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Sample records for single wheat kernel

  1. Development of nondestructive screening methods for single kernel characterization of wheat

    DEFF Research Database (Denmark)

    Nielsen, J.P.; Pedersen, D.K.; Munck, L.

    2003-01-01

    predictability. However, by applying an averaging approach, in which single seed replicate measurements are mathematically simulated, a very good NIT prediction model was achieved. This suggests that the single seed NIT spectra contain hardness information, but that a single seed hardness method with higher......The development of nondestructive screening methods for single seed protein, vitreousness, density, and hardness index has been studied for single kernels of European wheat. A single kernel procedure was applied involving, image analysis, near-infrared transmittance (NIT) spectroscopy, laboratory...

  2. Exploring abiotic stress on asynchronous protein metabolism in single kernels of wheat studied by NMR spectroscopy and chemometrics

    DEFF Research Database (Denmark)

    Winning, H.; Viereck, N.; Wollenweber, B.

    2009-01-01

    at the vegetative growth stage had little effect on the parameters investigated. For the first time, H-1 HR-MAS NMR spectra of grains taken during grain-filling were analysed by an advanced multiway model. In addition to the results from the chemical protein analysis and the H-1 HR-MAS NMR spectra of single kernels...... was to examine the implications of different drought treatments on the protein fractions in grains of winter wheat using H-1 nuclear magnetic resonance spectroscopy followed by chemometric analysis. Triticum aestivum L. cv. Vinjett was studied in a semi-field experiment and subjected to drought episodes either...... at terminal spikelet, during grain-filling or at both stages. Principal component trajectories of the total protein content and the protein fractions of flour as well as the H-1 NMR spectra of single wheat kernels, wheat flour, and wheat methanol extracts were analysed to elucidate the metabolic development...

  3. Occurrence of 'super soft' wheat kernel texture in hexaploid and tetraploid wheats

    Science.gov (United States)

    Wheat kernel texture is a key trait that governs milling performance, flour starch damage, flour particle size, flour hydration properties, and baking quality. Kernel texture is commonly measured using the Perten Single Kernel Characterization System (SKCS). The SKCS returns texture values (Hardness...

  4. Influence of wheat kernel physical properties on the pulverizing process.

    Science.gov (United States)

    Dziki, Dariusz; Cacak-Pietrzak, Grażyna; Miś, Antoni; Jończyk, Krzysztof; Gawlik-Dziki, Urszula

    2014-10-01

    The physical properties of wheat kernel were determined and related to pulverizing performance by correlation analysis. Nineteen samples of wheat cultivars about similar level of protein content (11.2-12.8 % w.b.) and obtained from organic farming system were used for analysis. The kernel (moisture content 10 % w.b.) was pulverized by using the laboratory hammer mill equipped with round holes 1.0 mm screen. The specific grinding energy ranged from 120 kJkg(-1) to 159 kJkg(-1). On the basis of data obtained many of significant correlations (p kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

  5. End-use quality of soft kernel durum wheat

    Science.gov (United States)

    Kernel texture is a major determinant of end-use quality of wheat. Durum wheat has very hard kernels. We developed soft kernel durum wheat via Ph1b-mediated homoeologous recombination. The Hardness locus was transferred from Chinese Spring to Svevo durum wheat via back-crossing. ‘Soft Svevo’ had SKC...

  6. Modeling of the endosperm crush response profile of hard red spring wheat using a single kernel characterization system

    Science.gov (United States)

    When a wheat endosperm is crushed the force profile shows viscoelastic response and the modulus of elasticity is an important parameter that might have substantial influence on wheat milling. An experiment was performed to model endosperm crush response profile (ECRP) and to determine the modulus o...

  7. Enhanced gluten properties in soft kernel durum wheat

    Science.gov (United States)

    Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...

  8. Flour quality and kernel hardness connection in winter wheat

    Directory of Open Access Journals (Sweden)

    Szabó B. P.

    2016-12-01

    Full Text Available Kernel hardness is controlled by friabilin protein and it depends on the relation between protein matrix and starch granules. Friabilin is present in high concentration in soft grain varieties and in low concentration in hard grain varieties. The high gluten, hard wheat our generally contains about 12.0–13.0% crude protein under Mid-European conditions. The relationship between wheat protein content and kernel texture is usually positive and kernel texture influences the power consumption during milling. Hard-textured wheat grains require more grinding energy than soft-textured grains.

  9. Identification of Fusarium damaged wheat kernels using image analysis

    Directory of Open Access Journals (Sweden)

    Ondřej Jirsa

    2011-01-01

    Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.

  10. Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

    Science.gov (United States)

    Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...

  11. Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

    Science.gov (United States)

    2013-01-01

    Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

  12. Mapping quantitative trait loci for a unique 'super soft' kernel trait in soft white wheat

    Science.gov (United States)

    Wheat (Triticum sp.) kernel texture is an important factor affecting milling, flour functionality, and end-use quality. Kernel texture is normally characterized as either hard or soft, the two major classes of texture. However, further variation is typically encountered in each class. Soft wheat var...

  13. Influence of soft kernel texture on the flour and baking quality of durum wheat

    Science.gov (United States)

    Durum wheat is predominantly grown in semi-arid to arid environments where common wheat does not flourish, especially in the Middle East, North Africa, Mediterranean Basin, and portions of North America. Durum kernels are extraordinarily hard when compared to their common wheat counterparts. Due to ...

