Impact of Wolbachia on infection with chikungunya and yellow fever viruses in the mosquito vector Aedes aegypti

Incidence of disease due to dengue (DENV), chikungunya (CHIKV) and yellow fever (YFV) viruses is increasing in many parts of the world. The viruses are primarily transmitted by Aedes aegypti, a highly domesticated mosquito species that is notoriously difficult to control. When transinfected into Ae. aegypti, the intracellular bacterium Wolbachia has recently been shown to inhibit replication of DENVs, CHIKV, malaria parasites and filarial nematodes, providing a potentially powerful biocontrol strategy for human pathogens. Because the extent of pathogen reduction can be influenced by the strain of bacterium, we examined whether the wMel strain of Wolbachia influenced CHIKV and YFV infection in Ae. aegypti. Following exposure to viremic blood meals, CHIKV infection and dissemination rates were significantly reduced in mosquitoes with the wMel strain of Wolbachia compared to Wolbachia-uninfected controls. However, similar rates of infection and dissemination were observed in wMel infected and non-infected Ae. aegypti when intrathoracic inoculation was used to deliver virus. YFV infection, dissemination and replication were similar in wMel-infected and control mosquitoes following intrathoracic inoculations. In contrast, mosquitoes with the wMelPop strain of Wolbachia showed at least a 10(4) times reduction in YFV RNA copies compared to controls. The extent of reduction in virus infection depended on Wolbachia strain, titer and strain of the virus, and mode of exposure. Although originally proposed for dengue biocontrol, our results indicate a Wolbachia-based strategy also holds considerable promise for YFV and CHIKV suppression.

Improving short utterance based I-vector speaker recognition using source and utterance-duration normalization techniques

A significant amount of speech is typically required for speaker verification system development and evaluation, especially in the presence of large intersession variability. This paper introduces a source and utterance duration normalized linear discriminant analysis (SUN-LDA) approaches to compensate session variability in short-utterance i-vector speaker verification systems. Two variations of SUN-LDA are proposed where normalization techniques are used to capture source variation from both short and full-length development i-vectors, one based upon pooling (SUN-LDA-pooled) and the other on concatenation (SUN-LDA-concat) across the duration and source-dependent session variation. Both the SUN-LDA-pooled and SUN-LDA-concat techniques are shown to provide improvement over traditional LDA on NIST 08 truncated 10sec-10sec evaluation conditions, with the highest improvement obtained with the SUN-LDA-concat technique achieving a relative improvement of 8% in EER for mis-matched conditions and over 3% for matched conditions over traditional LDA approaches.

A novel T-DNA vector design for selection of transgenic lines with simple transgene integration and stable transgene expression

Plants transformed with Agrobacterium frequently contain T-DNA concatamers with direct-repeat (d/r) or inverted-repeat (i/r) transgene integrations, and these repetitive T-DNA insertions are often associated with transgene silencing. To facilitate the selection of transgenic lines with simple T-DNA insertions, we constructed a binary vector (pSIV) based on the principle of hairpin RNA (hpRNA)-induced gene silencing. The vector is designed so that any transformed cells that contain more than one insertion per locus should generate hpRNA against the selective marker gene, leading to its silencing. These cells should, therefore, be sensitive to the selective agent and less likely to regenerate. Results from Arabidopsis and tobacco transformation showed that pSIV gave considerably fewer transgenic lines with repetitive insertions than did a conventional T-DNA vector (pCON). Furthermore, the transgene was more stably expressed in the pSIV plants than in the pCON plants. Rescue of plant DNA flanking sequences from pSIV plants was significantly more frequent than from pCON plants, suggesting that pSIV is potentially useful for T-DNA tagging. Our results revealed a perfect correlation between the presence of tail-to-tail inverted repeats and transgene silencing, supporting the view that read-through hpRNA transcript derived from i/r T-DNA insertions is a primary inducer of transgene silencing in plants. © CSIRO 2005.

Marker gene elimination from transgenic barley, using co-transformation with adjacent 'twin T-DNAs' on a standard Agrobacterium transformation vector

We have tested a methodology for the elimination of the selectable marker gene after Agrobacterium-mediated transformation of barley. This involves segregation of the selectable marker gene away from the gene of interest following co-transformation using a plasmid carrying two T-DNAs, which were located adjacent to each other with no intervening region. A standard binary transformation vector was modified by insertion of a small section composed of an additional left and right T-DNA border, so that the selectable marker gene and the site for insertion of the gene of interest (GOI) were each flanked by a left and right border. Using this vector three different GOIs were transformed into barley. Analysis of transgene inheritance was facilitated by a novel and rapid assay utilizing PCR amplification from macerated leaf tissue. Co-insertion was observed in two thirds of transformants, and among these approximately one quarter had transgene inserts which segregated in the next generation to yield selectable marker-free transgenic plants. Insertion of non-T-DNA plasmid sequences was observed in only one of fourteen SMF lines tested. This technique thus provides a workable system for generating transgenic barley free from selectable marker genes, thereby obviating public concerns regarding proliferation of these genes.

