionary relationships of these two vectors, 118 sequences of 663 base pairs (barcode region of the mitochondrial DNA cytochrome oxidase I – COI) were generated from 72 L. umbratilis and 46 L. anduzei individuals captured, respectively, in six and five localities of the Brazilian Amazon. The efficiency of the barcode region to differentiate the L. umbratilis lineages I and II was also evaluated. The data were analyzed using the pairwise genetic distances matrix and the Neighbor-Joining (NJ) tree, both based on the Kimura Two Parameter (K2P) evolutionary model. Results The analyses resulted in 67 haplotypes: 32 for L. umbratilis and 35 for L. anduzei. The mean intra-specific genetic distance was 0.008 (0.002 to 0.010 for L. umbratilis; 0.008 to 0.014 for L. anduzei), whereas the mean interspecific genetic distance was 0.044 (0.041 to 0.046), supporting the barcoding gap. Between the L. umbratilis lineages I and II, it was 0.009 to 0.010. The NJ tree analysis strongly supported monophyletic clades for both L. umbratilis and L. anduzei, whereas the L. umbratilis lineages I and II formed two poorly supported monophyletic subclades. Conclusions The barcode region clearly separated the two species and may therefore constitute a valuable tool in the identification of the sand fly vectors of Leishmania in endemic leishmaniasis areas. However, the barcode region had not enough power to separate the two lineages of L. umbratilis, likely reflecting incipient species that have not yet reached the status of distinct species. PMID:24021095

Molecular taxonomy of the two Leishmania vectors Lutzomyia umbratilis and Lutzomyia anduzei (Diptera: Psychodidae) from the Brazilian Amazon.

PubMed

Scarpassa, Vera Margarete; Alencar, Ronildo Baiatone

2013-09-11

Lutzomyia umbratilis (a probable species complex) is the main vector of Leishmania guyanensis in the northern region of Brazil. Lutzomyia anduzei has been implicated as a secondary vector of this parasite. These species are closely related and exhibit high morphological similarity in the adult stage; therefore, they have been wrongly identified, both in the past and in the present. This shows the need for employing integrated taxonomy. With the aim of gathering information on the molecular taxonomy and evolutionary relationships of these two vectors, 118 sequences of 663 base pairs (barcode region of the mitochondrial DNA cytochrome oxidase I - COI) were generated from 72 L. umbratilis and 46 L. anduzei individuals captured, respectively, in six and five localities of the Brazilian Amazon. The efficiency of the barcode region to differentiate the L. umbratilis lineages I and II was also evaluated. The data were analyzed using the pairwise genetic distances matrix and the Neighbor-Joining (NJ) tree, both based on the Kimura Two Parameter (K2P) evolutionary model. The analyses resulted in 67 haplotypes: 32 for L. umbratilis and 35 for L. anduzei. The mean intra-specific genetic distance was 0.008 (0.002 to 0.010 for L. umbratilis; 0.008 to 0.014 for L. anduzei), whereas the mean interspecific genetic distance was 0.044 (0.041 to 0.046), supporting the barcoding gap. Between the L. umbratilis lineages I and II, it was 0.009 to 0.010. The NJ tree analysis strongly supported monophyletic clades for both L. umbratilis and L. anduzei, whereas the L. umbratilis lineages I and II formed two poorly supported monophyletic subclades. The barcode region clearly separated the two species and may therefore constitute a valuable tool in the identification of the sand fly vectors of Leishmania in endemic leishmaniasis areas. However, the barcode region had not enough power to separate the two lineages of L. umbratilis, likely reflecting incipient species that have not yet reached the status of distinct species.

Genetic manipulation of Bacillus methanolicus, a gram-positive, thermotolerant methylotroph.

PubMed Central

Cue, D; Lam, H; Dillingham, R L; Hanson, R S; Flickinger, M C

1997-01-01

We report the fist genetic transformation system, shuttle vectors, and integrative vectors for the thermotolerant, methylotrophic bacterium Bacillus methanolicus. By using a polyethylene glycol-mediated transformation procedure, we have successfully transformed B. methanolicus with both integrative and multicopy plasmids. For plasmids with a single BmeTI recognition site, dam methylation of plasmid DNA (in vivo or in vitro) was found to enhance transformation efficiency from 7- to 11-fold. Two low-copy-number Escherichia coli-B, methanolicus shuttle plasmids, pDQ507 and pDQ508, are described. pDQ508 caries the replication origin cloned from a 17-kb endogenous B. methanolicus plasmid, pBM1. pDQ507 carries a cloned B. methanolicus DNA fragment, pmr-1, possibly of chromosomal origin, that supports maintenance of pDQ507 as a circular, extrachromosomal DNA molecule. Deletion analysis of pDQ507 indicated two regions required for replication, i.e., a 90-bp AT-rich segment containing a 46-bp imperfect, inverted repeat sequence and a second region 65% homologous to the B. subtilis dpp operon. We also evaluated two E. coli-B. subtilis vectors, pEN1 and pHP13, for use as E. coli-B. methanolicus shuttle vectors. The plasmids pHP13, pDQ507, and pDQ508 were segregationally and structurally stable in B. methanolicus for greater than 60 generations of growth under nonselective conditions; pEN1 was segregationally unstable. Single-stranded plasmid DNA was detected in B. methanolicus transformants carrying either pEN1, pHP13, or pDQ508, suggesting that pDQ508, like the B. subtilis plasmids, is replicated by a rolling-circle mechanism. These studies provide the basic tools for the genetic manipulation of B. methanolicus. PMID:9097439

Genetic manipulation of Bacillus methanolicus, a gram-positive, thermotolerant methylotroph.

PubMed

Cue, D; Lam, H; Dillingham, R L; Hanson, R S; Flickinger, M C

1997-04-01

We report the fist genetic transformation system, shuttle vectors, and integrative vectors for the thermotolerant, methylotrophic bacterium Bacillus methanolicus. By using a polyethylene glycol-mediated transformation procedure, we have successfully transformed B. methanolicus with both integrative and multicopy plasmids. For plasmids with a single BmeTI recognition site, dam methylation of plasmid DNA (in vivo or in vitro) was found to enhance transformation efficiency from 7- to 11-fold. Two low-copy-number Escherichia coli-B, methanolicus shuttle plasmids, pDQ507 and pDQ508, are described. pDQ508 caries the replication origin cloned from a 17-kb endogenous B. methanolicus plasmid, pBM1. pDQ507 carries a cloned B. methanolicus DNA fragment, pmr-1, possibly of chromosomal origin, that supports maintenance of pDQ507 as a circular, extrachromosomal DNA molecule. Deletion analysis of pDQ507 indicated two regions required for replication, i.e., a 90-bp AT-rich segment containing a 46-bp imperfect, inverted repeat sequence and a second region 65% homologous to the B. subtilis dpp operon. We also evaluated two E. coli-B. subtilis vectors, pEN1 and pHP13, for use as E. coli-B. methanolicus shuttle vectors. The plasmids pHP13, pDQ507, and pDQ508 were segregationally and structurally stable in B. methanolicus for greater than 60 generations of growth under nonselective conditions; pEN1 was segregationally unstable. Single-stranded plasmid DNA was detected in B. methanolicus transformants carrying either pEN1, pHP13, or pDQ508, suggesting that pDQ508, like the B. subtilis plasmids, is replicated by a rolling-circle mechanism. These studies provide the basic tools for the genetic manipulation of B. methanolicus.

Analysis of the clonal repertoire of gene-corrected cells in gene therapy.

PubMed

Paruzynski, Anna; Glimm, Hanno; Schmidt, Manfred; Kalle, Christof von

2012-01-01

Gene therapy-based clinical phase I/II studies using integrating retroviral vectors could successfully treat different monogenetic inherited diseases. However, with increased efficiency of this therapy, severe side effects occurred in various gene therapy trials. In all cases, integration of the vector close to or within a proto-oncogene contributed substantially to the development of the malignancies. Thus, the in-depth analysis of integration site patterns is of high importance to uncover potential clonal outgrowth and to assess the safety of gene transfer vectors and gene therapy protocols. The standard and nonrestrictive linear amplification-mediated PCR (nrLAM-PCR) in combination with high-throughput sequencing exhibits technologies that allow to comprehensively analyze the clonal repertoire of gene-corrected cells and to assess the safety of the used vector system at an early stage on the molecular level. It enables clarifying the biological consequences of the vector system on the fate of the transduced cell. Furthermore, the downstream performance of real-time PCR allows a quantitative estimation of the clonality of individual cells and their clonal progeny. Here, we present a guideline that should allow researchers to perform comprehensive integration site analysis in preclinical and clinical studies. Copyright © 2012 Elsevier Inc. All rights reserved.

A Novel System for Simultaneous or Sequential Integration of Multiple Gene-Loading Vectors into a Defined Site of a Human Artificial Chromosome

PubMed Central

Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

2014-01-01

Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming. PMID:25303219

A novel system for simultaneous or sequential integration of multiple gene-loading vectors into a defined site of a human artificial chromosome.

PubMed

Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

2014-01-01

Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming.

GGOS working group on ground networks and communications

NASA Technical Reports Server (NTRS)

Pearlman, M.; Altamimi, Z.; Beck, N.; Forsberg, R.; Gurtner, W.; Kenyon, S.; Behrend, D.; Lemoine, F. G.; Ma, C.; Noll, C. E.;

Big Data and machine learning in radiation oncology: State of the art and future prospects.

PubMed

Bibault, Jean-Emmanuel; Giraud, Philippe; Burgun, Anita

2016-11-01

Precision medicine relies on an increasing amount of heterogeneous data. Advances in radiation oncology, through the use of CT Scan, dosimetry and imaging performed before each fraction, have generated a considerable flow of data that needs to be integrated. In the same time, Electronic Health Records now provide phenotypic profiles of large cohorts of patients that could be correlated to this information. In this review, we describe methods that could be used to create integrative predictive models in radiation oncology. Potential uses of machine learning methods such as support vector machine, artificial neural networks, and deep learning are also discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

CFD in Support of Wind Tunnel Testing for Aircraft/Weapons Integration

DTIC Science & Technology

2004-06-01

Warming flux vector splitting scheme. Viscous rate t mies s to the oDentati ote t fluxes (computed using spatial central differencing) in erotate try...computations factors to eliminate them from the current computation. performed. The grid system consisted of 18 x 106 points These newly i-blanked grid...273-295. 130 14. van Leer, B., "Towards the Ultimate Conservative 18 . Suhs, N.E., and R.W. Tramel, "PEGSUS 4.0 Users Manual." Difference Scheme V. A

A transposase strategy for creating libraries of circularly permuted proteins.

PubMed

Mehta, Manan M; Liu, Shirley; Silberg, Jonathan J

2012-05-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions.

A transposase strategy for creating libraries of circularly permuted proteins

PubMed Central

Mehta, Manan M.; Liu, Shirley; Silberg, Jonathan J.

2012-01-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions. PMID:22319214

DNA transformations of Candida tropicalis with replicating and integrative vectors.

PubMed

Sanglard, D; Fiechter, A

1992-12-01

The alkane-assimilating yeast Candida tropicalis was used as a host for DNA transformations. A stable ade2 mutant (Ha900) obtained by UV-mutagenesis was used as a recipient for different vectors carrying selectable markers. A first vector, pMK16, that was developed for the transformation of C. albicans and carries an ADE2 gene marker and a Candida autonomously replicating sequence (CARS) element promoting autonomous replication, was compatible for transforming Ha900. Two transformant types were observed: (i) pink transformants which easily lose pMK16 under non-selective growth conditions; (ii) white transformants, in which the same plasmid exhibited a higher mitotic stability. In both cases pMK16 could be rescued from these cells in Escherichia coli. A second vector, pADE2, containing the isolated C. tropicalis ADE2, gene, was used to transform Ha900. This vector integrated in the yeast genome at homologous sites of the ade2 locus. Different integration types were observed at one or both ade2 alleles in single or in tandem repeats.

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

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

Shitara, Shingo; Kakeda, Minoru; Nagata, Keiko

2008-05-09

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

Direct In Vivo Reprogramming with Sendai Virus Vectors Improves Cardiac Function after Myocardial Infarction.

PubMed

Miyamoto, Kazutaka; Akiyama, Mizuha; Tamura, Fumiya; Isomi, Mari; Yamakawa, Hiroyuki; Sadahiro, Taketaro; Muraoka, Naoto; Kojima, Hidenori; Haginiwa, Sho; Kurotsu, Shota; Tani, Hidenori; Wang, Li; Qian, Li; Inoue, Makoto; Ide, Yoshinori; Kurokawa, Junko; Yamamoto, Tsunehisa; Seki, Tomohisa; Aeba, Ryo; Yamagishi, Hiroyuki; Fukuda, Keiichi; Ieda, Masaki

2018-01-04

Direct cardiac reprogramming holds great promise for regenerative medicine. We previously generated directly reprogrammed induced cardiomyocyte-like cells (iCMs) by overexpression of Gata4, Mef2c, and Tbx5 (GMT) using retrovirus vectors. However, integrating vectors pose risks associated with insertional mutagenesis and disruption of gene expression and are inefficient. Here, we show that Sendai virus (SeV) vectors expressing cardiac reprogramming factors efficiently and rapidly reprogram both mouse and human fibroblasts into integration-free iCMs via robust transgene expression. SeV-GMT generated 100-fold more beating iCMs than retroviral-GMT and shortened the duration to induce beating cells from 30 to 10 days in mouse fibroblasts. In vivo lineage tracing revealed that the gene transfer of SeV-GMT was more efficient than retroviral-GMT in reprogramming resident cardiac fibroblasts into iCMs in mouse infarct hearts. Moreover, SeV-GMT improved cardiac function and reduced fibrosis after myocardial infarction. Thus, efficient, non-integrating SeV vectors may serve as a powerful system for cardiac regeneration. Copyright © 2017 Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Koulouri, Alexandra; Brookes, Mike; Rimpiläinen, Ville

2017-01-01

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

Modeling, analysis, control and design application guidelines of Doubly Fed Induction Generator (DFIG) for wind power applications

NASA Astrophysics Data System (ADS)

Masaud, Tarek

Double Fed Induction Generators (DFIG) has been widely used for the past two decades in large wind farms. However, there are many open-ended problems yet to be solved before they can be implemented in some specific applications. This dissertation deals with the general analysis, modeling, control and applications of the DFIG for large wind farm applications. A detailed "d-q" model of DFIG along with other applications is simulated using the MATLAB/Simulink platform. The simulation results have been discussed in detail in both sub-synchronous and super-synchronous mode of operation. An improved vector control strategy based on the rotor flux oriented vector control has been proposed to control the active power output of the DFIG. The new vector control strategy is compared with the stator flux oriented vector control which is commonly used. It is observed that the new improved vector control method provides a better active power tracking accuracy compare with the stator flux oriented vector control. The behavior of the DFIG -based wind farm under the various grid disturbances is also studied in this dissertation. The implementation of the Flexible AC Transmission System devices (FACTS) to overcome the voltage stability issue for such applications is investigated. The study includes the implementation of both a static synchronous compensator (STATCOM), and the static VAR compensator (SVC) as dynamic reactive power compensators at the point of common coupling to support DFIG-based wind farm during disturbances. Integrating FACTS protect the grid connected DFIG-based wind farm from going offline during and after the disturbances. It is found that the both devices improve the transient performance and therefore helps the wind turbine generator system to remain in service during grid faults. A comparison between the performance of the two devices in terms of the amount of reactive power injected, time response and the application cost has been discussed in this dissertation. Finally, the integration of the battery energy storage system (BESS) into a grid connected DFIG- based wind turbine as a proposed solution to smooth out the output power during wind speed variations is also addressed.

Efficacy and safety of a clinically relevant foamy vector design in human hematopoietic repopulating cells.

PubMed

Everson, Elizabeth M; Hocum, Jonah D; Trobridge, Grant D

2018-06-23

Previous studies have shown that foamy viral (FV) vectors are a promising alternative to gammaretroviral and lentiviral vectors and insulators can improve FV vector safety. However, in a previous analysis of insulator effects on FV vector safety, strong viral promoters were used to elicit genotoxic events. Here we developed and analyzed the efficacy and safety of a high-titer, clinically relevant FV vector driven by the housekeeping promoter elongation factor-1α and insulated with an enhancer blocking A1 insulator (FV-EGW-A1). Human CD34 + cord blood cells were exposed to an enhanced green fluorescent protein expressing vector, FV-EGW-A1, at a multiplicity of infection of 10 and then maintained in vitro or transplanted into immunodeficient mice. Flow cytometry was used to measure engraftment and marking in vivo. FV vector integration sites were analyzed to assess safety. FV-EGW-A1 resulted in high-marking, multi-lineage engraftment of human repopulating cells with no evidence of silencing. Engraftment was highly polyclonal with no clonal dominance and a promising safety profile based on integration site analysis. An FV vector with an elongation factor-1α promoter and an A1 insulator is a promising vector design for use in the clinic. This article is protected by copyright. All rights reserved.

Testing of the Support Vector Machine for Binary-Class Classification

NASA Technical Reports Server (NTRS)

Scholten, Matthew

2011-01-01

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

lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.

PubMed

Sun, Lei; Liu, Hui; Zhang, Lin; Meng, Jia

2015-01-01

Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

EEG-based driver fatigue detection using hybrid deep generic model.

PubMed

Phyo Phyo San; Sai Ho Ling; Rifai Chai; Tran, Yvonne; Craig, Ashley; Hung Nguyen

2016-08-01

Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer. Alternatively, Support Vector Machine (SVM) itself is unable to learn complicated invariance, but produces good decision surface when applied to well-behaved features. Consolidating unsupervised high-level feature extraction techniques, DGM and SVM classification makes the integrated framework stronger and enhance mutually in feature extraction and classification. The experimental results showed that the proposed DBN-based driver fatigue monitoring system achieves better testing accuracy of 73.29 % with 91.10 % sensitivity and 55.48 % specificity. In short, the proposed hybrid DGM-based SVM is an effective method for the detection of driver fatigue in EEG.

Optimizing the method for generation of integration-free induced pluripotent stem cells from human peripheral blood.

PubMed

Gu, Haihui; Huang, Xia; Xu, Jing; Song, Lili; Liu, Shuping; Zhang, Xiao-Bing; Yuan, Weiping; Li, Yanxin

2018-06-15

Generation of induced pluripotent stem cells (iPSCs) from human peripheral blood provides a convenient and low-invasive way to obtain patient-specific iPSCs. The episomal vector is one of the best approaches for reprogramming somatic cells to pluripotent status because of its simplicity and affordability. However, the efficiency of episomal vector reprogramming of adult peripheral blood cells is relatively low compared with cord blood and bone marrow cells. In the present study, integration-free human iPSCs derived from peripheral blood were established via episomal technology. We optimized mononuclear cell isolation and cultivation, episomal vector promoters, and a combination of transcriptional factors to improve reprogramming efficiency. Here, we improved the generation efficiency of integration-free iPSCs from human peripheral blood mononuclear cells by optimizing the method of isolating mononuclear cells from peripheral blood, by modifying the integration of culture medium, and by adjusting the duration of culture time and the combination of different episomal vectors. With this optimized protocol, a valuable asset for banking patient-specific iPSCs has been established.

Implementing a vector surveillance-response system for chagas disease control: a 4-year field trial in Nicaragua.

PubMed

Yoshioka, Kota; Tercero, Doribel; Pérez, Byron; Nakamura, Jiro; Pérez, Lenin

2017-03-06

Chagas disease is one of the neglected tropical diseases (NTDs). International goals for its control involve elimination of vector-borne transmission. Central American countries face challenges in establishing sustainable vector control programmes, since the main vector, Triatoma dimidiata, cannot be eliminated. In 2012, the Ministry of Health in Nicaragua started a field test of a vector surveillance-response system to control domestic vector infestation. This paper reports the main findings from this pilot study. This study was carried out from 2012 to 2015 in the Municipality of Totogalpa. The Japan International Cooperation Agency provided technical cooperation in designing and monitoring the surveillance-response system until 2014. This system involved 1) vector reports by householders to health facilities, 2) data analysis and planning of responses at the municipal health centre and 3) house visits or insecticide spraying by health personnel as a response. We registered all vector reports and responses in a digital database. The collected data were used to describe and analyse the system performance in terms of amount of vector reports as well as rates and timeliness of responses. During the study period, T. dimidiata was reported 396 times. Spatiotemporal analysis identified some high-risk clusters. All houses reported to be infested were visited by health personnel in 2013 and this response rate dropped to 39% in 2015. Rates of insecticide spraying rose above 80% in 2013 but no spraying was carried out in the following 2 years. The timeliness of house visits improved significantly after the responsibility was transferred from a vector control technician to primary health care staff. We argue that the proposed vector surveillance-response system is workable within the resource-constrained health system in Nicaragua. Integration to the primary health care services was a key to improve the system performance. Continual efforts are necessary to keep adapting the surveillance-response system to the dynamic health systems. We also discuss that the goal of eliminating vector-borne transmission remains unachievable. This paper provides lessons not only for Chagas disease control in Central America, but also for control efforts for other NTDs that need a sustainable surveillance-response system to support elimination.

An improved ternary vector system for Agrobacterium-mediated rapid maize transformation.

PubMed

Anand, Ajith; Bass, Steven H; Wu, Emily; Wang, Ning; McBride, Kevin E; Annaluru, Narayana; Miller, Michael; Hua, Mo; Jones, Todd J

2018-05-01

A simple and versatile ternary vector system that utilizes improved accessory plasmids for rapid maize transformation is described. This system facilitates high-throughput vector construction and plant transformation. The super binary plasmid pSB1 is a mainstay of maize transformation. However, the large size of the base vector makes it challenging to clone, the process of co-integration is cumbersome and inefficient, and some Agrobacterium strains are known to give rise to spontaneous mutants resistant to tetracycline. These limitations present substantial barriers to high throughput vector construction. Here we describe a smaller, simpler and versatile ternary vector system for maize transformation that utilizes improved accessory plasmids requiring no co-integration step. In addition, the newly described accessory plasmids have restored virulence genes found to be defective in pSB1, as well as added virulence genes. Testing of different configurations of the accessory plasmids in combination with T-DNA binary vector as ternary vectors nearly doubles both the raw transformation frequency and the number of transformation events of usable quality in difficult-to-transform maize inbreds. The newly described ternary vectors enabled the development of a rapid maize transformation method for elite inbreds. This vector system facilitated screening different origins of replication on the accessory plasmid and T-DNA vector, and four combinations were identified that have high (86-103%) raw transformation frequency in an elite maize inbred.

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.

Integrating Transgenic Vector Manipulation with Clinical Interventions to Manage Vector-Borne Diseases.

PubMed

Okamoto, Kenichi W; Gould, Fred; Lloyd, Alun L

2016-03-01

Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication) can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted). We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences-consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even modest perturbations induced by weak interventions can exhibit strong, albeit transient, epidemiological effects. This, together with our finding that under some conditions combining strategies could have transient adverse epidemiological effects suggests that a relatively long time horizon may be necessary to discern the efficacy of alternative intervention strategies.

Integrating Transgenic Vector Manipulation with Clinical Interventions to Manage Vector-Borne Diseases

PubMed Central

Okamoto, Kenichi W.; Gould, Fred; Lloyd, Alun L.

2016-01-01

Many vector-borne diseases lack effective vaccines and medications, and the limitations of traditional vector control have inspired novel approaches based on using genetic engineering to manipulate vector populations and thereby reduce transmission. Yet both the short- and long-term epidemiological effects of these transgenic strategies are highly uncertain. If neither vaccines, medications, nor transgenic strategies can by themselves suffice for managing vector-borne diseases, integrating these approaches becomes key. Here we develop a framework to evaluate how clinical interventions (i.e., vaccination and medication) can be integrated with transgenic vector manipulation strategies to prevent disease invasion and reduce disease incidence. We show that the ability of clinical interventions to accelerate disease suppression can depend on the nature of the transgenic manipulation deployed (e.g., whether vector population reduction or replacement is attempted). We find that making a specific, individual strategy highly effective may not be necessary for attaining public-health objectives, provided suitable combinations can be adopted. However, we show how combining only partially effective antimicrobial drugs or vaccination with transgenic vector manipulations that merely temporarily lower vector competence can amplify disease resurgence following transient suppression. Thus, transgenic vector manipulation that cannot be sustained can have adverse consequences—consequences which ineffective clinical interventions can at best only mitigate, and at worst temporarily exacerbate. This result, which arises from differences between the time scale on which the interventions affect disease dynamics and the time scale of host population dynamics, highlights the importance of accounting for the potential delay in the effects of deploying public health strategies on long-term disease incidence. We find that for systems at the disease-endemic equilibrium, even modest perturbations induced by weak interventions can exhibit strong, albeit transient, epidemiological effects. This, together with our finding that under some conditions combining strategies could have transient adverse epidemiological effects suggests that a relatively long time horizon may be necessary to discern the efficacy of alternative intervention strategies. PMID:26962871

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

PubMed

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

2015-08-05

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

A Subdivision-Based Representation for Vector Image Editing.

PubMed

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

2012-11-01

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

One Solution of the Forward Problem of DC Resistivity Well Logging by the Method of Volume Integral Equations with Allowance for Induced Polarization

NASA Astrophysics Data System (ADS)

Kevorkyants, S. S.

2018-03-01

For theoretically studying the intensity of the influence exerted by the polarization of the rocks on the results of direct current (DC) well logging, a solution is suggested for the direct inner problem of the DC electric logging in the polarizable model of plane-layered medium containing a heterogeneity by the example of the three-layer model of the hosting medium. Initially, the solution is presented in the form of a traditional vector volume-integral equation of the second kind (IE2) for the electric current density vector. The vector IE2 is solved by the modified iteration-dissipation method. By the transformations, the initial IE2 is reduced to the equation with the contraction integral operator for an axisymmetric model of electrical well-logging of the three-layer polarizable medium intersected by an infinitely long circular cylinder. The latter simulates the borehole with a zone of penetration where the sought vector consists of the radial J r and J z axial (relative to the cylinder's axis) components. The decomposition of the obtained vector IE2 into scalar components and the discretization in the coordinates r and z lead to a heterogeneous system of linear algebraic equations with a block matrix of the coefficients representing 2x2 matrices whose elements are the triple integrals of the mixed derivatives of the second-order Green's function with respect to the parameters r, z, r', and z'. With the use of the analytical transformations and standard integrals, the integrals over the areas of the partition cells and azimuthal coordinate are reduced to single integrals (with respect to the variable t = cos ϕ on the interval [-1, 1]) calculated by the Gauss method for numerical integration. For estimating the effective coefficient of polarization of the complex medium, it is suggested to use the Siegel-Komarov formula.

A Hybrid Neuro-Fuzzy Model For Integrating Large Earth-Science Datasets

NASA Astrophysics Data System (ADS)

Porwal, A.; Carranza, J.; Hale, M.

2004-12-01

A GIS-based hybrid neuro-fuzzy approach to integration of large earth-science datasets for mineral prospectivity mapping is described. It implements a Takagi-Sugeno type fuzzy inference system in the framework of a four-layered feed-forward adaptive neural network. Each unique combination of the datasets is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent datasets. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location) is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a prospectivity map. The procedure is demonstrated by an application to regional-scale base metal prospectivity mapping in a study area located in the Aravalli metallogenic province (western India). A comparison of the hybrid neuro-fuzzy approach with pure knowledge-driven fuzzy and pure data-driven neural network approaches indicates that the former offers a superior method for integrating large earth-science datasets for predictive spatial mathematical modelling.

Applications of lentiviral vectors in molecular imaging.

PubMed

Chatterjee, Sushmita; De, Abhijit

2014-06-01

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

Computation of Surface Integrals of Curl Vector Fields

ERIC Educational Resources Information Center

Hu, Chenglie

2007-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Homologous Recombination-Independent Large Gene Cassette Knock-in in CHO Cells Using TALEN and MMEJ-Directed Donor Plasmids

PubMed Central

Sakuma, Tetsushi; Takenaga, Mitsumasa; Kawabe, Yoshinori; Nakamura, Takahiro; Kamihira, Masamichi; Yamamoto, Takashi

2015-01-01

Gene knock-in techniques have rapidly evolved in recent years, along with the development and maturation of genome editing technology using programmable nucleases. We recently reported a novel strategy for microhomology-mediated end-joining-dependent integration of donor DNA by using TALEN or CRISPR/Cas9 and optimized targeting vectors, named PITCh (Precise Integration into Target Chromosome) vectors. Here we describe TALEN and PITCh vector-mediated integration of long gene cassettes, including a single-chain Fv-Fc (scFv-Fc) gene, in Chinese hamster ovary (CHO) cells, with comparison of targeting and cloning efficiency among several donor design and culture conditions. We achieved 9.6-kb whole plasmid integration and 7.6-kb backbone-free integration into a defined genomic locus in CHO cells. Furthermore, we confirmed the reasonable productivity of recombinant scFv-Fc protein of the knock-in cells. Using our protocol, the knock-in cell clones could be obtained by a single transfection and a single limiting dilution using a 96-well plate, without constructing targeting vectors containing long homology arms. Thus, the study described herein provides a highly practical strategy for gene knock-in of large DNA in CHO cells, which accelerates high-throughput generation of cell lines stably producing any desired biopharmaceuticals, including huge antibody proteins. PMID:26473830

Homologous Recombination-Independent Large Gene Cassette Knock-in in CHO Cells Using TALEN and MMEJ-Directed Donor Plasmids.

PubMed

Sakuma, Tetsushi; Takenaga, Mitsumasa; Kawabe, Yoshinori; Nakamura, Takahiro; Kamihira, Masamichi; Yamamoto, Takashi

2015-10-09

Gene knock-in techniques have rapidly evolved in recent years, along with the development and maturation of genome editing technology using programmable nucleases. We recently reported a novel strategy for microhomology-mediated end-joining-dependent integration of donor DNA by using TALEN or CRISPR/Cas9 and optimized targeting vectors, named PITCh (Precise Integration into Target Chromosome) vectors. Here we describe TALEN and PITCh vector-mediated integration of long gene cassettes, including a single-chain Fv-Fc (scFv-Fc) gene, in Chinese hamster ovary (CHO) cells, with comparison of targeting and cloning efficiency among several donor design and culture conditions. We achieved 9.6-kb whole plasmid integration and 7.6-kb backbone-free integration into a defined genomic locus in CHO cells. Furthermore, we confirmed the reasonable productivity of recombinant scFv-Fc protein of the knock-in cells. Using our protocol, the knock-in cell clones could be obtained by a single transfection and a single limiting dilution using a 96-well plate, without constructing targeting vectors containing long homology arms. Thus, the study described herein provides a highly practical strategy for gene knock-in of large DNA in CHO cells, which accelerates high-throughput generation of cell lines stably producing any desired biopharmaceuticals, including huge antibody proteins.

VectorBase: a data resource for invertebrate vector genomics

PubMed Central

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

2009-01-01

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

Genetic engineering in Actinoplanes sp. SE50/110 - development of an intergeneric conjugation system for the introduction of actinophage-based integrative vectors.

PubMed

Gren, Tetiana; Ortseifen, Vera; Wibberg, Daniel; Schneiker-Bekel, Susanne; Bednarz, Hanna; Niehaus, Karsten; Zemke, Till; Persicke, Marcus; Pühler, Alfred; Kalinowski, Jörn

2016-08-20

The α-glucosidase inhibitor acarbose is used for treatment of diabetes mellitus type II, and is manufactured industrially with overproducing derivatives of Actinoplanes sp. SE50/110, reportedly obtained by conventional mutagenesis. Despite of high industrial significance, only limited information exists regarding acarbose metabolism, function and regulation of these processes, due to the absence of proper genetic engineering methods and tools developed for this strain. Here, a basic toolkit for genetic engineering of Actinoplanes sp. SE50/110 was developed, comprising a standardized protocol for a DNA transfer through Escherichia coli-Actinoplanes intergeneric conjugation and applied for the transfer of ϕC31, ϕBT1 and VWB actinophage-based integrative vectors. Integration sites, occurring once per genome for all vectors, were sequenced and characterized for the first time in Actinoplanes sp. SE50/110. Notably, in case of ϕC31 based vector pSET152, the integration site is highly conserved, while for ϕBT1 and the VWB based vectors pRT801 and pSOK804, respectively, no sequence similarities to those in other bacteria were detected. The studied plasmids were proven to be stable and neutral with respect to strain morphology and acarbose production, enabling future use for genetic manipulations of Actinoplanes sp. SE50/110. To further broaden the spectrum of available tools, a GUS reporter system, based on the pSET152 derived vector, was also established in Actinoplanes sp. SE50/110. Copyright © 2016 Elsevier B.V. All rights reserved.

Transformation of Sordaria macrospora to hygromycin B resistance: characterization of transformants by electrophoretic karyotyping and tetrad analysis.

PubMed

Walz, M; Kück, U

1995-12-01

The ascomycete Sordaria macrospora was transformed using different plasmid molecules containing the bacterial hygromycin B resistance gene (hph) under the control of different expression signals. The highest transformation frequency was obtained with vector pMW1. On this plasmid molecule, expression of the hph gene is directed by the upstream region of the isopenicillin N synthetase gene (pcbC) from the deuteromycete Acremonium chrysogenum. Southern analysis suggests that the vector copies are integrated as tandem repeats into the S. macrospora chromosomes and that duplicated sequences are most probably not inactivated by methylation during meiosis. Furthermore, the hygromycin B resistance (hygR) is not correlated with the number of integrated vector molecules. Electrophoretic karyotyping was used to further characterize S. macrospora transformants. Five chromosomal bands were separated by pulsed-field gel electrophoresis (PFGE) representing seven chromosomes with a total genome size of 39.5Mb. Hybridization analysis revealed ectopic integration of vector DNA into different chromosomes. In a few transformants, major rearrangements were detected. Transformants were sexually propagated to analyze the fate of the heterologous vector DNA. Although the hygR phenotype is stably maintained during mitosis, about a third of all lines tested showed loss of the resistance marker gene after meiosis. However, as was concluded from electrophoretic karyotyping, the resistant spores showed a Mendelian segregation of the integrated vector molecules in at least three consecutive generations. Our data indicate that heterologous marker genes can be used for transformation tagging, or the molecular mapping of chromosomal loci in S. macrospora.

Optimal multiguidance integration in insect navigation.

PubMed

Hoinville, Thierry; Wehner, Rüdiger

2018-03-13

In the last decades, desert ants have become model organisms for the study of insect navigation. In finding their way, they use two major navigational routines: path integration using a celestial compass and landmark guidance based on sets of panoramic views of the terrestrial environment. It has been claimed that this information would enable the insect to acquire and use a centralized cognitive map of its foraging terrain. Here, we present a decentralized architecture, in which the concurrently operating path integration and landmark guidance routines contribute optimally to the directions to be steered, with "optimal" meaning maximizing the certainty (reliability) of the combined information. At any one time during its journey, the animal computes a path integration (global) vector and landmark guidance (local) vector, in which the length of each vector is proportional to the certainty of the individual estimates. Hence, these vectors represent the limited knowledge that the navigator has at any one place about the direction of the goal. The sum of the global and local vectors indicates the navigator's optimal directional estimate. Wherever applied, this decentralized model architecture is sufficient to simulate the results of quite a number of diverse cue-conflict experiments, which have recently been performed in various behavioral contexts by different authors in both desert ants and honeybees. They include even those experiments that have deliberately been designed by former authors to strengthen the evidence for a metric cognitive map in bees.

Safe engineering of CAR T cells for adoptive cell therapy of cancer using long-term episomal gene transfer.