  14. Agricultural factors affecting Fusarium communities in wheat kernels.

    Science.gov (United States)

    Karlsson, Ida; Friberg, Hanna; Kolseth, Anna-Karin; Steinberg, Christian; Persson, Paula

    2017-07-03

    Fusarium head blight (FHB) is a devastating disease of cereals caused by Fusarium fungi. The disease is of great economic importance especially owing to reduced grain quality due to contamination by a range of mycotoxins produced by Fusarium. Disease control and prediction is difficult because of the many Fusarium species associated with FHB. Different species may respond differently to control methods and can have both competitive and synergistic interactions. Therefore, it is important to understand how agricultural practices affect Fusarium at the community level. Lower levels of Fusarium mycotoxin contamination of organically produced cereals compared with conventionally produced have been reported, but the causes of these differences are not well understood. The aim of our study was to investigate the effect of agricultural factors on Fusarium abundance and community composition in different cropping systems. Winter wheat kernels were collected from 18 organically and conventionally cultivated fields in Sweden, paired based on their geographical distance and the wheat cultivar grown. We characterised the Fusarium community in harvested wheat kernels using 454 sequencing of translation elongation factor 1-α amplicons. In addition, we quantified Fusarium spp. using real-time PCR to reveal differences in biomass between fields. We identified 12 Fusarium operational taxonomic units (OTUs) with a median of 4.5 OTUs per field. Fusarium graminearum was the most abundant species, while F. avenaceum had the highest occurrence. The abundance of Fusarium spp. ranged two orders of magnitude between fields. Two pairs of Fusarium species co-occurred between fields: F. poae with F. tricinctum and F. culmorum with F. sporotrichoides. We could not detect any difference in Fusarium communities between the organic and conventional systems. However, agricultural intensity, measured as the number of pesticide applications and the amount of nitrogen fertiliser applied, had an

  15. New durum wheat with soft kernel texture: milling performance and end-use quality analysis of the Hardness locus in Triticum turgidum ssp. durum

    Science.gov (United States)

    Wheat kernel texture dictates U.S. wheat market class. Durum wheat has limited demand and culinary end-uses compared to bread wheat because of its extremely hard kernel texture which preclude conventional milling. ‘Soft Svevo’, a new durum cultivar with soft kernel texture comparable to a soft white...

  16. New durum wheat with soft kernel texture: end-use quality analysis of the Hardness locus in Triticum turgidum ssp. durum

    Science.gov (United States)

    Wheat kernel texture dictates U.S. wheat market class. Durum wheat has limited demand and culinary end-uses compared to bread wheat because of its extremely hard kernel texture which precludes conventional milling. ‘Soft Svevo’, a new durum cultivar with soft kernel texture comparable to a soft whit...

  17. Survival rate of Plodia interpunctella (Lepidoptera: Pyralidae: On different states of wheat and rye kernels previously infested by beetle pests

    Directory of Open Access Journals (Sweden)

    Vukajlović Filip N.

    2017-01-01

    Full Text Available The present study was undertaken to determine survival rate of Plodia interpunctella (Hübner, 1813, reared on different mechanical states of Vizija winter wheat cultivar and Raša winter rye cultivar, previously infested with different beetle pests. Wheat was previously infested with Rhyzopertha dominica, Sitophilus granarius, Oryzaephilus surinamensis and Cryptolestes ferrugineus, while rye was infested only with O. surinamensis. Kernels were tested in three different mechanical states: (A whole undamaged kernels; (B kernels already damaged by pests and (C original storage kernels (mixture of B and C type. No P. interpunctella adult emerged on wheat kernels, while 36 adults developed on rye kernels. The highest abundance reached beetle species who fed with a mixture of kernels damaged by pests and whole undamaged kernels. Development and survival rate of five different storage insect pests depends on type of kernels and there exist significant survivorship correlations among them.

  18. Effect of Protein Molecular Weight Distribution on Kernel and Baking Characteristics and Intra-varietal Variation in Hard Spring Wheats

    Science.gov (United States)

    Specific wheat protein fractions are known to have distinct associations with wheat quality traits. Research was conducted on 10 hard spring wheat cultivars grown at two North Dakota locations to identify protein fractions that affected wheat kernel characteristics and breadmaking quality. SDS ext...

  19. The influence of soft kernel texture on the flour, water absorption, rheology, and baking quality of durum wheat

    Science.gov (United States)

    Durum (T. turgidum subsp. durum) wheat production worldwide is substantially less than that of common wheat (Triticum aestivum). Durum kernels are extremely hard; leading to most durum wheat being milled into semolina. Durum wheat production is limited in part due to the relatively limited end-user ...

  20. Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population.

    Science.gov (United States)

    Cheng, Ruiru; Kong, Zhongxin; Zhang, Liwei; Xie, Quan; Jia, Haiyan; Yu, Dong; Huang, Yulong; Ma, Zhengqiang

    2017-07-01

    Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement. Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419 × Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

  1. Diversity, distribution of Puroindoline genes and their effect on kernel hardness in a diverse panel of Chinese wheat germplasm.

    Science.gov (United States)

    Ma, Xiaoling; Sajjad, Muhammad; Wang, Jing; Yang, Wenlong; Sun, Jiazhu; Li, Xin; Zhang, Aimin; Liu, Dongcheng

    2017-09-20

    Kernel hardness, which has great influence on the end-use properties of common wheat, is mainly controlled by Puroindoline genes, Pina and Pinb. Using EcoTILLING platform, we herein investigated the allelic variations of Pina and Pinb genes and their association with the Single Kernel Characterization System (SKCS) hardness index in a diverse panel of wheat germplasm. The kernel hardness varied from 1.4 to 102.7, displaying a wide range of hardness index. In total, six Pina and nine Pinb alleles resulting in 15 genotypes were detected in 1787 accessions. The most common alleles are the wild type Pina-D1a (90.4%) and Pina-D1b (7.4%) for Pina, and Pinb-D1b (43.6%), Pinb-D1a (41.1%) and Pinb-D1p (12.8%) for Pinb. All the genotypes have hard type kernel hardness of SKCS index (>60.0), except the wild types of Pina and Pinb combination (Pina-D1a/Pinb-D1a). The most frequent genotypes in Chinese and foreign cultivars was Pina-D1a/Pinb-D1b (46.3 and 39.0%, respectively) and in Chinese landraces was Pina-D1a/Pinb-D1a (54.2%). The frequencies of hard type accessions are increasing from 35.5% in the region IV, to 40.6 and 61.4% in the regions III and II, and then to 77.0% in the region I, while those of soft type are accordingly decreasing along with the increase of latitude. Varieties released after 2000 in Beijing, Hebei, Shandong and Henan have higher average kernel hardness index than that released before 2000. The kernel hardness in a diverse panel of Chinese wheat germplasm revealed an increasing of kernel hardness generally along with the latitude across China. The wild type Pina-D1a and Pinb-D1a, and one Pinb mutant (Pinb-D1b) are the most common alleles of six Pina and nine Pinb alleles, and a new double null genotype (Pina-D1x/Pinb-D1ah) possessed relatively high SKCS hardness index. More hard type varieties were released in recent years with different prevalence of Pin-D1 combinations in different regions. This work would benefit the understanding of the selection