Improving short utterance i-vector speaker verification using utterance variance modelling and compensation techniques

This paper proposes techniques to improve the performance of i-vector based speaker verification systems when only short utterances are available. Short-length utterance i-vectors vary with speaker, session variations, and the phonetic content of the utterance. Well established methods such as linear discriminant analysis (LDA), source-normalized LDA (SN-LDA) and within-class covariance normalisation (WCCN) exist for compensating the session variation but we have identified the variability introduced by phonetic content due to utterance variation as an additional source of degradation when short-duration utterances are used. To compensate for utterance variations in short i-vector speaker verification systems using cosine similarity scoring (CSS), we have introduced a short utterance variance normalization (SUVN) technique and a short utterance variance (SUV) modelling approach at the i-vector feature level. A combination of SUVN with LDA and SN-LDA is proposed to compensate the session and utterance variations and is shown to provide improvement in performance over the traditional approach of using LDA and/or SN-LDA followed by WCCN. An alternative approach is also introduced using probabilistic linear discriminant analysis (PLDA) approach to directly model the SUV. The combination of SUVN, LDA and SN-LDA followed by SUV PLDA modelling provides an improvement over the baseline PLDA approach. We also show that for this combination of techniques, the utterance variation information needs to be artificially added to full-length i-vectors for PLDA modelling.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Secure computation of the vector dominance problem

Suppose two parties, holding vectors A = (a 1,a 2,...,a n ) and B = (b 1,b 2,...,b n ) respectively, wish to know whether a i  > b i for all i, without disclosing any private input. This problem is called the vector dominance problem, and is closely related to the well-studied problem for securely comparing two numbers (Yao’s millionaires problem). In this paper, we propose several protocols for this problem, which improve upon existing protocols on round complexity or communication/computation complexity.

Fault diagnosis of low speed bearing based on acoustic emission signal and multi-class relevance vector machine

This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

pGreen : a versatile and flexible binary Ti vector for Agrobacterium-mediated plant transformation

Binary Ti vectors are the plasmid vectors of choice in Agrobacterium-mediated plant transformation protocols. The pGreen series of binary Ti vectors are configured for ease-of-use and to meet the demands of a wide range of transformation procedures for many plant species. This plasmid system allows any arrangement of selectable marker and reporter gene at the right and left T-DNA borders without compromising the choice of restriction sites for cloning, since the pGreen cloning sites are based on the well-known pBluescript general vector plasmids. Its size and copy number in Escherichia coli offers increased efficiencies in routine in vitro recombination procedures. pGreen can replicate in Agrobacterium only if another plasmid, pSoup, is co-resident in the same strain. pSoup provides replication functions in trans for pGreen. The removal of RepA and Mob functions has enabled the size of pGreen to be kept to a minimum. Versions of pGreen have been used to transform several plant species with the same efficiencies as other binary Ti vectors. Information on the pGreen plasmid system is supplemented by an Internet site (http://www.pgreen.ac.uk) through which comprehensive information, protocols, order forms and lists of different pGreen marker gene permutations can be found.

Bit-stream-based space vector modulators

Bit-stream-based control, which uses one bit wide signals to control power electronics applications, is a new approach for controller design in power electronic systems. This study presents a novel family of three-phase space vector modulators, which are based on the bit-stream technique and suitable for three-phase inverter systems. Each of the proposed modulators simultaneously converts a two-phase reference to the three-phase domain and reduces switching frequencies to reasonable levels. The modulators do not require carrier oscillators, trigonometric functions or, in some cases, sector detectors. A complete three-phase modulator can be implemented in as few as 102 logic elements. The performance of the proposed modulators is compared through simulation and experimental testing of a 6 kW, three-phase DC-to-AC inverter. Subject to limits on the modulation index, the proposed modulators deliver spread-spectrum output currents with total harmonic distortion comparable to a standard carrier-based space vector pulse width modulator.

Series in vector spherical harmonics : an efficient tool for solution of nonlinear problems in spherical plasmas

The series expansion of the plasma fields and currents in vector spherical harmonics has been demonstrated to be an efficient technique for solution of nonlinear problems in spherically bounded plasmas. Using this technique, it is possible to describe the nonlinear plasma response to the rotating high-frequency magnetic field applied to the magnetically confined plasma sphere. The effect of the external magnetic field on the current drive and field configuration is studied. The results obtained are important for continuous current drive experiments in compact toruses. © 2000 American Institute of Physics.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

A Bit-Stream based space vector modulator

Bit-Stream based control, which uses one bit wide signals to control power electronics applications, is a new approach for controller design in power electronic systems. Bit-Stream signals are inherently high frequency in nature, and as such some form of down sampling or modulating is essential to avoid excessive switching losses. This paper presents a novel three-phase space vector modulator, which is based on the Bit-Stream technique and suitable for standard three-phase inverter systems. The proposed modulator simultaneously converts a two phase reference to the three-phase domain and reduces switching frequencies to reasonable levels. The modulator consumes relatively few logic elements and does not require sector detectors, carrier oscillators or trigonometric functions. The performance of the modulator was evaluated using ModelSim. Results indicate that, subject to limits on the modulation index, the proposed modulator delivers a spread-spectrum output with total harmonic distortion comparable to standard space vector pulse width modulation techniques.