PubMed

Jin, Chuan; Fotaki, Grammatiki; Ramachandran, Mohanraj; Nilsson, Berith; Essand, Magnus; Yu, Di

2016-07-01

Chimeric antigen receptor (CAR) T-cell therapy is a new successful treatment for refractory B-cell leukemia. Successful therapeutic outcome depends on long-term expression of CAR transgene in T cells, which is achieved by delivering transgene using integrating gamma retrovirus (RV) or lentivirus (LV). However, uncontrolled RV/LV integration in host cell genomes has the potential risk of causing insertional mutagenesis. Herein, we describe a novel episomal long-term cell engineering method using non-integrating lentiviral (NILV) vector containing a scaffold/matrix attachment region (S/MAR) element, for either expression of transgenes or silencing of target genes. The insertional events of this vector into the genome of host cells are below detection level. CD19 CAR T cells engineered with a NILV-S/MAR vector have similar levels of CAR expression as T cells engineered with an integrating LV vector, even after numerous rounds of cell division. NILV-S/MAR-engineered CD19 CAR T cells exhibited similar cytotoxic capacity upon CD19(+) target cell recognition as LV-engineered T cells and are as effective in controlling tumor growth in vivo We propose that NILV-S/MAR vectors are superior to current options as they enable long-term transgene expression without the risk of insertional mutagenesis and genotoxicity. © 2016 The Authors. Published under the terms of the CC BY 4.0 license.

Application of Diagnostic Analysis Tools to the Ares I Thrust Vector Control System

NASA Technical Reports Server (NTRS)

Maul, William A.; Melcher, Kevin J.; Chicatelli, Amy K.; Johnson, Stephen B.

2010-01-01

The NASA Ares I Crew Launch Vehicle is being designed to support missions to the International Space Station (ISS), to the Moon, and beyond. The Ares I is undergoing design and development utilizing commercial-off-the-shelf tools and hardware when applicable, along with cutting edge launch technologies and state-of-the-art design and development. In support of the vehicle s design and development, the Ares Functional Fault Analysis group was tasked to develop an Ares Vehicle Diagnostic Model (AVDM) and to demonstrate the capability of that model to support failure-related analyses and design integration. One important component of the AVDM is the Upper Stage (US) Thrust Vector Control (TVC) diagnostic model-a representation of the failure space of the US TVC subsystem. This paper first presents an overview of the AVDM, its development approach, and the software used to implement the model and conduct diagnostic analysis. It then uses the US TVC diagnostic model to illustrate details of the development, implementation, analysis, and verification processes. Finally, the paper describes how the AVDM model can impact both design and ground operations, and how some of these impacts are being realized during discussions of US TVC diagnostic analyses with US TVC designers.

Problem of ticks and tick-borne diseases in India with special emphasis on progress in tick control research: a review.

PubMed

Ghosh, Srikant; Nagar, Gaurav

2014-12-01

Ticks, as vectors of several zoonotic diseases, are ranked second only to mosquitoes as vectors. The diseases spread by ticks are a major constraint to animal productivity while causing morbidity and mortality in both animals and humans. A number of tick species have been recognised since long as vectors of lethal pathogens, viz. Crimean-Congo haemorrhagic fever virus (CCHFV), Kyasanur forest disease virus (KFDV), Babesia spp, Theileria, Rickettsia conorii, Anaplasma marginale, etc. and the damages caused by them are well-recognised. There is a need to reassess the renewed threat posed by the tick vectors and to prioritize the tick control research programme. This review is focused on the major tick-borne human and animal diseases in India and the progress in vector control research with emphasis on acaricide resistance, tick vaccine and the development of potential phytoacaricides as an integral part of integrated tick control programme.

Towards an integrated approach in surveillance of vector-borne diseases in Europe

PubMed Central

2011-01-01

Vector borne disease (VBD) emergence is a complex and dynamic process. Interactions between multiple disciplines and responsible health and environmental authorities are often needed for an effective early warning, surveillance and control of vectors and the diseases they transmit. To fully appreciate this complexity, integrated knowledge about the human and the vector population is desirable. In the current paper, important parameters and terms of both public health and medical entomology are defined in order to establish a common language that facilitates collaboration between the two disciplines. Special focus is put on the different VBD contexts with respect to the current presence or absence of the disease, the pathogen and the vector in a given location. Depending on the context, whether a VBD is endemic or not, surveillance activities are required to assess disease burden or threat, respectively. Following a decision for action, surveillance activities continue to assess trends. PMID:21967706

Proper projective symmetry in LRS Bianchi type V spacetimes

NASA Astrophysics Data System (ADS)

Shabbir, Ghulam; Mahomed, K. S.; Mahomed, F. M.; Moitsheki, R. J.

2018-04-01

In this paper, we investigate proper projective vector fields of locally rotationally symmetric (LRS) Bianchi type V spacetimes using direct integration and algebraic techniques. Despite the non-degeneracy in the Riemann tensor eigenvalues, we classify proper Bianchi type V spacetimes and show that the above spacetimes do not admit proper projective vector fields. Here, in all the cases projective vector fields are Killing vector fields.

Operations of the Far Ultraviolet Spectroscopic Explorer : A `Dynamic' Flux Calibration.

NASA Astrophysics Data System (ADS)

Ehrenreich, D.; Dupuis, J.; Dixon, W. V.; Sahnow, D. J.; Kruk, J. W.

2003-05-01

The FUSE flux calibration is based on model-atmosphere predictions of the spectra of well studied white-dwarf stars. Calibration operations, however, are a highly `dynamic' process consisting of repeatedly measuring these standard stars, deriving corrections, and integrating the results into CALFUSE, the FUSE science pipeline. With suitable scheduling, those calibration observation campaigns let us characterize short term and long term variations of the sensitivity. One particular issue addressed by these observations is monitoring possible degradation of the FUSE optical coatings by atomic oxygen present in the upper atmosphere. We have attempted to minimize this by avoiding pointing close to the instantaneous velocity vector of the spacecraft (the ram vector). Prior to Cycle 3, the minimum permitted angle between the line of sight and the ram vector was 20 degrees. This was reduced to 15 degrees during Cycle 3 to increase our sky coverage, and will be further reduced to 10 degrees for Cycle 4. This relaxation of ram constraints has been preceded by a tailored calibration program in which white dwarf measurements are obtained before and after observations performed for a limited time below the current ram vector constraint. This relaxation of the ram vector constraint will considerably expand the ability of FUSE to observe sources at low declination. This work is based on data obtained for the Guaranteed Time Team by the NASA-CNES-CSA FUSE mission operated by the Johns Hopkins University. Financial support to U.S. participants has been provided by NASA contract NAS5-32985.

Vector neural network signal integration for radar application

NASA Astrophysics Data System (ADS)

Bierman, Gregory S.

1994-07-01

The Litton Data Systems Vector Neural Network (VNN) is a unique multi-scan integration algorithm currently in development. The target of interest is a low-flying cruise missile. Current tactical radar cannot detect and track the missile in ground clutter at tactically useful ranges. The VNN solves this problem by integrating the energy from multiple frames to effectively increase the target's signal-to-noise ratio. The implementation plan is addressing the APG-63 radar. Real-time results will be available by March 1994.

A direct comparison of two nonviral gene therapy vectors for somatic integration: in vivo evaluation of the bacteriophage integrase phiC31 and the Sleeping Beauty transposase.

PubMed

Ehrhardt, Anja; Xu, Hui; Huang, Zan; Engler, Jeffrey A; Kay, Mark A

2005-05-01

In this study we performed a head-to-head comparison of the integrase phiC31 derived from a Streptomyces phage and the Sleeping Beauty (SB) transposase, a member of the TC1/mariner superfamily of transposable elements. Mouse liver was cotransfused with a vector containing our most robust human coagulation factor IX expression cassette and the appropriate recombinase recognition site and either a phiC31- or a SB transposase-expressing vector. To analyze transgene persistence and to prove somatic integration in vivo we induced cell cycling of mouse hepatocytes and found that the transgene expression levels dropped by only 16 to 21% and 56 to 66% in mice that received phiC31 and SB, respectively. Notably, no difference in the toxicity profile was detected in mice treated with either recombinase. Moreover we observed that with the integrase-mediated gene transfer, transgene expression levels were dependent on the remaining noncoding vector sequences, which also integrate into the host genome. Further analyses of a hot spot of integration after phiC31-mediated integration revealed small chromosomal deletions at the target site and that the recombination process was not dependent on the orientation in which the phiC31 recognition site attached to the pseudo-recognition sites in the host genome. Coupled together with ongoing improvements in both systems this study suggests that both nonviral vector systems will have important roles in achieving stable gene transfer in vivo.

[Support vector machine?assisted diagnosis of human malignant gastric tissues based on dielectric properties].

PubMed

Zhang, Sa; Li, Zhou; Xin, Xue-Gang

2017-12-20

To achieve differential diagnosis of normal and malignant gastric tissues based on discrepancies in their dielectric properties using support vector machine. The dielectric properties of normal and malignant gastric tissues at the frequency ranging from 42.58 to 500 MHz were measured by coaxial probe method, and the Cole?Cole model was used to fit the measured data. Receiver?operating characteristic (ROC) curve analysis was used to evaluate the discrimination capability with respect to permittivity, conductivity, and Cole?Cole fitting parameters. Support vector machine was used for discriminating normal and malignant gastric tissues, and the discrimination accuracy was calculated using k?fold cross? The area under the ROC curve was above 0.8 for permittivity at the 5 frequencies at the lower end of the measured frequency range. The combination of the support vector machine with the permittivity at all these 5 frequencies combined achieved the highest discrimination accuracy of 84.38% with a MATLAB runtime of 3.40 s. The support vector machine?assisted diagnosis is feasible for human malignant gastric tissues based on the dielectric properties.

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

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

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

Recombinant adeno-associated virus mediates a high level of gene transfer but less efficient integration in the K562 human hematopoietic cell line.

PubMed Central

Malik, P; McQuiston, S A; Yu, X J; Pepper, K A; Krall, W J; Podsakoff, G M; Kurtzman, G J; Kohn, D B

1997-01-01

We tested the ability of a recombinant adeno-associated virus (rAAV) vector to express and integrate exogenous DNA into human hematopoietic cells in the absence of selection. We developed an rAAV vector, AAV-tNGFR, carrying a truncated rat nerve growth factor receptor (tNGFR) cDNA as a cell surface reporter under the control of the Moloney murine leukemia virus (MoMuLV) long terminal repeat. An analogous MoMuLV-based retroviral vector (L-tNGFR) was used in parallel, and gene transfer and expression in human hematopoietic cells were assessed by flow cytometry and DNA analyses. Following gene transfer into K562 cells with AAV-tNGFR at a multiplicity of infection (MOI) of 13 infectious units (IU), 26 to 38% of cells expressed tNGFR on the surface early after transduction, but the proportion of tNGFR expressing cells steadily declined to 3.0 to 3.5% over 1 month of culture. At an MOI of 130 IU, nearly all cells expressed tNGFR immediately posttransduction, but the proportion of cells expressing tNGFR declined to 62% over 2 months of culture. The decline in the proportion of AAV-tNGFR-expressing cells was associated with ongoing losses of vector genomes. In contrast, K562 cells transduced with the retroviral vector L-tNGFR expressed tNGFR in a constant fraction. Integration analyses on clones showed that integration occurred at different sites. Integration frequencies were estimated at about 49% at an MOI of 130 and 2% at an MOI of 1.3. Transduction of primary human CD34+ progenitor cells by AAV-tNGFR was less efficient than with K562 cells and showed a declining percentage of cells expressing tNGFR over 2 weeks of culture. Thus, purified rAAV caused very high gene transfer and expression in human hematopoietic cells early after transduction, which steadily declined during cell passage in the absence of selection. Although the efficiency of integration was low, overall integration was markedly improved at a high MOI. While prolonged episomal persistence may be adequate for gene therapy of nondividing cells, a very high MOI or improvements in basic aspects of AAV-based vectors may be necessary to improve integration frequency in the rapidly dividing hematopoietic cell population. PMID:9032306

Recombinant adeno-associated virus mediates a high level of gene transfer but less efficient integration in the K562 human hematopoietic cell line.

PubMed

Malik, P; McQuiston, S A; Yu, X J; Pepper, K A; Krall, W J; Podsakoff, G M; Kurtzman, G J; Kohn, D B

1997-03-01

We tested the ability of a recombinant adeno-associated virus (rAAV) vector to express and integrate exogenous DNA into human hematopoietic cells in the absence of selection. We developed an rAAV vector, AAV-tNGFR, carrying a truncated rat nerve growth factor receptor (tNGFR) cDNA as a cell surface reporter under the control of the Moloney murine leukemia virus (MoMuLV) long terminal repeat. An analogous MoMuLV-based retroviral vector (L-tNGFR) was used in parallel, and gene transfer and expression in human hematopoietic cells were assessed by flow cytometry and DNA analyses. Following gene transfer into K562 cells with AAV-tNGFR at a multiplicity of infection (MOI) of 13 infectious units (IU), 26 to 38% of cells expressed tNGFR on the surface early after transduction, but the proportion of tNGFR expressing cells steadily declined to 3.0 to 3.5% over 1 month of culture. At an MOI of 130 IU, nearly all cells expressed tNGFR immediately posttransduction, but the proportion of cells expressing tNGFR declined to 62% over 2 months of culture. The decline in the proportion of AAV-tNGFR-expressing cells was associated with ongoing losses of vector genomes. In contrast, K562 cells transduced with the retroviral vector L-tNGFR expressed tNGFR in a constant fraction. Integration analyses on clones showed that integration occurred at different sites. Integration frequencies were estimated at about 49% at an MOI of 130 and 2% at an MOI of 1.3. Transduction of primary human CD34+ progenitor cells by AAV-tNGFR was less efficient than with K562 cells and showed a declining percentage of cells expressing tNGFR over 2 weeks of culture. Thus, purified rAAV caused very high gene transfer and expression in human hematopoietic cells early after transduction, which steadily declined during cell passage in the absence of selection. Although the efficiency of integration was low, overall integration was markedly improved at a high MOI. While prolonged episomal persistence may be adequate for gene therapy of nondividing cells, a very high MOI or improvements in basic aspects of AAV-based vectors may be necessary to improve integration frequency in the rapidly dividing hematopoietic cell population.

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.

O Electromagnetic Power Waves and Power Density Components.

NASA Astrophysics Data System (ADS)

Petzold, Donald Wayne

1980-12-01

On January 10, 1884 Lord Rayleigh presented a paper entitled "On the Transfer of Energy in the Electromagnetic Field" to the Royal Society of London. This paper had been authored by the late Fellow of Trinity College, Cambridge, Professor J. H. Poynting and in it he claimed that there was a general law for the transfer of electromagnetic energy. He argued that associated with each point in space is a quantity, that has since been called the Poynting vector, that is a measure of the rate of energy flow per unit area. His analysis was concerned with the integration of this power density vector at all points over an enclosing surface of a specific volume. The interpretation of this Poynting vector as a true measure of the local power density was viewed with great skepticism unless the vector was integrated over a closed surface, as the development of the concept required. However, within the last decade or so Shadowitz indicates that a number of prominent authors have argued that the criticism of the interpretation of Poynting's vector as a local power density vector is unjustified. The present paper is not concerned with these arguments but instead is concerned with a decomposition of Poynting's power density vector into two and only two components: one vector which has the same direction as Poynting's vector and which is called the forward power density vector, and another vector, directed opposite to the Poynting vector and called the reverse power density vector. These new local forward and reverse power density vectors will be shown to be dependent upon forward and reverse power wave vectors and these vectors in turn will be related to newly defined forward and reverse components of the electric and magnetic fields. The sum of these forward and reverse power density vectors, which is simply the original Poynting vector, is associated with the total electromagnetic energy traveling past the local point. Another vector which is the difference between the forward and reverse power density vectors and which will be shown to be associated with the total electric and magnetic field energy densities existing at a local point will also be introduced. These local forward and reverse power density vectors may be integrated over a surface to determine the forward and reverse powers and from these results problems related to maximum power transfer or efficiency of electromagnetic energy transmission in space may be studied in a manner similar to that presently being done with transmission lines, wave guides, and more recently with two port multiport lumped parameter systems. These new forward and reverse power density vectors at a point in space are analogous to the forward and revoltages or currents and power waves as used with the transmission line, waveguide, or port. These power wave vectors in space are a generalization of the power waves as developed by Penfield, Youla, and Kurokawa and used with the scattering parameters associated with transmission lines, waveguides and ports.

View-Dependent Streamline Deformation and Exploration

PubMed Central

Tong, Xin; Edwards, John; Chen, Chun-Ming; Shen, Han-Wei; Johnson, Chris R.; Wong, Pak Chung

2016-01-01

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual clutter in 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely. PMID:26600061

View-Dependent Streamline Deformation and Exploration

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

Tong, Xin; Edwards, John; Chen, Chun-Ming

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual cluttering for visualizing 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures.more » Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.« less

Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques

NASA Technical Reports Server (NTRS)

Saha, Bhaskar; Goebel, kai

2007-01-01

Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to the modern Condition- Based Maintenance (CBM)/Prognostic Health Management (PHM) paradigm. The application of the Bayesian techniques to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation as in Particle Filters (PF), provides a powerful tool to integrate the diagnosis and prognosis of battery health. The RVM, which is a Bayesian treatment of the Support Vector Machine (SVM), is used for model identification, while the PF framework uses the learnt model, statistical estimates of noise and anticipated operational conditions to provide estimates of remaining useful life (RUL) in the form of a probability density function (PDF). This type of prognostics generates a significant value addition to the management of any operation involving electrical systems.

View-Dependent Streamline Deformation and Exploration.

PubMed

Tong, Xin; Edwards, John; Chen, Chun-Ming; Shen, Han-Wei; Johnson, Chris R; Wong, Pak Chung

2016-07-01

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual clutter in 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.

ViSBARD: Visual System for Browsing, Analysis and Retrieval of Data

NASA Astrophysics Data System (ADS)

Roberts, D. Aaron; Boller, Ryan; Rezapkin, V.; Coleman, J.; McGuire, R.; Goldstein, M.; Kalb, V.; Kulkarni, R.; Luckyanova, M.; Byrnes, J.; Kerbel, U.; Candey, R.; Holmes, C.; Chimiak, R.; Harris, B.

2018-04-01

ViSBARD interactively visualizes and analyzes space physics data. It provides an interactive integrated 3-D and 2-D environment to determine correlations between measurements across many spacecraft. It supports a variety of spacecraft data products and MHD models and is easily extensible to others. ViSBARD provides a way of visualizing multiple vector and scalar quantities as measured by many spacecraft at once. The data are displayed three-dimesionally along the orbits which may be displayed either as connected lines or as points. The data display allows the rapid determination of vector configurations, correlations between many measurements at multiple points, and global relationships. With the addition of magnetohydrodynamic (MHD) model data, this environment can also be used to validate simulation results with observed data, use simulated data to provide a global context for sparse observed data, and apply feature detection techniques to the simulated data.

Pupal habitat productivity of Anopheles gambiae complex mosquitoes in a rural village in western Kenya.

PubMed

Mutuku, Francis M; Bayoh, M Nabie; Gimnig, John E; Vulule, John M; Kamau, Luna; Walker, Edward D; Kabiru, Ephantus; Hawley, William A

2006-01-01

The productivity of larval habitats of the malaria vector Anopheles gambiae for pupae (the stage preceding adult metamorphosis) is poorly known, yet adult emergence from habitats is the primary determinant of vector density. To assess it, we used absolute sampling methods in four studies involving daily sampling for 25 days in 6 habitat types in a village in western Kenya. Anopheles gambiae s.s. comprised 82.5% of emergent adults and Anopheles arabiensis the remainder. Pupal production occurred from a subset of habitats, primarily soil burrow pits, and was discontinuous in time, even when larvae occupied all habitats continuously. Habitat stability was positively associated with pupal productivity. In a dry season, pupal productivity was distributed between burrow pits and pools in streambeds. Overall, these data support the notion that source reduction measures against recognizably productive habitats would be a useful component of an integrated management program for An. gambiae in villages.

Global-constrained hidden Markov model applied on wireless capsule endoscopy video segmentation

NASA Astrophysics Data System (ADS)

Wan, Yiwen; Duraisamy, Prakash; Alam, Mohammad S.; Buckles, Bill

2012-06-01

Accurate analysis of wireless capsule endoscopy (WCE) videos is vital but tedious. Automatic image analysis can expedite this task. Video segmentation of WCE into the four parts of the gastrointestinal tract is one way to assist a physician. The segmentation approach described in this paper integrates pattern recognition with statiscal analysis. Iniatially, a support vector machine is applied to classify video frames into four classes using a combination of multiple color and texture features as the feature vector. A Poisson cumulative distribution, for which the parameter depends on the length of segments, models a prior knowledge. A priori knowledge together with inter-frame difference serves as the global constraints driven by the underlying observation of each WCE video, which is fitted by Gaussian distribution to constrain the transition probability of hidden Markov model.Experimental results demonstrated effectiveness of the approach.

The Design of a Templated C++ Small Vector Class for Numerical Computing

NASA Technical Reports Server (NTRS)

Moran, Patrick J.

2000-01-01

We describe the design and implementation of a templated C++ class for vectors. The vector class is templated both for vector length and vector component type; the vector length is fixed at template instantiation time. The vector implementation is such that for a vector of N components of type T, the total number of bytes required by the vector is equal to N * size of (T), where size of is the built-in C operator. The property of having a size no bigger than that required by the components themselves is key in many numerical computing applications, where one may allocate very large arrays of small, fixed-length vectors. In addition to the design trade-offs motivating our fixed-length vector design choice, we review some of the C++ template features essential to an efficient, succinct implementation. In particular, we highlight some of the standard C++ features, such as partial template specialization, that are not supported by all compilers currently. This report provides an inventory listing the relevant support currently provided by some key compilers, as well as test code one can use to verify compiler capabilities.

An Efficient Wait-Free Vector

DOE PAGES

Feldman, Steven; Valera-Leon, Carlos; Dechev, Damian

2016-03-01

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector,more » and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel’s TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Finally, unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.« less

An integrated method for atherosclerotic carotid plaque segmentation in ultrasound image.

PubMed

Qian, Chunjun; Yang, Xiaoping

2018-01-01

Carotid artery atherosclerosis is an important cause of stroke. Ultrasound imaging has been widely used in the diagnosis of atherosclerosis. Therefore, segmenting atherosclerotic carotid plaque in ultrasound image is an important task. Accurate plaque segmentation is helpful for the measurement of carotid plaque burden. In this paper, we propose and evaluate a novel learning-based integrated framework for plaque segmentation. In our study, four different classification algorithms, along with the auto-context iterative algorithm, were employed to effectively integrate features from ultrasound images and later also the iteratively estimated and refined probability maps together for pixel-wise classification. The four classification algorithms were support vector machine with linear kernel, support vector machine with radial basis function kernel, AdaBoost and random forest. The plaque segmentation was implemented in the generated probability map. The performance of the four different learning-based plaque segmentation methods was tested on 29 B-mode ultrasound images. The evaluation indices for our proposed methods were consisted of sensitivity, specificity, Dice similarity coefficient, overlap index, error of area, absolute error of area, point-to-point distance, and Hausdorff point-to-point distance, along with the area under the ROC curve. The segmentation method integrated the random forest and an auto-context model obtained the best results (sensitivity 80.4 ± 8.4%, specificity 96.5 ± 2.0%, Dice similarity coefficient 81.0 ± 4.1%, overlap index 68.3 ± 5.8%, error of area -1.02 ± 18.3%, absolute error of area 14.7 ± 10.9%, point-to-point distance 0.34 ± 0.10 mm, Hausdorff point-to-point distance 1.75 ± 1.02 mm, and area under the ROC curve 0.897), which were almost the best, compared with that from the existed methods. Our proposed learning-based integrated framework investigated in this study could be useful for atherosclerotic carotid plaque segmentation, which will be helpful for the measurement of carotid plaque burden. Copyright © 2017 Elsevier B.V. All rights reserved.

Impact of the Central Polypurine Tract on the Kinetics of Human Immunodeficiency Virus Type 1 Vector Transduction

PubMed Central

Van Maele, Bénédicte; De Rijck, Jan; De Clercq, Erik; Debyser, Zeger

2003-01-01

Lentiviral vectors derived from human immunodeficiency virus type 1 (HIV-1) show great promise as gene carriers for future gene therapy. Insertion of a fragment containing the central polypurine tract (cPPT) in HIV-1 vector constructs is known to enhance transduction efficiency drastically, reportedly by facilitating the nuclear import of HIV-1 cDNA through a central DNA flap. We have studied the impact of the cPPT on the kinetics of HIV-1 vector transduction by real-time PCR. The kinetics of total HIV-1 DNA, two-long-terminal-repeat (2-LTR) circles, and, by an Alu-PCR, integrated proviral DNA were monitored. About 6 to 12 h after transduction, the total HIV-1 DNA reached a maximum level, followed by a steep decrease. The 2-LTR circles peaked after 24 to 48 h and were diluted upon cell division. Integration of HIV-1 DNA was first detected at 12 h postinfection. When HIV-1 vectors that contained the cPPT were used, DNA synthesis was similar but a threefold higher amount of 2-LTR circles was detected, confirming the impact on nuclear import. Moreover, a 10-fold increase in the amount of integrated DNA was observed in the presence of the cPPT. Only in the absence of the cPPT was a saturation in 2-LTR circle formation seen at a high multiplicity of infection, suggesting a role for the cPPT in overcoming a barrier to the nuclear import of HIV-1 DNA. A major effect of the central DNA flap on the juxtaposition of both LTRs is unlikely, since transduction with HIV-1 vectors containing ectopic cPPT fragments resulted in increased amounts of 2-LTR circles as well as integrated DNA. Inhibitors of transduction by cPPT-containing HIV vectors were also studied by real-time PCR. The reverse transcriptase inhibitor azidothymidine (AZT) and the nonnucleoside reverse transcriptase inhibitor α-APA clearly inhibited viral DNA synthesis, whereas integrase inhibitors such as the diketo acid L-708,906 and the pyranodipyrimidine V-165 specifically inhibited integration. PMID:12663775

A Systematic Strategy for Screening and Application of Specific Biomarkers in Hepatotoxicity Using Metabolomics Combined With ROC Curves and SVMs.

PubMed

Li, Yubo; Wang, Lei; Ju, Liang; Deng, Haoyue; Zhang, Zhenzhu; Hou, Zhiguo; Xie, Jiabin; Wang, Yuming; Zhang, Yanjun

2016-04-01

Current studies that evaluate toxicity based on metabolomics have primarily focused on the screening of biomarkers while largely neglecting further verification and biomarker applications. For this reason, we used drug-induced hepatotoxicity as an example to establish a systematic strategy for screening specific biomarkers and applied these biomarkers to evaluate whether the drugs have potential hepatotoxicity toxicity. Carbon tetrachloride (5 ml/kg), acetaminophen (1500 mg/kg), and atorvastatin (5 mg/kg) are established as rat hepatotoxicity models. Fifteen common biomarkers were screened by multivariate statistical analysis and integration analysis-based metabolomics data. The receiver operating characteristic curve was used to evaluate the sensitivity and specificity of the biomarkers. We obtained 10 specific biomarker candidates with an area under the curve greater than 0.7. Then, a support vector machine model was established by extracting specific biomarker candidate data from the hepatotoxic drugs and nonhepatotoxic drugs; the accuracy of the model was 94.90% (92.86% sensitivity and 92.59% specificity) and the results demonstrated that those ten biomarkers are specific. 6 drugs were used to predict the hepatotoxicity by the support vector machines model; the prediction results were consistent with the biochemical and histopathological results, demonstrating that the model was reliable. Thus, this support vector machine model can be applied to discriminate the between the hepatic or nonhepatic toxicity of drugs. This approach not only presents a new strategy for screening-specific biomarkers with greater diagnostic significance but also provides a new evaluation pattern for hepatotoxicity, and it will be a highly useful tool in toxicity estimation and disease diagnoses. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Advances in Non-Viral DNA Vectors for Gene Therapy

PubMed Central

Hardee, Cinnamon L.; Arévalo-Soliz, Lirio Milenka; Hornstein, Benjamin D.; Zechiedrich, Lynn

2017-01-01

Uses of viral vectors have thus far eclipsed uses of non-viral vectors for gene therapy delivery in the clinic. Viral vectors, however, have certain issues involving genome integration, the inability to be delivered repeatedly, and possible host rejection. Fortunately, development of non-viral DNA vectors has progressed steadily, especially in plasmid vector length reduction, now allowing these tools to fill in specifically where viral or other non-viral vectors may not be the best options. In this review, we examine the improvements made to non-viral DNA gene therapy vectors, highlight opportunities for their further development, address therapeutic needs for which their use is the logical choice, and discuss their future expansion into the clinic. PMID:28208635

Adeno-Associated Virus Type 2 Wild-Type and Vector-Mediated Genomic Integration Profiles of Human Diploid Fibroblasts Analyzed by Third-Generation PacBio DNA Sequencing

PubMed Central

Hüser, Daniela; Gogol-Döring, Andreas; Chen, Wei

2014-01-01

ABSTRACT Genome-wide analysis of adeno-associated virus (AAV) type 2 integration in HeLa cells has shown that wild-type AAV integrates at numerous genomic sites, including AAVS1 on chromosome 19q13.42. Multiple GAGY/C repeats, resembling consensus AAV Rep-binding sites are preferred, whereas rep-deficient AAV vectors (rAAV) regularly show a random integration profile. This study is the first study to analyze wild-type AAV integration in diploid human fibroblasts. Applying high-throughput third-generation PacBio-based DNA sequencing, integration profiles of wild-type AAV and rAAV are compared side by side. Bioinformatic analysis reveals that both wild-type AAV and rAAV prefer open chromatin regions. Although genomic features of AAV integration largely reproduce previous findings, the pattern of integration hot spots differs from that described in HeLa cells before. DNase-Seq data for human fibroblasts and for HeLa cells reveal variant chromatin accessibility at preferred AAV integration hot spots that correlates with variant hot spot preferences. DNase-Seq patterns of these sites in human tissues, including liver, muscle, heart, brain, skin, and embryonic stem cells further underline variant chromatin accessibility. In summary, AAV integration is dependent on cell-type-specific, variant chromatin accessibility leading to random integration profiles for rAAV, whereas wild-type AAV integration sites cluster near GAGY/C repeats. IMPORTANCE Adeno-associated virus type 2 (AAV) is assumed to establish latency by chromosomal integration of its DNA. This is the first genome-wide analysis of wild-type AAV2 integration in diploid human cells and the first to compare wild-type to recombinant AAV vector integration side by side under identical experimental conditions. Major determinants of wild-type AAV integration represent open chromatin regions with accessible consensus AAV Rep-binding sites. The variant chromatin accessibility of different human tissues or cell types will have impact on vector targeting to be considered during gene therapy. PMID:25031342

Parallel/Vector Integration Methods for Dynamical Astronomy

NASA Astrophysics Data System (ADS)

Fukushima, Toshio

1999-01-01

This paper reviews three recent works on the numerical methods to integrate ordinary differential equations (ODE), which are specially designed for parallel, vector, and/or multi-processor-unit(PU) computers. The first is the Picard-Chebyshev method (Fukushima, 1997a). It obtains a global solution of ODE in the form of Chebyshev polynomial of large (> 1000) degree by applying the Picard iteration repeatedly. The iteration converges for smooth problems and/or perturbed dynamics. The method runs around 100-1000 times faster in the vector mode than in the scalar mode of a certain computer with vector processors (Fukushima, 1997b). The second is a parallelization of a symplectic integrator (Saha et al., 1997). It regards the implicit midpoint rules covering thousands of timesteps as large-scale nonlinear equations and solves them by the fixed-point iteration. The method is applicable to Hamiltonian systems and is expected to lead an acceleration factor of around 50 in parallel computers with more than 1000 PUs. The last is a parallelization of the extrapolation method (Ito and Fukushima, 1997). It performs trial integrations in parallel. Also the trial integrations are further accelerated by balancing computational load among PUs by the technique of folding. The method is all-purpose and achieves an acceleration factor of around 3.5 by using several PUs. Finally, we give a perspective on the parallelization of some implicit integrators which require multiple corrections in solving implicit formulas like the implicit Hermitian integrators (Makino and Aarseth, 1992), (Hut et al., 1995) or the implicit symmetric multistep methods (Fukushima, 1998), (Fukushima, 1999).

Characterizing Complexity of Containerized Cargo X-ray Images

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

Wang, Guangxing; Martz, Harry; Glenn, Steven

X-ray imaging can be used to inspect cargos imported into the United States. In order to better understand the performance of X-ray inspection systems, the X-ray characteristics (density, complexity) of cargo need to be quantified. In this project, an image complexity measure called integrated power spectral density (IPSD) was studied using both DNDO engineered cargos and stream-of-commerce (SOC) cargos. A joint distribution of cargo density and complexity was obtained. A support vector machine was used to classify the SOC cargos into four categories to estimate the relative fractions.

Advanced Design of Dumbbell-shaped Genetic Minimal Vectors Improves Non-coding and Coding RNA Expression.

PubMed

Jiang, Xiaoou; Yu, Han; Teo, Cui Rong; Tan, Genim Siu Xian; Goh, Sok Chin; Patel, Parasvi; Chua, Yiqiang Kevin; Hameed, Nasirah Banu Sahul; Bertoletti, Antonio; Patzel, Volker

2016-09-01

Dumbbell-shaped DNA minimal vectors lacking nontherapeutic genes and bacterial sequences are considered a stable, safe alternative to viral, nonviral, and naked plasmid-based gene-transfer systems. We investigated novel molecular features of dumbbell vectors aiming to reduce vector size and to improve the expression of noncoding or coding RNA. We minimized small hairpin RNA (shRNA) or microRNA (miRNA) expressing dumbbell vectors in size down to 130 bp generating the smallest genetic expression vectors reported. This was achieved by using a minimal H1 promoter with integrated transcriptional terminator transcribing the RNA hairpin structure around the dumbbell loop. Such vectors were generated with high conversion yields using a novel protocol. Minimized shRNA-expressing dumbbells showed accelerated kinetics of delivery and transcription leading to enhanced gene silencing in human tissue culture cells. In primary human T cells, minimized miRNA-expressing dumbbells revealed higher stability and triggered stronger target gene suppression as compared with plasmids and miRNA mimics. Dumbbell-driven gene expression was enhanced up to 56- or 160-fold by implementation of an intron and the SV40 enhancer compared with control dumbbells or plasmids. Advanced dumbbell vectors may represent one option to close the gap between durable expression that is achievable with integrating viral vectors and short-term effects triggered by naked RNA.

A T Matrix Method Based upon Scalar Basis Functions

NASA Technical Reports Server (NTRS)

Mackowski, D.W.; Kahnert, F. M.; Mishchenko, Michael I.

2013-01-01

A surface integral formulation is developed for the T matrix of a homogenous and isotropic particle of arbitrary shape, which employs scalar basis functions represented by the translation matrix elements of the vector spherical wave functions. The formulation begins with the volume integral equation for scattering by the particle, which is transformed so that the vector and dyadic components in the equation are replaced with associated dipole and multipole level scalar harmonic wave functions. The approach leads to a volume integral formulation for the T matrix, which can be extended, by use of Green's identities, to the surface integral formulation. The result is shown to be equivalent to the traditional surface integral formulas based on the VSWF basis.