  2. Kernel Function Tuning for Single-Layer Neural Networks

    Czech Academy of Sciences Publication Activity Database

    Vidnerová, Petra; Neruda, Roman

    -, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/

  3. Fumonisin B1 and beauvericin accumulation in wheat kernels after seed-borne infection with Fusarium proliferatum

    Directory of Open Access Journals (Sweden)

    Zhiqing Guo

    2016-08-01

    Full Text Available Fusarium proliferatum is a fungal pathogen causing ear rot of maize. The fungus infects a range of other plants but the economic impact of these diseases has not been established. Recently, F. proliferatum and its mycotoxin fumonisin were found in wheat grains. Here we report that seed-borne infection of wheat with F. proliferatum resulted in systemic colonization of wheat plants and contamination of wheat grains with fumonisins and beauvericin. F. proliferatum strains originating from different hosts were able to infect wheat via seeds. Colonization of wheat plants with the fungus was highest in the stems, followed by leaves; one third of the strains reached kernels, causing accumulation of fumonisins and beauvericin to 15–55 µg kg-1. The results show that seed-borne infection of wheat with F. proliferatum can lead to contamination of wheat kernels with mycotoxins fumonisins and beauvericin.  

  4. Fructan biosynthesis and degradation as part of plant metabolism controlling sugar fluxes during durum wheat kernel maturation

    Directory of Open Access Journals (Sweden)

    Sara eCimini

    2015-02-01

    Full Text Available Wheat kernels contain fructans, fructose based oligosaccharides with prebiotic properties, in levels between 2 and 35 weight % depending on the developmental stage of the kernel. To improve knowledge on the metabolic pathways leading to fructan storage and degradation, carbohydrate fluxes occurring during durum wheat kernel development were analyzed. Kernels were collected at various developmental stages and quali-quantitative analysis of carbohydrates (mono- and di-saccharides, fructans, starch was performed, alongside analysis of the activities and gene expression of the enzymes involved in their biosynthesis and hydrolysis. High resolution HPAEC-PAD of fructan contained in durum wheat kernels revealed that fructan content is higher at the beginning of kernel development, when fructans with higher DP, such as bifurcose and 1,1-nystose, were mainly found. The changes in fructan pool observed during kernel maturation might be part of the signaling pathways influencing carbohydrate metabolism and storage in wheat kernels during development. During the first developmental stages fructan accumulation may contribute to make kernels more effective Suc sinks and to participate in osmotic regulation while the observed decrease in their content may mark the transition to later developmental stages, transition that is also orchestrated by changes in redox balance.

  5. Wheat kernel dimensions: how do they contribute to kernel weight at ...

    Indian Academy of Sciences (India)

    2011-12-02

    Dec 2, 2011 ... yield components, is greatly influenced by kernel dimensions. (KD), such as ..... six linkage gaps, and it covered 3010.70 cM of the whole genome with an ...... Ersoz E. et al. 2009 The Genetic architecture of maize flowering.

  6. Effect of kernel size and mill type on protein, milling yield, and baking quality of hard red spring wheat

    Science.gov (United States)

    Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end-use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, ...

  7. Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map

    Directory of Open Access Journals (Sweden)

    Ajay Kumar

    2016-03-01

    Full Text Available Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL, developed using an elite (ND 705 and a nonadapted genotype (PI 414566, was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL and width (KW are genetically independent, while a large number (∼59% of the quantitative trait loci (QTL for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A and (7A genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools.

  8. Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

    Science.gov (United States)

    Kumar, Ajay; Mantovani, E E; Seetan, R; Soltani, A; Echeverry-Solarte, M; Jain, S; Simsek, S; Doehlert, D; Alamri, M S; Elias, E M; Kianian, S F; Mergoum, M

    2016-03-01

    Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools. Copyright © 2016 Crop Science Society of America.

  9. Genetic analysis of kernel texture (grain hardness) in a hard red spring wheat (Triticum aestivum L.) bi-parental population

    Science.gov (United States)

    Grain hardness is a very important trait in determining wheat market class and also influences milling and baking traits. At the grain Hardness (Ha) locus on chromosome 5DS, there are two primary mutations responsible for conveying a harder kernel texture among U.S. hard red spring wheats: (1) the P...

  10. Statistical analysis of the influence of wheat black point kernels on selected indicators of wheat flour quality

    Directory of Open Access Journals (Sweden)

    Petrov Verica D.

    2011-01-01

    Full Text Available The influence of wheat black point kernels on selected indicators of wheat flour quality - farinograph and extensograph indicators, amylolytic activity, wet gluten and flour ash content, were examined in this study. The examinations were conducted on samples of wheat harvested in the years 2007 and 2008 from the area of Central Banat in four treatments-control (without black point flour and with 2, 4 and 10% of black point flour which was added as a replacement for a part of the control sample. Statistically significant differences between treatments were observed on the dough stability, falling number and extensibility. The samples with 10% of black point flour had the lowest dough stability and the highest amylolytic activity and extensibility. There was a trend of the increasing 15 min drop and water absorption with the increased share of black point flour. Extensograph area, resistance and ratio resistance to extensibility decreased with the addition of black point flour, but not properly. Mahalanobis distance indicates that the addition of 10% black point flour had the greatest influence on the observed quality indicators, thus proving that black point contributes to the technological quality of wheat, i.e .flour.

  11. Magnetic resonance imaging of single rice kernels during cooking

    NARCIS (Netherlands)

    Mohoric, A.; Vergeldt, F.J.; Gerkema, E.; Jager, de P.A.; Duynhoven, van J.P.M.; Dalen, van G.; As, van H.

    2004-01-01

    The RARE imaging method was used to monitor the cooking of single rice kernels in real time and with high spatial resolution in three dimensions. The imaging sequence is optimized for rapid acquisition of signals with short relaxation times using centered out RARE. Short scan time and high spatial

  12. Evaluation of date kernel oils and their effects on wheat flour characteristics

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    Elsakr, A. S.

