Detection and molecular characterisation of Pyrenopeziza brassicae isolates resistant to methyl benzimidazole carbamates

BACKGROUND Methyl benzimidazole carbamate (MBC) fungicides are used to control the oilseed rape pathogen Pyrenopeziza brassicae. Resistance to MBCs has been reported in P. brassicae, but the molecular mechanism(s) associated with reductions in sensitivity have not been verified in this species. Elucidation of the genetic changes responsible for resistance, hypothesised to be target-site mutations in β-tubulin, will enable resistance diagnostics and thereby inform resistance management strategies. RESULTS P. brassicae isolates were classified as sensitive, moderately resistant or resistant to MBCs. Crossing P. brassicae isolates of different MBC sensitivities indicated that resistance was conferred by a single gene. The MBC-target encoding gene β-tubulin was cloned and sequenced. Reduced MBC sensitivity of field isolates correlated with β-tubulin amino acid substitutions L240F and E198A. The highest level of MBC resistance was measured for isolates carrying E198A. Negative cross-resistance between MBCs and the fungicides diethofencarb and zoxamide was only measured in E198A isolates. PCR-RFLP was used to screen isolates for the presence of L240F and E198A. The substitutions E198G and F200Y were also detected in DNA samples from P. brassicae populations after cloning and sequencing of PCR products. The frequencies of L240F and E198A in different P. brassicae populations were quantified by pyrosequencing. There were no differences in the frequencies of these alleles between P. brassicae populations sampled from different locations or after fungicide treatment regimes. CONCLUSIONS The molecular mechanisms affecting sensitivity to MBCs in P. brassicae have been identified. Pyrosequencing assays are a powerful tool for quantifying fungicide-resistant alleles in pathogen populations.

Scalable and fault tolerant failure detection and consensus

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum's User Level Failure Mitigation proposal has introduced an operation, MPI_Comm_shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI_Comm_shrink operation requires a fault tolerant failure detection and consensus algorithm. This paper presents and compares two novel failure detection and consensus algorithms. The proposed algorithms are based on Gossip protocols and are inherently fault-tolerant and scalable. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in both algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus.

On the detection and attribution of gravity waves generated by the 20 March 2015 solar eclipse

Internal gravity waves are generated as adjustment radiation whenever a sudden change in forcing causes the atmosphere to depart from its large-scale balanced state. Such a forcing anomaly occurs during a solar eclipse, when the Moon’s shadow cools part of the Earth’s surface. The resulting atmospheric gravity waves are associated with pressure and temperature perturbations, which in principle are detectable both at the surface and aloft. In this study, surface pressure and temperature data from two UK sites at Reading and Lerwick are analysed for eclipse-driven gravity-wave perturbations during the 20 March 2015 solar eclipse over north-west Europe. Radiosonde wind data from the same two sites are also analysed using a moving parcel analysis method, to determine the periodicities of the waves aloft. On this occasion, the perturbations both at the surface and aloft are found not to be confidently attributable to eclipse-driven gravity waves. We conclude that the complex synoptic weather conditions over the UK at the time of this particular eclipse helped to mask any eclipse-driven gravity waves.

Detection and attribution of human influence on regional precipitation

Understanding how human influence on climate is affecting precipitation around the world is immensely important for defining mitigation policies, and for adaptation planning. Yet despite increasing evidence for the influence of climate change on global patterns of precipitation, and expectations that significant changes in regional precipitation should have already occurred as a result of human influence on climate, compelling evidence of anthropogenic fingerprints on regional precipitation is obscured by observational and modelling uncertainties and is likely to remain so using current methods for years to come. This is in spite of substantial ongoing improvements in models, new reanalyses and a satellite record that spans over thirty years. If we are to quantify how human-induced climate change is affecting the regional water cycle, we need to consider novel ways of identifying the effects of natural and anthropogenic influences on precipitation that take full advantage of our physical expectations.