Genetics and evolution of triatomines: from phylogeny to vector control

PubMed Central

Gourbière, S; Dorn, P; Tripet, F; Dumonteil, E

2012-01-01

Triatomines are hemipteran bugs acting as vectors of the protozoan parasite Trypanosoma cruzi. This parasite causes Chagas disease, one of the major parasitic diseases in the Americas. Studies of triatomine genetics and evolution have been particularly useful in the design of rational vector control strategies, and are reviewed here. The phylogeography of several triatomine species is now slowly emerging, and the struggle to reconcile the phenotypic, phylogenetic, ecological and epidemiological species concepts makes for a very dynamic field. Population genetic studies using different markers indicate a wide range of population structures, depending on the triatomine species, ranging from highly fragmented to mobile, interbreeding populations. Triatomines transmit T. cruzi in the context of complex interactions between the insect vectors, their bacterial symbionts and the parasites; however, an integrated view of the significance of these interactions in triatomine biology, evolution and in disease transmission is still lacking. The development of novel genetic markers, together with the ongoing sequencing of the Rhodnius prolixus genome and more integrative studies, will provide key tools to expanding our understanding of these important insect vectors and allow the design of improved vector control strategies. PMID:21897436

Development of oral CTL vaccine using a CTP-integrated Sabin 1 poliovirus-based vector system.

PubMed

Han, Seung-Soo; Lee, Jinjoo; Jung, Yideul; Kang, Myeong-Ho; Hong, Jung-Hyub; Cha, Min-Suk; Park, Yu-Jin; Lee, Ezra; Yoon, Cheol-Hee; Bae, Yong-Soo

2015-09-11

We developed a CTL vaccine vector by modification of the RPS-Vax system, a mucosal vaccine vector derived from a poliovirus Sabin 1 strain, and generated an oral CTL vaccine against HIV-1. A DNA fragment encoding a cytoplasmic transduction peptide (CTP) was integrated into the RPS-Vax system to generate RPS-CTP, a CTL vaccine vector. An HIV-1 p24 cDNA fragment was introduced into the RPS-CTP vector system and a recombinant poliovirus (rec-PV) named vRPS-CTP/p24 was produced. vRPS-CTP/p24 was genetically stable and efficiently induced Th1 immunity and p24-specific CTLs in immunized poliovirus receptor-transgenic (PVR-Tg) mice. In challenge experiments, PVR-Tg mice that were pre-immunized orally with vRPS-CTP/p24 were resistant to challenge with a lethal dose of p24-expressing recombinant vaccinia virus (rMVA-p24). These results suggested that the RPS-CTP vector system had potential for developing oral CTL vaccines against infectious diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Human health improvement in Sub-Saharan Africa through integrated management of arthropod transmitted diseases and natural resources.

PubMed

Baumgärtner, J; Bieri, M; Buffoni, G; Gilioli, G; Gopalan, H; Greiling, J; Tikubet, G; Van Schayk, I

2001-01-01

A concept of an ecosystem approach to human health improvement in Sub-Saharan Africa is presented here. Three factors mainly affect the physical condition of the human body: the abiotic environment, vector-transmitted diseases, and natural resources. Our concept relies on ecological principles embedded in a social context and identifies three sets of subsystems for study and management: human disease subsystems, natural resource subsystems, and decision-support subsystems. To control human diseases and to secure food from resource subsystems including livestock or crops, integrated preventive approaches are preferred over exclusively curative and sectorial approaches. Environmental sustainability - the basis for managing matter and water flows - contributes to a healthy human environment and constitutes the basis for social sustainability. For planning and implementation of the human health improvement scheme, participatory decision-support subsystems adapted to the local conditions need to be designed through institutional arrangements. The applicability of this scheme is demonstrated in urban and rural Ethiopia.

Intershot Analysis of Flows in DIII-D

NASA Astrophysics Data System (ADS)

Meyer, W. H.; Allen, S. L.; Samuell, C. M.; Howard, J.

2016-10-01

Analysis of the DIII-D flow diagnostic data require demodulation of interference images, and inversion of the resultant line integrated emissivity and flow (phase) images. Four response matrices are pre-calculated: the emissivity line integral and the line integral of the scalar product of the lines-of-site with the orthogonal unit vectors of parallel flow. Equilibrium data determines the relative weight of the component matrices used in the final flow inversion matrix. Serial processing has been used for the lower divertor viewing flow camera 800x600 pixel image. The full cross section viewing camera will require parallel processing of the 2160x2560 pixel image. We will discuss using a Posix thread pool and a Tesla K40c GPU in the processing of this data. Prepared by LLNL under Contract DE-AC52-07NA27344. This material is based upon work supported by the U.S. DOE, Office of Science, Fusion Energy Sciences.

Climate Change, Public Health, and Decision Support: The New Threat of Vector-borne Disease

NASA Astrophysics Data System (ADS)

Grant, F.; Kumar, S.

2011-12-01

Climate change and vector-borne diseases constitute a massive threat to human development. It will not be enough to cut emissions of greenhouse gases-the tide of the future has already been established. Climate change and vector-borne diseases are already undermining the world's efforts to reduce extreme poverty. It is in the best interests of the world leaders to think in terms of concerted global actions, but adaptation and mitigation must be accomplished within the context of local community conditions, resources, and needs. Failure to act will continue to consign developed countries to completely avoidable health risks and significant expense. Failure to act will also reduce poorest of the world's population-some 2.6 billion people-to a future of diminished opportunity. Northrop Grumman has taken significant steps forward to develop the tools needed to assess climate change impacts on public health, collect relevant data for decision making, model projections at regional and local levels; and, deliver information and knowledge to local and regional stakeholders. Supporting these tools is an advanced enterprise architecture consisting of high performance computing, GIS visualization, and standards-based architecture. To address current deficiencies in local planning and decision making with respect to regional climate change and its effect on human health, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model to develop decision aids that translate the regional climate data into actionable information for users. For the present climate WRF was forced with the Max Planck Institute European Center/Hamburg Model version 5 (ECHAM5) General Circulation Model 20th century simulation. For the 21th century climate, we used an ECHAM5 simulation with the Special Report on Emissions (SRES) A1B emissions scenario. WRF was run in nested mode at spatial resolution of 108 km, 36 km and 12 km and 28 vertical levels. This model was examined relative to two mosquito vectors, both competent carriers of dengue fever, a viral, vector-borne disease. Models which incorporate public health considerations can enable decision makers to take proactive steps to mitigate the impacts and adapt to the changing environmental conditions. In this paper we provide a snapshot of our climate initiative and some examples relative to our public health practice work in vector-borne diseases to illustrate how integrated decision support could be of assistance to regional and local communities worldwide.

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

NASA Astrophysics Data System (ADS)

Li, Tao

2018-06-01

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

Vector-Free and Transgene-Free Human iPS Cells Differentiate into Functional Neurons and Enhance Functional Recovery after Ischemic Stroke in Mice

PubMed Central

Mohamad, Osama; Faulkner, Ben; Chen, Dongdong; Yu, Shan Ping; Wei, Ling

2013-01-01

Stroke is a leading cause of human death and disability in the adult population in the United States and around the world. While stroke treatment is limited, stem cell transplantation has emerged as a promising regenerative therapy to replace or repair damaged tissues and enhance functional recovery after stroke. Recently, the creation of induced pluripotent stem (iPS) cells through reprogramming of somatic cells has revolutionized cell therapy by providing an unlimited source of autologous cells for transplantation. In addition, the creation of vector-free and transgene-free human iPS (hiPS) cells provides a new generation of stem cells with a reduced risk of tumor formation that was associated with the random integration of viral vectors seen with previous techniques. However, the potential use of these cells in the treatment of ischemic stroke has not been explored. In the present investigation, we examined the neuronal differentiation of vector-free and transgene-free hiPS cells and the transplantation of hiPS cell-derived neural progenitor cells (hiPS-NPCs) in an ischemic stroke model in mice. Vector-free hiPS cells were maintained in feeder-free and serum-free conditions and differentiated into functional neurons in vitro using a newly developed differentiation protocol. Twenty eight days after transplantation in stroke mice, hiPS-NPCs showed mature neuronal markers in vivo. No tumor formation was seen up to 12 months after transplantation. Transplantation of hiPS-NPCs restored neurovascular coupling, increased trophic support and promoted behavioral recovery after stroke. These data suggest that using vector-free and transgene-free hiPS cells in stem cell therapy are safe and efficacious in enhancing recovery after focal ischemic stroke in mice. PMID:23717557

Heading-vector navigation based on head-direction cells and path integration.

PubMed

Kubie, John L; Fenton, André A

2009-05-01

Insect navigation is guided by heading vectors that are computed by path integration. Mammalian navigation models, on the other hand, are typically based on map-like place representations provided by hippocampal place cells. Such models compute optimal routes as a continuous series of locations that connect the current location to a goal. We propose a "heading-vector" model in which head-direction cells or their derivatives serve both as key elements in constructing the optimal route and as the straight-line guidance during route execution. The model is based on a memory structure termed the "shortcut matrix," which is constructed during the initial exploration of an environment when a set of shortcut vectors between sequential pairs of visited waypoint locations is stored. A mechanism is proposed for calculating and storing these vectors that relies on a hypothesized cell type termed an "accumulating head-direction cell." Following exploration, shortcut vectors connecting all pairs of waypoint locations are computed by vector arithmetic and stored in the shortcut matrix. On re-entry, when local view or place representations query the shortcut matrix with a current waypoint and goal, a shortcut trajectory is retrieved. Since the trajectory direction is in head-direction compass coordinates, navigation is accomplished by tracking the firing of head-direction cells that are tuned to the heading angle. Section 1 of the manuscript describes the properties of accumulating head-direction cells. It then shows how accumulating head-direction cells can store local vectors and perform vector arithmetic to perform path-integration-based homing. Section 2 describes the construction and use of the shortcut matrix for computing direct paths between any pair of locations that have been registered in the shortcut matrix. In the discussion, we analyze the advantages of heading-based navigation over map-based navigation. Finally, we survey behavioral evidence that nonhippocampal, heading-based navigation is used in small mammals and humans. Copyright 2008 Wiley-Liss, Inc.

Integration Site and Clonal Expansion in Human Chronic Retroviral Infection and Gene Therapy

PubMed Central

Niederer, Heather A.; Bangham, Charles R. M.

2014-01-01

Retroviral vectors have been successfully used therapeutically to restore expression of genes in a range of single-gene diseases, including several primary immunodeficiency disorders. Although clinical trials have shown remarkable results, there have also been a number of severe adverse events involving malignant outgrowth of a transformed clonal population. This clonal expansion is influenced by the integration site profile of the viral integrase, the transgene expressed, and the effect of the viral promoters on the neighbouring host genome. Infection with the pathogenic human retrovirus HTLV-1 also causes clonal expansion of cells containing an integrated HTLV-1 provirus. Although the majority of HTLV-1-infected people remain asymptomatic, up to 5% develop an aggressive T cell malignancy. In this review we discuss recent findings on the role of the genomic integration site in determining the clonality and the potential for malignant transformation of cells carrying integrated HTLV-1 or gene therapy vectors, and how these results have contributed to the understanding of HTLV-1 pathogenesis and to improvements in gene therapy vector safety. PMID:25365582

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

Feldman, Steven; Valera-Leon, Carlos; Dechev, Damian

The vector is a fundamental data structure, which provides constant-time access to a dynamically-resizable range of elements. Currently, there exist no wait-free vectors. The only non-blocking version supports only a subset of the sequential vector API and exhibits significant synchronization overhead caused by supporting opposing operations. Since many applications operate in phases of execution, wherein each phase only a subset of operations are used, this overhead is unnecessary for the majority of the application. To address the limitations of the non-blocking version, we present a new design that is wait-free, supports more of the operations provided by the sequential vector,more » and provides alternative implementations of key operations. These alternatives allow the developer to balance the performance and functionality of the vector as requirements change throughout execution. Compared to the known non-blocking version and the concurrent vector found in Intel’s TBB library, our design outperforms or provides comparable performance in the majority of tested scenarios. Over all tested scenarios, the presented design performs an average of 4.97 times more operations per second than the non-blocking vector and 1.54 more than the TBB vector. In a scenario designed to simulate the filling of a vector, performance improvement increases to 13.38 and 1.16 times. This work presents the first ABA-free non-blocking vector. Finally, unlike the other non-blocking approach, all operations are wait-free and bounds-checked and elements are stored contiguously in memory.« less

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

PubMed

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

2015-02-01

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

Plant microRNA-Target Interaction Identification Model Based on the Integration of Prediction Tools and Support Vector Machine

PubMed Central

Meng, Jun; Shi, Lin; Luan, Yushi

2014-01-01

Background Confident identification of microRNA-target interactions is significant for studying the function of microRNA (miRNA). Although some computational miRNA target prediction methods have been proposed for plants, results of various methods tend to be inconsistent and usually lead to more false positive. To address these issues, we developed an integrated model for identifying plant miRNA–target interactions. Results Three online miRNA target prediction toolkits and machine learning algorithms were integrated to identify and analyze Arabidopsis thaliana miRNA-target interactions. Principle component analysis (PCA) feature extraction and self-training technology were introduced to improve the performance. Results showed that the proposed model outperformed the previously existing methods. The results were validated by using degradome sequencing supported Arabidopsis thaliana miRNA-target interactions. The proposed model constructed on Arabidopsis thaliana was run over Oryza sativa and Vitis vinifera to demonstrate that our model is effective for other plant species. Conclusions The integrated model of online predictors and local PCA-SVM classifier gained credible and high quality miRNA-target interactions. The supervised learning algorithm of PCA-SVM classifier was employed in plant miRNA target identification for the first time. Its performance can be substantially improved if more experimentally proved training samples are provided. PMID:25051153

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.

Electrotransformation of Lactobacillus delbrueckii subsp. bulgaricus and L. delbrueckii subsp. lactis with Various Plasmids

PubMed Central

Serror, Pascale; Sasaki, Takashi; Ehrlich, S. Dusko; Maguin, Emmanuelle

2002-01-01

We describe, for the first time, a detailed electroporation procedure for Lactobacillus delbrueckii. Three L. delbrueckii strains were successfully transformed. Under optimal conditions, the transformation efficiency was 104 transformants per μg of DNA. Using this procedure, we identified several plasmids able to replicate in L. delbrueckii and integrated an integrative vector based on phage integrative elements into the L. delbrueckii subsp. bulgaricus chromosome. These vectors provide a good basis for developing molecular tools for L. delbrueckii and open the field of genetic studies in L. delbrueckii. PMID:11772607

Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization.

PubMed

Sun, Shiliang; Xie, Xijiong

2016-09-01

Semisupervised learning has been an active research topic in machine learning and data mining. One main reason is that labeling examples is expensive and time-consuming, while there are large numbers of unlabeled examples available in many practical problems. So far, Laplacian regularization has been widely used in semisupervised learning. In this paper, we propose a new regularization method called tangent space intrinsic manifold regularization. It is intrinsic to data manifold and favors linear functions on the manifold. Fundamental elements involved in the formulation of the regularization are local tangent space representations, which are estimated by local principal component analysis, and the connections that relate adjacent tangent spaces. Simultaneously, we explore its application to semisupervised classification and propose two new learning algorithms called tangent space intrinsic manifold regularized support vector machines (TiSVMs) and tangent space intrinsic manifold regularized twin SVMs (TiTSVMs). They effectively integrate the tangent space intrinsic manifold regularization consideration. The optimization of TiSVMs can be solved by a standard quadratic programming, while the optimization of TiTSVMs can be solved by a pair of standard quadratic programmings. The experimental results of semisupervised classification problems show the effectiveness of the proposed semisupervised learning algorithms.

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

NASA Astrophysics Data System (ADS)

Manikanta, K.; Rajan, K. S.

2017-09-01

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

A universal expression/silencing vector in plants.

PubMed

Peretz, Yuval; Mozes-Koch, Rita; Akad, Fuad; Tanne, Edna; Czosnek, Henryk; Sela, Ilan

2007-12-01

A universal vector (IL-60 and auxiliary constructs), expressing or silencing genes in every plant tested to date, is described. Plants that have been successfully manipulated by the IL-60 system include hard-to-manipulate species such as wheat (Triticum duram), pepper (Capsicum annuum), grapevine (Vitis vinifera), citrus, and olive (Olea europaea). Expression or silencing develops within a few days in tomato (Solanum lycopersicum), wheat, and most herbaceous plants and in up to 3 weeks in woody trees. Expression, as tested in tomato, is durable and persists throughout the life span of the plant. The vector is, in fact, a disarmed form of Tomato yellow leaf curl virus, which is applied as a double-stranded DNA and replicates as such. However, the disarmed virus does not support rolling-circle replication, and therefore viral progeny single-stranded DNA is not produced. IL-60 does not integrate into the plant's genome, and the construct, including the expressed gene, is not heritable. IL-60 is not transmitted by the Tomato yellow leaf curl virus's natural insect vector. In addition, artificial satellites were constructed that require a helper virus for replication, movement, and expression. With IL-60 as the disarmed helper "virus," transactivation occurs, resulting in an inducible expressing/silencing system. The system's potential is demonstrated by IL-60-derived suppression of a viral-silencing suppressor of Grapevine virus A, resulting in Grapevine virus A-resistant/tolerant plants.

Can we estimate total magnetization directions from aeromagnetic data using Helbig's integrals?

USGS Publications Warehouse

Phillips, J.D.

2005-01-01

An algorithm that implements Helbig's (1963) integrals for estimating the vector components (mx, my, mz) of tile magnetic dipole moment from the first order moments of the vector magnetic field components (??X, ??Y, ??Z) is tested on real and synthetic data. After a grid of total field aeromagnetic data is converted to vector component grids using Fourier filtering, Helbig's infinite integrals are evaluated as finite integrals in small moving windows using a quadrature algorithm based on the 2-D trapezoidal rule. Prior to integration, best-fit planar surfaces must be removed from the component data within the data windows in order to make the results independent of the coordinate system origin. Two different approaches are described for interpreting the results of the integration. In the "direct" method, results from pairs of different window sizes are compared to identify grid nodes where the angular difference between solutions is small. These solutions provide valid estimates of total magnetization directions for compact sources such as spheres or dipoles, but not for horizontally elongated or 2-D sources. In the "indirect" method, which is more forgiving of source geometry, results of the quadrature analysis are scanned for solutions that are parallel to a specified total magnetization direction.

PGRP-LD mediates A. stephensi vector competency by regulating homeostasis of microbiota-induced peritrophic matrix synthesis

PubMed Central

Song, Xiumei; Wang, Mengfei; Dong, Li

2018-01-01

Peptidoglycan recognition proteins (PGRPs) and commensal microbes mediate pathogen infection outcomes in insect disease vectors. Although PGRP-LD is retained in multiple vectors, its role in host defense remains elusive. Here we report that Anopheles stephensi PGRP-LD protects the vector from malaria parasite infection by regulating gut homeostasis. Specifically, knock down of PGRP-LD (dsLD) increased susceptibility to Plasmodium berghei infection, decreased the abundance of gut microbiota and changed their spatial distribution. This outcome resulted from a change in the structural integrity of the peritrophic matrix (PM), which is a chitinous and proteinaceous barrier that lines the midgut lumen. Reduction of microbiota in dsLD mosquitoes due to the upregulation of immune effectors led to dysregulation of PM genes and PM fragmentation. Elimination of gut microbiota in antibiotic treated mosquitoes (Abx) led to PM loss and increased vectorial competence. Recolonization of Abx mosquitoes with indigenous Enterobacter sp. restored PM integrity and decreased mosquito vectorial capacity. Silencing PGRP-LD in mosquitoes without PM didn’t influence their vector competence. Our results indicate that PGPR-LD protects the gut microbiota by preventing hyper-immunity, which in turn promotes PM structurally integrity. The intact PM plays a key role in limiting P. berghei infection. PMID:29489896

Transcranial Magnetic Stimulation: An Automated Procedure to Obtain Coil-specific Models for Field Calculations.

PubMed

Madsen, Kristoffer H; Ewald, Lars; Siebner, Hartwig R; Thielscher, Axel

2015-01-01

Field calculations for transcranial magnetic stimulation (TMS) are increasingly implemented online in neuronavigation systems and in more realistic offline approaches based on finite-element methods. They are often based on simplified and/or non-validated models of the magnetic vector potential of the TMS coils. To develop an approach to reconstruct the magnetic vector potential based on automated measurements. We implemented a setup that simultaneously measures the three components of the magnetic field with high spatial resolution. This is complemented by a novel approach to determine the magnetic vector potential via volume integration of the measured field. The integration approach reproduces the vector potential with very good accuracy. The vector potential distribution of a standard figure-of-eight shaped coil determined with our setup corresponds well with that calculated using a model reconstructed from x-ray images. The setup can supply validated models for existing and newly appearing TMS coils. Copyright © 2015 Elsevier Inc. All rights reserved.

Recent Advances in Preclinical Developments Using Adenovirus Hybrid Vectors.

PubMed

Ehrke-Schulz, Eric; Zhang, Wenli; Gao, Jian; Ehrhardt, Anja

2017-10-01

Adenovirus (Ad)-based vectors are efficient gene-transfer vehicles to deliver foreign DNA into living organisms, offering large cargo capacity and low immunogenicity and genotoxicity. As Ad shows low integration rates of their genomes into host chromosomes, vector-derived gene expression decreases due to continuous cell cycling in regenerating tissues and dividing cell populations. To overcome this hurdle, adenoviral delivery can be combined with mechanisms leading to maintenance of therapeutic DNA and long-term effects of the desired treatment. Several hybrid Ad vectors (AdV) exploiting various strategies for long-term treatment have been developed and characterized. This review summarizes recent developments of preclinical approaches using hybrid AdVs utilizing either the Sleeping Beauty transposase system for somatic integration into host chromosomes or designer nucleases, including transcription activator-like effector nucleases and clustered regularly interspaced short palindromic repeats/CRISPR-associated protein-9 nuclease for permanent gene editing. Further options on how to optimize these vectors further are discussed, which may lead to future clinical applications of these versatile gene-therapy tools.

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.

Can vector control play a useful supplementary role against bancroftian filariasis?

PubMed Central

Maxwell, C. A.; Mohammed, K.; Kisumku, U.; Curtis, C. F.

1999-01-01

A single campaign of mass treatment for bancroftian filariasis with diethylcarbamazine (DEC) in Makunduchi, a town in Zanzibar, United Republic of Tanzania, combined with elimination of mosquito breeding in pit latrines with polystyrene beads was followed by a progressive decline over a 5-year period in the microfilarial rate from 49% to 3%. Evidence that vector control had contributed to this long-term decline was obtained by comparison with another town, Moga, where a DEC campaign was used without vector control and where resurgence of microfilariae could be observed 3-6 years after the campaign. In Zanzibar town, treatment of 3844 wet pit latrines and cesspits with polystyrene beads reduced the adult mosquito population in houses by about 65%. Supplementary treatment of open drains and marshes with Bacillus sphaericus produced little or no additional reduction compared to a sector of the town where only pit treatment with polystyrene was carried out. The cost and effort of achieving the 65% reduction in mosquito population could hardly be justified for its impact on filariasis alone, but its noticeable impact on biting nuisance might help to gain community support for an integrated programme. PMID:10083712

Introduction to Vector Field Visualization

NASA Technical Reports Server (NTRS)

Kao, David; Shen, Han-Wei

2010-01-01

Vector field visualization techniques are essential to help us understand the complex dynamics of flow fields. These can be found in a wide range of applications such as study of flows around an aircraft, the blood flow in our heart chambers, ocean circulation models, and severe weather predictions. The vector fields from these various applications can be visually depicted using a number of techniques such as particle traces and advecting textures. In this tutorial, we present several fundamental algorithms in flow visualization including particle integration, particle tracking in time-dependent flows, and seeding strategies. For flows near surfaces, a wide variety of synthetic texture-based algorithms have been developed to depict near-body flow features. The most common approach is based on the Line Integral Convolution (LIC) algorithm. There also exist extensions of LIC to support more flexible texture generations for 3D flow data. This tutorial reviews these algorithms. Tensor fields are found in several real-world applications and also require the aid of visualization to help users understand their data sets. Examples where one can find tensor fields include mechanics to see how material respond to external forces, civil engineering and geomechanics of roads and bridges, and the study of neural pathway via diffusion tensor imaging. This tutorial will provide an overview of the different tensor field visualization techniques, discuss basic tensor decompositions, and go into detail on glyph based methods, deformation based methods, and streamline based methods. Practical examples will be used when presenting the methods; and applications from some case studies will be used as part of the motivation.

Community detection in complex networks using proximate support vector clustering

NASA Astrophysics Data System (ADS)

Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

2018-03-01

Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Bacteriophage-based vectors for site-specific insertion of DNA in the chromosome of Corynebacteria.

PubMed

Oram, Mark; Woolston, Joelle E; Jacobson, Andrew D; Holmes, Randall K; Oram, Diana M

2007-04-15

In Corynebacterium diphtheriae, diphtheria toxin is encoded by the tox gene of some temperate corynephages such as beta. beta-like corynephages are capable of inserting into the C. diphtheriae chromosome at two specific sites, attB1 and attB2. Transcription of the phage-encoded tox gene, and many chromosomally encoded genes, is regulated by the DtxR protein in response to Fe(2+) levels. Characterizing DtxR-dependent gene regulation is pivotal in understanding diphtheria pathogenesis and mechanisms of iron-dependent gene expression; although this has been hampered by a lack of molecular genetic tools in C. diphtheriae and related Coryneform species. To expand the systems for genetic manipulation of C. diphtheriae, we constructed plasmid vectors capable of integrating into the chromosome. These plasmids contain the beta-encoded attP site and the DIP0182 integrase gene of C. diphtheriae NCTC13129. When these vectors were delivered to the cytoplasm of non-lysogenic C. diphtheriae, they integrated into either the attB1 or attB2 sites with comparable frequency. Lysogens were also transformed with these vectors, by virtue of the second attB site. An integrated vector carrying an intact dtxR gene complemented the mutant phenotypes of a C. diphtheriae DeltadtxR strain. Additionally, strains of beta-susceptible C. ulcerans, and C. glutamicum, a species non-permissive for beta, were each transformed with these vectors. This work significantly extends the tools available for targeted transformation of both pathogenic and non-pathogenic Corynebacterium species.

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

PubMed

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

2017-12-01

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

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

PubMed

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

2017-01-01

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

A Fast Reduced Kernel Extreme Learning Machine.

PubMed

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

2016-04-01

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

Support vector machines

NASA Technical Reports Server (NTRS)

Garay, Michael J.; Mazzoni, Dominic; Davies, Roger; Wagstaff, Kiri

2004-01-01

Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

Lysine acetylation sites prediction using an ensemble of support vector machine classifiers.

PubMed

Xu, Yan; Wang, Xiao-Bo; Ding, Jun; Wu, Ling-Yun; Deng, Nai-Yang

2010-05-07

Lysine acetylation is an essentially reversible and high regulated post-translational modification which regulates diverse protein properties. Experimental identification of acetylation sites is laborious and expensive. Hence, there is significant interest in the development of computational methods for reliable prediction of acetylation sites from amino acid sequences. In this paper we use an ensemble of support vector machine classifiers to perform this work. The experimentally determined acetylation lysine sites are extracted from Swiss-Prot database and scientific literatures. Experiment results show that an ensemble of support vector machine classifiers outperforms single support vector machine classifier and other computational methods such as PAIL and LysAcet on the problem of predicting acetylation lysine sites. The resulting method has been implemented in EnsemblePail, a web server for lysine acetylation sites prediction available at http://www.aporc.org/EnsemblePail/. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Product Quality Modelling Based on Incremental Support Vector Machine

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

Mining protein function from text using term-based support vector machines

PubMed Central

Rice, Simon B; Nenadic, Goran; Stapley, Benjamin J

2005-01-01

Background Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. Results The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. Conclusion A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2. PMID:15960835

An integrated vector system for cellular studies of phage display-derived peptides.

PubMed

Voss, Stephan D; DeGrand, Alec M; Romeo, Giulio R; Cantley, Lewis C; Frangioni, John V

2002-09-15

Peptide phage display is a method by which large numbers of diverse peptides can be screened for binding to a target of interest. Even when successful, the rate-limiting step is usually validation of peptide bioactivity using living cells. In this paper, we describe an integrated system of vectors that expedites both the screening and the characterization processes. Library construction and screening is performed using an optimized type 3 phage display vector, mJ(1), which is shown to accept peptide libraries of at least 23 amino acids in length. Peptide coding sequences are shuttled from mJ(1) into one of three families of mammalian expression vectors for cell physiological studies. The vector pAL(1) expresses phage display-derived peptides as Gal4 DNA binding domain fusion proteins for transcriptional activation studies. The vectors pG(1), pG(1)N, and pG(1)C express phage display-derived peptides as green fluorescent protein fusions targeted to the entire cell, nucleus, or cytoplasm, respectively. The vector pAP(1) expresses phage display-derived peptides as fusions to secreted placental alkaline phosphatase. Such enzyme fusions can be used as highly sensitive affinity reagents for high-throughput assays and for cloning of peptide-binding cell surface receptors. Taken together, this system of vectors should facilitate the development of phage display-derived peptides into useful biomolecules.

CARSVM: a class association rule-based classification framework and its application to gene expression data.

PubMed

Kianmehr, Keivan; Alhajj, Reda

2008-09-01

In this study, we aim at building a classification framework, namely the CARSVM model, which integrates association rule mining and support vector machine (SVM). The goal is to benefit from advantages of both, the discriminative knowledge represented by class association rules and the classification power of the SVM algorithm, to construct an efficient and accurate classifier model that improves the interpretability problem of SVM as a traditional machine learning technique and overcomes the efficiency issues of associative classification algorithms. In our proposed framework: instead of using the original training set, a set of rule-based feature vectors, which are generated based on the discriminative ability of class association rules over the training samples, are presented to the learning component of the SVM algorithm. We show that rule-based feature vectors present a high-qualified source of discrimination knowledge that can impact substantially the prediction power of SVM and associative classification techniques. They provide users with more conveniences in terms of understandability and interpretability as well. We have used four datasets from UCI ML repository to evaluate the performance of the developed system in comparison with five well-known existing classification methods. Because of the importance and popularity of gene expression analysis as real world application of the classification model, we present an extension of CARSVM combined with feature selection to be applied to gene expression data. Then, we describe how this combination will provide biologists with an efficient and understandable classifier model. The reported test results and their biological interpretation demonstrate the applicability, efficiency and effectiveness of the proposed model. From the results, it can be concluded that a considerable increase in classification accuracy can be obtained when the rule-based feature vectors are integrated in the learning process of the SVM algorithm. In the context of applicability, according to the results obtained from gene expression analysis, we can conclude that the CARSVM system can be utilized in a variety of real world applications with some adjustments.

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

Alpharetroviral Vector-mediated Gene Therapy for X-CGD: Functional Correction and Lack of Aberrant Splicing

PubMed Central

Kaufmann, Kerstin B.; Brendel, Christian; Suerth, Julia D.; Mueller-Kuller, Uta; Chen-Wichmann, Linping; Schwäble, Joachim; Pahujani, Shweta; Kunkel, Hana; Schambach, Axel; Baum, Christopher; Grez, Manuel

2013-01-01

Comparative integrome analysis has revealed that the most neutral integration pattern among retroviruses is attributed to alpharetroviruses. We chose X-linked chronic granulomatous disease (X-CGD) as model to evaluate the potential of self-inactivating (SIN) alpharetroviral vectors for gene therapy of monogenic diseases. Therefore, we combined the alpharetroviral vector backbone with the elongation factor-1α short promoter, both considered to possess a low genotoxic profile, to drive transgene (gp91phox) expression. Following efficient transduction transgene expression was sustained and provided functional correction of the CGD phenotype in a cell line model at low vector copy number. Further analysis in a murine X-CGD transplantation model revealed gene-marking of bone marrow cells and oxidase positive granulocytes in peripheral blood. Transduction of human X-CGD CD34+ cells provided functional correction up to wild-type levels and long-term expression upon transplantation into a humanized mouse model. In contrast to lentiviral vectors, no aberrantly spliced transcripts containing cellular exons fused to alpharetroviral sequences were found in transduced cells, implying that the safety profile of alpharetroviral vectors may extend beyond their neutral integration profile. Taken together, this highlights the potential of this SIN alpharetroviral system as a platform for new candidate vectors for future gene therapy of hematopoietic disorders. PMID:23207695

Genome Investigations of Vector Competence in Aedes aegypti to Inform Novel Arbovirus Disease Control Approaches

PubMed Central

Severson, David W.; Behura, Susanta K.

2016-01-01

Dengue (DENV), yellow fever, chikungunya, and Zika virus transmission to humans by a mosquito host is confounded by both intrinsic and extrinsic variables. Besides virulence factors of the individual arboviruses, likelihood of virus transmission is subject to variability in the genome of the primary mosquito vector, Aedes aegypti. The “vectorial capacity” of A. aegypti varies depending upon its density, biting rate, and survival rate, as well as its intrinsic ability to acquire, host and transmit a given arbovirus. This intrinsic ability is known as “vector competence”. Based on whole transcriptome analysis, several genes and pathways have been predicated to have an association with a susceptible or refractory response in A. aegypti to DENV infection. However, the functional genomics of vector competence of A. aegypti is not well understood, primarily due to lack of integrative approaches in genomic or transcriptomic studies. In this review, we focus on the present status of genomics studies of DENV vector competence in A. aegypti as limited information is available relative to the other arboviruses. We propose future areas of research needed to facilitate the integration of vector and virus genomics and environmental factors to work towards better understanding of vector competence and vectorial capacity in natural conditions. PMID:27809220

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

PubMed Central

Beruvides, Gerardo

2017-01-01

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions. PMID:28906450

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

2017-09-14

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

Prediction of plant pre-microRNAs and their microRNAs in genome-scale sequences using structure-sequence features and support vector machine.

PubMed

Meng, Jun; Liu, Dong; Sun, Chao; Luan, Yushi

2014-12-30

MicroRNAs (miRNAs) are a family of non-coding RNAs approximately 21 nucleotides in length that play pivotal roles at the post-transcriptional level in animals, plants and viruses. These molecules silence their target genes by degrading transcription or suppressing translation. Studies have shown that miRNAs are involved in biological responses to a variety of biotic and abiotic stresses. Identification of these molecules and their targets can aid the understanding of regulatory processes. Recently, prediction methods based on machine learning have been widely used for miRNA prediction. However, most of these methods were designed for mammalian miRNA prediction, and few are available for predicting miRNAs in the pre-miRNAs of specific plant species. Although the complete Solanum lycopersicum genome has been published, only 77 Solanum lycopersicum miRNAs have been identified, far less than the estimated number. Therefore, it is essential to develop a prediction method based on machine learning to identify new plant miRNAs. A novel classification model based on a support vector machine (SVM) was trained to identify real and pseudo plant pre-miRNAs together with their miRNAs. An initial set of 152 novel features related to sequential structures was used to train the model. By applying feature selection, we obtained the best subset of 47 features for use with the Back Support Vector Machine-Recursive Feature Elimination (B-SVM-RFE) method for the classification of plant pre-miRNAs. Using this method, 63 features were obtained for plant miRNA classification. We then developed an integrated classification model, miPlantPreMat, which comprises MiPlantPre and MiPlantMat, to identify plant pre-miRNAs and their miRNAs. This model achieved approximately 90% accuracy using plant datasets from nine plant species, including Arabidopsis thaliana, Glycine max, Oryza sativa, Physcomitrella patens, Medicago truncatula, Sorghum bicolor, Arabidopsis lyrata, Zea mays and Solanum lycopersicum. Using miPlantPreMat, 522 Solanum lycopersicum miRNAs were identified in the Solanum lycopersicum genome sequence. We developed an integrated classification model, miPlantPreMat, based on structure-sequence features and SVM. MiPlantPreMat was used to identify both plant pre-miRNAs and the corresponding mature miRNAs. An improved feature selection method was proposed, resulting in high classification accuracy, sensitivity and specificity.

Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data

PubMed Central

Tran, Truyen; Luo, Wei; Phung, Dinh; Venkatesh, Svetha

2016-01-01

Background: Modeling patient flow is crucial in understanding resource demand and prioritization. We study patient outflow from an open ward in an Australian hospital, where currently bed allocation is carried out by a manager relying on past experiences and looking at demand. Automatic methods that provide a reasonable estimate of total next-day discharges can aid in efficient bed management. The challenges in building such methods lie in dealing with large amounts of discharge noise introduced by the nonlinear nature of hospital procedures, and the nonavailability of real-time clinical information in wards. Objective Our study investigates different models to forecast the total number of next-day discharges from an open ward having no real-time clinical data. Methods We compared 5 popular regression algorithms to model total next-day discharges: (1) autoregressive integrated moving average (ARIMA), (2) the autoregressive moving average with exogenous variables (ARMAX), (3) k-nearest neighbor regression, (4) random forest regression, and (5) support vector regression. Although the autoregressive integrated moving average model relied on past 3-month discharges, nearest neighbor forecasting used median of similar discharges in the past in estimating next-day discharge. In addition, the ARMAX model used the day of the week and number of patients currently in ward as exogenous variables. For the random forest and support vector regression models, we designed a predictor set of 20 patient features and 88 ward-level features. Results Our data consisted of 12,141 patient visits over 1826 days. Forecasting quality was measured using mean forecast error, mean absolute error, symmetric mean absolute percentage error, and root mean square error. When compared with a moving average prediction model, all 5 models demonstrated superior performance with the random forests achieving 22.7% improvement in mean absolute error, for all days in the year 2014. Conclusions In the absence of clinical information, our study recommends using patient-level and ward-level data in predicting next-day discharges. Random forest and support vector regression models are able to use all available features from such data, resulting in superior performance over traditional autoregressive methods. An intelligent estimate of available beds in wards plays a crucial role in relieving access block in emergency departments. PMID:27444059

VISPA2: a scalable pipeline for high-throughput identification and annotation of vector integration sites.

PubMed

Spinozzi, Giulio; Calabria, Andrea; Brasca, Stefano; Beretta, Stefano; Merelli, Ivan; Milanesi, Luciano; Montini, Eugenio

2017-11-25

Bioinformatics tools designed to identify lentiviral or retroviral vector insertion sites in the genome of host cells are used to address the safety and long-term efficacy of hematopoietic stem cell gene therapy applications and to study the clonal dynamics of hematopoietic reconstitution. The increasing number of gene therapy clinical trials combined with the increasing amount of Next Generation Sequencing data, aimed at identifying integration sites, require both highly accurate and efficient computational software able to correctly process "big data" in a reasonable computational time. Here we present VISPA2 (Vector Integration Site Parallel Analysis, version 2), the latest optimized computational pipeline for integration site identification and analysis with the following features: (1) the sequence analysis for the integration site processing is fully compliant with paired-end reads and includes a sequence quality filter before and after the alignment on the target genome; (2) an heuristic algorithm to reduce false positive integration sites at nucleotide level to reduce the impact of Polymerase Chain Reaction or trimming/alignment artifacts; (3) a classification and annotation module for integration sites; (4) a user friendly web interface as researcher front-end to perform integration site analyses without computational skills; (5) the time speedup of all steps through parallelization (Hadoop free). We tested VISPA2 performances using simulated and real datasets of lentiviral vector integration sites, previously obtained from patients enrolled in a hematopoietic stem cell gene therapy clinical trial and compared the results with other preexisting tools for integration site analysis. On the computational side, VISPA2 showed a > 6-fold speedup and improved precision and recall metrics (1 and 0.97 respectively) compared to previously developed computational pipelines. These performances indicate that VISPA2 is a fast, reliable and user-friendly tool for integration site analysis, which allows gene therapy integration data to be handled in a cost and time effective fashion. Moreover, the web access of VISPA2 ( http://openserver.itb.cnr.it/vispa/ ) ensures accessibility and ease of usage to researches of a complex analytical tool. We released the source code of VISPA2 in a public repository ( https://bitbucket.org/andreacalabria/vispa2 ).

Practical Integration-Free Episomal Methods for Generating Human Induced Pluripotent Stem Cells.

PubMed

Kime, Cody; Rand, Tim A; Ivey, Kathryn N; Srivastava, Deepak; Yamanaka, Shinya; Tomoda, Kiichiro

2015-10-06

The advent of induced pluripotent stem (iPS) cell technology has revolutionized biomedicine and basic research by yielding cells with embryonic stem (ES) cell-like properties. The use of iPS-derived cells for cell-based therapies and modeling of human disease holds great potential. While the initial description of iPS cells involved overexpression of four transcription factors via viral vectors that integrated within genomic DNA, advances in recent years by our group and others have led to safer and higher quality iPS cells with greater efficiency. Here, we describe commonly practiced methods for non-integrating induced pluripotent stem cell generation using nucleofection of episomal reprogramming plasmids. These methods are adapted from recent studies that demonstrate increased hiPS cell reprogramming efficacy with the application of three powerful episomal hiPS cell reprogramming factor vectors and the inclusion of an accessory vector expressing EBNA1. Copyright © 2015 John Wiley & Sons, Inc.

Modulating ectopic gene expression levels by using retroviral vectors equipped with synthetic promoters.

PubMed

Ferreira, Joshua P; Peacock, Ryan W S; Lawhorn, Ingrid E B; Wang, Clifford L

2011-12-01

The human cytomegalovirus and elongation factor 1α promoters are constitutive promoters commonly employed by mammalian expression vectors. These promoters generally produce high levels of expression in many types of cells and tissues. To generate a library of synthetic promoters capable of generating a range of low, intermediate, and high expression levels, the TATA and CAAT box elements of these promoters were mutated. Other promoter variants were also generated by random mutagenesis. Evaluation using plasmid vectors integrated at a single site in the genome revealed that these various synthetic promoters were capable of expression levels spanning a 40-fold range. Retroviral vectors were equipped with the synthetic promoters and evaluated for their ability to reproduce the graded expression demonstrated by plasmid integration. A vector with a self-inactivating long terminal repeat could neither reproduce the full range of expression levels nor produce stable expression. Using a second vector design, the different synthetic promoters enabled stable expression over a broad range of expression levels in different cell lines. The online version of this article (doi:10.1007/s11693-011-9089-0) contains supplementary material, which is available to authorized users.

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

PubMed

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

2013-01-01

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

Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

PubMed

Munsell, B C; Wu, G; Fridriksson, J; Thayer, K; Mofrad, N; Desisto, N; Shen, D; Bonilha, L

2017-09-09

Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks that support naming ability. Importantly, naming is frequently impaired in other neurological disorders and by contrasting the neuronal structures supporting naming in TLE with other diseases, it will become possible to elucidate the common systems supporting naming. We aimed to evaluate the neuronal networks that support naming in TLE by using a machine learning algorithm intended to predict naming performance in subjects with medication refractory TLE using only the structural brain connectome reconstructed from diffusion tensor imaging. A connectome-based prediction framework was developed using network properties from anatomically defined brain regions across the entire brain, which were used in a multi-task machine learning algorithm followed by support vector regression. Nodal eigenvector centrality, a measure of regional network integration, predicted approximately 60% of the variance in naming. The nodes with the highest regression weight were bilaterally distributed among perilimbic sub-networks involving mainly the medial and lateral temporal lobe regions. In the context of emerging evidence regarding the role of large structural networks that support language processing, our results suggest intact naming relies on the integration of sub-networks, as opposed to being dependent on isolated brain areas. In the case of TLE, these sub-networks may be disproportionately indicative naming processes that are dependent semantic integration from memory and lexical retrieval, as opposed to multi-modal perception or motor speech production. Copyright © 2017. Published by Elsevier Inc.

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

DTIC Science & Technology

2013-05-28

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

Consolidating tactical planning and implementation frameworks for integrated vector management in Uganda.

PubMed

Okia, Michael; Okui, Peter; Lugemwa, Myers; Govere, John M; Katamba, Vincent; Rwakimari, John B; Mpeka, Betty; Chanda, Emmanuel

2016-04-14

Integrated vector management (IVM) is the recommended approach for controlling some vector-borne diseases (VBD). In the face of current challenges to disease vector control, IVM is vital to achieve national targets set for VBD control. Though global efforts, especially for combating malaria, now focus on elimination and eradication, IVM remains useful for Uganda which is principally still in the control phase of the malaria continuum. This paper outlines the processes undertaken to consolidate tactical planning and implementation frameworks for IVM in Uganda. The Uganda National Malaria Control Programme with its efforts to implement an IVM approach to vector control was the 'case' for this study. Integrated management of malaria vectors in Uganda remained an underdeveloped component of malaria control policy. In 2012, knowledge and perceptions of malaria vector control policy and IVM were assessed, and recommendations for a specific IVM policy were made. In 2014, a thorough vector control needs assessment (VCNA) was conducted according to WHO recommendations. The findings of the VCNA informed the development of the national IVM strategic guidelines. Information sources for this study included all available data and accessible archived documentary records on VBD control in Uganda. The literature was reviewed and adapted to the local context and translated into the consolidated tactical framework. WHO recommends implementation of IVM as the main strategy to vector control and has encouraged member states to adopt the approach. However, many VBD-endemic countries lack IVM policy frameworks to guide implementation of the approach. In Uganda most VBD coexists and could be managed more effectively if done in tandem. In order to successfully control malaria and other VBD and move towards their elimination, the country needs to scale up proven and effective vector control interventions and also learn from the experience of other countries. The IVM strategy is important in consolidating inter-sectoral collaboration and coordination and providing the tactical direction for effective deployment of vector control interventions along the five key elements of the approach and to align them with contemporary epidemiology of VBD in the country. Uganda has successfully established an evidence-based IVM approach and consolidated strategic planning and operational frameworks for VBD control. However, operating implementation arrangements as outlined in the national strategic guidelines for IVM and managing insecticide resistance, as well as improving vector surveillance, are imperative. In addition, strengthened information, education and communication/behaviour change and communication, collaboration and coordination will be crucial in scaling up and using vector control interventions.

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.

Numerical Simulations of Light Bullets, Using The Full Vector, Time Dependent, Nonlinear Maxwell Equations

NASA Technical Reports Server (NTRS)

Goorjian, Peter M.; Silberberg, Yaron; Kwak, Dochan (Technical Monitor)

1994-01-01

This paper will present results in computational nonlinear optics. An algorithm will be described that solves the full vector nonlinear Maxwell's equations exactly without the approximations that are currently made. Present methods solve a reduced scalar wave equation, namely the nonlinear Schrodinger equation, and neglect the optical carrier. Also, results will be shown of calculations of 2-D electromagnetic nonlinear waves computed by directly integrating in time the nonlinear vector Maxwell's equations. The results will include simulations of 'light bullet' like pulses. Here diffraction and dispersion will be counteracted by nonlinear effects. The time integration efficiently implements linear and nonlinear convolutions for the electric polarization, and can take into account such quantum effects as Kerr and Raman interactions. The present approach is robust and should permit modeling 2-D and 3-D optical soliton propagation, scattering, and switching directly from the full-vector Maxwell's equations.

Gene Therapy with the Sleeping Beauty Transposon System.

PubMed

Kebriaei, Partow; Izsvák, Zsuzsanna; Narayanavari, Suneel A; Singh, Harjeet; Ivics, Zoltán

2017-11-01

The widespread clinical implementation of gene therapy requires the ability to stably integrate genetic information through gene transfer vectors in a safe, effective, and economical manner. The latest generation of Sleeping Beauty (SB) transposon vectors fulfills these requirements, and may overcome limitations associated with viral gene transfer vectors and transient nonviral gene delivery approaches that are prevalent in ongoing clinical trials. The SB system enables high-level stable gene transfer and sustained transgene expression in multiple primary human somatic cell types, thereby representing a highly attractive gene transfer strategy for clinical use. Here, we review the most important aspects of using SB for gene therapy, including vectorization as well as genomic integration features. We also illustrate the path to successful clinical implementation by highlighting the application of chimeric antigen receptor (CAR)-modified T cells in cancer immunotherapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Numerical Simulations of Light Bullets, Using The Full Vector, Time Dependent, Nonlinear Maxwell Equations

NASA Technical Reports Server (NTRS)

Goorjian, Peter M.; Silberberg, Yaron; Kwak, Dochan (Technical Monitor)

1995-01-01

This paper will present results in computational nonlinear optics. An algorithm will be described that solves the full vector nonlinear Maxwell's equations exactly without the approximations that we currently made. Present methods solve a reduced scalar wave equation, namely the nonlinear Schrodinger equation, and neglect the optical carrier. Also, results will be shown of calculations of 2-D electromagnetic nonlinear waves computed by directly integrating in time the nonlinear vector Maxwell's equations. The results will include simulations of 'light bullet' like pulses. Here diffraction and dispersion will be counteracted by nonlinear effects. The time integration efficiently implements linear and nonlinear convolutions for the electric polarization, and can take into account such quantum effects as Karr and Raman interactions. The present approach is robust and should permit modeling 2-D and 3-D optical soliton propagation, scattering, and switching directly from the full-vector Maxwell's equations.

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.

Generalized vector calculus on convex domain

NASA Astrophysics Data System (ADS)

Agrawal, Om P.; Xu, Yufeng

2015-06-01

In this paper, we apply recently proposed generalized integral and differential operators to develop generalized vector calculus and generalized variational calculus for problems defined over a convex domain. In particular, we present some generalization of Green's and Gauss divergence theorems involving some new operators, and apply these theorems to generalized variational calculus. For fractional power kernels, the formulation leads to fractional vector calculus and fractional variational calculus for problems defined over a convex domain. In special cases, when certain parameters take integer values, we obtain formulations for integer order problems. Two examples are presented to demonstrate applications of the generalized variational calculus which utilize the generalized vector calculus developed in the paper. The first example leads to a generalized partial differential equation and the second example leads to a generalized eigenvalue problem, both in two dimensional convex domains. We solve the generalized partial differential equation by using polynomial approximation. A special case of the second example is a generalized isoperimetric problem. We find an approximate solution to this problem. Many physical problems containing integer order integrals and derivatives are defined over arbitrary domains. We speculate that future problems containing fractional and generalized integrals and derivatives in fractional mechanics will be defined over arbitrary domains, and therefore, a general variational calculus incorporating a general vector calculus will be needed for these problems. This research is our first attempt in that direction.

Vector-model-supported approach in prostate plan optimization

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

Liu, Eva Sau Fan; Department of Health Technology and Informatics, The Hong Kong Polytechnic University; Wu, Vincent Wing Cheung

Lengthy time consumed in traditional manual plan optimization can limit the use of step-and-shoot intensity-modulated radiotherapy/volumetric-modulated radiotherapy (S&S IMRT/VMAT). A vector model base, retrieving similar radiotherapy cases, was developed with respect to the structural and physiologic features extracted from the Digital Imaging and Communications in Medicine (DICOM) files. Planning parameters were retrieved from the selected similar reference case and applied to the test case to bypass the gradual adjustment of planning parameters. Therefore, the planning time spent on the traditional trial-and-error manual optimization approach in the beginning of optimization could be reduced. Each S&S IMRT/VMAT prostate reference database comprised 100more » previously treated cases. Prostate cases were replanned with both traditional optimization and vector-model-supported optimization based on the oncologists' clinical dose prescriptions. A total of 360 plans, which consisted of 30 cases of S&S IMRT, 30 cases of 1-arc VMAT, and 30 cases of 2-arc VMAT plans including first optimization and final optimization with/without vector-model-supported optimization, were compared using the 2-sided t-test and paired Wilcoxon signed rank test, with a significance level of 0.05 and a false discovery rate of less than 0.05. For S&S IMRT, 1-arc VMAT, and 2-arc VMAT prostate plans, there was a significant reduction in the planning time and iteration with vector-model-supported optimization by almost 50%. When the first optimization plans were compared, 2-arc VMAT prostate plans had better plan quality than 1-arc VMAT plans. The volume receiving 35 Gy in the femoral head for 2-arc VMAT plans was reduced with the vector-model-supported optimization compared with the traditional manual optimization approach. Otherwise, the quality of plans from both approaches was comparable. Vector-model-supported optimization was shown to offer much shortened planning time and iteration number without compromising the plan quality.« less

A helper virus-free HSV-1 vector containing the vesicular glutamate transporter-1 promoter supports expression preferentially in VGLUT1-containing glutamatergic neurons.

PubMed

Zhang, Guo-rong; Geller, Alfred I

2010-05-17

Multiple potential uses of direct gene transfer into neurons require restricting expression to specific classes of glutamatergic neurons. Thus, it is desirable to develop vectors containing glutamatergic class-specific promoters. The three vesicular glutamate transporters (VGLUTs) are expressed in distinct populations of neurons, and VGLUT1 is the predominant VGLUT in the neocortex, hippocampus, and cerebellar cortex. We previously reported a plasmid (amplicon) Herpes Simplex Virus (HSV-1) vector that placed the Lac Z gene under the regulation of the VGLUT1 promoter (pVGLUT1lac). Using helper virus-free vector stocks, we showed that this vector supported approximately 90% glutamatergic neuron-specific expression in postrhinal (POR) cortex, in rats sacrificed at either 4 days or 2 months after gene transfer. We now show that pVGLUT1lac supports expression preferentially in VGLUT1-containing glutamatergic neurons. pVGLUT1lac vector stock was injected into either POR cortex, which contains primarily VGLUT1-containing glutamatergic neurons, or into the ventral medial hypothalamus (VMH), which contains predominantly VGLUT2-containing glutamatergic neurons. Rats were sacrificed at 4 days after gene transfer, and the types of cells expressing ss-galactosidase were determined by immunofluorescent costaining. Cell counts showed that pVGLUT1lac supported expression in approximately 10-fold more cells in POR cortex than in the VMH, whereas a control vector supported expression in similar numbers of cells in these two areas. Further, in POR cortex, pVGLUT1lac supported expression predominately in VGLUT1-containing neurons, and, in the VMH, pVGLUT1lac showed an approximately 10-fold preference for the rare VGLUT1-containing neurons. VGLUT1-specific expression may benefit specific experiments on learning or specific gene therapy approaches, particularly in the neocortex. Copyright 2010 Elsevier B.V. All rights reserved.

Biological and Clinical Characterization of Novel lncRNAs Associated with Metastatic Prostate Cancer

DTIC Science & Technology

2015-11-01

R. Bedenis, N. McGregor, T. Ma, W. Chen, S. Han, X. Jing, X. Cao, X. Wang, B. Chandler, W. Yan, J . Siddiqui, L.P. Kunju, S.M. Dhanasekaran, K.J...antagonizes the SWI/SNF complex. Nat Genet 2013;45: 1392–8. 8. Tomlins SA, Aubin SM, Siddiqui J , Lonigro RJ, Sefton-Miller L, Miick S, et al. Urine TMPRSS2...support vector machine. Nucleic Acids Res 2007;35:W345–9. 13. Yu J , Mani RS, Cao Q, Brenner CJ, Cao X, Wang X, et al. An integrated network of androgen

High-order distance-based multiview stochastic learning in image classification.

PubMed

Yu, Jun; Rui, Yong; Tang, Yuan Yan; Tao, Dacheng

2014-12-01

How do we find all images in a larger set of images which have a specific content? Or estimate the position of a specific object relative to the camera? Image classification methods, like support vector machine (supervised) and transductive support vector machine (semi-supervised), are invaluable tools for the applications of content-based image retrieval, pose estimation, and optical character recognition. However, these methods only can handle the images represented by single feature. In many cases, different features (or multiview data) can be obtained, and how to efficiently utilize them is a challenge. It is inappropriate for the traditionally concatenating schema to link features of different views into a long vector. The reason is each view has its specific statistical property and physical interpretation. In this paper, we propose a high-order distance-based multiview stochastic learning (HD-MSL) method for image classification. HD-MSL effectively combines varied features into a unified representation and integrates the labeling information based on a probabilistic framework. In comparison with the existing strategies, our approach adopts the high-order distance obtained from the hypergraph to replace pairwise distance in estimating the probability matrix of data distribution. In addition, the proposed approach can automatically learn a combination coefficient for each view, which plays an important role in utilizing the complementary information of multiview data. An alternative optimization is designed to solve the objective functions of HD-MSL and obtain different views on coefficients and classification scores simultaneously. Experiments on two real world datasets demonstrate the effectiveness of HD-MSL in image classification.

Bacteriophage-based Vectors for Site-specific Insertion of DNA in the Chromosome of Corynebacteria

PubMed Central

Oram, Mark; Woolston, Joelle E.; Jacobson, Andrew D.; Holmes, Randall K.; Oram, Diana M.

2007-01-01

In Corynebacterium diphtheriae, diphtheria toxin is encoded by the tox gene of some temperate corynephages such as β. β-like corynephages are capable of inserting into the C. diphtheriae chromosome at two specific sites, attB1 and attB2. Transcription of the phage-encoded tox gene, and many chromosomally-encoded genes, is regulated by the DtxR protein in response to Fe2+ levels. Characterizing DtxR-dependent gene regulation is pivotal in understanding diphtheria pathogenesis and mechanisms of iron-dependent gene expression; although this has been hampered by a lack of molecular genetic tools in C. diphtheriae and related Coryneform species. To expand the systems for genetic manipulation of C. diphtheriae, we constructed plasmid vectors capable of integrating into the chromosome. These plasmids contain the β-encoded attP site and the DIP0182 integrase gene of C. diphtheriae NCTC13129. When these vectors were delivered to the cytoplasm of non-lysogenic C. diphtheriae, they integrated into either the attB1 or attB2 sites with comparable frequency. Lysogens were also transformed with these vectors, by virtue of the second attB site. An integrated vector carrying an intact dtxR gene complemented the mutant phenotypes of a C. diphtheriae ΔdtxR strain. Additionally, strains of β-susceptible C. ulcerans, and C. glutamicum, a species non-permissive for β, were each transformed with these vectors. This work significantly extends the tools available for targeted transformation of both pathogenic and non-pathogenic Corynebacterium species. PMID:17275217

Sustainable dengue prevention and control through a comprehensive integrated approach: the Sri Lankan perspective.

PubMed

Tissera, Hasitha; Pannila-Hetti, Nimalka; Samaraweera, Preshila; Weeraman, Jayantha; Palihawadana, Paba; Amarasinghe, Ananda

2016-09-01

Dengue is a leading public health problem in Sri Lanka. All 26 districts and all age groups are affected, with high disease transmission; the estimated average annual incidence is 175/100 000 population. Harnessing the World Health Organization Global strategy for dengue prevention and control, 2012-2020, Sri Lanka has pledged in its National Strategic Framework to achieve a mortality from dengue below 0.1% and to reduce morbidity by 50% (from the average of the last 5 years) by 2020. Turning points in the country's dengue-control programme have been the restructuring and restrategizing of the core functions; this has involved establishment of a separate dengue-control unit to coordinate integrated vector management, and creation of a presidential task force. There has been great progress in disease surveillance, clinical management and vector control. Enhanced real-time surveillance for early warning allows ample preparedness for an outbreak. National guidelines with enhanced diagnostics have significantly improved clinical management of dengue, reducing the case-fatality rate to 0.2%. Proactive integrated vector management, with multisector partnership, has created a positive vector-control environment; however, sustaining this momentum is a challenge. Robust surveillance, evidence-based clinical management, sustainable vector control and effective communication are key strategies that will be implemented to achieve set targets. Improved early detection and a standardized treatment protocol with enhanced diagnostics at all medical care institutions will lead to further reduction in mortality. Making the maximum effort to minimize outbreaks through sustainable vector control in the three dimensions of risk mapping, innovation and risk modification will enable a reduction in morbidity.

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Finite element area and line integral transforms for generalization of aperture function and geometry in Kirchhoff scalar diffraction theory

NASA Astrophysics Data System (ADS)

Kraus, Hal G.

1993-02-01

Two finite element-based methods for calculating Fresnel region and near-field region intensities resulting from diffraction of light by two-dimensional apertures are presented. The first is derived using the Kirchhoff area diffraction integral and the second is derived using a displaced vector potential to achieve a line integral transformation. The specific form of each of these formulations is presented for incident spherical waves and for Gaussian laser beams. The geometry of the two-dimensional diffracting aperture(s) is based on biquadratic isoparametric elements, which are used to define apertures of complex geometry. These elements are also used to build complex amplitude and phase functions across the aperture(s), which may be of continuous or discontinuous form. The finite element transform integrals are accurately and efficiently integrated numerically using Gaussian quadrature. The power of these methods is illustrated in several examples which include secondary obstructions, secondary spider supports, multiple mirror arrays, synthetic aperture arrays, apertures covered by screens, apodization, phase plates, and off-axis apertures. Typically, the finite element line integral transform results in significant gains in computational efficiency over the finite element Kirchhoff transform method, but is also subject to some loss in generality.

Characterization of genetic elements required for site-specific integration of Lactobacillus delbrueckii subsp. bulgaricus bacteriophage mv4 and construction of an integration-proficient vector for Lactobacillus plantarum.

PubMed Central

Dupont, L; Boizet-Bonhoure, B; Coddeville, M; Auvray, F; Ritzenthaler, P

1995-01-01

Temperate phage mv4 integrates its DNA into the chromosome of Lactobacillus delbrueckii subsp. bulgaricus strains via site-specific recombination. Nucleotide sequencing of a 2.2-kb attP-containing phage fragment revealed the presence of four open reading frames. The larger open reading frame, close to the attP site, encoded a 427-amino-acid polypeptide with similarity in its C-terminal domain to site-specific recombinases of the integrase family. Comparison of the sequences of attP, bacterial attachment site attB, and host-phage junctions attL and attR identified a 17-bp common core sequence, where strand exchange occurs during recombination. Analysis of the attB sequence indicated that the core region overlaps the 3' end of a tRNA(Ser) gene. Phage mv4 DNA integration into the tRNA(Ser) gene preserved an intact tRNA(Ser) gene at the attL site. An integration vector based on the mv4 attP site and int gene was constructed. This vector transforms a heterologous host, L. plantarum, through site-specific integration into the tRNA(Ser) gene of the genome and will be useful for development of an efficient integration system for a number of additional bacterial species in which an identical tRNA gene is present. PMID:7836291

Explicit time integration of finite element models on a vectorized, concurrent computer with shared memory

NASA Technical Reports Server (NTRS)

Gilbertsen, Noreen D.; Belytschko, Ted

1990-01-01

The implementation of a nonlinear explicit program on a vectorized, concurrent computer with shared memory is described and studied. The conflict between vectorization and concurrency is described and some guidelines are given for optimal block sizes. Several example problems are summarized to illustrate the types of speed-ups which can be achieved by reprogramming as compared to compiler optimization.

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

NASA Astrophysics Data System (ADS)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

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

Mathematical support for automated geometry analysis of lathe machining of oblique peakless round-nose tools

NASA Astrophysics Data System (ADS)

Filippov, A. V.; Tarasov, S. Yu; Podgornyh, O. A.; Shamarin, N. N.; Filippova, E. O.

2017-01-01

Automatization of engineering processes requires developing relevant mathematical support and a computer software. Analysis of metal cutting kinematics and tool geometry is a necessary key task at the preproduction stage. This paper is focused on developing a procedure for determining the geometry of oblique peakless round-nose tool lathe machining with the use of vector/matrix transformations. Such an approach allows integration into modern mathematical software packages in distinction to the traditional analytic description. Such an advantage is very promising for developing automated control of the preproduction process. A kinematic criterion for the applicable tool geometry has been developed from the results of this study. The effect of tool blade inclination and curvature on the geometry-dependent process parameters was evaluated.

Standardized Metadata for Human Pathogen/Vector Genomic Sequences

PubMed Central

Dugan, Vivien G.; Emrich, Scott J.; Giraldo-Calderón, Gloria I.; Harb, Omar S.; Newman, Ruchi M.; Pickett, Brett E.; Schriml, Lynn M.; Stockwell, Timothy B.; Stoeckert, Christian J.; Sullivan, Dan E.; Singh, Indresh; Ward, Doyle V.; Yao, Alison; Zheng, Jie; Barrett, Tanya; Birren, Bruce; Brinkac, Lauren; Bruno, Vincent M.; Caler, Elizabet; Chapman, Sinéad; Collins, Frank H.; Cuomo, Christina A.; Di Francesco, Valentina; Durkin, Scott; Eppinger, Mark; Feldgarden, Michael; Fraser, Claire; Fricke, W. Florian; Giovanni, Maria; Henn, Matthew R.; Hine, Erin; Hotopp, Julie Dunning; Karsch-Mizrachi, Ilene; Kissinger, Jessica C.; Lee, Eun Mi; Mathur, Punam; Mongodin, Emmanuel F.; Murphy, Cheryl I.; Myers, Garry; Neafsey, Daniel E.; Nelson, Karen E.; Nierman, William C.; Puzak, Julia; Rasko, David; Roos, David S.; Sadzewicz, Lisa; Silva, Joana C.; Sobral, Bruno; Squires, R. Burke; Stevens, Rick L.; Tallon, Luke; Tettelin, Herve; Wentworth, David; White, Owen; Will, Rebecca; Wortman, Jennifer; Zhang, Yun; Scheuermann, Richard H.

2014-01-01

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium’s minimal information (MIxS) and NCBI’s BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant. PMID:24936976

Heterogeneous Feeding Patterns of the Dengue Vector, Aedes aegypti, on Individual Human Hosts in Rural Thailand

PubMed Central

Harrington, Laura C.; Fleisher, Andrew; Ruiz-Moreno, Diego; Vermeylen, Francoise; Wa, Chrystal V.; Poulson, Rebecca L.; Edman, John D.; Clark, John M.; Jones, James W.; Kitthawee, Sangvorn; Scott, Thomas W.

2014-01-01

Background Mosquito biting frequency and how bites are distributed among different people can have significant epidemiologic effects. An improved understanding of mosquito vector-human interactions would refine knowledge of the entomological processes supporting pathogen transmission and could reveal targets for minimizing risk and breaking pathogen transmission cycles. Methodology and principal findings We used human DNA blood meal profiling of the dengue virus (DENV) vector, Aedes aegypti, to quantify its contact with human hosts and to infer epidemiologic implications of its blood feeding behavior. We determined the number of different people bitten, biting frequency by host age, size, mosquito age, and the number of times each person was bitten. Of 3,677 engorged mosquitoes collected and 1,186 complete DNA profiles, only 420 meals matched people from the study area, indicating that Ae. aegypti feed on people moving transiently through communities to conduct daily business. 10–13% of engorged mosquitoes fed on more than one person. No biting rate differences were detected between high- and low-dengue transmission seasons. We estimate that 43–46% of engorged mosquitoes bit more than one person within each gonotrophic cycle. Most multiple meals were from residents of the mosquito collection house or neighbors. People ≤25 years old were bitten less often than older people. Some hosts were fed on frequently, with three hosts bitten nine times. Interaction networks for mosquitoes and humans revealed biologically significant blood feeding hotspots, including community marketplaces. Conclusion and significance High multiple-feeding rates and feeding on community visitors are likely important features in the efficient transmission and rapid spread of DENV. These results help explain why reducing vector populations alone is difficult for dengue prevention and support the argument for additional studies of mosquito feeding behavior, which when integrated with a greater understanding of human behavior will refine estimates of risk and strategies for dengue control. PMID:25102306

Standardized metadata for human pathogen/vector genomic sequences.

PubMed

Dugan, Vivien G; Emrich, Scott J; Giraldo-Calderón, Gloria I; Harb, Omar S; Newman, Ruchi M; Pickett, Brett E; Schriml, Lynn M; Stockwell, Timothy B; Stoeckert, Christian J; Sullivan, Dan E; Singh, Indresh; Ward, Doyle V; Yao, Alison; Zheng, Jie; Barrett, Tanya; Birren, Bruce; Brinkac, Lauren; Bruno, Vincent M; Caler, Elizabet; Chapman, Sinéad; Collins, Frank H; Cuomo, Christina A; Di Francesco, Valentina; Durkin, Scott; Eppinger, Mark; Feldgarden, Michael; Fraser, Claire; Fricke, W Florian; Giovanni, Maria; Henn, Matthew R; Hine, Erin; Hotopp, Julie Dunning; Karsch-Mizrachi, Ilene; Kissinger, Jessica C; Lee, Eun Mi; Mathur, Punam; Mongodin, Emmanuel F; Murphy, Cheryl I; Myers, Garry; Neafsey, Daniel E; Nelson, Karen E; Nierman, William C; Puzak, Julia; Rasko, David; Roos, David S; Sadzewicz, Lisa; Silva, Joana C; Sobral, Bruno; Squires, R Burke; Stevens, Rick L; Tallon, Luke; Tettelin, Herve; Wentworth, David; White, Owen; Will, Rebecca; Wortman, Jennifer; Zhang, Yun; Scheuermann, Richard H

2014-01-01

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium's minimal information (MIxS) and NCBI's BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant.

High-level recombinant protein expression in transgenic plants by using a double-inducible viral vector

PubMed Central

Werner, Stefan; Breus, Oksana; Symonenko, Yuri; Marillonnet, Sylvestre; Gleba, Yuri

2011-01-01

We describe here a unique ethanol-inducible process for expression of recombinant proteins in transgenic plants. The process is based on inducible release of viral RNA replicons from stably integrated DNA proreplicons. A simple treatment with ethanol releases the replicon leading to RNA amplification and high-level protein production. To achieve tight control of replicon activation and spread in the uninduced state, the viral vector has been deconstructed, and its two components, the replicon and the cell-to-cell movement protein, have each been placed separately under the control of an inducible promoter. Transgenic Nicotiana benthamiana plants incorporating this double-inducible system demonstrate negligible background expression, high (over 0.5 × 104-fold) induction multiples, and high absolute levels of protein expression upon induction (up to 4.3 mg/g fresh biomass). The process can be easily scaled up, supports expression of practically important recombinant proteins, and thus can be directly used for industrial manufacturing. PMID:21825158

A novel packaging system for the generation of helper-free oncolytic MVM vector stocks.

PubMed

Brandenburger, A; Russell, S

1996-10-01

MVM-based autonomous parvoviral vectors have been shown to target the expression of heterologous genes in neoplastic cells and are therefore of interest for cancer gene therapy. The traditional method for production of parvoviral vectors requires the cotransfection of vector and helper plasmids into MVM-permissive cell lines, but recombination between the cotransfected plasmids invariably gives rise to vector stocks that are heavily contaminated with wild-type MVM. Therefore, to minimise recombination between the vector and helper genomes we have utilised a cell line in which the MVM helper functions are expressed inducibly from a modified MVM genome that is stably integrated into the host cell chromosome. Using this MVM packaging cell line, we could reproducibly generate MVM vector stocks that contained no detectable helper virus.

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

PubMed

Gürtler, Ricardo E; Yadon, Zaida E

2015-02-01

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

Preclinical development of BCG.HIVA2auxo.int, harboring an integrative expression vector, for a HIV-TB Pediatric vaccine. Enhancement of stability and specific HIV-1 T-cell immunity.