    1991-06-01

    Full Text Available Date kernels constitute about 13% of the whole date fruit, and cotain moderate amounts of oils with relatively high caloric values. Agwa soft and Aprimi dry date kernel oils were used in this work. Results showed that Aprimi date kernel oils have high levels of both caproic acid and stearic acid of 23.04 and 18.40% respectively, while Agwa kernel oils have high levels of caprylic acid and capric acid of 22.31 and 12.20%. Moreover Agwa oils achieved higher amounts of unsaponifiable matters, sterols and tocopherols. The addition of soft and dry date kernel oils did not improve the wheat flour strength but raised its resistance to extensibility.

    Las pepitas de dátiles constituyen alrededor del 13% del fruto entero, y contienen cantidades moderadas de aceite con valores calóricos relativamente altos. En este trabajo se han utilizado aceites de pepitas de dátiles Agwa blandas y Aprimi secas. Los resultados mostraron que los aceites de pepitas de dátiles Aprimi tienen altos niveles de ácidos caproico y esteárico, 23’04 y 18'40% respectivamente, mientras que los aceites de pepitas Agwa tienen niveles altos de ácidos caprílico y cáprico, 22'31 y 12'20%. Por otra parte los aceites Agwa alcanzaron valores elevados de materia insaponificable, esteroles y tocoferoles. La adición de aceites de pepitas de dátiles secas y blandas no mejoró el poder de la harina de trigo pero incrementó su resistencia a la extensibilidad.

  13. QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress.

    Science.gov (United States)

    Cui, Fa; Fan, Xiaoli; Chen, Mei; Zhang, Na; Zhao, Chunhua; Zhang, Wei; Han, Jie; Ji, Jun; Zhao, Xueqiang; Yang, Lijuan; Zhao, Zongwu; Tong, Yiping; Wang, Tao; Li, Junming

    2016-03-01

    QTLs for kernel characteristics and tolerance to N stress were identified, and the functions of ten known genes with regard to these traits were specified. Kernel size and quality characteristics in wheat (Triticum aestivum L.) ultimately determine the end use of the grain and affect its commodity price, both of which are influenced by the application of nitrogen (N) fertilizer. This study characterized quantitative trait loci (QTLs) for kernel size and quality and examined the responses of these traits to low-N stress using a recombinant inbred line population derived from Kenong 9204 × Jing 411. Phenotypic analyses were conducted in five trials that each included low- and high-N treatments. We identified 109 putative additive QTLs for 11 kernel size and quality characteristics and 49 QTLs for tolerance to N stress, 27 and 14 of which were stable across the tested environments, respectively. These QTLs were distributed across all wheat chromosomes except for chromosomes 3A, 4D, 6D, and 7B. Eleven QTL clusters that simultaneously affected kernel size- and quality-related traits were identified. At nine locations, 25 of the 49 QTLs for N deficiency tolerance coincided with the QTLs for kernel characteristics, indicating their genetic independence. The feasibility of indirect selection of a superior genotype for kernel size and quality under high-N conditions in breeding programs designed for a lower input management system are discussed. In addition, we specified the functions of Glu-A1, Glu-B1, Glu-A3, Glu-B3, TaCwi-A1, TaSus2, TaGS2-D1, PPO-D1, Rht-B1, and Ha with regard to kernel characteristics and the sensitivities of these characteristics to N stress. This study provides useful information for the genetic improvement of wheat kernel size, quality, and resistance to N stress.

  14. Biocontrol of Fusarium graminearum Growth and Deoxynivalenol Production in Wheat Kernels with Bacterial Antagonists

    Directory of Open Access Journals (Sweden)

    Cuijuan Shi

    2014-01-01

    Full Text Available Fusarium graminearum is the main causal pathogen affecting small-grain cereals, and it produces deoxynivalenol, a kind of mycotoxin, which displays a wide range of toxic effects in human and animals. Bacterial strains isolated from peanut shells were investigated for their activities against F. graminearum by dual-culture plate and tip-culture assays. Among them, twenty strains exhibited potent inhibition to the growth of F. graminearum, and the inhibition rates ranged from 41.41% to 54.55% in dual-culture plate assay and 92.70% to 100% in tip-culture assay. Furthermore, eighteen strains reduced the production of deoxynivalenol by 16.69% to 90.30% in the wheat kernels assay. Finally, the strains with the strongest inhibitory activity were identified by morphological, physiological, biochemical methods and also 16S rDNA and gyrA gene analysis as Bacillus amyloliquefaciens. The current study highlights the potential application of antagonistic microorganisms and their metabolites in the prevention of fungal growth and mycotoxin production in wheat kernels. As a biological strategy, it might avoid safety problems and nutrition loss which always caused by physical and chemical strategies.

  15. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  16. Fumonisins production potential of Fusarium verticillioides isolated from Serbian maize and wheat kernels

    Directory of Open Access Journals (Sweden)

    Krstović Saša Z.

    2017-01-01

    Full Text Available The production of fumonisins by potentially toxigenic Fusarium verticillioides isolates originating from Serbian maize and wheat kernels was tested in vitro. A total of six F. verticillioides isolates were incubated on yeast extract sucrose medium (YESA for 4 weeks at 25 °C in the dark. Their toxin production potential was tested by applying a modified HPLC method for determination of fumonisins in cereals, since the TLC method gave no results. Analyses were performed on a HPLC-FLD system after sample extraction from YESA and extract cleanup on a SPE column. Although the isolates were tested for fumonisin B1, B2 and B3, only fumonisin B1 was detected. The results showed that all tested isolates had toxigenic potential for fumonisin B1 production. The average fumonisin B1 production of the isolates ranged from 7 to 289 μg/kg, thus indicating a highly variable toxigenic potential among the isolates. Isolate 1282 expressed the highest toxigenic potential for fumonisin B1 production (289 μg/kg, while isolate 2533/A showed a questionable potential for fumonisin production (7 μg/kg. [Project of the Serbian Ministry of Education, Science and Technological Development, Grant no. TR 31023

  17. Detection of Fusarium in single wheat kernels using spectral Imaging

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Waalwijk, C.; Young, I.T.

    2005-01-01

    Fusarium head blight (FHB) is a harmful fungal disease that occurs in small grains. Non-destructive detection of this disease is traditionally done using spectroscopy or image processing. In this paper the combination of these two in the form of spectral imaging is evaluated. Transmission spectral

  18. Wheat in the Mediterranean revisited--tetraploid wheat landraces assessed with elite bread wheat Single Nucleotide Polymorphism markers.