Use of the DNA Checkerboard hybridization method for detection and quantitation of Candida species in oral microbiota

The DNA Checkerboard method enables the simultaneous identification of distinct microorganisms in a large number of samples and employs up to 45 whole genomic DNA probes to gram-negative and gram-positive bacterial species present in subgingival biofilms. Collectively, they account for 55%-60% of the bacteria in subgingival biofilms. In this study, we present the DNA Checkerboard hybridization as an alternative method for the detection and quantitation of Candida species in oral cavities. Our results reveal that DNA Checkerboard is sensitive enough and constitutes a powerful and appropriate method for detecting and quantifying Candida species found in the oral cavity.

Aeromonas detection and their toxins from drinking water from reservoirs and drinking fountains

Aeromonads are inhabitants of aquatic ecosystems and are described as being involved in intestinal disturbances and other infections. A total of 200 drinking water samples from domestic and public reservoirs and drinking fountains located in Sao Paulo (Brazil), were analyzed for the presence of Aeromonas. Samples were concentrated by membrane filtration and enriched in APW. ADA medium was used for Aeromonas isolation and colonies were confirmed by biochemical characterization. Strains isolated were tested for hemolysin and toxin production. Aeromonas was detected in 12 samples (6.0%). Aeromonas strains (96) were isolated and identified as: A. caviae (41.7%), A. hydrophila (15.7%), A. allosacharophila (10.4%), A. schubertii (1.0%) and Aeromonas spp. (31.2%). The results revealed that 70% of A. caviare, 66.7% of A. hydrophila, 80% of A. allosacharophila and 46.6% of Aeromonas spp. were hemolytic. The assay for checking production of toxins showed that 17.5% of A. caviae, 73.3% of A. hydrophila, 60% of A. allosacharophila, 100% of A. schubertii, and 33.3% of Aeromonas spp. were able to produce toxins. The results demonstrated the pathogenic potential of Aeromonas, indicating that the presence of this emerging pathogen in water systems is a public health concern.

Comparing detection and location performance of perpendicular and parallel broadside GPR antenna orientations

GPR (Ground Penetrating Radar) results are shown for perpendicular broadside and parallel broadside antenna orientations. Performance in detection and localization of concrete tubes and steel tanks is compared as a function of acquisition configuration. The comparison is done using 100 MHz and 200 MHz center frequency antennas. All tubes and tanks are buried at the geophysical test site of IAG/USP in Sao Paulo city, Brazil. The results show that the long steel pipe with a 38-mm diameter was well detected with the perpendicular broadside configuration. The concrete tubes were better detected with the parallel broadside configuration, clearly showing hyperbolic diffraction events from all targets up to 2-m depth. Steel tanks were detected with the two configurations. However, the parallel broadside configuration was generated to a much lesser extent an apparent hyperbolic reflection corresponding to constructive interference of diffraction hyperbolas of adjacent targets placed at the same depth. Vertical concrete tubes and steel tanks were better contained with parallel broadside antennas, where the apexes of the diffraction hyperbolas better corresponded to the horizontal location of the buried target disposition. The two configurations provide details about buried targets emphasizing how GPR multi-component configurations have the potential to improve the subsurface image quality as well as to discriminate different buried targets. It is judged that they hold some applicability in geotechnical and geoscientific studies. (C) 2009 Elsevier B.V. All rights reserved.

Objective Detection and Delineation of Oral Neoplasia Using Autofluorescence Imaging

Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.

Multiple camera people detection and tracking using support integration

This paper proposes a method to locate and track people by combining evidence from multiple cameras using the homography constraint. The proposed method use foreground pixels from simple background subtraction to compute evidence of the location of people on a reference ground plane. The algorithm computes the amount of support that basically corresponds to the ""foreground mass"" above each pixel. Therefore, pixels that correspond to ground points have more support. The support is normalized to compensate for perspective effects and accumulated on the reference plane for all camera views. The detection of people on the reference plane becomes a search for regions of local maxima in the accumulator. Many false positives are filtered by checking the visibility consistency of the detected candidates against all camera views. The remaining candidates are tracked using Kalman filters and appearance models. Experimental results using challenging data from PETS`06 show good performance of the method in the presence of severe occlusion. Ground truth data also confirms the robustness of the method. (C) 2010 Elsevier B.V. All rights reserved.