PubMed

Mahant, Aakash; Saubi, Narcís; Eto, Yoshiki; Guitart, Núria; Gatell, Josep Ma; Hanke, Tomáš; Joseph, Joan

2017-08-03

One of the critical issues that should be addressed in the development of a BCG-based HIV vaccine is genetic plasmid stability. Therefore, to address this issue we have considered using integrative vectors and the auxotrophic mutant of BCG complemented with a plasmid carrying a wild-type complementing gene. In this study, we have constructed an integrative E. coli-mycobacterial shuttle plasmid, p2auxo.HIVA int , expressing the HIV-1 clade A immunogen HIVA. This shuttle vector uses an antibiotic resistance-free mechanism for plasmid selection and maintenance. It was first transformed into a glycine auxotrophic E. coli strain and subsequently transformed into a lysine auxotrophic Mycobacterium bovis BCG strain to generate the vaccine BCG.HIVA 2auxo.int . Presence of the HIVA gene sequence and protein expression was confirmed. We demonstrated that the in vitro stability of the integrative plasmid p2auxo.HIVA int was increased 4-fold, as compared with the BCG strain harboring the episomal plasmid, and was genetically and phenotypically characterized. The BCG.HIVA 2auxo.int vaccine in combination with modified vaccinia virus Ankara (MVA).HIVA was found to be safe and induced HIV-1 and Mycobacterium tuberculosis-specific interferon-γ-producing T-cell responses in adult BALB/c mice. We have engineered a more stable and immunogenic BCG-vectored vaccine using the prototype immunogen HIVA. Thus, the use of integrative expression vectors and the antibiotic-free plasmid selection system based on "double" auxotrophic complementation are likely to improve the mycobacterial vaccine stability in vivo and immunogenicity to develop not only recombinant BCG-based vaccines expressing second generation of HIV-1 immunogens but also other major pediatric pathogens to prime protective responses shortly following birth.

High-efficiency transformation of Pichia stipitis based on its URA3 gene and a homologous autonomous replication sequence, ARS2.

PubMed Central

Yang, V W; Marks, J A; Davis, B P; Jeffries, T W

1994-01-01

This paper describes the first high-efficiency transformation system for the xylose-fermenting yeast Pichia stipitis. The system includes integrating and autonomously replicating plasmids based on the gene for orotidine-5'-phosphate decarboxylase (URA3) and an autonomous replicating sequence (ARS) element (ARS2) isolated from P. stipitis CBS 6054. Ura- auxotrophs were obtained by selecting for resistance to 5-fluoroorotic acid and were identified as ura3 mutants by transformation with P. stipitis URA3. P. stipitis URA3 was cloned by its homology to Saccharomyces cerevisiae URA3, with which it is 69% identical in the coding region. P. stipitis ARS elements were cloned functionally through plasmid rescue. These sequences confer autonomous replication when cloned into vectors bearing the P. stipitis URA3 gene. P. stipitis ARS2 has features similar to those of the consensus ARS of S. cerevisiae and other ARS elements. Circular plasmids bearing the P. stipitis URA3 gene with various amounts of flanking sequences produced 600 to 8,600 Ura+ transformants per micrograms of DNA by electroporation. Most transformants obtained with circular vectors arose without integration of vector sequences. One vector yielded 5,200 to 12,500 Ura+ transformants per micrograms of DNA after it was linearized at various restriction enzyme sites within the P. stipitis URA3 insert. Transformants arising from linearized vectors produced stable integrants, and integration events were site specific for the genomic ura3 in 20% of the transformants examined. Plasmids bearing the P. stipitis URA3 gene and ARS2 element produced more than 30,000 transformants per micrograms of plasmid DNA. Autonomously replicating plasmids were stable for at least 50 generations in selection medium and were present at an average of 10 copies per nucleus. Images PMID:7811063

Integration of celestial compass cues in the central complex of the locust brain.

PubMed

Pegel, Uta; Pfeiffer, Keram; Homberg, Uwe

2018-01-29

Many insects rely on celestial compass cues such as the polarization pattern of the sky for spatial orientation. In the desert locust, the central complex (CX) houses multiple sets of neurons, sensitive to the oscillation plane of polarized light and thus probably acts as an internal polarization compass. We investigated whether other sky compass cues like direct sunlight or the chromatic gradient of the sky might contribute to this compass. We recorded from polarization-sensitive CX neurons while an unpolarized green or ultraviolet light spot was moved around the head of the animal. All types of neuron that were sensitive to the plane of polarization ( E -vector) above the animal also responded to the unpolarized light spots in an azimuth-dependent way. The tuning to the unpolarized light spots was independent of wavelength, suggesting that the neurons encode solar azimuth based on direct sunlight and not on the sky chromatic gradient. Two cell types represented the natural 90 deg relationship between solar azimuth and zenithal E -vector orientation, providing evidence to suggest that solar azimuth information supports the internal polarization compass. Most neurons showed advances in their tuning to the E -vector and the unpolarized light spots dependent on rotation direction, consistent with anticipatory signaling. The amplitude of responses and its variability were dependent on the level of background firing, possibly indicating different internal states. The integration of polarization and solar azimuth information strongly suggests that besides the polarization pattern of the sky, direct sunlight might be an important cue for sky compass navigation in the locust. © 2018. Published by The Company of Biologists Ltd.

Vector analogues of the Maggi-Rubinowicz theory of edge diffraction

NASA Astrophysics Data System (ADS)

Meneghini, R.; Shu, P.; Bay, J.

1980-10-01

The Maggi-Rubinowicz technique for scalar and electromagnetic fields is interpreted as a transformation of an integral over an open surface to a line integral around its rim. Maggi-Rubinowicz analogues are found for several vector physical optics representations. For diffraction from a circular aperture, a numerical comparison between these formulations shows the two methods are in agreement. To circumvent certain convergence difficulties in the Maggi-Rubinowicz integrals that occur as the observer approaches the shadow boundary, a variable mesh integration is used. For the examples considered, where the ratio of the aperture diameter to wavelength is about ten, the Maggi-Rubinowicz formulation yields an 8 to 10 fold decrease in computation time relative to the physical optics formulation.

Vector analogues of the Maggi-Rubinowicz theory of edge diffraction

NASA Technical Reports Server (NTRS)

Meneghini, R.; Shu, P.; Bay, J.

1980-01-01

The Maggi-Rubinowicz technique for scalar and electromagnetic fields is interpreted as a transformation of an integral over an open surface to a line integral around its rim. Maggi-Rubinowicz analogues are found for several vector physical optics representations. For diffraction from a circular aperture, a numerical comparison between these formulations shows the two methods are in agreement. To circumvent certain convergence difficulties in the Maggi-Rubinowicz integrals that occur as the observer approaches the shadow boundary, a variable mesh integration is used. For the examples considered, where the ratio of the aperture diameter to wavelength is about ten, the Maggi-Rubinowicz formulation yields an 8 to 10 fold decrease in computation time relative to the physical optics formulation.

Analysis of near-field components of a plasmonic optical antenna and their contribution to quantum dot infrared photodetector enhancement.

PubMed

Gu, Guiru; Vaillancourt, Jarrod; Lu, Xuejun

2014-10-20

In this paper, we analyze near-field vector components of a metallic circular disk array (MCDA) plasmonic optical antenna and their contribution to quantum dot infrared photodetector (QDIP) enhancement. The near-field vector components of the MCDA optical antenna and their distribution in the QD active region are simulated. The near-field overlap integral with the QD active region is calculated at different wavelengths and compared with the QDIP enhancement spectrum. The x-component (E(x)) of the near-field vector shows a larger intensity overlap integral and stronger correlation with the QDIP enhancement than E(z) and thus is determined to be the major near-field component to the QDIP enhancement.

The derivation of vector magnetic fields from Stokes profiles - Integral versus least squares fitting techniques

NASA Technical Reports Server (NTRS)

Ronan, R. S.; Mickey, D. L.; Orrall, F. Q.

1987-01-01

The results of two methods for deriving photospheric vector magnetic fields from the Zeeman effect, as observed in the Fe I line at 6302.5 A at high spectral resolution (45 mA), are compared. The first method does not take magnetooptical effects into account, but determines the vector magnetic field from the integral properties of the Stokes profiles. The second method is an iterative least-squares fitting technique which fits the observed Stokes profiles to the profiles predicted by the Unno-Rachkovsky solution to the radiative transfer equation. For sunspot fields above about 1500 gauss, the two methods are found to agree in derived azimuthal and inclination angles to within about + or - 20 deg.

Identifying saltcedar with hyperspectral data and support vector machines

USDA-ARS?s Scientific Manuscript database

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

Remarks towards the spectrum of the Heisenberg spin chain type models

NASA Astrophysics Data System (ADS)

Burdík, Č.; Fuksa, J.; Isaev, A. P.; Krivonos, S. O.; Navrátil, O.

2015-05-01

The integrable close and open chain models can be formulated in terms of generators of the Hecke algebras. In this review paper, we describe in detail the Bethe ansatz for the XXX and the XXZ integrable close chain models. We find the Bethe vectors for two-component and inhomogeneous models. We also find the Bethe vectors for the fermionic realization of the integrable XXX and XXZ close chain models by means of the algebraic and coordinate Bethe ansatz. Special modification of the XXZ closed spin chain model ("small polaron model") is considered. Finally, we discuss some questions relating to the general open Hecke chain models.

Real Time Data Management for Estimating Probabilities of Incidents and Near Misses

NASA Astrophysics Data System (ADS)

Stanitsas, P. D.; Stephanedes, Y. J.

2011-08-01

Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use strategies at complex intersections and motorways remain. These are related to increasing system performance in identification, analysis, detection and prediction of traffic state in real time. This research develops dynamic models to estimate the probability of road incidents, such as crashes and conflicts, and incident-prone conditions based on real-time data. The models support integration of anticipatory information and fee-based road use strategies in traveller information and management. Development includes macroscopic/microscopic probabilistic models, neural networks, and vector autoregressions tested via machine vision at EU and US sites.

MIRO and IRbase: IT Tools for the Epidemiological Monitoring of Insecticide Resistance in Mosquito Disease Vectors

PubMed Central

Dialynas, Emmanuel; Topalis, Pantelis; Vontas, John; Louis, Christos

2009-01-01

Background Monitoring of insect vector populations with respect to their susceptibility to one or more insecticides is a crucial element of the strategies used for the control of arthropod-borne diseases. This management task can nowadays be achieved more efficiently when assisted by IT (Information Technology) tools, ranging from modern integrated databases to GIS (Geographic Information System). Here we describe an application ontology that we developed de novo, and a specially designed database that, based on this ontology, can be used for the purpose of controlling mosquitoes and, thus, the diseases that they transmit. Methodology/Principal Findings The ontology, named MIRO for Mosquito Insecticide Resistance Ontology, developed using the OBO-Edit software, describes all pertinent aspects of insecticide resistance, including specific methodology and mode of action. MIRO, then, forms the basis for the design and development of a dedicated database, IRbase, constructed using open source software, which can be used to retrieve data on mosquito populations in a temporally and spatially separate way, as well as to map the output using a Google Earth interface. The dependency of the database on the MIRO allows for a rational and efficient hierarchical search possibility. Conclusions/Significance The fact that the MIRO complies with the rules set forward by the OBO (Open Biomedical Ontologies) Foundry introduces cross-referencing with other biomedical ontologies and, thus, both MIRO and IRbase are suitable as parts of future comprehensive surveillance tools and decision support systems that will be used for the control of vector-borne diseases. MIRO is downloadable from and IRbase is accessible at VectorBase, the NIAID-sponsored open access database for arthropod vectors of disease. PMID:19547750

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints.

PubMed

Klamt, Steffen; Regensburger, Georg; Gerstl, Matthias P; Jungreuthmayer, Christian; Schuster, Stefan; Mahadevan, Radhakrishnan; Zanghellini, Jürgen; Müller, Stefan

2017-04-01

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints

PubMed Central

Klamt, Steffen; Gerstl, Matthias P.; Jungreuthmayer, Christian; Mahadevan, Radhakrishnan; Müller, Stefan

2017-01-01

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks. PMID:28406903

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Heterogeneous data fusion and intelligent techniques embedded in a mobile application for real-time chronic disease management.

PubMed

Bellos, Christos; Papadopoulos, Athanassios; Rosso, Roberto; Fotiadis, Dimitrios I

2011-01-01

CHRONIOUS system is an integrated platform aiming at the management of chronic disease patients. One of the most important components of the system is a Decision Support System (DSS) that has been developed in a Smart Device (SD). This component decides on patient's current health status by combining several data, which are acquired either by wearable sensors or manually inputted by the patient or retrieved from the specific database. In case no abnormal situation has been tracked, the DSS takes no action and remains deactivated until next abnormal situation pack of data are being acquired or next scheduled data being transmitted. The DSS that has been implemented is an integrated classification system with two parallel classifiers, combining an expert system (rule-based system) and a supervised classifier, such as Support Vector Machines (SVM), Random Forests, artificial Neural Networks (aNN like the Multi-Layer Perceptron), Decision Trees and Naïve Bayes. The above categorized system is useful for providing critical information about the health status of the patient.

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.

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

PubMed Central

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

2013-01-01

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

Developing a local least-squares support vector machines-based neuro-fuzzy model for nonlinear and chaotic time series prediction.

PubMed

Miranian, A; Abdollahzade, M

2013-02-01

Local modeling approaches, owing to their ability to model different operating regimes of nonlinear systems and processes by independent local models, seem appealing for modeling, identification, and prediction applications. In this paper, we propose a local neuro-fuzzy (LNF) approach based on the least-squares support vector machines (LSSVMs). The proposed LNF approach employs LSSVMs, which are powerful in modeling and predicting time series, as local models and uses hierarchical binary tree (HBT) learning algorithm for fast and efficient estimation of its parameters. The HBT algorithm heuristically partitions the input space into smaller subdomains by axis-orthogonal splits. In each partitioning, the validity functions automatically form a unity partition and therefore normalization side effects, e.g., reactivation, are prevented. Integration of LSSVMs into the LNF network as local models, along with the HBT learning algorithm, yield a high-performance approach for modeling and prediction of complex nonlinear time series. The proposed approach is applied to modeling and predictions of different nonlinear and chaotic real-world and hand-designed systems and time series. Analysis of the prediction results and comparisons with recent and old studies demonstrate the promising performance of the proposed LNF approach with the HBT learning algorithm for modeling and prediction of nonlinear and chaotic systems and time series.

Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).

PubMed

Poil, S-S; Bollmann, S; Ghisleni, C; O'Gorman, R L; Klaver, P; Ball, J; Eich-Höchli, D; Brandeis, D; Michels, L

2014-08-01

Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification. This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value. ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67% and specificity of 83% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers. Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood. Spectral biomarkers may have both diagnostic and prognostic value. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Assessing the performance of multiple spectral-spatial features of a hyperspectral image for classification of urban land cover classes using support vector machines and artificial neural network

NASA Astrophysics Data System (ADS)

Pullanagari, Reddy; Kereszturi, Gábor; Yule, Ian J.; Ghamisi, Pedram

2017-04-01

Accurate and spatially detailed mapping of complex urban environments is essential for land managers. Classifying high spectral and spatial resolution hyperspectral images is a challenging task because of its data abundance and computational complexity. Approaches with a combination of spectral and spatial information in a single classification framework have attracted special attention because of their potential to improve the classification accuracy. We extracted multiple features from spectral and spatial domains of hyperspectral images and evaluated them with two supervised classification algorithms; support vector machines (SVM) and an artificial neural network. The spatial features considered are produced by a gray level co-occurrence matrix and extended multiattribute profiles. All of these features were stacked, and the most informative features were selected using a genetic algorithm-based SVM. After selecting the most informative features, the classification model was integrated with a segmentation map derived using a hidden Markov random field. We tested the proposed method on a real application of a hyperspectral image acquired from AisaFENIX and on widely used hyperspectral images. From the results, it can be concluded that the proposed framework significantly improves the results with different spectral and spatial resolutions over different instrumentation.

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

PubMed

Dropulic, Boro

2005-07-01

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

Data integration modeling applied to drill hole planning through semi-supervised learning: A case study from the Dalli Cu-Au porphyry deposit in the central Iran

NASA Astrophysics Data System (ADS)

Fatehi, Moslem; Asadi, Hooshang H.

2017-04-01

In this study, the application of a transductive support vector machine (TSVM), an innovative semi-supervised learning algorithm, has been proposed for mapping the potential drill targets at a detailed exploration stage. The semi-supervised learning method is a hybrid of supervised and unsupervised learning approach that simultaneously uses both training and non-training data to design a classifier. By using the TSVM algorithm, exploration layers at the Dalli porphyry Cu-Au deposit in the central Iran were integrated to locate the boundary of the Cu-Au mineralization for further drilling. By applying this algorithm on the non-training (unlabeled) and limited training (labeled) Dalli exploration data, the study area was classified in two domains of Cu-Au ore and waste. Then, the results were validated by the earlier block models created, using the available borehole and trench data. In addition to TSVM, the support vector machine (SVM) algorithm was also implemented on the study area for comparison. Thirty percent of the labeled exploration data was used to evaluate the performance of these two algorithms. The results revealed 87 percent correct recognition accuracy for the TSVM algorithm and 82 percent for the SVM algorithm. The deepest inclined borehole, recently drilled in the western part of the Dalli deposit, indicated that the boundary of Cu-Au mineralization, as identified by the TSVM algorithm, was only 15 m off from the actual boundary intersected by this borehole. According to the results of the TSVM algorithm, six new boreholes were suggested for further drilling at the Dalli deposit. This study showed that the TSVM algorithm could be a useful tool for enhancing the mineralization zones and consequently, ensuring a more accurate drill hole planning.

Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.

PubMed

Hettige, Nuwan C; Nguyen, Thai Binh; Yuan, Chen; Rajakulendran, Thanara; Baddour, Jermeen; Bhagwat, Nikhil; Bani-Fatemi, Ali; Voineskos, Aristotle N; Mallar Chakravarty, M; De Luca, Vincenzo

2017-07-01

Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integration of many risk factors in order to build an algorithm that predicts which patients are likely to attempt suicide. Currently it is unclear how to integrate previously identified risk factors into a clinically relevant predictive tool to estimate the probability of a patient with schizophrenia for attempting suicide. We conducted a cross-sectional assessment on a sample of 345 participants diagnosed with schizophrenia spectrum disorders. Suicide attempters and non-attempters were clearly identified using the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Suicide Ideation Scale (BSS). We developed four classification algorithms using a regularized regression, random forest, elastic net and support vector machine models with sociocultural and clinical variables as features to train the models. All classification models performed similarly in identifying suicide attempters and non-attempters. Our regularized logistic regression model demonstrated an accuracy of 67% and an area under the curve (AUC) of 0.71, while the random forest model demonstrated 66% accuracy and an AUC of 0.67. Support vector classifier (SVC) model demonstrated an accuracy of 67% and an AUC of 0.70, and the elastic net model demonstrated and accuracy of 65% and an AUC of 0.71. Machine learning algorithms offer a relatively successful method for incorporating many clinical features to predict individuals at risk for future suicide attempts. Increased performance of these models using clinically relevant variables offers the potential to facilitate early treatment and intervention to prevent future suicide attempts. Copyright © 2017 Elsevier Inc. All rights reserved.

Development and Testing of a Dual Accelerometer Vector Sensor for AUV Acoustic Surveys †

PubMed Central

Mantouka, Agni; Felisberto, Paulo; Santos, Paulo; Zabel, Friedrich; Saleiro, Mário; Jesus, Sérgio M.; Sebastião, Luís

2017-01-01

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of the WiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS has the potential to contribute to this aim in various ways, for example, owing to its spatial filtering capability, it may reduce the amount of post processing by discriminating the bottom from the surface reflections. Additionally, its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The present paper is focused on results related to acoustic wave azimuth estimation as an example of its spatial filtering capabilities. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. Sensitivity and directionality of these three sensors were measured in a tank, whilst the direction estimation capabilities of the accelerometers paired with the hydrophone, forming a vector sensor, were evaluated on a Medusa Class AUV, which was sailing around a deployed sound source. Results of these measurements are presented in this paper. PMID:28594342

Development and Testing of a Dual Accelerometer Vector Sensor for AUV Acoustic Surveys.

PubMed

Mantouka, Agni; Felisberto, Paulo; Santos, Paulo; Zabel, Friedrich; Saleiro, Mário; Jesus, Sérgio M; Sebastião, Luís

2017-06-08

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of the WiMUST project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS has the potential to contribute to this aim in various ways, for example, owing to its spatial filtering capability, it may reduce the amount of post processing by discriminating the bottom from the surface reflections. Additionally, its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The present paper is focused on results related to acoustic wave azimuth estimation as an example of its spatial filtering capabilities. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. Sensitivity and directionality of these three sensors were measured in a tank, whilst the direction estimation capabilities of the accelerometers paired with the hydrophone, forming a vector sensor, were evaluated on a Medusa Class AUV, which was sailing around a deployed sound source. Results of these measurements are presented in this paper.

Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Transient Expression of an LEDGF/p75 Chimera Retargets Lentivector Integration and Functionally Rescues in a Model for X-CGD

PubMed Central

Vets, Sofie; De Rijck, Jan; Brendel, Christian; Grez, Manuel; Bushman, Frederic; Debyser, Zeger; Gijsbers, Rik

2013-01-01

Retrovirus-based vectors are commonly used as delivery vehicles to correct genetic diseases because of their ability to integrate new sequences stably. However, adverse events in which vector integration activates proto-oncogenes, leading to clonal expansion and leukemogenesis hamper their application. The host cell-encoded lens epithelium-derived growth factor (LEDGF/p75) binds lentiviral integrase and targets integration to active transcription units. We demonstrated earlier that replacing the LEDGF/p75 chromatin interaction domain with an alternative DNA-binding protein could retarget integration. Here, we show that transient expression of the chimeric protein using mRNA electroporation efficiently redirects lentiviral vector (LV) integration in wild-type (WT) cells. We then employed this technology in a model for X-linked chronic granulomatous disease (X-CGD) using myelomonocytic PLB-985 gp91−/− cells. Following electroporation with mRNA encoding the LEDGF-chimera, the cells were treated with a therapeutic lentivector encoding gp91phox. Integration site analysis revealed retargeted integration away from genes and towards heterochromatin-binding protein 1β (CBX1)-binding sites, in regions enriched in marks associated with gene silencing. Nevertheless, gp91phox expression was stable for at least 6 months after electroporation and NADPH-oxidase activity was restored to normal levels as determined by superoxide production. Together, these data provide proof-of-principle that transient expression of engineered LEDGF-chimera can retarget lentivector integration and rescues the disease phenotype in a cell model, opening perspectives for safer gene therapy. PMID:23462964

Integrated metatranscriptomics and metaproteomics for the characterization of bacterial microbiota in unfed Ixodes ricinus.

PubMed

Hernández-Jarguín, Angélica; Díaz-Sánchez, Sandra; Villar, Margarita; de la Fuente, José

2018-05-05

An innovative metaomics approach integrating metatranscriptomics and metaproteomics was used to characterize bacterial communities in the microbiota of the Lyme borreliosis spirochete vector, Ixodes ricinus (Acari: Ixodidae). Whole internal tissues and salivary glands from unfed larvae and female ticks, respectively were used. Reused I. ricinus RNA-sequencing data for metranscriptomics analysis together with metaproteomics provided a better characterization of tick bacterial microbiota by increasing bacteria identification and support for identified bacteria with putative functional implications. The results showed the presence of symbiotic, commensal, soil, environmental, and pathogenic bacteria in the I. ricinus microbiota, including previously unrecognized commensal and soil microorganisms. The results of the metaomics approach may have implications in the characterization of putative mechanisms by which pathogen infection manipulates tick microbiota to facilitate infection. Metaomics approaches integrating different omics datasets would provide a better description of tick microbiota compositions, and insights into tick interactions with microbiota, pathogens and hosts. Copyright © 2018 Elsevier GmbH. All rights reserved.

Implementation of Malaria Dynamic Models in Municipality Level Early Warning Systems in Colombia. Part I: Description of Study Sites

PubMed Central

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M.; Quiñónes, Martha L.; Jiménez, Mónica M.; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J.; Thomson, Madeleine C.

2014-01-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. PMID:24891460

Integral control of plant gravitropism through the interplay of hormone signaling and gene regulation.

PubMed

Rodrigo, Guillermo; Jaramillo, Alfonso; Blázquez, Miguel A

2011-08-17

The interplay between hormone signaling and gene regulatory networks is instrumental in promoting the development of living organisms. In particular, plants have evolved mechanisms to sense gravity and orient themselves accordingly. Here, we present a mathematical model that reproduces plant gravitropic responses based on known molecular genetic interactions for auxin signaling coupled with a physical description of plant reorientation. The model allows one to analyze the spatiotemporal dynamics of the system, triggered by an auxin gradient that induces differential growth of the plant with respect to the gravity vector. Our model predicts two important features with strong biological implications: 1), robustness of the regulatory circuit as a consequence of integral control; and 2), a higher degree of plasticity generated by the molecular interplay between two classes of hormones. Our model also predicts the ability of gibberellins to modulate the tropic response and supports the integration of the hormonal role at the level of gene regulation. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Applying spectral unmixing and support vector machine to airborne hyperspectral imagery for detecting giant reed

USDA-ARS?s Scientific Manuscript database

This study evaluated linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and support vector machine (SVM) techniques for detecting and mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern ...

Support vector machines classifiers of physical activities in preschoolers

USDA-ARS?s Scientific Manuscript database

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

Fabric wrinkle characterization and classification using modified wavelet coefficients and optimized support-vector-machine classifier

USDA-ARS?s Scientific Manuscript database

This paper presents a novel wrinkle evaluation method that uses modified wavelet coefficients and an optimized support-vector-machine (SVM) classification scheme to characterize and classify wrinkle appearance of fabric. Fabric images were decomposed with the wavelet transform (WT), and five parame...

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

EPA Science Inventory

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

Determination of elementary first integrals of a generalized Raychaudhuri equation by the Darboux integrability method

NASA Astrophysics Data System (ADS)

Choudhury, A. Ghose; Guha, Partha; Khanra, Barun

2009-10-01

The Darboux integrability method is particularly useful to determine first integrals of nonplanar autonomous systems of ordinary differential equations, whose associated vector fields are polynomials. In particular, we obtain first integrals for a variant of the generalized Raychaudhuri equation, which has appeared in string inspired modern cosmology.

Alpharetroviral self-inactivating vectors produced by a superinfection-resistant stable packaging cell line allow genetic modification of primary human T lymphocytes.

PubMed

Labenski, Verena; Suerth, Julia D; Barczak, Elke; Heckl, Dirk; Levy, Camille; Bernadin, Ornellie; Charpentier, Emmanuelle; Williams, David A; Fehse, Boris; Verhoeyen, Els; Schambach, Axel

2016-08-01

Primary human T lymphocytes represent an important cell population for adoptive immunotherapies, including chimeric-antigen and T-cell receptor applications, as they have the capability to eliminate non-self, virus-infected and tumor cells. Given the increasing numbers of clinical immunotherapy applications, the development of an optimal vector platform for genetic T lymphocyte engineering, which allows cost-effective high-quality vector productions, remains a critical goal. Alpharetroviral self-inactivating vectors (ARV) have several advantages compared to other vector platforms, including a more random genomic integration pattern and reduced likelihood for inducing aberrant splicing of integrated proviruses. We developed an ARV platform for the transduction of primary human T lymphocytes. We demonstrated functional transgene transfer using the clinically relevant herpes-simplex-virus thymidine kinase variant TK.007. Proof-of-concept of alpharetroviral-mediated T-lymphocyte engineering was shown in vitro and in a humanized transplantation model in vivo. Furthermore, we established a stable, human alpharetroviral packaging cell line in which we deleted the entry receptor (SLC1A5) for RD114/TR-pseudotyped ARVs to prevent superinfection and enhance genomic integrity of the packaging cell line and viral particles. We showed that superinfection can be entirely prevented, while maintaining high recombinant virus titers. Taken together, this resulted in an improved production platform representing an economic strategy for translating the promising features of ARVs for therapeutic T-lymphocyte engineering. Copyright © 2016 Elsevier Ltd. All rights reserved.

Integration of the shallow water equations on the sphere using a vector semi-Lagrangian scheme with a multigrid solver

NASA Technical Reports Server (NTRS)

Bates, J. R.; Semazzi, F. H. M.; Higgins, R. W.; Barros, Saulo R. M.

1990-01-01

A vector semi-Lagrangian semi-implicit two-time-level finite-difference integration scheme for the shallow water equations on the sphere is presented. A C-grid is used for the spatial differencing. The trajectory-centered discretization of the momentum equation in vector form eliminates pole problems and, at comparable cost, gives greater accuracy than a previous semi-Lagrangian finite-difference scheme which used a rotated spherical coordinate system. In terms of the insensitivity of the results to increasing timestep, the new scheme is as successful as recent spectral semi-Lagrangian schemes. In addition, the use of a multigrid method for solving the elliptic equation for the geopotential allows efficient integration with an operation count which, at high resolution, is of lower order than in the case of the spectral models. The properties of the new scheme should allow finite-difference models to compete with spectral models more effectively than has previously been possible.

The impact of cHS4 insulators on DNA transposon vector mobilization and silencing in retinal pigment epithelium cells.

PubMed

Sharma, Nynne; Hollensen, Anne Kruse; Bak, Rasmus O; Staunstrup, Nicklas Heine; Schrøder, Lisbeth Dahl; Mikkelsen, Jacob Giehm

2012-01-01

DNA transposons have become important vectors for efficient non-viral integration of transgenes into genomic DNA. The Sleeping Beauty (SB), piggyBac (PB), and Tol2 transposable elements have distinct biological properties and currently represent the most promising transposon systems for animal transgenesis and gene therapy. A potential obstacle, however, for persistent function of integrating vectors is transcriptional repression of the element and its genetic cargo. In this study we analyze the insulating effect of the 1.2-kb 5'-HS4 chicken β-globin (cHS4) insulator element in the context of SB, PB, and Tol2 transposon vectors. By examining transgene expression from genomically inserted transposon vectors encoding a marker gene driven by a silencing-prone promoter, we detect variable levels of transcriptional silencing for the three transposon systems in retinal pigment epithelium cells. Notably, the PB system seems less vulnerable to silencing. Incorporation of cHS4 insulator sequences into the transposon vectors results in 2.2-fold and 1.5-fold increased transgene expression levels for insulated SB and PB vectors, respectively, but an improved persistency of expression was not obtained for insulated transgenes. Colony formation assays and quantitative excision assays unveil enhanced SB transposition efficiencies by the inclusion of the cHS4 element, resulting in a significant increase in the stable transfection rate for insulated SB transposon vectors in human cell lines. Our findings reveal a positive impact of cHS4 insulator inclusion for SB and PB vectors in terms of increased transgene expression levels and improved SB stable transfection rates, but also the lack of a long-term protective effect of the cHS4 insulator against progressive transgene silencing in retinal pigment epithelium cells.

The Impact of cHS4 Insulators on DNA Transposon Vector Mobilization and Silencing in Retinal Pigment Epithelium Cells

PubMed Central

Sharma, Nynne; Hollensen, Anne Kruse; Bak, Rasmus O.; Staunstrup, Nicklas Heine; Schrøder, Lisbeth Dahl; Mikkelsen, Jacob Giehm

2012-01-01

DNA transposons have become important vectors for efficient non-viral integration of transgenes into genomic DNA. The Sleeping Beauty (SB), piggyBac (PB), and Tol2 transposable elements have distinct biological properties and currently represent the most promising transposon systems for animal transgenesis and gene therapy. A potential obstacle, however, for persistent function of integrating vectors is transcriptional repression of the element and its genetic cargo. In this study we analyze the insulating effect of the 1.2-kb 5′-HS4 chicken β-globin (cHS4) insulator element in the context of SB, PB, and Tol2 transposon vectors. By examining transgene expression from genomically inserted transposon vectors encoding a marker gene driven by a silencing-prone promoter, we detect variable levels of transcriptional silencing for the three transposon systems in retinal pigment epithelium cells. Notably, the PB system seems less vulnerable to silencing. Incorporation of cHS4 insulator sequences into the transposon vectors results in 2.2-fold and 1.5-fold increased transgene expression levels for insulated SB and PB vectors, respectively, but an improved persistency of expression was not obtained for insulated transgenes. Colony formation assays and quantitative excision assays unveil enhanced SB transposition efficiencies by the inclusion of the cHS4 element, resulting in a significant increase in the stable transfection rate for insulated SB transposon vectors in human cell lines. Our findings reveal a positive impact of cHS4 insulator inclusion for SB and PB vectors in terms of increased transgene expression levels and improved SB stable transfection rates, but also the lack of a long-term protective effect of the cHS4 insulator against progressive transgene silencing in retinal pigment epithelium cells. PMID:23110238

Projected economic losses due to vector and vector-borne parasitic diseases in livestock of India and its significance in implementing the concept of integrated practices for vector management

PubMed Central

Narladkar, B. W.

2018-01-01

Broadly, species of arthropods infesting livestock are grouped into flies (biting and non-biting), fleas, lice (biting and sucking), ticks (soft and hard), and mites (burrowing, non-burrowing, and follicular). Among which, biting and non-biting flies and ticks are the potent vectors for many bacterial, viral, rickettsial, and protozoan diseases. Vectors of livestock are having economic significance on three points (1) direct losses from their bite and annoyance, worries, and psychological disturbances produced during the act of biting and feeding, (2) diseases they transmit, and (3) expenditure incurred for their control. Flies such as Culicoides spp. and Musca spp. and various species of hard ticks play important role in disease transmission in addition to their direct effects. For control of vectors, recent concept of integrated pest management (IPM) provides the best solution and also addresses the problems related to acaricide resistance and environmental protection from hazardous chemicals. However, to successfully implement the concept of IPM, for each vector species, estimation of two monitory benchmarks, i.e., economic injury level (EIL) and economic threshold level (ETL) is essential prerequisite. For many vector species and under several circumstances, estimation of EIL and ETL appears to be difficult. Under such scenario, although may not be exact, an approximate estimate can be accrued by taking into account several criteria such as percent prevalence of vectors in a geographical area, percent losses produced, total livestock population, and current prices of livestock products such as milk, meat, and wool. Method for approximate estimation is first time described and elaborated in the present review article. PMID:29657396

Impact of vectorborne parasitic neglected tropical diseases on child health.

PubMed

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

2016-07-01

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

Operational efficiency and sustainability of vector control of malaria and dengue: descriptive case studies from the Philippines

PubMed Central

2012-01-01

Background Analysis is lacking on the management of vector control systems in disease-endemic countries with respect to the efficiency and sustainability of operations. Methods Three locations were selected, at the scale of province, municipality and barangay (i.e. village). Data on disease incidence, programme activities, and programme management were collected on-site through meetings and focus group discussions. Results Adaptation of disease control strategies to the epidemiological situation per barangay, through micro-stratification, brings gains in efficiency, but should be accompanied by further capacity building on local situational analysis for better selection and targeting of vector control interventions within the barangay. An integrated approach to vector control, aiming to improve the rational use of resources, was evident with a multi-disease strategy for detection and response, and by the use of combinations of vector control methods. Collaboration within the health sector was apparent from the involvement of barangay health workers, re-orientation of job descriptions and the creation of a disease surveillance unit. The engagement of barangay leaders and use of existing community structures helped mobilize local resources and voluntary services for vector control. In one location, local authorities and the community were involved in the planning, implementation and evaluation of malaria control, which triggered local programme ownership. Conclusions Strategies that contributed to an improved efficiency and sustainability of vector control operations were: micro-stratification, integration of vector control within the health sector, a multi-disease approach, involvement of local authorities, and empowerment of communities. Capacity building on situational analysis and vector surveillance should be addressed through national policy and guidelines. PMID:22873707

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

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

Liu, Eva Sau Fan; Department of Health Technology and Informatics, The Hong Kong Polytechnic University; Wu, Vincent Wing Cheung

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, followingmore » the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.« less

Helper-dependent adenoviral vectors for liver-directed gene therapy

PubMed Central

Brunetti-Pierri, Nicola; Ng, Philip

2011-01-01

Helper-dependent adenoviral (HDAd) vectors devoid of all viral-coding sequences are promising non-integrating vectors for liver-directed gene therapy because they have a large cloning capacity, can efficiently transduce a wide variety of cell types from various species independent of the cell cycle and can result in long-term transgene expression without chronic toxicity. The main obstacle preventing clinical applications of HDAd for liver-directed gene therapy is the host innate inflammatory response against the vector capsid proteins that occurs shortly after intravascular vector administration resulting in acute toxicity, the severity of which is dependent on vector dose. Intense efforts have been focused on elucidating the factors involved in this acute response and various strategies have been investigated to improve the therapeutic index of HDAd vectors. These strategies have yielded encouraging results with the potential for clinical translation. PMID:21470977

Characterization of the spatial and temporal dynamics of the dengue vector population established in urban areas of Fernando de Noronha, a Brazilian oceanic island.