    Science.gov (United States)

    Oliveira, Hugo R; Hagenblad, Jenny; Leino, Matti W; Leigh, Fiona J; Lister, Diane L; Penã-Chocarro, Leonor; Jones, Martin K

    2014-05-08

    Single Nucleotide Polymorphism (SNP) panels recently developed for the assessment of genetic diversity in wheat are primarily based on elite varieties, mostly those of bread wheat. The usefulness of such SNP panels for studying wheat evolution and domestication has not yet been fully explored and ascertainment bias issues can potentially affect their applicability when studying landraces and tetraploid ancestors of bread wheat. We here evaluate whether population structure and evolutionary history can be assessed in tetraploid landrace wheats using SNP markers previously developed for the analysis of elite cultivars of hexaploid wheat. We genotyped more than 100 tetraploid wheat landraces and wild emmer wheat accessions, some of which had previously been screened with SSR markers, for an existing SNP panel and obtained publically available genotypes for the same SNPs for hexaploid wheat varieties and landraces. Results showed that quantification of genetic diversity can be affected by ascertainment bias but that the effects of ascertainment bias can at least partly be alleviated by merging SNPs to haplotypes. Analyses of population structure and genetic differentiation show strong subdivision between the tetraploid wheat subspecies, except for durum and rivet that are not separable. A more detailed population structure of durum landraces could be obtained than with SSR markers. The results also suggest an emmer, rather than durum, ancestry of bread wheat and with gene flow from wild emmer. SNP markers developed for elite cultivars show great potential for inferring population structure and can address evolutionary questions in landrace wheat. Issues of marker genome specificity and mapping need, however, to be addressed. Ascertainment bias does not seem to interfere with the ability of a SNP marker system developed for elite bread wheat accessions to detect population structure in other types of wheat.

  19. Thermal neutron scattering kernels for sapphire and silicon single crystals

    International Nuclear Information System (INIS)

    Cantargi, F.; Granada, J.R.; Mayer, R.E.

    2015-01-01

    Highlights: • Thermal cross section libraries for sapphire and silicon single crystals were generated. • Debye model was used to represent the vibrational frequency spectra to feed the NJOY code. • Sapphire total cross section was measured at Centro Atómico Bariloche. • Cross section libraries were validated with experimental data available. - Abstract: Sapphire and silicon are materials usually employed as filters in facilities with thermal neutron beams. Due to the lack of the corresponding thermal cross section libraries for those materials, necessary in calculations performed in order to optimize beams for specific applications, here we present the generation of new thermal neutron scattering kernels for those materials. The Debye model was used in both cases to represent the vibrational frequency spectra required to feed the NJOY nuclear data processing system in order to produce the corresponding libraries in ENDF and ACE format. These libraries were validated with available experimental data, some from the literature and others obtained at the pulsed neutron source at Centro Atómico Bariloche

  20. The lignin pyrolysis composition and pyrolysis products of palm kernel shell, wheat straw, and pine sawdust

    International Nuclear Information System (INIS)

    Chang, Guozhang; Huang, Yanqin; Xie, Jianjun; Yang, Huikai; Liu, Huacai; Yin, Xiuli; Wu, Chuangzhi

    2016-01-01

    Highlights: • The primarily pyrolysis composition of PKS lignin was p-hydroxyphenyl unit. • Higher phenol yield and lower gas energy yield were obtained from PKS pyrolysis. • PKS produced more bio-oil and biochar than WS and PS from pyrolysis at 650–850 °C. • PKS-char had poorer gasification reactivity due to higher ordering carbon degree. - Abstract: The lignin monomer composition of palm kernel shell (PKS) was characterized using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), and the characteristics and distributions of products obtained from PKS pyrolysis were investigated using Py-GC/MS, GC, and a specially designed pyrolysis apparatus. The gasification reactivity of PKS biochar was also characterized using thermogravimetry (TG) and Raman spectroscopy. All the results were compared with those obtained from wheat straw (WS) and pine sawdust (PS). The results showed that PKS lignin is primarily composed of p-hydroxyphenyl structural units, while WS and PS lignins are mainly made up of guaiacyl units. Both the mass and energy yields of non-condensable gases from PKS pyrolysis were lower than those obtained from WS and PS pyrolysis at 650–850 °C, owing to the lower volatile content (75.21%) and lack of methoxy groups in PKS. Compared with WS and PS, higher bio-oil productivity was observed during PKS pyrolysis. Phenols were the main component of PKS bio-oil from pyrolysis at 500 °C, and the phenol content of PKS bio-oil (13.49%) was higher than in WS bio-oil (1.62%) and PS bio-oil (0.55%). A higher yield of biochar (on an ash-free basis) was also obtained from PKS pyrolysis. Because of its greater relative degree of ordered carbon, PKS biochar exhibited lower in situ reactivity during CO_2 or H_2O gasification than WS and PS biochars. A longer residence time and addition of steam were found to be beneficial during PKS biochar gasification.

  1. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in ... 518501, India; Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur College of Engineering, Anantapur 515002, India ...

  2. TaGS5-3A, a grain size gene selected during wheat improvement for larger kernel and yield.

    Science.gov (United States)

    Ma, Lin; Li, Tian; Hao, Chenyang; Wang, Yuquan; Chen, Xinhong; Zhang, Xueyong

    2016-05-01

    Grain size is a dominant component of grain weight in cereals. Earlier studies have shown that OsGS5 plays a major role in regulating both grain size and weight in rice via promotion of cell division. In this study, we isolated TaGS5 homoeologues in wheat and mapped them on chromosomes 3A, 3B and 3D. Temporal and spatial expression analysis showed that TaGS5 homoeologues were preferentially expressed in young spikes and developing grains. Two alleles of TaGS5-3A, TaGS5-3A-T and TaGS5-3A-G were identified in wheat accessions, and a functional marker was developed to discriminate them. Association analysis revealed that TaGS5-3A-T was significantly correlated with larger grain size and higher thousand kernel weight. Biochemical assays showed that TaGS5-3A-T possesses a higher enzymatic activity than TaGS5-3A-G. Transgenic rice lines overexpressing TaGS5-3A-T also exhibited larger grain size and higher thousand kernel weight than TaGS5-3A-G lines, and the transcript levels of cell cycle-related genes in TaGS5-3A-T lines were higher than those in TaGS5-3A-G lines. Furthermore, systematic evolution analysis in diploid, tetraploid and hexaploid wheat showed that TaGS5-3A underwent strong artificial selection during wheat polyploidization events and the frequency changes of two alleles demonstrated that TaGS5-3A-T was favoured in global modern wheat cultivars. These results suggest that TaGS5-3A is a positive regulator of grain size and its favoured allele TaGS5-3A-T exhibits a larger potential application in wheat high-yield breeding. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

  3. Multiple kernel learning using single stage function approximation for binary classification problems

    Science.gov (United States)

    Shiju, S.; Sumitra, S.