Recovery of DNA for the detection and genotyping of human papillomavirus from clinical cervical specimens stored for up to 2 years in a universal collection medium with denaturing reagent

The recovery and stability of DNA for the detection and genotyping of HPV in UCM-containing specimens, after exposure to denaturing reagents and stored for up to 2 years were evaluated. Samples were collected from 60 women who had cervical cytology specimens harboring cervical intraepithelial neoplasia (CIN) 2 or 3. All samples were stored in UCM and had been frozen at -20 degrees C following the addition of the denaturing reagent (sodium hydroxide) and the removal of the aliquot required for Hybrid Capture 2 testing for the identification of HPV DNA. The samples had been stored for 6, 12 and 24 months (20 samples for each storage time). HPV DNA extraction was performed according to a protocol designed specifically and the presence and quality of DNA was confirmed by human P-globin detection using the consensus primers G73 and G74. HPV DNA was amplified using the consensus primers PGMY09 and PGMY11, and reverse line-blot hybridization was used to detect type-specific amplicons for 37 HPV types. The DNA extracted from the denatured specimen was recovered in 57/60 (95%) of the samples. HPV DNA was detected in 56/57 (98%) of the recovered samples. Twenty-six of the 56 samples recovered (48%) were genotyped successfully. (c) 2007 Elsevier B.V. All rights reserved.

Detection and Characterization of Cholesterol-Oxidized Products Using HPLC Coupled to Dopant Assisted Atmospheric Pressure Photoionization Tandem Mass Spectrometry

Oxidation of cholesterol (Ch) by a variety of reactive oxygen species gives rise mainly to hydroperoxides and aldehydes. Despite the growing interest in Ch-oxidized products, the detection and characterization of these products is still a matter of concern. In this work, the main Ch-oxidized products, namely, 3 beta-hydroxycholest-5-ene-7 alpha-hydroperoxide (7 alpha-OOH), 3 beta-5 alpha-cholest-6-ene-5-hydroperoxide (5 alpha-OOH), 3 beta-hydroxycholest-4-ene-6 alpha-hydroperoxide (6 alpha-OOH), 3 beta-hydroxycholest-4-ene-6 beta-hydroperoxide (6 beta-OOH), and 3 beta-hydroxy-5 beta-hydroxy-B-norcholestane-6 beta-carboxaldehyde (ChAld), were detected in the same analysis using high-performance liquid chromatography (HPLC) coupled to dopant assisted atmospheric pressure photoionization tandem mass spectrometry. The use of selected reaction monitoring mode (SRM) allowed a sensitive detection of each oxidized product, while the enhanced product ion mode (EPI) helped to improve the confidence of the analyses. Isotopic labeling experiments enabled one to elucidate mechanistic features during fragmentation processes. The characteristic fragmentation pattern of Ch-oxidized products is the consecutive loss of 1120 molecules, yielding cationic fragments at m/z 401, 383, and 365. Homolytic scissions of the peroxide bond are also seen. With (18)O-labeling approach, it was possible to establish a fragmentation order for each isomer. The SRM transitions ratio along with EPI and (18)O-labeled experiments give detailed information about differences for water elimination, allowing a proper discrimination between the isomers:Phis is of special interest considering the emerging role of Ch-oxidized products in the development of diseases.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Color detection and segmentation for road and traffic signs

This paper aims to present three new methods for color detection and segmentation of road signs. The images are taken by a digital camera mounted in a car. The RGB images are converted into IHLS color space, and new methods are applied to extract the colors of the road signs under consideration. The methods are tested on hundreds of outdoor images in different light conditions, and they show high robustness. This project is part of the research taking place in Dalarna University / Sweden in the field of the ITS.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis

LOPES-DOS-SANTOS, V. , CONDE-OCAZIONEZ, S. ; NICOLELIS, M. A. L. , RIBEIRO, S. T. , TORT, A. B. L. . Neuronal assembly detection and cell membership specification by principal component analysis. Plos One, v. 6, p. e20996, 2011.