PubMed

Regis, Lêda N; Acioli, Ridelane Veiga; Silveira, José Constantino; de Melo-Santos, Maria Alice Varjal; da Cunha, Mércia Cristiane Santana; Souza, Fátima; Batista, Carlos Alberto Vieira; Barbosa, Rosângela Maria Rodrigues; de Oliveira, Cláudia Maria Fontes; Ayres, Constância Flávia Junqueira; Monteiro, Antonio Miguel Vieira; Souza, Wayner Vieira

2014-09-01

Aedes aegypti has played a major role in the dramatic expansion of dengue worldwide. The failure of control programs in reducing the rhythm of global dengue expansion through vector control suggests the need for studies to support more appropriated control strategies. We report here the results of a longitudinal study on Ae. aegypti population dynamics through continuous egg sampling aiming to characterize the infestation of urban areas of a Brazilian oceanic island, Fernando de Noronha. The spatial and temporal distribution of the dengue vector population in urban areas of the island was described using a monitoring system (SMCP-Aedes) based on a 103-trap network for Aedes egg sampling, using GIS and spatial statistics analysis tools. Mean egg densities were estimated over a 29-month period starting in 2011 and producing monthly maps of mosquito abundance. The system detected continuous Ae. aegypti oviposition in most traps. The high global positive ovitrap index (POI=83.7% of 2815 events) indicated the frequent presence of blood-fed-egg laying females at every sampling station. Egg density (eggs/ovitrap/month) reached peak values of 297.3 (0 - 2020) in May and 295 (0 - 2140) in August 2012. The presence of a stable Ae. aegypti population established throughout the inhabited areas of the island was demonstrated. A strong association between egg abundance and rainfall with a 2-month lag was observed, which combined with a first-order autocorrelation observed in the series of egg counts can provide an important forecasting tool. This first description of the characteristics of the island infestation by the dengue vector provides baseline information to analyze relationships between the spatial distribution of the vector and dengue cases, and to the development of integrated vector control strategies. Copyright © 2014 Elsevier B.V. All rights reserved.

Reverse chemical ecology approach for the identification of a mosquito oviposition attractant

USDA-ARS?s Scientific Manuscript database

Pheromones and other semiochemicals play a crucial role in today’s integrated pest and vector management strategies for controlling populations of insects causing loses to agriculture and vectoring diseases to humans. These semiochemicals are typically discovered by bioassay-guided approaches. Here,...

Test aspects of the JPL Viterbi decoder

NASA Technical Reports Server (NTRS)

Breuer, M. A.

1989-01-01

The generation of test vectors and design-for-test aspects of the Jet Propulsion Laboratory (JPL) Very Large Scale Integration (VLSI) Viterbi decoder chip is discussed. Each processor integrated circuit (IC) contains over 20,000 gates. To achieve a high degree of testability, a scan architecture is employed. The logic has been partitioned so that very few test vectors are required to test the entire chip. In addition, since several blocks of logic are replicated numerous times on this chip, test vectors need only be generated for each block, rather than for the entire circuit. These unique blocks of logic have been identified and test sets generated for them. The approach employed for testing was to use pseudo-exhaustive test vectors whenever feasible. That is, each cone of logid is tested exhaustively. Using this approach, no detailed logic design or fault model is required. All faults which modify the function of a block of combinational logic are detected, such as all irredundant single and multiple stuck-at faults.

Gene inactivation in the plant pathogen Glomerella cingulata: three strategies for the disruption of the pectin lyase gene pnlA.

PubMed

Bowen, J K; Templeton, M D; Sharrock, K R; Crowhurst, R N; Rikkerink, E H

1995-01-20

The feasibility of performing routine transformation-mediated mutagenesis in Glomerella cingulata was analysed by adopting three one-step gene disruption strategies targeted at the pectin lyase gene pnlA. The efficiencies of disruption following transformation with gene replacement- or gene truncation-disruption vectors were compared. To effect replacement-disruption, G. cingulata was transformed with a vector carrying DNA from the pnlA locus in which the majority of the coding sequence had been replaced by the gene for hygromycin B resistance. Two of the five transformants investigated contained an inactivated pnlA gene (pnlA-); both also contained ectopically integrated vector sequences. The efficacy of gene disruption by transformation with two gene truncation-disruption vectors was also assessed. Both vectors carried at 5' and 3' truncated copy of the pnlA coding sequence, adjacent to the gene for hygromycin B resistance. The promoter sequences controlling the selectable marker differed in the two vectors. In one vector the homologous G. cingulata gpdA promoter controlled hygromycin B phosphotransferase expression (homologous truncation vector), whereas in the second vector promoter elements were from the Aspergillus nidulans gpdA gene (heterologous truncation vector). Following transformation with the homologous truncation vector, nine transformants were analysed by Southern hybridisation; no transformants contained a disrupted pnlA gene. Of nineteen heterologous truncation vector transformants, three contained a disrupted pnlA gene; Southern analysis revealed single integrations of vector sequence at pnlA in two of these transformants. pnlA mRNA was not detected by Northern hybridisation in pnlA- transformants. pnlA- transformants failed to produce a PNLA protein with a pI identical to one normally detected in wild-type isolates by silver and activity staining of isoelectric focussing gels. Pathogenesis on Capsicum and apple was unaffected by disruption of the pnlA gene, indicating that the corresponding gene product, PNLA, is not essential for pathogenicity. Gene disruption is a feasible method for selectively mutating defined loci in G. cingulata for functional analysis of the corresponding gene products.

1-norm support vector novelty detection and its sparseness.

PubMed

Zhang, Li; Zhou, WeiDa

2013-12-01

This paper proposes a 1-norm support vector novelty detection (SVND) method and discusses its sparseness. 1-norm SVND is formulated as a linear programming problem and uses two techniques for inducing sparseness, or the 1-norm regularization and the hinge loss function. We also find two upper bounds on the sparseness of 1-norm SVND, or exact support vector (ESV) and kernel Gram matrix rank bounds. The ESV bound indicates that 1-norm SVND has a sparser representation model than SVND. The kernel Gram matrix rank bound can loosely estimate the sparseness of 1-norm SVND. Experimental results show that 1-norm SVND is feasible and effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics

PubMed Central

HUANG, SHUJUN; CAI, NIANGUANG; PACHECO, PEDRO PENZUTI; NARANDES, SHAVIRA; WANG, YANG; XU, WAYNE

2017-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. PMID:29275361

JPRS Report, Science & Technology, USSR: Earth Sciences

DTIC Science & Technology

1988-12-06

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

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.

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

PubMed

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

2010-01-28

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

Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates

USDA-ARS?s Scientific Manuscript database

Methods based on sequence data analysis facilitate the tracking of disease outbreaks, allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are used postfactum after an outbreak has happened. Here, we show that support vector machine a...

Support vector machine incremental learning triggered by wrongly predicted samples

NASA Astrophysics Data System (ADS)

Tang, Ting-long; Guan, Qiu; Wu, Yi-rong

2018-05-01

According to the classic Karush-Kuhn-Tucker (KKT) theorem, at every step of incremental support vector machine (SVM) learning, the newly adding sample which violates the KKT conditions will be a new support vector (SV) and migrate the old samples between SV set and non-support vector (NSV) set, and at the same time the learning model should be updated based on the SVs. However, it is not exactly clear at this moment that which of the old samples would change between SVs and NSVs. Additionally, the learning model will be unnecessarily updated, which will not greatly increase its accuracy but decrease the training speed. Therefore, how to choose the new SVs from old sets during the incremental stages and when to process incremental steps will greatly influence the accuracy and efficiency of incremental SVM learning. In this work, a new algorithm is proposed to select candidate SVs and use the wrongly predicted sample to trigger the incremental processing simultaneously. Experimental results show that the proposed algorithm can achieve good performance with high efficiency, high speed and good accuracy.

Prediction of Spirometric Forced Expiratory Volume (FEV1) Data Using Support Vector Regression

NASA Astrophysics Data System (ADS)

Kavitha, A.; Sujatha, C. M.; Ramakrishnan, S.

2010-01-01

In this work, prediction of forced expiratory volume in 1 second (FEV1) in pulmonary function test is carried out using the spirometer and support vector regression analysis. Pulmonary function data are measured with flow volume spirometer from volunteers (N=175) using a standard data acquisition protocol. The acquired data are then used to predict FEV1. Support vector machines with polynomial kernel function with four different orders were employed to predict the values of FEV1. The performance is evaluated by computing the average prediction accuracy for normal and abnormal cases. Results show that support vector machines are capable of predicting FEV1 in both normal and abnormal cases and the average prediction accuracy for normal subjects was higher than that of abnormal subjects. Accuracy in prediction was found to be high for a regularization constant of C=10. Since FEV1 is the most significant parameter in the analysis of spirometric data, it appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.

Quantum Support Vector Machine for Big Data Classification

NASA Astrophysics Data System (ADS)

Rebentrost, Patrick; Mohseni, Masoud; Lloyd, Seth

2014-09-01

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

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.

Packaging of Human Chromosome 19-Specific Adeno-Associated Virus (AAV) Integration Sites in AAV Virions during AAV Wild-Type and Recombinant AAV Vector Production

PubMed Central

Hüser, Daniela; Weger, Stefan; Heilbronn, Regine

2003-01-01

Adeno-associated virus type 2 (AAV-2) establishes latency by site-specific integration into a unique locus on human chromosome 19, called AAVS1. During the development of a sensitive real-time PCR assay for site-specific integration, AAV-AAVS1 junctions were reproducibly detected in highly purified AAV wild-type and recombinant AAV vector stocks. A series of controls documented that the junctions were packaged in AAV capsids and were newly generated during a single round of AAV production. Cloned junctions displayed variable AAV sequences fused to AAVS1. These data suggest that packaged junctions represent footprints of AAV integration during productive infection. Apparently, AAV latency established by site-specific integration and the helper virus-dependent, productive AAV cycle are more closely related than previously thought. PMID:12663794

Predicting complications of percutaneous coronary intervention using a novel support vector method.

PubMed

Lee, Gyemin; Gurm, Hitinder S; Syed, Zeeshan

2013-01-01

To explore the feasibility of a novel approach using an augmented one-class learning algorithm to model in-laboratory complications of percutaneous coronary intervention (PCI). Data from the Blue Cross Blue Shield of Michigan Cardiovascular Consortium (BMC2) multicenter registry for the years 2007 and 2008 (n=41 016) were used to train models to predict 13 different in-laboratory PCI complications using a novel one-plus-class support vector machine (OP-SVM) algorithm. The performance of these models in terms of discrimination and calibration was compared to the performance of models trained using the following classification algorithms on BMC2 data from 2009 (n=20 289): logistic regression (LR), one-class support vector machine classification (OC-SVM), and two-class support vector machine classification (TC-SVM). For the OP-SVM and TC-SVM approaches, variants of the algorithms with cost-sensitive weighting were also considered. The OP-SVM algorithm and its cost-sensitive variant achieved the highest area under the receiver operating characteristic curve for the majority of the PCI complications studied (eight cases). Similar improvements were observed for the Hosmer-Lemeshow χ(2) value (seven cases) and the mean cross-entropy error (eight cases). The OP-SVM algorithm based on an augmented one-class learning problem improved discrimination and calibration across different PCI complications relative to LR and traditional support vector machine classification. Such an approach may have value in a broader range of clinical domains.

Predicting complications of percutaneous coronary intervention using a novel support vector method

PubMed Central

Lee, Gyemin; Gurm, Hitinder S; Syed, Zeeshan

2013-01-01

Objective To explore the feasibility of a novel approach using an augmented one-class learning algorithm to model in-laboratory complications of percutaneous coronary intervention (PCI). Materials and methods Data from the Blue Cross Blue Shield of Michigan Cardiovascular Consortium (BMC2) multicenter registry for the years 2007 and 2008 (n=41 016) were used to train models to predict 13 different in-laboratory PCI complications using a novel one-plus-class support vector machine (OP-SVM) algorithm. The performance of these models in terms of discrimination and calibration was compared to the performance of models trained using the following classification algorithms on BMC2 data from 2009 (n=20 289): logistic regression (LR), one-class support vector machine classification (OC-SVM), and two-class support vector machine classification (TC-SVM). For the OP-SVM and TC-SVM approaches, variants of the algorithms with cost-sensitive weighting were also considered. Results The OP-SVM algorithm and its cost-sensitive variant achieved the highest area under the receiver operating characteristic curve for the majority of the PCI complications studied (eight cases). Similar improvements were observed for the Hosmer–Lemeshow χ2 value (seven cases) and the mean cross-entropy error (eight cases). Conclusions The OP-SVM algorithm based on an augmented one-class learning problem improved discrimination and calibration across different PCI complications relative to LR and traditional support vector machine classification. Such an approach may have value in a broader range of clinical domains. PMID:23599229

LDA boost classification: boosting by topics

NASA Astrophysics Data System (ADS)

Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li

2012-12-01

AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.

Integrating machine learning to achieve an automatic parameter prediction for practical continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Liu, Weiqi; Huang, Peng; Peng, Jinye; Fan, Jianping; Zeng, Guihua

2018-02-01

For supporting practical quantum key distribution (QKD), it is critical to stabilize the physical parameters of signals, e.g., the intensity, phase, and polarization of the laser signals, so that such QKD systems can achieve better performance and practical security. In this paper, an approach is developed by integrating a support vector regression (SVR) model to optimize the performance and practical security of the QKD system. First, a SVR model is learned to precisely predict the time-along evolutions of the physical parameters of signals. Second, such predicted time-along evolutions are employed as feedback to control the QKD system for achieving the optimal performance and practical security. Finally, our proposed approach is exemplified by using the intensity evolution of laser light and a local oscillator pulse in the Gaussian modulated coherent state QKD system. Our experimental results have demonstrated three significant benefits of our SVR-based approach: (1) it can allow the QKD system to achieve optimal performance and practical security, (2) it does not require any additional resources and any real-time monitoring module to support automatic prediction of the time-along evolutions of the physical parameters of signals, and (3) it is applicable to any measurable physical parameter of signals in the practical QKD system.

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform.

PubMed

Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader

2012-09-01

In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Auto and hetero-associative memory using a 2-D optical logic gate

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor)

1992-01-01

An optical system for auto-associative and hetero-associative recall utilizing Hamming distance as the similarity measure between a binary input image vector V(sup k) and a binary image vector V(sup m) in a first memory array using an optical Exclusive-OR gate for multiplication of each of a plurality of different binary image vectors in memory by the input image vector. After integrating the light of each product V(sup k) x V(sup m), a shortest Hamming distance detection electronics module determines which product has the lowest light intensity and emits a signal that activates a light emitting diode to illuminate a corresponding image vector in a second memory array for display. That corresponding image vector is identical to the memory image vector V(sup m) in the first memory array for auto-associative recall or related to it, such as by name, for hetero-associative recall.

Minimum impulse three-body trajectories.

NASA Technical Reports Server (NTRS)

D'Amario, L.; Edelbaum, T. N.

1973-01-01

A rapid and accurate method of calculating optimal impulsive transfers in the restricted problem of three bodies has been developed. The technique combines a multi-conic method of trajectory integration with primer vector theory and an accelerated gradient method of trajectory optimization. A unique feature is that the state transition matrix and the primer vector are found analytical without additional integrations or differentiations. The method has been applied to the determination of optimal two and three impulse transfers between the L2 libration point and circular orbits about both the earth and the moon.

Transient Expression of an LEDGF/p75 Chimera Retargets Lentivector Integration and Functionally Rescues in a Model for X-CGD.

PubMed

Vets, Sofie; De Rijck, Jan; Brendel, Christian; Grez, Manuel; Bushman, Frederic; Debyser, Zeger; Gijsbers, Rik

2013-03-05

Retrovirus-based vectors are commonly used as delivery vehicles to correct genetic diseases because of their ability to integrate new sequences stably. However, adverse events in which vector integration activates proto-oncogenes, leading to clonal expansion and leukemogenesis hamper their application. The host cell-encoded lens epithelium-derived growth factor (LEDGF/p75) binds lentiviral integrase and targets integration to active transcription units. We demonstrated earlier that replacing the LEDGF/p75 chromatin interaction domain with an alternative DNA-binding protein could retarget integration. Here, we show that transient expression of the chimeric protein using mRNA electroporation efficiently redirects lentiviral vector (LV) integration in wild-type (WT) cells. We then employed this technology in a model for X-linked chronic granulomatous disease (X-CGD) using myelomonocytic PLB-985 gp91(-/-) cells. Following electroporation with mRNA encoding the LEDGF-chimera, the cells were treated with a therapeutic lentivector encoding gp91(phox). Integration site analysis revealed retargeted integration away from genes and towards heterochromatin-binding protein 1β (CBX1)-binding sites, in regions enriched in marks associated with gene silencing. Nevertheless, gp91(phox) expression was stable for at least 6 months after electroporation and NADPH-oxidase activity was restored to normal levels as determined by superoxide production. Together, these data provide proof-of-principle that transient expression of engineered LEDGF-chimera can retarget lentivector integration and rescues the disease phenotype in a cell model, opening perspectives for safer gene therapy.Molecular Therapy - Nucleic Acids (2013) 2, e77; doi:10.1038/mtna.2013.4; published online 5 March 2013.

Visual navigation in insects: coupling of egocentric and geocentric information

PubMed

Wehner; Michel; Antonsen

1996-01-01

Social hymenopterans such as bees and ants are central-place foragers; they regularly depart from and return to fixed positions in their environment. In returning to the starting point of their foraging excursion or to any other point, they could resort to two fundamentally different ways of navigation by using either egocentric or geocentric systems of reference. In the first case, they would rely on information continuously collected en route (path integration, dead reckoning), i.e. integrate all angles steered and all distances covered into a mean home vector. In the second case, they are expected, at least by some authors, to use a map-based system of navigation, i.e. to obtain positional information by virtue of the spatial position they occupy within a larger environmental framework. In bees and ants, path integration employing a skylight compass is the predominant mechanism of navigation, but geocentred landmark-based information is used as well. This information is obtained while the animal is dead-reckoning and, hence, added to the vector course. For example, the image of the horizon skyline surrounding the nest entrance is retinotopically stored while the animal approaches the goal along its vector course. As shown in desert ants (genus Cataglyphis), there is neither interocular nor intraocular transfer of landmark information. Furthermore, this retinotopically fixed, and hence egocentred, neural snapshot is linked to an external (geocentred) system of reference. In this way, geocentred information might more and more complement and potentially even supersede the egocentred information provided by the path-integration system. In competition experiments, however, Cataglyphis never frees itself of its homeward-bound vector - its safety-line, so to speak - by which it is always linked to home. Vector information can also be transferred to a longer-lasting (higher-order) memory. There is no need to invoke the concept of the mental analogue of a topographic map - a metric map - assembled by the insect navigator. The flexible use of vectors, snapshots and landmark-based routes suffices to interpret the insect's behaviour. The cognitive-map approach in particular, and the representational paradigm in general, are discussed.

Loa loa vectors Chrysops spp.: perspectives on research, distribution, bionomics, and implications for elimination of lymphatic filariasis and onchocerciasis.

PubMed

Kelly-Hope, Louise; Paulo, Rossely; Thomas, Brent; Brito, Miguel; Unnasch, Thomas R; Molyneux, David

2017-04-05

Loiasis is a filarial disease caused Loa loa. The main vectors are Chrysops silacea and C. dimidiata which are confined to the tropical rainforests of Central and West Africa. Loiasis is a mild disease, but individuals with high microfilaria loads may suffer from severe adverse events if treated with ivermectin during mass drug administration campaigns for the elimination of lymphatic filariasis and onchocerciasis. This poses significant challenges for elimination programmes and alternative interventions are required in L. loa co-endemic areas. The control of Chrysops has not been considered as a viable cost-effective intervention; we reviewed the current knowledge of Chrysops vectors to assess the potential for control as well as identified areas for future research. We identified 89 primary published documents on the two main L. loa vectors C. silacea and C dimidiata. These were collated into a database summarising the publication, field and laboratory procedures, species distributions, ecology, habitats and methods of vector control. The majority of articles were from the 1950-1960s. Field studies conducted in Cameroon, Democratic Republic of Congo, Equatorial Guinea, Nigeria and Sudan highlighted that C. silacea is the most important and widespread vector. This species breeds in muddy streams or swampy areas of forests or plantations, descends from forest canopies to feed on humans during the day, is more readily adapted to human dwellings and attracted to wood fires. Main vector targeted measures proposed to impact on L. loa transmission included personal repellents, household screening, indoor residual spraying, community-based environmental management, adulticiding and larviciding. This is the first comprehensive review of the major L. loa vectors for several decades. It highlights key vector transmission characteristics that may be targeted for vector control providing insights into the potential for integrated vector management, with multiple diseases being targeted simultaneously, with shared human and financial resources and multiple impact. Integrated vector management programmes for filarial infections, especially in low transmission areas of onchocerciasis, require innovative approaches and alternative strategies if the elimination targets established by the World Health Organization are to be achieved.

An integrated analysis for determining the geographical origin of medicinal herbs using ICP-AES/ICP-MS and (1)H NMR analysis.

PubMed

Kwon, Yong-Kook; Bong, Yeon-Sik; Lee, Kwang-Sik; Hwang, Geum-Sook

2014-10-15

ICP-MS and (1)H NMR are commonly used to determine the geographical origin of food and crops. In this study, data from multielemental analysis performed by ICP-AES/ICP-MS and metabolomic data obtained from (1)H NMR were integrated to improve the reliability of determining the geographical origin of medicinal herbs. Astragalus membranaceus and Paeonia albiflora with different origins in Korea and China were analysed by (1)H NMR and ICP-AES/ICP-MS, and an integrated multivariate analysis was performed to characterise the differences between their origins. Four classification methods were applied: linear discriminant analysis (LDA), k-nearest neighbour classification (KNN), support vector machines (SVM), and partial least squares-discriminant analysis (PLS-DA). Results were compared using leave-one-out cross-validation and external validation. The integration of multielemental and metabolomic data was more suitable for determining geographical origin than the use of each individual data set alone. The integration of the two analytical techniques allowed diverse environmental factors such as climate and geology, to be considered. Our study suggests that an appropriate integration of different types of analytical data is useful for determining the geographical origin of food and crops with a high degree of reliability. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

Jewell, Chris P; Brown, Richard G

2015-07-06

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

Efficient generation of integration-free human induced pluripotent stem cells from keratinocytes by simple transfection of episomal vectors.

PubMed

Piao, Yulan; Hung, Sandy Shen-Chi; Lim, Shiang Y; Wong, Raymond Ching-Bong; Ko, Minoru S H

2014-07-01

Keratinocytes represent an easily accessible cell source for derivation of human induced pluripotent stem (hiPS) cells, reportedly achieving higher reprogramming efficiency than fibroblasts. However, most studies utilized a retroviral or lentiviral method for reprogramming of keratinocytes, which introduces undesirable transgene integrations into the host genome. Moreover, current protocols of generating integration-free hiPS cells from keratinocytes are mostly inefficient. In this paper, we describe a more efficient, simple-to-use, and cost-effective method for generating integration-free hiPS cells from keratinocytes. Our improved method using lipid-mediated transfection achieved a reprogramming efficiency of ∼0.14% on average. Keratinocyte-derived hiPS cells showed no integration of episomal vectors, expressed stem cell-specific markers and possessed potentials to differentiate into all three germ layers by in vitro embryoid body formation as well as in vivo teratoma formation. To our knowledge, this represents the most efficient method to generate integration-free hiPS cells from keratinocytes. ©AlphaMed Press.

Support Vector Machines: Relevance Feedback and Information Retrieval.

ERIC Educational Resources Information Center

Drucker, Harris; Shahrary, Behzad; Gibbon, David C.

2002-01-01

Compares support vector machines (SVMs) to Rocchio, Ide regular and Ide dec-hi algorithms in information retrieval (IR) of text documents using relevancy feedback. If the preliminary search is so poor that one has to search through many documents to find at least one relevant document, then SVM is preferred. Includes nine tables. (Contains 24…

Subpixel urban land cover estimation: comparing cubist, random forests, and support vector regression

Treesearch

Jeffrey T. Walton

2008-01-01

Three machine learning subpixel estimation methods (Cubist, Random Forests, and support vector regression) were applied to estimate urban cover. Urban forest canopy cover and impervious surface cover were estimated from Landsat-7 ETM+ imagery using a higher resolution cover map resampled to 30 m as training and reference data. Three different band combinations (...

Applications of Support Vector Machine (SVM) Learning in Cancer Genomics.

PubMed

Huang, Shujun; Cai, Nianguang; Pacheco, Pedro Penzuti; Narrandes, Shavira; Wang, Yang; Xu, Wayne

2018-01-01

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput technologies lead to production of large amounts of genomic and epigenomic data, the classification feature of SVMs is expanding its use in cancer genomics, leading to the discovery of new biomarkers, new drug targets, and a better understanding of cancer driver genes. Herein we reviewed the recent progress of SVMs in cancer genomic studies. We intend to comprehend the strength of the SVM learning and its future perspective in cancer genomic applications. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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%.

Object recognition of ladar with support vector machine

NASA Astrophysics Data System (ADS)

Sun, Jian-Feng; Li, Qi; Wang, Qi

2005-01-01

Intensity, range and Doppler images can be obtained by using laser radar. Laser radar can detect much more object information than other detecting sensor, such as passive infrared imaging and synthetic aperture radar (SAR), so it is well suited as the sensor of object recognition. Traditional method of laser radar object recognition is extracting target features, which can be influenced by noise. In this paper, a laser radar recognition method-Support Vector Machine is introduced. Support Vector Machine (SVM) is a new hotspot of recognition research after neural network. It has well performance on digital written and face recognition. Two series experiments about SVM designed for preprocessing and non-preprocessing samples are performed by real laser radar images, and the experiments results are compared.

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

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

Support vector machine for automatic pain recognition

NASA Astrophysics Data System (ADS)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

Techniques utilized in the simulated altitude testing of a 2D-CD vectoring and reversing nozzle

NASA Technical Reports Server (NTRS)

Block, H. Bruce; Bryant, Lively; Dicus, John H.; Moore, Allan S.; Burns, Maureen E.; Solomon, Robert F.; Sheer, Irving

1988-01-01

Simulated altitude testing of a two-dimensional, convergent-divergent, thrust vectoring and reversing exhaust nozzle was accomplished. An important objective of this test was to develop test hardware and techniques to properly operate a vectoring and reversing nozzle within the confines of an altitude test facility. This report presents detailed information on the major test support systems utilized, the operational performance of the systems and the problems encountered, and test equipment improvements recommended for future tests. The most challenging support systems included the multi-axis thrust measurement system, vectored and reverse exhaust gas collection systems, and infrared temperature measurement systems used to evaluate and monitor the nozzle. The feasibility of testing a vectoring and reversing nozzle of this type in an altitude chamber was successfully demonstrated. Supporting systems performed as required. During reverser operation, engine exhaust gases were successfully captured and turned downstream. However, a small amount of exhaust gas spilled out the collector ducts' inlet openings when the reverser was opened more than 60 percent. The spillage did not affect engine or nozzle performance. The three infrared systems which viewed the nozzle through the exhaust collection system worked remarkably well considering the harsh environment.

Adeno-Associated Virus Vectors and Stem Cells: Friends or Foes?

PubMed

Brown, Nolan; Song, Liujiang; Kollu, Nageswara R; Hirsch, Matthew L

2017-06-01

The infusion of healthy stem cells into a patient-termed "stem-cell therapy"-has shown great promise for the treatment of genetic and non-genetic diseases, including mucopolysaccharidosis type 1, Parkinson's disease, multiple sclerosis, numerous immunodeficiency disorders, and aplastic anemia. Stem cells for cell therapy can be collected from the patient (autologous) or collected from another "healthy" individual (allogeneic). The use of allogenic stem cells is accompanied with the potentially fatal risk that the transplanted donor T cells will reject the patient's cells-a process termed "graft-versus-host disease." Therefore, the use of autologous stem cells is preferred, at least from the immunological perspective. However, an obvious drawback is that inherently as "self," they contain the disease mutation. As such, autologous cells for use in cell therapies often require genetic "correction" (i.e., gene addition or editing) prior to cell infusion and therefore the requirement for some form of nucleic acid delivery, which sets the stage for the AAV controversy discussed herein. Despite being the most clinically applied gene delivery context to date, unlike other more concerning integrating and non-integrating vectors such as retroviruses and adenovirus, those based on adeno-associated virus (AAV) have not been employed in the clinic. Furthermore, published data regarding AAV vector transduction of stem cells are inconsistent in regards to vector transduction efficiency, while the pendulum swings far in the other direction with demonstrations of AAV vector-induced toxicity in undifferentiated cells. The variation present in the literature examining the transduction efficiency of AAV vectors in stem cells may be due to numerous factors, including inconsistencies in stem-cell collection, cell culture, vector preparation, and/or transduction conditions. This review summarizes the controversy surrounding AAV vector transduction of stem cells, hopefully setting the stage for future elucidation and eventual therapeutic applications.

Adenovirus Vectors Target Several Cell Subtypes of Mammalian Inner Ear In Vivo

PubMed Central

Li, Wenyan; Shen, Jun

2016-01-01

Mammalian inner ear harbors diverse cell types that are essential for hearing and balance. Adenovirus is one of the major vectors to deliver genes into the inner ear for functional studies and hair cell regeneration. To identify adenovirus vectors that target specific cell subtypes in the inner ear, we studied three adenovirus vectors, carrying a reporter gene encoding green fluorescent protein (GFP) from two vendors or with a genome editing gene Cre recombinase (Cre), by injection into postnatal days 0 (P0) and 4 (P4) mouse cochlea through scala media by cochleostomy in vivo. We found three adenovirus vectors transduced mouse inner ear cells with different specificities and expression levels, depending on the type of adenoviral vectors and the age of mice. The most frequently targeted region was the cochlear sensory epithelium, including auditory hair cells and supporting cells. Adenovirus with GFP transduced utricular supporting cells as well. This study shows that adenovirus vectors are capable of efficiently and specifically transducing different cell types in the mammalian inner ear and provides useful tools to study inner ear gene function and to evaluate gene therapy to treat hearing loss and vestibular dysfunction. PMID:28116172

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

PubMed Central

Jewell, Chris P.; Brown, Richard G.

2015-01-01

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

AAVS1-Targeted Plasmid Integration in AAV Producer Cell Lines.

PubMed

Luo, Yuxia; Frederick, Amy; Martin, John M; Scaria, Abraham; Cheng, Seng H; Armentano, Donna; Wadsworth, Samuel C; Vincent, Karen A

2017-06-01

Adeno-associated virus (AAV) producer cell lines are created via transfection of HeLaS3 cells with a single plasmid containing three components (the vector sequence, the AAV rep and cap genes, and a selectable marker gene). As this plasmid contains both the cis (Rep binding sites) and trans (Rep protein encoded by the rep gene) elements required for site-specific integration, it was predicted that plasmid integration might occur within the AAVS1 locus on human chromosome 19 (chr19). The objective of this study was to investigate whether integration in AAVS1 might be correlated with vector yield. Plasmid integration sites within several independent cell lines were assessed via Southern, fluorescence in situ hybridization (FISH) and PCR analyses. In the Southern analyses, the presence of fragments detected by both rep- and AAVS1-specific probes suggested that for several mid- and high-producing lines, plasmid DNA had integrated into the AAVS1 locus. Analysis with puroR and AAVS1-specific probes suggested that integration in AAVS1 was a more widespread phenomenon. High-producing AAV2-secreted alkaline phosphatase (SEAP) lines (masterwell 82 [MW82] and MW278) were evaluated via FISH using probes specific for the plasmid, AAVS1, and a chr19 marker. FISH analysis detected two plasmid integration sites in MW278 (neither in AAVS1), while a total of three sites were identified in MW82 (two in AAVS1). An inverse PCR assay confirmed integration within AAVS1 for several mid- and high-producing lines. In summary, the FISH, Southern, and PCR data provide evidence of site-specific integration of the plasmid within AAVS1 in several AAV producer cell lines. The data also suggest that integration in AAVS1 is a general phenomenon that is not necessarily restricted to high producers. The results also suggest that plasmid integration within the AAVS1 locus is not an absolute requirement for a high vector yield.

Insulated Foamy Viral Vectors

PubMed Central

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

2016-01-01

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

Stable Local Volatility Calibration Using Kernel Splines

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

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.

Development of novel types of plastid transformation vectors and evaluation of factors controlling expression.

PubMed

Herz, Stefan; Füssl, Monika; Steiger, Sandra; Koop, Hans-Ulrich

2005-12-01

Two new vector types for plastid transformation were developed and uidA reporter gene expression was compared to standard transformation vectors. The first vector type does not contain any plastid promoter, instead it relies on extension of existing plastid operons and was therefore named "operon-extension" vector. When a strongly expressed plastid operon like psbA was extended by the reporter gene with this vector type, the expression level was superior to that of a standard vector under control of the 16S rRNA promoter. Different insertion sites, promoters and 5'-UTRs were analysed for their effect on reporter gene expression with standard and operon-extension vectors. The 5'-UTR of phage 7 gene 10 in combination with a modified N-terminus was found to yield the highest expression levels. Expression levels were also strongly dependent on external factors like plant or leaf age or light intensity. In the second vector type, named "split" plastid transformation vector, modules of the expression cassette were distributed on two separate vectors. Upon co-transformation of plastids with these vectors, the complete expression cassette became inserted into the plastome. This result can be explained by successive co-integration of the split vectors and final loop-out recombination of the duplicated sequences. The split vector concept was validated with different vector pairs.

[Sendai virus vector: vector development and its application to health care and biotechnology].

PubMed

Iida, Akihiro

2007-06-01

Sendai virus (SeV) is an enveloped virus with a nonsegmented negative-strand RNA genome and a member of the paramyxovirus family. We have developed SeV vector which has shown a high efficiently of gene transfer and expression of foreign genes to a wide range of dividing and non-dividing mammalian cells and tissues. One of the characteristics of the vector is that the genome is located exclusively in the cytoplasm of infected cells and does not go through a DNA phase; thus there is no concern about unwanted integration of foreign sequences into chromosomal DNA. Therefore, this new class of "cytoplasmic RNA vector", an RNA vector with cytoplasmic expression, is expected to be a safer and more efficient viral vector than existing vectors for application to human therapy in various fields including gene therapy and vaccination. In this review, I describe development of Sendai virus vector, its application in the field of biotechnology and clinical application aiming to treat for a large number of diseases including cancer, cardiovascular disease, infectious diseases and neurologic disorders.

Helper-Dependent Adenoviral Vectors.