    2017-12-01

    In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

  4. Interaction Effect Of Irradiation And Fertilization On Grain Yield, Kernel Weight And Severity Of Wheat To Septoria Tritici Blotch

    International Nuclear Information System (INIS)

    Arabi, M. A.; Jawhar, M.

    2004-01-01

    Field research was undertaken, for two growing seasons, to investigate the effects of soil fertilization with potassium (K 2 SO 4 , 36% K) and nitrogen (urea, 46% N), seed irradiation with gamma rays (0, 5, 10 and 15 Gy) and their combinations on the grain yield, 1000-kernel weight and severity of Mycosphaerella graminicola on wheat. Two Syrian wheat cultivars; Bohuth 6 (Triticum aestivum L.) and Bohuth 5 (T. turgidum var durum Desf.) were used in this study. Plants were inoculated with a mixture of 15 virulent isolates of the pathogen at the growth stage (GS) 33-34. Results indicated that the average response to fertilizer application and irradiation treatments was dependent on the susceptibility level of cultivars compared with the control. The level of infection of the combined NK and 15 Gy treatment was reduced by 9 and 46 % in 1998 and by 6 and 42 % in 1999 for Bohuth 5 and Bohuth 6, respectively. This was associated with increased grain yield by 68 and 59% in 1998 and 59 and 33% in 1999, respectively. Highest yield losses from M. graminicola occurred in the treatment of nil fertilization and irradiation. Grain weight was increased by various treatments applied, but such an increase was highest in the combined NK and 15 Gy treatment. This combined treatment appeared to be more effective on calcareous soils, which are typical of Mediterranean environments. (Authors)

  5. Effects of kernel weight and source-limitation on wheat grain yield ...

    African Journals Online (AJOL)

    DRmohammadi

    2012-02-09

    Feb 9, 2012 ... Many regions need wheat cultivars that are capable of high yields when the weather is beneficial but produce stable yields when conditions are adverse. These geno- types should have high yield potential in both favorable and high temperature environments (Yang et al., 2002a;. Ahmed et al., 2011a, b).

  6. Heat damage and in vitro starch digestibility of puffed wheat kernels.

    Science.gov (United States)

    Cattaneo, Stefano; Hidalgo, Alyssa; Masotti, Fabio; Stuknytė, Milda; Brandolini, Andrea; De Noni, Ivano

    2015-12-01

    The effect of processing conditions on heat damage, starch digestibility, release of advanced glycation end products (AGEs) and antioxidant capacity of puffed cereals was studied. The determination of several markers arising from Maillard reaction proved pyrraline (PYR) and hydroxymethylfurfural (HMF) as the most reliable indices of heat load applied during puffing. The considerable heat load was evidenced by the high levels of both PYR (57.6-153.4 mg kg(-1) dry matter) and HMF (13-51.2 mg kg(-1) dry matter). For cost and simplicity, HMF looked like the most appropriate index in puffed cereals. Puffing influenced starch in vitro digestibility, being most of the starch (81-93%) hydrolyzed to maltotriose, maltose and glucose whereas only limited amounts of AGEs were released. The relevant antioxidant capacity revealed by digested puffed kernels can be ascribed to both the new formed Maillard reaction products and the conditions adopted during in vitro digestion. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Comparison of tungsten carbide and stainless steel ball bearings for grinding single maize kernels in a reciprocating grinder

    Science.gov (United States)

    Reciprocating grinders can grind single maize kernels by shaking the kernel in a vial with a ball bearing. This process results in a grind quality that is not satisfactory for many experiments. Tungesten carbide ball bearings are nearly twice as dense as steel, so we compared their grinding performa...

  8. Haplotypes of the TaGS5-A1 gene are associated with thousand-kernel weight in Chinese bread wheat

    Directory of Open Access Journals (Sweden)

    Wang Sha Sha

    2016-06-01

    Full Text Available In previous work, we cloned TaGS5 gene and found the association of TaGS5-A1 alleles with agronomic traits. In this study, the promoter sequence of the TaGS5-A1 gene was isolated from bread wheat. Sequencing results revealed that a G insertion was found in position -1925 bp of the TaGS5-A1 gene (Reference to ATG, which occurred in the Sp1 domain of the promoter sequence. Combined with previous single nucleotide polymorphism (SNP in the TaGS5-A1 exon sequence, four genotypes were formed at the TaGS5-A1 locus and were designated as TaGS5-A1a-a, TaGS5-A1a-b, TaGS5-A1b-a, and TaGS5-A1b-b, respectively. Analysis of the association of TaGS5-A1 alleles with agronomic traits indicated that cultivars with the TaGS5-A1a-b allele possessed significantly higher thousand-kernel weight (TKW and lower plant height than cultivars with the TaGS5-A1a-a allele, and cultivars with the TaGS5-A1b-b allele showed higher TKW than cultivars with the TaGS5-A1b-a allele. The differences of these traits between the TaGS5-A1a-a and TaGS5-A1a-b alleles were larger than those of the TaGS5-A1b-a and TaGS5-A1b-b alleles, suggesting that the -1925G insertion plays the more important role in TaGS5-A1a genotypes than in TaGS5-A1b genotypes. qRT-PCR indicated that TaGS5-A1b-b possessed the significantly highest expression level among four TaGS5-A1 haplotypes in mature seeds and further showed a significantly higher expression level than TaGS5-A1b-a at five different developmental stages of the seeds, suggesting that high expression of TaGS5-A1 was positively associated with high TKW in bread wheat. This study could provide a relatively superior genotype in view of TKW in wheat breeding programs and could also provide important information for dissection of the regulatory mechanism of the yield-related traits.