PubMed

Rosewell, Amanda; Vetrini, Francesco; Ng, Philip

2011-10-29

Helper-dependent adenoviral vectors are devoid of all viral coding sequences, possess a large cloning capacity, and can efficiently transduce a wide variety of cell types from various species independent of the cell cycle to mediate long-term transgene expression without chronic toxicity. These non-integrating vectors hold tremendous potential for a variety of gene transfer and gene therapy applications. Here, we review the production technologies, applications, obstacles to clinical translation and their potential resolutions, and the future challenges and unanswered questions regarding this promising gene transfer technology.

Helper-Dependent Adenoviral Vectors

PubMed Central

Rosewell, Amanda; Vetrini, Francesco; Ng, Philip

2012-01-01

Helper-dependent adenoviral vectors are devoid of all viral coding sequences, possess a large cloning capacity, and can efficiently transduce a wide variety of cell types from various species independent of the cell cycle to mediate long-term transgene expression without chronic toxicity. These non-integrating vectors hold tremendous potential for a variety of gene transfer and gene therapy applications. Here, we review the production technologies, applications, obstacles to clinical translation and their potential resolutions, and the future challenges and unanswered questions regarding this promising gene transfer technology. PMID:24533227

Mathematical Methods for Optical Physics and Engineering

NASA Astrophysics Data System (ADS)

Gbur, Gregory J.

2011-01-01

1. Vector algebra; 2. Vector calculus; 3. Vector calculus in curvilinear coordinate systems; 4. Matrices and linear algebra; 5. Advanced matrix techniques and tensors; 6. Distributions; 7. Infinite series; 8. Fourier series; 9. Complex analysis; 10. Advanced complex analysis; 11. Fourier transforms; 12. Other integral transforms; 13. Discrete transforms; 14. Ordinary differential equations; 15. Partial differential equations; 16. Bessel functions; 17. Legendre functions and spherical harmonics; 18. Orthogonal functions; 19. Green's functions; 20. The calculus of variations; 21. Asymptotic techniques; Appendices; References; Index.

Saccharomyces cerevisiae Shuttle vectors.

PubMed

Gnügge, Robert; Rudolf, Fabian

2017-05-01

Yeast shuttle vectors are indispensable tools in yeast research. They enable cloning of defined DNA sequences in Escherichia coli and their direct transfer into Saccharomyces cerevisiae cells. There are three types of commonly used yeast shuttle vectors: centromeric plasmids, episomal plasmids and integrating plasmids. In this review, we discuss the different plasmid systems and their characteristic features. We focus on their segregational stability and copy number and indicate how to modify these properties. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

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

PubMed Central

2012-01-01

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

Vector ecology and integrated control procedures

PubMed Central

Laird, Marshall

1963-01-01

The elucidation of population regulatory mechanisms calls for exhaustive biological and ecological studies of whole ecosystems. Until lately, little effort was made to relate insect control activities to such a background, and the use of non-selective pesticides has often resulted in biotic equilibria being disrupted to the ultimate advantage of the organism under attack or of some other undesirable species. However, there is a growing realization in the field of economic entomology at large that biotic control agents usually constitute the major portion of the environmental resistance to increases in pest numbers and that insecticides should be fitted into the ecosystem, and not imposed upon it—in fact, that integrated control procedures are called for. The author considers such integrated procedures from the standpoint of vector control. His paper points out their potentialities in helping to solve resistance problems and in increasing the selectivity of control operations. It further suggests that they offer the means of achieving economical and lasting reductions of vector populations to levels at which human disease transmission is interrupted and pest problems lose much of their importance. PMID:20604165

On the Improvement of Convergence Performance for Integrated Design of Wind Turbine Blade Using a Vector Dominating Multi-objective Evolution Algorithm

NASA Astrophysics Data System (ADS)

Wang, L.; Wang, T. G.; Wu, J. H.; Cheng, G. P.

2016-09-01

A novel multi-objective optimization algorithm incorporating evolution strategies and vector mechanisms, referred as VD-MOEA, is proposed and applied in aerodynamic- structural integrated design of wind turbine blade. In the algorithm, a set of uniformly distributed vectors is constructed to guide population in moving forward to the Pareto front rapidly and maintain population diversity with high efficiency. For example, two- and three- objective designs of 1.5MW wind turbine blade are subsequently carried out for the optimization objectives of maximum annual energy production, minimum blade mass, and minimum extreme root thrust. The results show that the Pareto optimal solutions can be obtained in one single simulation run and uniformly distributed in the objective space, maximally maintaining the population diversity. In comparison to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation for handling complex problems of multi-variables, multi-objectives and multi-constraints. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrated design of wind turbine blade.

Anisotropic fractal media by vector calculus in non-integer dimensional space

NASA Astrophysics Data System (ADS)

Tarasov, Vasily E.

2014-08-01

A review of different approaches to describe anisotropic fractal media is proposed. In this paper, differentiation and integration non-integer dimensional and multi-fractional spaces are considered as tools to describe anisotropic fractal materials and media. We suggest a generalization of vector calculus for non-integer dimensional space by using a product measure method. The product of fractional and non-integer dimensional spaces allows us to take into account the anisotropy of the fractal media in the framework of continuum models. The integration over non-integer-dimensional spaces is considered. In this paper differential operators of first and second orders for fractional space and non-integer dimensional space are suggested. The differential operators are defined as inverse operations to integration in spaces with non-integer dimensions. Non-integer dimensional space that is product of spaces with different dimensions allows us to give continuum models for anisotropic type of the media. The Poisson's equation for fractal medium, the Euler-Bernoulli fractal beam, and the Timoshenko beam equations for fractal material are considered as examples of application of suggested generalization of vector calculus for anisotropic fractal materials and media.

Integrated Design Analysis and Optimisation of Aircraft Structures (L’Analyse pour la Conception Integree et l’Optimisation des Structures d’Aeronefs)

DTIC Science & Technology

1992-02-01

Division (Code RM) ONERA Office of Aeronautics & Space Technology 29 ave de la Division Leclerc NASA Hq 92320 Chfitillon Washington DC 20546 France United...Vector of thickness variables. V’ = [ t2 ........ tN Vector of thickness changes. AV ’= [rt, 5t2 ......... tNJ TI 7-9 Vector of strain derivatives. F...ds, ds, I d, 1i’,= dt, dr2 ........ dt--N Vector of buckling derivatives. dX d). , dt1 dt2 dtN Then 5F= Vs’i . AV and SX V,’. AV The linearised

Associative Pattern Recognition In Analog VLSI Circuits

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1995-01-01

Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.

Data layer integration for the national map of the united states

USGS Publications Warehouse

Usery, E.L.; Finn, M.P.; Starbuck, M.

2009-01-01

The integration of geographic data layers in multiple raster and vector formats, from many different organizations and at a variety of resolutions and scales, is a significant problem for The National Map of the United States being developed by the U.S. Geological Survey. Our research has examined data integration from a layer-based approach for five of The National Map data layers: digital orthoimages, elevation, land cover, hydrography, and transportation. An empirical approach has included visual assessment by a set of respondents with statistical analysis to establish the meaning of various types of integration. A separate theoretical approach with established hypotheses tested against actual data sets has resulted in an automated procedure for integration of specific layers and is being tested. The empirical analysis has established resolution bounds on meanings of integration with raster datasets and distance bounds for vector data. The theoretical approach has used a combination of theories on cartographic transformation and generalization, such as T??pfer's radical law, and additional research concerning optimum viewing scales for digital images to establish a set of guiding principles for integrating data of different resolutions.

Advancing integrated tick management to mitigate burden of tick-borne diseases

USDA-ARS?s Scientific Manuscript database

More than half of the world’s population is at risk of exposure to vector-borne pathogens. Annually, more than 1 billion people are infected and more than 1 million die from vector-borne diseases, including those caused by pathogens transmitted by ticks. The problem with tick borne diseases (TBD) is...

Using Vector and Extended Boolean Matching in an Expert System for Selecting Foster Homes.

ERIC Educational Resources Information Center

Fox, Edward A.; Winett, Sheila G.

1990-01-01

Describes FOCES (Foster Care Expert System), a prototype expert system for choosing foster care placements for children which integrates information retrieval techniques with artificial intelligence. The use of prototypes and queries in Prolog routines, extended Boolean matching, and vector correlation are explained, as well as evaluation by…

Gene therapy decreases seizures in a model of Incontinentia pigmenti.

PubMed

Dogbevia, Godwin K; Töllner, Kathrin; Körbelin, Jakob; Bröer, Sonja; Ridder, Dirk A; Grasshoff, Hanna; Brandt, Claudia; Wenzel, Jan; Straub, Beate K; Trepel, Martin; Löscher, Wolfgang; Schwaninger, Markus

2017-07-01

Incontinentia pigmenti (IP) is a genetic disease leading to severe neurological symptoms, such as epileptic seizures, but no specific treatment is available. IP is caused by pathogenic variants that inactivate the Nemo gene. Replacing Nemo through gene therapy might provide therapeutic benefits. In a mouse model of IP, we administered a single intravenous dose of the adeno-associated virus (AAV) vector, AAV-BR1-CAG-NEMO, delivering the Nemo gene to the brain endothelium. Spontaneous epileptic seizures and the integrity of the blood-brain barrier (BBB) were monitored. The endothelium-targeted gene therapy improved the integrity of the BBB. In parallel, it reduced the incidence of seizures and delayed their occurrence. Neonate mice intravenously injected with the AAV-BR1-CAG-NEMO vector developed no hepatocellular carcinoma or other major adverse effects 11 months after vector injection, demonstrating that the vector has a favorable safety profile. The data show that the BBB is a target of antiepileptic treatment and, more specifically, provide evidence for the therapeutic benefit of a brain endothelial-targeted gene therapy in IP. Ann Neurol 2017;82:93-104. © 2017 American Neurological Association.

Wide Awake and Ready to Move: 20 Years of Non-Viral Therapeutic Genome Engineering with the Sleeping Beauty Transposon System.

PubMed

Hodge, Russ; Narayanavari, Suneel A; Izsvák, Zsuzsanna; Ivics, Zoltán

2017-10-01

Gene therapies will only become a widespread tool in the clinical treatment of human diseases with the advent of gene transfer vectors that integrate genetic information stably, safely, effectively, and economically. Two decades after the discovery of the Sleeping Beauty (SB) transposon, it has been transformed into a vector system that is fulfilling these requirements. SB may well overcome some of the limitations associated with viral gene transfer vectors and transient non-viral gene delivery approaches that are being used in the majority of ongoing clinical trials. The SB system has achieved a high level of stable gene transfer and sustained transgene expression in multiple primary human somatic cell types, representing crucial steps that may permit its clinical use in the near future. This article reviews the most important aspects of SB as a tool for gene therapy, including aspects of its vectorization and genomic integration. As an illustration, the clinical development of the SB system toward gene therapy of age-related macular degeneration and cancer immunotherapy is highlighted.

Estimation of Teacher Practices Based on Text Transcripts of Teacher Speech Using a Support Vector Machine Algorithm

ERIC Educational Resources Information Center

Araya, Roberto; Plana, Francisco; Dartnell, Pablo; Soto-Andrade, Jorge; Luci, Gina; Salinas, Elena; Araya, Marylen

2012-01-01

Teacher practice is normally assessed by observers who watch classes or videos of classes. Here, we analyse an alternative strategy that uses text transcripts and a support vector machine classifier. For each one of the 710 videos of mathematics classes from the 2005 Chilean National Teacher Assessment Programme, a single 4-minute slice was…

Improvement of a yeast self-excising integrative vector by prevention of expression leakage of the intronated Cre recombinase gene during plasmid maintenance in Escherichia coli.

PubMed

Agaphonov, Michael O

2017-12-01

The use of plasmids possessing a regulatable gene coding for a site-specific recombinase together with its recognition sequences significantly facilitates genome manipulations since it allows self-excision of the portion of the genetic construct integrated into the host genome. Stable maintenance of such plasmids in Escherichia coli, which is used for plasmid preparation, requires prevention of recombinase synthesis in this host, which can be achieved by interrupting the recombinase gene with an intron. Based on this approach, Saccharomyces cerevisiae and Hansenula polymorpha self-excising vectors possessing intronated gene for Cre recombinase and its recognition sites (LoxP) were previously constructed. However, this work shows instability of the H. polymorpha vectors during plasmid maintenance in E. coli cells. This could be due to recombination between the loxP sites caused by residual expression of the cre gene. Prevention of translation reinitiation on an internal methionine codon completely solved this problem. A similar modification was made in a self-excising vector designed for S. cerevisiae. Apart from substantial improvement of yeast self-excising vectors, the obtained results also narrow down the essential part of Cre sequence. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

OpenClimateGIS - A Web Service Providing Climate Model Data in Commonly Used Geospatial Formats

NASA Astrophysics Data System (ADS)

Erickson, T. A.; Koziol, B. W.; Rood, R. B.

2011-12-01

The goal of the OpenClimateGIS project is to make climate model datasets readily available in commonly used, modern geospatial formats used by GIS software, browser-based mapping tools, and virtual globes.The climate modeling community typically stores climate data in multidimensional gridded formats capable of efficiently storing large volumes of data (such as netCDF, grib) while the geospatial community typically uses flexible vector and raster formats that are capable of storing small volumes of data (relative to the multidimensional gridded formats). OpenClimateGIS seeks to address this difference in data formats by clipping climate data to user-specified vector geometries (i.e. areas of interest) and translating the gridded data on-the-fly into multiple vector formats. The OpenClimateGIS system does not store climate data archives locally, but rather works in conjunction with external climate archives that expose climate data via the OPeNDAP protocol. OpenClimateGIS provides a RESTful API web service for accessing climate data resources via HTTP, allowing a wide range of applications to access the climate data.The OpenClimateGIS system has been developed using open source development practices and the source code is publicly available. The project integrates libraries from several other open source projects (including Django, PostGIS, numpy, Shapely, and netcdf4-python).OpenClimateGIS development is supported by a grant from NOAA's Climate Program Office.

Ship Detection in Optical Satellite Image Based on RX Method and PCAnet

NASA Astrophysics Data System (ADS)

Shao, Xiu; Li, Huali; Lin, Hui; Kang, Xudong; Lu, Ting

2017-12-01

In this paper, we present a novel method for ship detection in optical satellite image based on the ReedXiaoli (RX) method and the principal component analysis network (PCAnet). The proposed method consists of the following three steps. First, the spatially adjacent pixels in optical image are arranged into a vector, transforming the optical image into a 3D cube image. By taking this process, the contextual information of the spatially adjacent pixels can be integrated to magnify the discrimination between ship and background. Second, the RX anomaly detection method is adopted to preliminarily extract ship candidates from the produced 3D cube image. Finally, real ships are further confirmed among ship candidates by applying the PCAnet and the support vector machine (SVM). Specifically, the PCAnet is a simple deep learning network which is exploited to perform feature extraction, and the SVM is applied to achieve feature pooling and decision making. Experimental results demonstrate that our approach is effective in discriminating between ships and false alarms, and has a good ship detection performance.

Measurement and assessment of carrying capacity of the environment in Ningbo, China.

PubMed

Liu, R Z; Borthwick, Alistair G L

2011-08-01

Carrying Capacity of the Environment (CCE) provides a useful measure of the sustainable development of a region. Approaches that use integrated assessment instead of measurement can lead to misinterpretation of sustainable development because of confusion between Environmental Stress (ES) indexes and CCE indexes, and the selection of over-simple linear plus models. The present paper proposes a comprehensive measurement system for CCE which comprises models of natural resources capacity, environmental assimilative capacity, ecosystem services capacity, and society supporting capacity. The corresponding measurable indexes are designed to assess CCE using a carrying capacity surplus ratio model and a vector of surplus ratio of carrying capacity model. The former aims at direct comparison of ES and CCE based on the values of basic indexes, and the latter uses a Euclidean vector to assess CCE states. The measurement and assessment approaches are applicable to Strategic Environmental Assessment (SEA) and environmental planning and management. A case study is presented for Ningbo, China, whereby all the basic indexes of ECC are measured and the CCE states assessed for 2005 and 2010. Copyright © 2011 Elsevier Ltd. All rights reserved.

Integrated Cognitive-neuroscience Architectures for Understanding Sensemaking (ICArUS): Phase 1 Test and Evaluation Development Guide

DTIC Science & Technology

2014-11-01

Integrated Cognitive-neuroscience Architectures for Understanding Sensemaking (ICArUS): Phase 1 Test and Evaluation Development Guide Craig...Self-initiated sensemaking ........................................................................................... 19 Feature Vector Format: Tasks...The Integrated Cognitive-neuroscience Architectures for Understanding Sensemaking (ICArUS) Program aimed to build computational cognitive

Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis.

PubMed

Wang, Shuai; Zhang, Yan; Lv, Luxian; Wu, Renrong; Fan, Xiaoduo; Zhao, Jingping; Guo, Wenbin

2018-02-01

Structural and functional abnormalities have been reported in the brain of patients with adolescent-onset schizophrenia (AOS). The brain regional functional synchronization in patients with AOS remains unclear. We analyzed resting-state functional magnetic resonance scans in 48 drug-naive patients with AOS and 31 healthy controls by using regional homogeneity (ReHo), a measurement that reflects brain local functional connectivity or synchronization and indicates regional integration of information processing. Then, receiver operating characteristic curves and support vector machines were used to evaluate the effect of abnormal regional homogeneity in differentiating patients from controls. Patients with AOS showed significantly increased ReHo values in the bilateral superior medial prefrontal cortex (MPFC) and significantly decreased ReHo values in the left superior temporal gyrus (STG), right precentral lobule, right inferior parietal lobule (IPL), and left paracentral lobule when compared with controls. A combination of the ReHo values in bilateral superior MPFC, left STG, and right IPL was able to discriminate patients from controls with the sensitivity of 88.24%, specificity of 91.89%, and accuracy of 90.14%. The brain regional functional synchronization abnormalities exist in drug-naive patients with AOS. A combination of ReHo values in these abnormal regions might serve as potential imaging biomarker to identify patients with AOS. Copyright © 2017 Elsevier B.V. All rights reserved.

An object-oriented approach to nested data parallelism

NASA Technical Reports Server (NTRS)

Sheffler, Thomas J.; Chatterjee, Siddhartha

1994-01-01

This paper describes an implementation technique for integrating nested data parallelism into an object-oriented language. Data-parallel programming employs sets of data called 'collections' and expresses parallelism as operations performed over the elements of a collection. When the elements of a collection are also collections, then there is the possibility for 'nested data parallelism.' Few current programming languages support nested data parallelism however. In an object-oriented framework, a collection is a single object. Its type defines the parallel operations that may be applied to it. Our goal is to design and build an object-oriented data-parallel programming environment supporting nested data parallelism. Our initial approach is built upon three fundamental additions to C++. We add new parallel base types by implementing them as classes, and add a new parallel collection type called a 'vector' that is implemented as a template. Only one new language feature is introduced: the 'foreach' construct, which is the basis for exploiting elementwise parallelism over collections. The strength of the method lies in the compilation strategy, which translates nested data-parallel C++ into ordinary C++. Extracting the potential parallelism in nested 'foreach' constructs is called 'flattening' nested parallelism. We show how to flatten 'foreach' constructs using a simple program transformation. Our prototype system produces vector code which has been successfully run on workstations, a CM-2, and a CM-5.

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

PubMed

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

2011-10-01

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

Epithelial–mesenchymal transition biomarkers and support vector machine guided model in preoperatively predicting regional lymph node metastasis for rectal cancer

PubMed Central

Fan, X-J; Wan, X-B; Huang, Y; Cai, H-M; Fu, X-H; Yang, Z-L; Chen, D-K; Song, S-X; Wu, P-H; Liu, Q; Wang, L; Wang, J-P

2012-01-01

Background: Current imaging modalities are inadequate in preoperatively predicting regional lymph node metastasis (RLNM) status in rectal cancer (RC). Here, we designed support vector machine (SVM) model to address this issue by integrating epithelial–mesenchymal-transition (EMT)-related biomarkers along with clinicopathological variables. Methods: Using tissue microarrays and immunohistochemistry, the EMT-related biomarkers expression was measured in 193 RC patients. Of which, 74 patients were assigned to the training set to select the robust variables for designing SVM model. The SVM model predictive value was validated in the testing set (119 patients). Results: In training set, eight variables, including six EMT-related biomarkers and two clinicopathological variables, were selected to devise SVM model. In testing set, we identified 63 patients with high risk to RLNM and 56 patients with low risk. The sensitivity, specificity and overall accuracy of SVM in predicting RLNM were 68.3%, 81.1% and 72.3%, respectively. Importantly, multivariate logistic regression analysis showed that SVM model was indeed an independent predictor of RLNM status (odds ratio, 11.536; 95% confidence interval, 4.113–32.361; P<0.0001). Conclusion: Our SVM-based model displayed moderately strong predictive power in defining the RLNM status in RC patients, providing an important approach to select RLNM high-risk subgroup for neoadjuvant chemoradiotherapy. PMID:22538975

A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization

PubMed Central

Wang, Xibin; Luo, Fengji; Qian, Ying; Ranzi, Gianluca

2016-01-01

With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to locate and access useful information for making decisions. To address this problem, there are information filtering systems, such as the personalized recommendation system (PRS) considered in this paper, that assist a person in identifying possible products or services of interest based on his/her preferences. Among available approaches, collaborative Filtering (CF) is one of the most widely used recommendation techniques. However, CF has some limitations, e.g., the relatively simple similarity calculation, cold start problem, etc. In this context, this paper presents a new regression model based on the support vector machine (SVM) classification and an improved PSO (IPSO) for the development of an electronic movie PRS. In its implementation, a SVM classification model is first established to obtain a preliminary movie recommendation list based on which a SVM regression model is applied to predict movies’ ratings. The proposed PRS not only considers the movie’s content information but also integrates the users’ demographic and behavioral information to better capture the users’ interests and preferences. The efficiency of the proposed method is verified by a series of experiments based on the MovieLens benchmark data set. PMID:27898691

A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization.

PubMed

Wang, Xibin; Luo, Fengji; Qian, Ying; Ranzi, Gianluca

2016-01-01

With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to locate and access useful information for making decisions. To address this problem, there are information filtering systems, such as the personalized recommendation system (PRS) considered in this paper, that assist a person in identifying possible products or services of interest based on his/her preferences. Among available approaches, collaborative Filtering (CF) is one of the most widely used recommendation techniques. However, CF has some limitations, e.g., the relatively simple similarity calculation, cold start problem, etc. In this context, this paper presents a new regression model based on the support vector machine (SVM) classification and an improved PSO (IPSO) for the development of an electronic movie PRS. In its implementation, a SVM classification model is first established to obtain a preliminary movie recommendation list based on which a SVM regression model is applied to predict movies' ratings. The proposed PRS not only considers the movie's content information but also integrates the users' demographic and behavioral information to better capture the users' interests and preferences. The efficiency of the proposed method is verified by a series of experiments based on the MovieLens benchmark data set.

Multivariate Models for Prediction of Human Skin Sensitization ...

EPA Pesticide Factsheets

One of the lnteragency Coordinating Committee on the Validation of Alternative Method's (ICCVAM) top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays - the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens TM assay - six physicochemical properties and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches , logistic regression and support vector machine, to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three logistic regression and three support vector machine) with the highest accuracy (92%) used: (1) DPRA, h-CLAT and read-across; (2) DPRA, h-CLAT, read-across and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens and log P. The models performed better at predicting human skin sensitization hazard than the murine

A study of EMR-based medical knowledge network and its applications.

PubMed

Zhao, Chao; Jiang, Jingchi; Xu, Zhiming; Guan, Yi

2017-05-01

Electronic medical records (EMRs) contain an amount of medical knowledge which can be used for clinical decision support. We attempt to integrate this medical knowledge into a complex network, and then implement a diagnosis model based on this network. The dataset of our study contains 992 records which are uniformly sampled from different departments of the hospital. In order to integrate the knowledge of these records, an EMR-based medical knowledge network (EMKN) is constructed. This network takes medical entities as nodes, and co-occurrence relationships between the two entities as edges. Selected properties of this network are analyzed. To make use of this network, a basic diagnosis model is implemented. Seven hundred records are randomly selected to re-construct the network, and the remaining 292 records are used as test records. The vector space model is applied to illustrate the relationships between diseases and symptoms. Because there may exist more than one actual disease in a record, the recall rate of the first ten results, and the average precision are adopted as evaluation measures. Compared with a random network of the same size, this network has a similar average length but a much higher clustering coefficient. Additionally, it can be observed that there are direct correlations between the community structure and the real department classes in the hospital. For the diagnosis model, the vector space model using disease as a base obtains the best result. At least one accurate disease can be obtained in 73.27% of the records in the first ten results. We constructed an EMR-based medical knowledge network by extracting the medical entities. This network has the small-world and scale-free properties. Moreover, the community structure showed that entities in the same department have a tendency to be self-aggregated. Based on this network, a diagnosis model was proposed. This model uses only the symptoms as inputs and is not restricted to a specific disease. The experiments conducted demonstrated that EMKN is a simple and universal technique to integrate different medical knowledge from EMRs, and can be used for clinical decision support. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Fast support vector data descriptions for novelty detection.

PubMed

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

2010-08-01

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

Support Vector Machine-Based Endmember Extraction

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

Filippi, Anthony M; Archibald, Richard K

Introduced in this paper is the utilization of Support Vector Machines (SVMs) to automatically perform endmember extraction from hyperspectral data. The strengths of SVM are exploited to provide a fast and accurate calculated representation of high-dimensional data sets that may consist of multiple distributions. Once this representation is computed, the number of distributions can be determined without prior knowledge. For each distribution, an optimal transform can be determined that preserves informational content while reducing the data dimensionality, and hence, the computational cost. Finally, endmember extraction for the whole data set is accomplished. Results indicate that this Support Vector Machine-Based Endmembermore » Extraction (SVM-BEE) algorithm has the capability of autonomously determining endmembers from multiple clusters with computational speed and accuracy, while maintaining a robust tolerance to noise.« less

Vector control programs in Saint Johns County, Florida and Guayas, Ecuador: successes and barriers to integrated vector management.

PubMed

Naranjo, Diana P; Qualls, Whitney A; Jurado, Hugo; Perez, Juan C; Xue, Rui-De; Gomez, Eduardo; Beier, John C

2014-07-02

Vector-borne diseases (VBDs) and mosquito control programs (MCPs) diverge in settings and countries, and lead control specialists need to be aware of the most effective control strategies. Integrated Vector Management (IVM) strategies, once implemented in MCPs, aim to reduce cost and optimize protection of the populations against VBDs. This study presents a strengths, weaknesses, opportunities, and threats (SWOT) analysis to compare IVM strategies used by MCPs in Saint Johns County, Florida and Guayas, Ecuador. This research evaluates MCPs strategies to improve vector control activities. Methods included descriptive findings of the MCP operations. Information was obtained from vector control specialists, directors, and residents through field trips, surveys, and questionnaires. Evaluations of the strategies and assets of the control programs where obtained through SWOT analysis and within an IVM approach. Organizationally, the Floridian MCP is a tax-based District able to make decisions independently from county government officials, with the oversight of an elected board of commissioners. The Guayas program is directed by the country government and assessed by non-governmental organizations like the World health Organization. Operationally, the Floridian MCP conducts entomological surveillance and the Ecuadorian MCP focuses on epidemiological monitoring of human disease cases. Strengths of both MCPs were their community participation and educational programs. Weaknesses for both MCPs included limitations in budgets and technical capabilities. Opportunities, for both MCPs, are additional funding and partnerships with private, non-governmental, and governmental organizations. Threats experienced by both MCPs included political constraints and changes in the social and ecological environment that affect mosquito densities and control efforts. IVM pillars for policy making were used to compare the information among the programs. Differences included how the Ecuadorian MCP relies heavily on the community for vector control while the American MCP relies on technologies and research. IVM based recommendations direct health policy leaders toward improving surveillance systems both entomologically and epidemiologically, improving community risk perceptions by integrating components of community participation, maximizing resources though the use of applied research, and protecting the environment by selecting low-risk pesticides. Outcomes of the research revealed that inter-sectorial and multidisciplinary interventions are critical to improve public health.

A Guided Tour of Mathematical Methods

NASA Astrophysics Data System (ADS)

Snieder, Roel

2009-04-01

1. Introduction; 2. Dimensional analysis; 3. Power series; 4. Spherical and cylindrical co-ordinates; 5. The gradient; 6. The divergence of a vector field; 7. The curl of a vector field; 8. The theorem of Gauss; 9. The theorem of Stokes; 10. The Laplacian; 11. Conservation laws; 12. Scale analysis; 13. Linear algebra; 14. The Dirac delta function; 15. Fourier analysis; 16. Analytic functions; 17. Complex integration; 18. Green's functions: principles; 19. Green's functions: examples; 20. Normal modes; 21. Potential theory; 22. Cartesian tensors; 23. Perturbation theory; 24. Asymptotic evaluation of integrals; 25. Variational calculus; 26. Epilogue, on power and knowledge; References.

Tensorial Minkowski functionals of triply periodic minimal surfaces

PubMed Central

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

2012-01-01

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

Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion.

PubMed

Smith, Rachel A; Kim, Youllee; Zhu, Xun; Doudou, Dimi Théodore; Sternberg, Eleanore D; Thomas, Matthew B

2018-01-01

This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes with attitudes and social pressures with norms) to predict participants' (N = 329) diffusion intentions. The findings showed that positive attitudes about the innovation's attributes were a consistent positive predictor of diffusion intentions: adopting it, maintaining it, and talking with others about it. As expected by the DOI and the IMB, the social pressure created by a descriptive norm positively predicted intentions to adopt and maintain the innovation. Drawing upon sharing research, we argued that the descriptive norm may dampen future talk about the innovation, because it may no longer be seen as a novel, useful topic to discuss. As predicted, the results showed that as the descriptive norm increased, the intention to talk about the innovation decreased. These results provide broad support for integrating the DOI and the IMB to predict diffusion and for efforts to draw on other research to understand motivations for social diffusion.

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Ecologists can enable communities to implement malaria vector control in Africa

PubMed Central

Mukabana, W Richard; Kannady, Khadija; Kiama, G Michael; Ijumba, Jasper N; Mathenge, Evan M; Kiche, Ibrahim; Nkwengulila, Gamba; Mboera, Leonard; Mtasiwa, Deo; Yamagata, Yoichi; van Schayk, Ingeborg; Knols, Bart GJ; Lindsay, Steven W; de Castro, Marcia Caldas; Mshinda, Hassan; Tanner, Marcel; Fillinger, Ulrike; Killeen, Gerry F

2006-01-01

Background Integrated vector management (IVM) for malaria control requires ecological skills that are very scarce and rarely applied in Africa today. Partnerships between communities and academic ecologists can address this capacity deficit, modernize the evidence base for such approaches and enable future scale up. Methods Community-based IVM programmes were initiated in two contrasting settings. On Rusinga Island, Western Kenya, community outreach to a marginalized rural community was achieved by University of Nairobi through a community-based organization. In Dar es Salaam, Tanzania, Ilala Municipality established an IVM programme at grassroots level, which was subsequently upgraded and expanded into a pilot scale Urban Malaria Control Programme with support from national academic institutes. Results Both programmes now access relevant expertise, funding and policy makers while the academic partners benefit from direct experience of community-based implementation and operational research opportunities. The communities now access up-to-date malaria-related knowledge and skills for translation into local action. Similarly, the academic partners have acquired better understanding of community needs and how to address them. Conclusion Until sufficient evidence is provided, community-based IVM remains an operational research activity. Researchers can never directly support every community in Africa so community-based IVM strategies and tactics will need to be incorporated into undergraduate teaching programmes to generate sufficient numbers of practitioners for national scale programmes. Academic ecologists at African institutions are uniquely positioned to enable the application of practical environmental and entomological skills for malaria control by communities at grassroots level and should be supported to fulfil this neglected role. PMID:16457724

The road to NHDPlus — Advancements in digital stream networks and associated catchments

USGS Publications Warehouse

Moore, Richard B.; Dewald, Thomas A.

2016-01-01

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water-related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium-resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate-and-transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user-defined applications.

Constraining primordial vector mode from B-mode polarization

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

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

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

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

PubMed

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

2010-01-01

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

A synthetic method for atmospheric diffusion simulation and environmental impact assessment of accidental pollution in the chemical industry in a WEBGIS context.

PubMed

Ni, Haochen; Rui, Yikang; Wang, Jiechen; Cheng, Liang

2014-09-05

The chemical industry poses a potential security risk to factory personnel and neighboring residents. In order to mitigate prospective damage, a synthetic method must be developed for an emergency response. With the development of environmental numeric simulation models, model integration methods, and modern information technology, many Decision Support Systems (DSSs) have been established. However, existing systems still have limitations, in terms of synthetic simulation and network interoperation. In order to resolve these limitations, the matured simulation model for chemical accidents was integrated into the WEB Geographic Information System (WEBGIS) platform. The complete workflow of the emergency response, including raw data (meteorology information, and accident information) management, numeric simulation of different kinds of accidents, environmental impact assessments, and representation of the simulation results were achieved. This allowed comprehensive and real-time simulation of acute accidents in the chemical industry. The main contribution of this paper is that an organizational mechanism of the model set, based on the accident type and pollutant substance; a scheduling mechanism for the parallel processing of multi-accident-type, multi-accident-substance, and multi-simulation-model; and finally a presentation method for scalar and vector data on the web browser on the integration of a WEB Geographic Information System (WEBGIS) platform. The outcomes demonstrated that this method could provide effective support for deciding emergency responses of acute chemical accidents.

A Synthetic Method for Atmospheric Diffusion Simulation and Environmental Impact Assessment of Accidental Pollution in the Chemical Industry in a WEBGIS Context

PubMed Central

Ni, Haochen; Rui, Yikang; Wang, Jiechen; Cheng, Liang

2014-01-01

The chemical industry poses a potential security risk to factory personnel and neighboring residents. In order to mitigate prospective damage, a synthetic method must be developed for an emergency response. With the development of environmental numeric simulation models, model integration methods, and modern information technology, many Decision Support Systems (DSSs) have been established. However, existing systems still have limitations, in terms of synthetic simulation and network interoperation. In order to resolve these limitations, the matured simulation model for chemical accidents was integrated into the WEB Geographic Information System (WEBGIS) platform. The complete workflow of the emergency response, including raw data (meteorology information, and accident information) management, numeric simulation of different kinds of accidents, environmental impact assessments, and representation of the simulation results were achieved. This allowed comprehensive and real-time simulation of acute accidents in the chemical industry. The main contribution of this paper is that an organizational mechanism of the model set, based on the accident type and pollutant substance; a scheduling mechanism for the parallel processing of multi-accident-type, multi-accident-substance, and multi-simulation-model; and finally a presentation method for scalar and vector data on the web browser on the integration of a WEB Geographic Information System (WEBGIS) platform. The outcomes demonstrated that this method could provide effective support for deciding emergency responses of acute chemical accidents. PMID:25198686

Nuclease-free Adeno-Associated Virus-Mediated Il2rg Gene Editing in X-SCID Mice.