  9. An obstructive sleep apnea detection approach using kernel density classification based on single-lead electrocardiogram.

    Science.gov (United States)

    Chen, Lili; Zhang, Xi; Wang, Hui

    2015-05-01

    Obstructive sleep apnea (OSA) is a common sleep disorder that often remains undiagnosed, leading to an increased risk of developing cardiovascular diseases. Polysomnogram (PSG) is currently used as a golden standard for screening OSA. However, because it is time consuming, expensive and causes discomfort, alternative techniques based on a reduced set of physiological signals are proposed to solve this problem. This study proposes a convenient non-parametric kernel density-based approach for detection of OSA using single-lead electrocardiogram (ECG) recordings. Selected physiologically interpretable features are extracted from segmented RR intervals, which are obtained from ECG signals. These features are fed into the kernel density classifier to detect apnea event and bandwidths for density of each class (normal or apnea) are automatically chosen through an iterative bandwidth selection algorithm. To validate the proposed approach, RR intervals are extracted from ECG signals of 35 subjects obtained from a sleep apnea database ( http://physionet.org/cgi-bin/atm/ATM ). The results indicate that the kernel density classifier, with two features for apnea event detection, achieves a mean accuracy of 82.07 %, with mean sensitivity of 83.23 % and mean specificity of 80.24 %. Compared with other existing methods, the proposed kernel density approach achieves a comparably good performance but by using fewer features without significantly losing discriminant power, which indicates that it could be widely used for home-based screening or diagnosis of OSA.

  10. Effects of grown origin, genotype, harvest year, and their interactions of wheat kernels on near infrared spectral fingerprints for geographical traceability.

    Science.gov (United States)

    Zhao, Haiyan; Guo, Boli; Wei, Yimin; Zhang, Bo

    2014-01-01

    The effects of origin, genotype, harvest year, and their interactions on wheat near infrared (NIR) spectra were studied to find the reasons for differences in NIR fingerprints of wheat from different geographical origins and the stability of NIR fingerprints among different years. Ten varieties were grown in three regions of China for 2 years. 180 kernel samples were analysed by NIR. The spectra after pre-treatment were analysed by principal component analysis, multi-way analysis of variance, and discriminant partial least-squares. The results showed that origin, genotype, year, and their interactions all had significant effects on wheat NIR fingerprints. The second overtones of N-H and C-H stretching vibrations and a combination of stretch and deformation of C-H group in wheat were mainly influenced by the geographical origin. The wavelength ranges 975-990 nm, 1200 nm, and 1355-1380 nm contained plenty of origin information to build robust discriminant models of wheat geographical origin. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Single corn kernel wide-line NMR oil analysis for breeding purpose

    Energy Technology Data Exchange (ETDEWEB)

    Wilmers, M C.C.; Rettori, C; Vargas, H; Barberis, G E [Universidade Estadual de Campinas (Brazil). Inst. de Fisica; da Silva, W J [Universidade Estadual de Campinas (Brazil). Inst. de Biologia

    1978-12-01

    The Wide-Line NMR technique was used to determine the oil content in single corn seeds. Using distinct radio frequency (RF) power, a systematic work was done in kernels with about 10% of moisture, and also in artificially dried seeds with approximated 5% of moisture. For nondried seeds NMR spectra showed clearly the presence of three resonances with different RF saturation factor. For dried seeds, the oil concentration determined by NMR was highly correlated (r = 0,997) with that determined by a gravimetric method. The highest discrepancy between the two methods was found to be about 1,3%. When relative measurements are required as in the case of single kernel for recurrent selection program, precision in the individual selected kernel will be about 2,5%. Applying this technique, a first cycle of recurrent selection using S/sub 1/ lines for low and high oil content was performed in an open pollinated variety. Gain from selection was 12.0 and 14.1% in the populations for high and low oil contents, respectively.

  12. Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.

    Science.gov (United States)

    Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J

    2014-01-01

    This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.

  13. End-use quality of CIMMYT-derived soft kernel durum wheat germplasm. II. Dough strength and pan bread quality

    Science.gov (United States)

    Durum wheat (Triticum turgidum ssp. durum) is considered unsuitable for the majority of commercial bread production because its weak gluten strength combined with flour particle size and flour starch damage after milling are not commensurate with hexaploid wheat flours. Recently a new durum cultivar...

  14. Single-kernel analysis of fumonisins and other fungal metabolites in maize from South African subsistence farmers.

    Science.gov (United States)

    Mogensen, J M; Sørensen, S M; Sulyok, M; van der Westhuizen, L; Shephard, G S; Frisvad, J C; Thrane, U; Krska, R; Nielsen, K F

    2011-12-01

    Fumonisins are important Fusarium mycotoxins mainly found in maize and derived products. This study analysed maize from five subsistence farmers in the former Transkei region of South Africa. Farmers had sorted kernels into good and mouldy quality. A total of 400 kernels from 10 batches were analysed; of these 100 were visually characterised as uninfected and 300 as infected. Of the 400 kernels, 15% were contaminated with 1.84-1428 mg kg(-1) fumonisins, and 4% (n=15) had a fumonisin content above 100 mg kg(-1). None of the visually uninfected maize had detectable amounts of fumonisins. The total fumonisin concentration was 0.28-1.1 mg kg(-1) for good-quality batches and 0.03-6.2 mg kg(-1) for mouldy-quality batches. The high fumonisin content in the batches was apparently caused by a small number (4%) of highly contaminated kernels, and removal of these reduced the average fumonisin content by 71%. Of the 400 kernels, 80 were screened for 186 microbial metabolites by liquid chromatography-tandem mass spectrometry, detecting 17 other fungal metabolites, including fusaric acid, equisetin, fusaproliferin, beauvericin, cyclosporins, agroclavine, chanoclavine, rugulosin and emodin. Fusaric acid in samples without fumonisins indicated the possibility of using non-toxinogenic Fusaria as biocontrol agents to reduce fumonisin exposure, as done for Aspergillus flavus. This is the first report of mycotoxin profiling in single naturally infected maize kernels. © 2011 Taylor & Francis

  15. Emotion Recognition from Single-Trial EEG Based on Kernel Fisher’s Emotion Pattern and Imbalanced Quasiconformal Kernel Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Yi-Hung Liu