PubMed

Hiramoto, Takafumi; Li, Li B; Funk, Sarah E; Hirata, Roli K; Russell, David W

2018-05-02

X-linked severe combined immunodeficiency (X-SCID) has been successfully treated by hematopoietic stem cell (HSC) transduction with retroviral vectors expressing the interleukin-2 receptor subunit gamma gene (IL2RG), but several patients developed malignancies due to vector integration near cellular oncogenes. This adverse side effect could in principle be avoided by accurate IL2RG gene editing with a vector that does not contain a functional promoter or IL2RG gene. Here, we show that adeno-associated virus (AAV) gene editing vectors can insert a partial Il2rg cDNA at the endogenous Il2rg locus in X-SCID murine bone marrow cells and that these ex vivo-edited cells repopulate transplant recipients and produce CD4 + and CD8 + T cells. Circulating, edited lymphocytes increased over time and appeared in secondary transplant recipients, demonstrating successful editing in long-term repopulating cells. Random vector integration events were nearly undetectable, and malignant transformation of the transplanted cells was not observed. Similar editing frequencies were observed in human hematopoietic cells. Our results demonstrate that therapeutically relevant HSC gene editing can be achieved by AAV vectors in the absence of site-specific nucleases and suggest that this may be a safe and effective therapy for hematopoietic diseases where in vivo selection can increase edited cell numbers. Copyright © 2018 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Characterization of Equine Infectious Anemia Virus Integration in the Horse Genome.

PubMed

Liu, Qiang; Wang, Xue-Feng; Ma, Jian; He, Xi-Jun; Wang, Xiao-Jun; Zhou, Jian-Hua

2015-06-19

Human immunodeficiency virus (HIV)-1 has a unique integration profile in the human genome relative to murine and avian retroviruses. Equine infectious anemia virus (EIAV) is another well-studied lentivirus that can also be used as a promising retro-transfection vector, but its integration into its native host has not been characterized. In this study, we mapped 477 integration sites of the EIAV strain EIAVFDDV13 in fetal equine dermal (FED) cells during in vitro infection. Published integration sites of EIAV and HIV-1 in the human genome were also analyzed as references. Our results demonstrated that EIAVFDDV13 tended to integrate into genes and AT-rich regions, and it avoided integrating into transcription start sites (TSS), which is consistent with EIAV and HIV-1 integration in the human genome. Notably, the integration of EIAVFDDV13 favored long interspersed elements (LINEs) and DNA transposons in the horse genome, whereas the integration of HIV-1 favored short interspersed elements (SINEs) in the human genome. The chromosomal environment near LINEs or DNA transposons potentially influences viral transcription and may be related to the unique EIAV latency states in equids. The data on EIAV integration in its natural host will facilitate studies on lentiviral infection and lentivirus-based therapeutic vectors.

MLV integration site selection is driven by strong enhancers and active promoters

PubMed Central

LaFave, Matthew C.; Varshney, Gaurav K.; Gildea, Derek E.; Wolfsberg, Tyra G.; Baxevanis, Andreas D.; Burgess, Shawn M.

2014-01-01

Retroviruses integrate into the host genome in patterns specific to each virus. Understanding the causes of these patterns can provide insight into viral integration mechanisms, pathology and genome evolution, and is critical to the development of safe gene therapy vectors. We generated murine leukemia virus integrations in human HepG2 and K562 cells and subjected them to second-generation sequencing, using a DNA barcoding technique that allowed us to quantify independent integration events. We characterized >3 700 000 unique integration events in two ENCODE-characterized cell lines. We find that integrations were most highly enriched in a subset of strong enhancers and active promoters. In both cell types, approximately half the integrations were found in <2% of the genome, demonstrating genomic influences even narrower than previously believed. The integration pattern of murine leukemia virus appears to be largely driven by regions that have high enrichment for multiple marks of active chromatin; the combination of histone marks present was sufficient to explain why some strong enhancers were more prone to integration than others. The approach we used is applicable to analyzing the integration pattern of any exogenous element and could be a valuable preclinical screen to evaluate the safety of gene therapy vectors. PMID:24464997

Characterization of Equine Infectious Anemia Virus Integration in the Horse Genome

PubMed Central

Liu, Qiang; Wang, Xue-Feng; Ma, Jian; He, Xi-Jun; Wang, Xiao-Jun; Zhou, Jian-Hua

2015-01-01

Human immunodeficiency virus (HIV)-1 has a unique integration profile in the human genome relative to murine and avian retroviruses. Equine infectious anemia virus (EIAV) is another well-studied lentivirus that can also be used as a promising retro-transfection vector, but its integration into its native host has not been characterized. In this study, we mapped 477 integration sites of the EIAV strain EIAVFDDV13 in fetal equine dermal (FED) cells during in vitro infection. Published integration sites of EIAV and HIV-1 in the human genome were also analyzed as references. Our results demonstrated that EIAVFDDV13 tended to integrate into genes and AT-rich regions, and it avoided integrating into transcription start sites (TSS), which is consistent with EIAV and HIV-1 integration in the human genome. Notably, the integration of EIAVFDDV13 favored long interspersed elements (LINEs) and DNA transposons in the horse genome, whereas the integration of HIV-1 favored short interspersed elements (SINEs) in the human genome. The chromosomal environment near LINEs or DNA transposons potentially influences viral transcription and may be related to the unique EIAV latency states in equids. The data on EIAV integration in its natural host will facilitate studies on lentiviral infection and lentivirus-based therapeutic vectors. PMID:26102582

Differential Galois theory and non-integrability of planar polynomial vector fields

NASA Astrophysics Data System (ADS)

Acosta-Humánez, Primitivo B.; Lázaro, J. Tomás; Morales-Ruiz, Juan J.; Pantazi, Chara

2018-06-01

We study a necessary condition for the integrability of the polynomials vector fields in the plane by means of the differential Galois Theory. More concretely, by means of the variational equations around a particular solution it is obtained a necessary condition for the existence of a rational first integral. The method is systematic starting with the first order variational equation. We illustrate this result with several families of examples. A key point is to check whether a suitable primitive is elementary or not. Using a theorem by Liouville, the problem is equivalent to the existence of a rational solution of a certain first order linear equation, the Risch equation. This is a classical problem studied by Risch in 1969, and the solution is given by the "Risch algorithm". In this way we point out the connection of the non integrability with some higher transcendent functions, like the error function.

Cigarette taxes and respiratory cancers: new evidence from panel co-integration analysis.

PubMed

Liu, Echu; Yu, Wei-Choun; Hsieh, Hsin-Ling

2011-01-01

Using a set of state-level longitudinal data from 1954 through 2005, this study investigates the "long-run equilibrium" relationship between cigarette excise taxes and the mortality rates of respiratory cancers in the United States. Statistical tests show that both cigarette excise taxes in real terms and mortality rates from respiratory cancers contain unit roots and are co-integrated. Estimates of co-integrating vectors indicated that a 10 percent increase in real cigarette excise tax rate leads to a 2.5 percent reduction in respiratory cancer mortality rate, implying a decline of 3,922 deaths per year, on a national level in the long run. These effects are statistically significant at the one percent level. Moreover, estimates of co-integrating vectors show that higher cigarette excise tax rates lead to lower mortality rates in most states; however, this relationship does not hold for Alaska, Florida, Hawaii, and Texas.

Optimization of fixture layouts of glass laser optics using multiple kernel regression.

PubMed

Su, Jianhua; Cao, Enhua; Qiao, Hong

2014-05-10

We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.

Huygens' optical vector wave field synthesis via in-plane electric dipole metasurface.

PubMed

Park, Hyeonsoo; Yun, Hansik; Choi, Chulsoo; Hong, Jongwoo; Kim, Hwi; Lee, Byoungho

2018-04-16

We investigate Huygens' optical vector wave field synthesis scheme for electric dipole metasurfaces with the capability of modulating in-plane polarization and complex amplitude and discuss the practical issues involved in realizing multi-modulation metasurfaces. The proposed Huygens' vector wave field synthesis scheme identifies the vector Airy disk as a synthetic unit element and creates a designed vector optical field by integrating polarization-controlled and complex-modulated Airy disks. The metasurface structure for the proposed vector field synthesis is analyzed in terms of the signal-to-noise ratio of the synthesized field distribution. The design of practical metasurface structures with true vector modulation capability is possible through the analysis of the light field modulation characteristics of various complex modulated geometric phase metasurfaces. It is shown that the regularization of meta-atoms is a key factor that needs to be considered in field synthesis, given that it is essential for a wide range of optical field synthetic applications, including holographic displays, microscopy, and optical lithography.

Nonviral vectors for cancer gene therapy: prospects for integrating vectors and combination therapies.

PubMed

Ohlfest, John R; Freese, Andrew B; Largaespada, David A

2005-12-01

Gene therapy has the potential to improve the clinical outcome of many cancers by transferring therapeutic genes into tumor cells or normal host tissue. Gene transfer into tumor cells or tumor-associated stroma is being employed to induce tumor cell death, stimulate anti-tumor immune response, inhibit angiogenesis, and control tumor cell growth. Viral vectors have been used to achieve this proof of principle in animal models and, in select cases, in human clinical trials. Nevertheless, there has been considerable interest in developing nonviral vectors for cancer gene therapy. Nonviral vectors are simpler, more amenable to large-scale manufacture, and potentially safer for clinical use. Nonviral vectors were once limited by low gene transfer efficiency and transient or steadily declining gene expression. However, recent improvements in plasmid-based vectors and delivery methods are showing promise in circumventing these obstacles. This article reviews the current status of nonviral cancer gene therapy, with an emphasis on combination strategies, long-term gene transfer using transposons and bacteriophage integrases, and future directions.

Herpes simplex virus type 1 (HSV-1)-derived recombinant vectors for gene transfer and gene therapy.

PubMed

Marconi, Peggy; Fraefel, Cornel; Epstein, Alberto L

2015-01-01

Herpes simplex virus type 1 (HSV-1 ) is a human pathogen whose lifestyle is based on a long-term dual interaction with the infected host, being able to establish both lytic and latent infections. The virus genome is a 153-kilobase pair (kbp) double-stranded DNA molecule encoding more than 80 genes. The interest of HSV-1 as gene transfer vector stems from its ability to infect many different cell types, both quiescent and proliferating cells, the very high packaging capacity of the virus capsid, the outstanding neurotropic adaptations that this virus has evolved, and the fact that it never integrates into the cellular chromosomes, thus avoiding the risk of insertional mutagenesis. Two types of vectors can be derived from HSV-1, recombinant vectors and amplicon vectors, and different methodologies have been developed to prepare large stocks of each type of vector. This chapter summarizes the approach most commonly used to prepare recombinant HSV-1 vectors through homologous recombination, either in eukaryotic cells or in bacteria.

Efficient generation of transgene-free human induced pluripotent stem cells (iPSCs) by temperature-sensitive Sendai virus vectors

PubMed Central

Ban, Hiroshi; Nishishita, Naoki; Fusaki, Noemi; Tabata, Toshiaki; Saeki, Koichi; Shikamura, Masayuki; Takada, Nozomi; Inoue, Makoto; Hasegawa, Mamoru; Kawamata, Shin; Nishikawa, Shin-Ichi

2011-01-01

After the first report of induced pluripotent stem cells (iPSCs), considerable efforts have been made to develop more efficient methods for generating iPSCs without foreign gene insertions. Here we show that Sendai virus vector, an RNA virus vector that carries no risk of integrating into the host genome, is a practical solution for the efficient generation of safer iPSCs. We improved the Sendai virus vectors by introducing temperature-sensitive mutations so that the vectors could be easily removed at nonpermissive temperatures. Using these vectors enabled the efficient production of viral/factor-free iPSCs from both human fibroblasts and CD34+ cord blood cells. Temperature-shift treatment was more effective in eliminating remaining viral vector-related genes. The resulting iPSCs expressed human embryonic stem cell markers and exhibited pluripotency. We suggest that generation of transgene-free iPSCs from cord blood cells should be an important step in providing allogeneic iPSC-derived therapy in the future. PMID:21821793

Large Animal Models for Foamy Virus Vector Gene Therapy

PubMed Central

Trobridge, Grant D.; Horn, Peter A.; Beard, Brian C.; Kiem, Hans-Peter

2012-01-01

Foamy virus (FV) vectors have shown great promise for hematopoietic stem cell (HSC) gene therapy. Their ability to efficiently deliver transgenes to multi-lineage long-term repopulating cells in large animal models suggests they will be effective for several human hematopoietic diseases. Here, we review FV vector studies in large animal models, including the use of FV vectors with the mutant O6-methylguanine-DNA methyltransferase, MGMTP140K to increase the number of genetically modified cells after transplantation. In these studies, FV vectors have mediated efficient gene transfer to polyclonal repopulating cells using short ex vivo transduction protocols designed to minimize the negative effects of ex vivo culture on stem cell engraftment. In this regard, FV vectors appear superior to gammaretroviral vectors, which require longer ex vivo culture to effect efficient transduction. FV vectors have also compared favorably with lentiviral vectors when directly compared in the dog model. FV vectors have corrected leukocyte adhesion deficiency and pyruvate kinase deficiency in the dog large animal model. FV vectors also appear safer than gammaretroviral vectors based on a reduced frequency of integrants near promoters and also near proto-oncogenes in canine repopulating cells. Together, these studies suggest that FV vectors should be highly effective for several human hematopoietic diseases, including those that will require relatively high percentages of gene-modified cells to achieve clinical benefit. PMID:23223198

Search for single production of vector-like top partner decaying to Wb at eγ collision

NASA Astrophysics Data System (ADS)

Yang, Bingfang; Shao, Hongbo; Han, Jinzhong

2018-03-01

In a simplified model including an SU(2) singlet T quark with charge 2/3, we investigate the single vector-like T production at the high energy eγ collision. We study the observability of the vector-like T focusing on the T→ Wb decay channel with W→ l\\bar{ν } at √{s}=2.0 TeV. In this analysis, only two free parameters are involved, namely the T quark coupling strength for single production g^{*} and the mass mT. We scan the parameter space and find that the correlation region of g^{*}\\in [0.24, 0.5] and mT\\in [800, 1360] GeV can be excluded with integrated luminosity L=100 fb^{-1} and the correlation region of g^{*}\\in [0.13, 0.5] and mT\\in [800, 1620] GeV can be excluded with integrated luminosity L=1000 fb^{-1} at 2σ level.

Electromechanical actuation for thrust vector control applications

NASA Technical Reports Server (NTRS)

Roth, Mary Ellen

1990-01-01

The advanced launch system (ALS), is a launch vehicle that is designed to be cost-effective, highly reliable, and operationally efficient with a goal of reducing the cost per pound to orbit. An electromechanical actuation (EMA) system is being developed as an attractive alternative to the hydraulic systems. The controller will integrate 20 kHz resonant link power management and distribution (PMAD) technology and pulse population modulation (PPM) techniques to implement field-oriented vector control (FOVC) of a new advanced induction motor. The driver and the FOVC will be microprocessor controlled. For increased system reliability, a built-in test (BITE) capability will be included. This involves introducing testability into the design of a system such that testing is calibrated and exercised during the design, manufacturing, maintenance, and prelaunch activities. An actuator will be integrated with the motor controller for performance testing of the EMA thrust vector control (TVC) system. The EMA system and work proposed for the future are discussed.

Integrated Tools for American Cutaneous Leishmaniasis Surveillance and Control: Intervention in an Endemic Area in Rio de Janeiro, RJ, Brazil

PubMed Central

Gouveia, Cheryl; de Oliveira, Rosely Magalhães; Zwetsch, Adriana; Motta-Silva, Daniel; Carvalho, Bruno Moreira; de Santana, Antônio Ferreira; Rangel, Elizabeth Ferreira

2012-01-01

American cutaneous leishmaniasis (ACL) is a focal disease whose surveillance and control require complex actions. The present study aimed to apply integrated tools related to entomological surveillance, environmental management, and health education practices in an ACL-endemic area in Rio de Janeiro city, RJ, Brazil. The distribution of the disease, the particular characteristics of the localities, and entomological data were used as additional information about ACL determinants. Environmental management actions were evaluated after health education practices. The frequency of ACL vectors Lutzomyia (N.) intermedia and L. migonei inside and outside houses varied according to environment characteristics, probably influenced by the way of life of the popular groups. In this kind of situation environmental management and community mobilization become essential, as they help both specialists and residents create strategies that can interfere in the dynamics of vector's population and the contact between man and vectors. PMID:22988458

Versatile rogue waves in scalar, vector, and multidimensional nonlinear systems

NASA Astrophysics Data System (ADS)

Chen, Shihua; Baronio, Fabio; Soto-Crespo, Jose M.; Grelu, Philippe; Mihalache, Dumitru

2017-11-01

This review is dedicated to recent progress in the active field of rogue waves, with an emphasis on the analytical prediction of versatile rogue wave structures in scalar, vector, and multidimensional integrable nonlinear systems. We first give a brief outline of the historical background of the rogue wave research, including referring to relevant up-to-date experimental results. Then we present an in-depth discussion of the scalar rogue waves within two different integrable frameworks—the infinite nonlinear Schrödinger (NLS) hierarchy and the general cubic-quintic NLS equation, considering both the self-focusing and self-defocusing Kerr nonlinearities. We highlight the concept of chirped Peregrine solitons, the baseband modulation instability as an origin of rogue waves, and the relation between integrable turbulence and rogue waves, each with illuminating examples confirmed by numerical simulations. Later, we recur to the vector rogue waves in diverse coupled multicomponent systems such as the long-wave short-wave equations, the three-wave resonant interaction equations, and the vector NLS equations (alias Manakov system). In addition to their intriguing bright-dark dynamics, a series of other peculiar structures, such as coexisting rogue waves, watch-hand-like rogue waves, complementary rogue waves, and vector dark three sisters, are reviewed. Finally, for practical considerations, we also remark on higher-dimensional rogue waves occurring in three closely-related (2  +  1)D nonlinear systems, namely, the Davey-Stewartson equation, the composite (2  +  1)D NLS equation, and the Kadomtsev-Petviashvili I equation. As an interesting contrast to the peculiar X-shaped light bullets, a concept of rogue wave bullets intended for high-dimensional systems is particularly put forward by combining contexts in nonlinear optics.

Decade-Long Safety and Function of Retroviral-Modified Chimeric Antigen Receptor T-cells

PubMed Central

Scholler, John; Brady, Troy L.; Binder-Scholl, Gwendolyn; Hwang, Wei-Ting; Plesa, Gabriela; Hege, Kristen M.; Vogel, Ashley N.; Kalos, Michael; Riley, James L.; Deeks, Steven G.; Mitsuyasu, Ronald T.; Bernstein, Wendy B.; Aronson, Naomi E.; Levine, Bruce L.; Bushman, Frederic D.; June, Carl H.

2015-01-01

The success of adoptive T cell gene transfer for treatment of cancer and HIV is predicated on generating a response that is both durable and safe. Here we report long term results from three clinical trials to evaluate gammaretroviral vector engineered T-cells for HIV. The vector encoded a chimeric antigen receptor (CAR) comprised of CD4 linked to the CD3-ζ signaling chain (CD4ζ). CAR T-cells were detected in 98% of samples tested for at least 11 years post-infusion at frequencies that exceed average T cell levels after most vaccine approaches. The CD4ζ transgene retained expression and function. There was no evidence of vector-induced immortalization of cells as integration site distributions showed no evidence of persistent clonal expansion or enrichment for integration sites near genes implicated in growth control or transformation. The CD4ζ T cells have stable levels of engraftment, with decay half-lives that exceed 16 years, in marked contrast to previous trials testing engineered T cells. These findings indicate that host immunosuppression prior to T cell transfer is not required in order to achieve long term persistence of gene-modified T cells. Further, our results emphasize the safety of T cells modified by retroviral gene transfer in clinical application, as measured in >500 patient years of follow up. Thus, previous safety issues with integrating viral vectors are hematopoietic stem cell or transgene intrinsic, and not a general feature of retroviral vectors. Engineered T cells are a promising form of synthetic biology for long term delivery of protein based therapeutics. These results provide a framework to guide the therapy of a wide spectrum of human diseases. PMID:22553251

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites.

PubMed

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M; Quiñónes, Martha L; Jiménez, Mónica M; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J; Thomson, Madeleine C

2014-07-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. © The American Society of Tropical Medicine and Hygiene.

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

ERIC Educational Resources Information Center

Chen, Chau-Kuang

2010-01-01

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

Progressive Classification Using Support Vector Machines

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; Kocurek, Michael

2009-01-01

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user can halt this reclassification process at any point, thereby obtaining the best possible result for a given amount of computation time. Alternatively, the results can be displayed as they are generated, providing the user with real-time feedback about the current accuracy of classification.

Automated image segmentation using support vector machines

NASA Astrophysics Data System (ADS)

Powell, Stephanie; Magnotta, Vincent A.; Andreasen, Nancy C.

2007-03-01

Neurodegenerative and neurodevelopmental diseases demonstrate problems associated with brain maturation and aging. Automated methods to delineate brain structures of interest are required to analyze large amounts of imaging data like that being collected in several on going multi-center studies. We have previously reported on using artificial neural networks (ANN) to define subcortical brain structures including the thalamus (0.88), caudate (0.85) and the putamen (0.81). In this work, apriori probability information was generated using Thirion's demons registration algorithm. The input vector consisted of apriori probability, spherical coordinates, and an iris of surrounding signal intensity values. We have applied the support vector machine (SVM) machine learning algorithm to automatically segment subcortical and cerebellar regions using the same input vector information. SVM architecture was derived from the ANN framework. Training was completed using a radial-basis function kernel with gamma equal to 5.5. Training was performed using 15,000 vectors collected from 15 training images in approximately 10 minutes. The resulting support vectors were applied to delineate 10 images not part of the training set. Relative overlap calculated for the subcortical structures was 0.87 for the thalamus, 0.84 for the caudate, 0.84 for the putamen, and 0.72 for the hippocampus. Relative overlap for the cerebellar lobes ranged from 0.76 to 0.86. The reliability of the SVM based algorithm was similar to the inter-rater reliability between manual raters and can be achieved without rater intervention.

Wavefront sensing with a thin diffuser

NASA Astrophysics Data System (ADS)

Berto, Pascal; Rigneault, Hervé; Guillon, Marc

2017-12-01

We propose and implement a broadband, compact, and low-cost wavefront sensing scheme by simply placing a thin diffuser in the close vicinity of a camera. The local wavefront gradient is determined from the local translation of the speckle pattern. The translation vector map is computed thanks to a fast diffeomorphic image registration algorithm and integrated to reconstruct the wavefront profile. The simple translation of speckle grains under local wavefront tip/tilt is ensured by the so-called "memory effect" of the diffuser. Quantitative wavefront measurements are experimentally demonstrated both for the few first Zernike polynomials and for phase-imaging applications requiring high resolution. We finally provided a theoretical description of the resolution limit that is supported experimentally.

Development of a unified guidance system for geocentric transfer. [for solar electric propulsion spacecraft

NASA Technical Reports Server (NTRS)

Cake, J. E.; Regetz, J. D., Jr.

1975-01-01

A method is presented for open loop guidance of a solar electric propulsion spacecraft to geosynchronous orbit. The method consists of determining the thrust vector profiles on the ground with an optimization computer program, and performing updates based on the difference between the actual trajectory and that predicted with a precision simulation computer program. The motivation for performing the guidance analysis during the mission planning phase is discussed, and a spacecraft design option that employs attitude orientation constraints is presented. The improvements required in both the optimization program and simulation program are set forth, together with the efforts to integrate the programs into the ground support software for the guidance system.

Development of a unified guidance system for geocentric transfer. [solar electric propulsion spacecraft

NASA Technical Reports Server (NTRS)

Cake, J. E.; Regetz, J. D., Jr.

1975-01-01

A method is presented for open loop guidance of a solar electric propulsion spacecraft to geosynchronsus orbit. The method consists of determining the thrust vector profiles on the ground with an optimization computer program, and performing updates based on the difference between the actual trajectory and that predicted with a precision simulation computer program. The motivation for performing the guidance analysis during the mission planning phase is discussed, and a spacecraft design option that employs attitude orientation constraints is presented. The improvements required in both the optimization program and simulation program are set forth, together with the efforts to integrate the programs into the ground support software for the guidance system.

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Transcriptional Enhancers Induce Insertional Gene Deregulation Independently From the Vector Type and Design

PubMed Central

Maruggi, Giulietta; Porcellini, Simona; Facchini, Giulia; Perna, Serena K; Cattoglio, Claudia; Sartori, Daniela; Ambrosi, Alessandro; Schambach, Axel; Baum, Christopher; Bonini, Chiara; Bovolenta, Chiara; Mavilio, Fulvio; Recchia, Alessandra

2009-01-01

The integration characteristics of retroviral (RV) vectors increase the probability of interfering with the regulation of cellular genes, and account for a tangible risk of insertional mutagenesis in treated patients. To assess the potential genotoxic risk of conventional or self-inactivating (SIN) γ-RV and lentiviral (LV) vectors independently from the biological consequences of the insertion event, we developed a quantitative assay based on real-time reverse transcriptase—PCR on low-density arrays to evaluate alterations of gene expression in individual primary T-cell clones. We show that the Moloney leukemia virus long terminal repeat (LTR) enhancer has the strongest activity in both a γ-RV and a LV vector context, while an internal cellular promoter induces deregulation of gene expression less frequently, at a shorter range and to a lower extent in both vector types. Downregulation of gene expression was observed only in the context of LV vectors. This study indicates that insertional gene activation is determined by the characteristics of the transcriptional regulatory elements carried by the vector, and is largely independent from the vector type or design. PMID:19293778

Continuous Influx of Genetic Material from Host to Virus Populations

PubMed Central

Gilbert, Clément; Peccoud, Jean; Chateigner, Aurélien; Moumen, Bouziane

2016-01-01

Many genes of large double-stranded DNA viruses have a cellular origin, suggesting that host-to-virus horizontal transfer (HT) of DNA is recurrent. Yet, the frequency of these transfers has never been assessed in viral populations. Here we used ultra-deep DNA sequencing of 21 baculovirus populations extracted from two moth species to show that a large diversity of moth DNA sequences (n = 86) can integrate into viral genomes during the course of a viral infection. The majority of the 86 different moth DNA sequences are transposable elements (TEs, n = 69) belonging to 10 superfamilies of DNA transposons and three superfamilies of retrotransposons. The remaining 17 sequences are moth sequences of unknown nature. In addition to bona fide DNA transposition, we uncover microhomology-mediated recombination as a mechanism explaining integration of moth sequences into viral genomes. Many sequences integrated multiple times at multiple positions along the viral genome. We detected a total of 27,504 insertions of moth sequences in the 21 viral populations and we calculate that on average, 4.8% of viruses harbor at least one moth sequence in these populations. Despite this substantial proportion, no insertion of moth DNA was maintained in any viral population after 10 successive infection cycles. Hence, there is a constant turnover of host DNA inserted into viral genomes each time the virus infects a moth. Finally, we found that at least 21 of the moth TEs integrated into viral genomes underwent repeated horizontal transfers between various insect species, including some lepidopterans susceptible to baculoviruses. Our results identify host DNA influx as a potent source of genetic diversity in viral populations. They also support a role for baculoviruses as vectors of DNA HT between insects, and call for an evaluation of possible gene or TE spread when using viruses as biopesticides or gene delivery vectors. PMID:26829124

Continuous Influx of Genetic Material from Host to Virus Populations.

PubMed

Gilbert, Clément; Peccoud, Jean; Chateigner, Aurélien; Moumen, Bouziane; Cordaux, Richard; Herniou, Elisabeth A

2016-02-01

Many genes of large double-stranded DNA viruses have a cellular origin, suggesting that host-to-virus horizontal transfer (HT) of DNA is recurrent. Yet, the frequency of these transfers has never been assessed in viral populations. Here we used ultra-deep DNA sequencing of 21 baculovirus populations extracted from two moth species to show that a large diversity of moth DNA sequences (n = 86) can integrate into viral genomes during the course of a viral infection. The majority of the 86 different moth DNA sequences are transposable elements (TEs, n = 69) belonging to 10 superfamilies of DNA transposons and three superfamilies of retrotransposons. The remaining 17 sequences are moth sequences of unknown nature. In addition to bona fide DNA transposition, we uncover microhomology-mediated recombination as a mechanism explaining integration of moth sequences into viral genomes. Many sequences integrated multiple times at multiple positions along the viral genome. We detected a total of 27,504 insertions of moth sequences in the 21 viral populations and we calculate that on average, 4.8% of viruses harbor at least one moth sequence in these populations. Despite this substantial proportion, no insertion of moth DNA was maintained in any viral population after 10 successive infection cycles. Hence, there is a constant turnover of host DNA inserted into viral genomes each time the virus infects a moth. Finally, we found that at least 21 of the moth TEs integrated into viral genomes underwent repeated horizontal transfers between various insect species, including some lepidopterans susceptible to baculoviruses. Our results identify host DNA influx as a potent source of genetic diversity in viral populations. They also support a role for baculoviruses as vectors of DNA HT between insects, and call for an evaluation of possible gene or TE spread when using viruses as biopesticides or gene delivery vectors.

Genetic modification of Lactobacillus plantarum by heterologous gene integration in a not functional region of the chromosome.

PubMed

Rossi, Franca; Capodaglio, Alessandro; Dellaglio, Franco

2008-08-01

This report describes the vector-free engineering of Lactobacillus plantarum by chromosomal integration of an exogenous gene without inactivation of physiological traits. The integrative plasmid vector pP7B6 was derived from pGIP73 by replacing the cbh site, encoding the L. plantarum conjugated bile salt hydrolase, with the prophage fragment P7B6, from L. plantarum Lp80 (DSM 4229). Plasmid pP7B6NI was obtained by inserting the nisin immunity gene nisI of Lactococcus lactis subsp. lactis DSM 20729, preceded by the constitutive promoter P32 from the same strain, in a unique XbaI site of fragment P7B6 and was used to electrotransform L. plantarum Lp80. A food grade recombinant L. plantarum Lp80NI, with 480-fold higher immunity to nisin than the wild type, was derived by integration of pP7B6NI followed by the excision of pP7B6. Polymerase chain reaction tests demonstrated that the integration of nisI in the prophage region had occurred and that the erythromycin resistance marker from pP7B6 was lost. Fifteen among 31 L. plantarum strains tested hybridized with P7B6, indicating that the integration of pP7B6-derived vectors might occur in some other L. plantarum strains. This was experimentally confirmed by constructing the recombinant strain L. plantarum LZNI from the dairy isolate L. plantarum LZ (LMG 24600).

Integrating and Analyzing Psychosocial and Stage Theories to Challenge the Development of the Injured Collegiate Athlete

PubMed Central

2003-01-01

Objective: To integrate a psychosocial developmental theory and a psychological stage theory for challenging an injured collegiate student-athlete's personal development and to highlight future areas of research. Data Sources: I searched Education Abstracts, ERIC, Social Science Citation Index, and SPORT Discus for the years 1990–2001 using the key words student-athlete, injury, psychological reaction, Chickering, and psychosocial. Data Synthesis: Stage theories are theoretic models that outline basic reactions to a stressor, regardless of age, sex, or ethnicity. In textbooks addressing the injured athlete, the Kubler-Ross stages of bereavement constitute one of the most commonly presented stage theories addressing the psychological reaction to injury. Psychosocial theories, on the other hand, such as the Chickering and Reisser theory, are theoretic models developed in the educational literature that outline the personal development process (ie, vectors) through which adolescents and adults progress. For this review, the Kubler-Ross and Chickering and Reisser revised theories will be used to outline possible psychological reactions to injury throughout the development progression from vector 1, competence, through vector 7, integrity. Conclusions: The 1999 Athletic Training Clinical Proficiencies as outlined by the National Athletic Trainers' Association Education Council require clinical proficiencies in the area of psychosocial intervention and referral, yet psychosocial theory is rarely addressed in athletic training educational curricula or texts. Presenting a universal psychosocial developmental theory, such as the Chickering and Reisser 7 vectors, and integrating a common stage theory, such as the Kubler-Ross stages of bereavement, are beneficial in providing athletic training students and athletic trainers additional skills to recognize and mediate negative psychological reactions to injury and in illuminating new areas of research. PMID:16558677

Integrating and analyzing psychosocial and stage theories to challenge the development of the injured collegiate athlete.

PubMed

Harris, Laura L

2003-01-01

To integrate a psychosocial developmental theory and a psychological stage theory for challenging an injured collegiate student-athlete's personal development and to highlight future areas of research. I searched Education Abstracts, ERIC, Social Science Citation Index, and SPORT Discus for the years 1990-2001 using the key words student-athlete,injury,psychological reaction,Chickering, and psychosocial. Stage theories are theoretic models that outline basic reactions to a stressor, regardless of age, sex, or ethnicity. In textbooks addressing the injured athlete, the Kubler-Ross stages of bereavement constitute one of the most commonly presented stage theories addressing the psychological reaction to injury. Psychosocial theories, on the other hand, such as the Chickering and Reisser theory, are theoretic models developed in the educational literature that outline the personal development process (ie, vectors) through which adolescents and adults progress. For this review, the Kubler-Ross and Chickering and Reisser revised theories will be used to outline possible psychological reactions to injury throughout the development progression from vector 1, competence, through vector 7, integrity. The 1999 Athletic Training Clinical Proficiencies as outlined by the National Athletic Trainers' Association Education Council require clinical proficiencies in the area of psychosocial intervention and referral, yet psychosocial theory is rarely addressed in athletic training educational curricula or texts. Presenting a universal psychosocial developmental theory, such as the Chickering and Reisser 7 vectors, and integrating a common stage theory, such as the Kubler-Ross stages of bereavement, are beneficial in providing athletic training students and athletic trainers additional skills to recognize and mediate negative psychological reactions to injury and in illuminating new areas of research.

Evolutionary-driven support vector machines for determining the degree of liver fibrosis in chronic hepatitis C.

PubMed

Stoean, Ruxandra; Stoean, Catalin; Lupsor, Monica; Stefanescu, Horia; Badea, Radu

2011-01-01

Hepatic fibrosis, the principal pointer to the development of a liver disease within chronic hepatitis C, can be measured through several stages. The correct evaluation of its degree, based on recent different non-invasive procedures, is of current major concern. The latest methodology for assessing it is the Fibroscan and the effect of its employment is impressive. However, the complex interaction between its stiffness indicator and the other biochemical and clinical examinations towards a respective degree of liver fibrosis is hard to be manually discovered. In this respect, the novel, well-performing evolutionary-powered support vector machines are proposed towards an automated learning of the relationship between medical attributes and fibrosis levels. The traditional support vector machines have been an often choice for addressing hepatic fibrosis, while the evolutionary option has been validated on many real-world tasks and proven flexibility and good performance. The evolutionary approach is simple and direct, resulting from the hybridization of the learning component within support vector machines and the optimization engine of evolutionary algorithms. It discovers the optimal coefficients of surfaces that separate instances of distinct classes. Apart from a detached manner of establishing the fibrosis degree for new cases, a resulting formula also offers insight upon the correspondence between the medical factors and the respective outcome. What is more, a feature selection genetic algorithm can be further embedded into the method structure, in order to dynamically concentrate search only on the most relevant attributes. The data set refers 722 patients with chronic hepatitis C infection and 24 indicators. The five possible degrees of fibrosis range from F0 (no fibrosis) to F4 (cirrhosis). Since the standard support vector machines are among the most frequently used methods in recent artificial intelligence studies for hepatic fibrosis staging, the evolutionary method is viewed in comparison to the traditional one. The multifaceted discrimination into all five degrees of fibrosis and the slightly less difficult common separation into solely three related stages are both investigated. The resulting performance proves the superiority over the standard support vector classification and the attained formula is helpful in providing an immediate calculation of the liver stage for new cases, while establishing the presence/absence and comprehending the weight of each medical factor with respect to a certain fibrosis level. The use of the evolutionary technique for fibrosis degree prediction triggers simplicity and offers a direct expression of the influence of dynamically selected indicators on the corresponding stage. Perhaps most importantly, it significantly surpasses the classical support vector machines, which are both widely used and technically sound. All these therefore confirm the promise of the new methodology towards a dependable support within the medical decision-making. Copyright © 2010 Elsevier B.V. All rights reserved.