    2014-07-01

    Full Text Available Electroencephalogram-based emotion recognition (EEG-ER has received increasing attention in the fields of health care, affective computing, and brain-computer interface (BCI. However, satisfactory ER performance within a bi-dimensional and non-discrete emotional space using single-trial EEG data remains a challenging task. To address this issue, we propose a three-layer scheme for single-trial EEG-ER. In the first layer, a set of spectral powers of different EEG frequency bands are extracted from multi-channel single-trial EEG signals. In the second layer, the kernel Fisher’s discriminant analysis method is applied to further extract features with better discrimination ability from the EEG spectral powers. The feature vector produced by layer 2 is called a kernel Fisher’s emotion pattern (KFEP, and is sent into layer 3 for further classification where the proposed imbalanced quasiconformal kernel support vector machine (IQK-SVM serves as the emotion classifier. The outputs of the three layer EEG-ER system include labels of emotional valence and arousal. Furthermore, to collect effective training and testing datasets for the current EEG-ER system, we also use an emotion-induction paradigm in which a set of pictures selected from the International Affective Picture System (IAPS are employed as emotion induction stimuli. The performance of the proposed three-layer solution is compared with that of other EEG spectral power-based features and emotion classifiers. Results on 10 healthy participants indicate that the proposed KFEP feature performs better than other spectral power features, and IQK-SVM outperforms traditional SVM in terms of the EEG-ER accuracy. Our findings also show that the proposed EEG-ER scheme achieves the highest classification accuracies of valence (82.68% and arousal (84.79% among all testing methods.

  16. Kernel PLS Estimation of Single-trial Event-related Potentials

    Science.gov (United States)

    Rosipal, Roman; Trejo, Leonard J.

    2004-01-01

    Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

  17. SCAP-82, Single Scattering, Albedo Scattering, Point-Kernel Analysis in Complex Geometry

    International Nuclear Information System (INIS)

    Disney, R.K.; Vogtman, S.E.

    1987-01-01

    1 - Description of problem or function: SCAP solves for radiation transport in complex geometries using the single or albedo scatter point kernel method. The program is designed to calculate the neutron or gamma ray radiation level at detector points located within or outside a complex radiation scatter source geometry or a user specified discrete scattering volume. Geometry is describable by zones bounded by intersecting quadratic surfaces within an arbitrary maximum number of boundary surfaces per zone. Anisotropic point sources are describable as pointwise energy dependent distributions of polar angles on a meridian; isotropic point sources may also be specified. The attenuation function for gamma rays is an exponential function on the primary source leg and the scatter leg with a build- up factor approximation to account for multiple scatter on the scat- ter leg. The neutron attenuation function is an exponential function using neutron removal cross sections on the primary source leg and scatter leg. Line or volumetric sources can be represented as a distribution of isotropic point sources, with un-collided line-of-sight attenuation and buildup calculated between each source point and the detector point. 2 - Method of solution: A point kernel method using an anisotropic or isotropic point source representation is used, line-of-sight material attenuation and inverse square spatial attenuation between the source point and scatter points and the scatter points and detector point is employed. A direct summation of individual point source results is obtained. 3 - Restrictions on the complexity of the problem: - The SCAP program is written in complete flexible dimensioning so that no restrictions are imposed on the number of energy groups or geometric zones. The geometric zone description is restricted to zones defined by boundary surfaces defined by the general quadratic equation or one of its degenerate forms. The only restriction in the program is that the total

  18. Molecular and cytogenetic characterization of the 5DS-5BS chromosome translocation conditioning soft kernel texture in durum wheat

    Science.gov (United States)

    Cultivar ‘Soft Svevo’, a new non-GMO soft durum cultivar with soft kernel texture, was developed through a 5DS(5BS) chromosomal translocation from event. cv. Chinese Spring, and subsequently used to create new soft durum germplasm. The development of Soft Svevo featured the Ph1b-mediated homoeologou...

  19. The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses.

    Directory of Open Access Journals (Sweden)

    Yotam Luz

    Full Text Available Spike-Timing Dependent Plasticity (STDP is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.

  20. Evaluation of the Single-precision Floatingpoint Vector Add Kernel Using the Intel FPGA SDK for OpenCL

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Zheming [Argonne National Lab. (ANL), Argonne, IL (United States); Yoshii, Kazutomo [Argonne National Lab. (ANL), Argonne, IL (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-04-20

    Open Computing Language (OpenCL) is a high-level language that enables software programmers to explore Field Programmable Gate Arrays (FPGAs) for application acceleration. The Intel FPGA software development kit (SDK) for OpenCL allows a user to specify applications at a high level and explore the performance of low-level hardware acceleration. In this report, we present the FPGA performance and power consumption results of the single-precision floating-point vector add OpenCL kernel using the Intel FPGA SDK for OpenCL on the Nallatech 385A FPGA board. The board features an Arria 10 FPGA. We evaluate the FPGA implementations using the compute unit duplication and kernel vectorization optimization techniques. On the Nallatech 385A FPGA board, the maximum compute kernel bandwidth we achieve is 25.8 GB/s, approximately 76% of the peak memory bandwidth. The power consumption of the FPGA device when running the kernels ranges from 29W to 42W.

  1. Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

    Science.gov (United States)

    Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

    2013-02-01

    This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

  2. Wheat for Kids! [and] Teacher's Guide.

    Science.gov (United States)

    Idaho Wheat Commission, Boise.

    "Wheat for Kids" contains information at the elementary school level about: the structure of the wheat kernel; varieties of wheat and their uses; growing wheat; making wheat dough; the U.S. Department of Agriculture Food Guide Pyramid and nutrition; Idaho's part of the international wheat market; recipes; and word games based on the…

  3. Soft durum wheat - a paradigm shift

    Science.gov (United States)

    Two traits define most aspects of wheat quality and utilization: kernel texture (hardness) and gluten. The former is far simpler genetically and is controlled by two genes, Puroindoline a and Puroindoline b. Durum wheat lacks puroindolines and has very hard kernels. As such, durum wheat when milled ...

  4. Wheat Quality Council, Hard Spring Wheat Technical Committee, 2017 Crop

    Science.gov (United States)

    Nine experimental lines of hard spring wheat were grown at up to six locations in 2017 and evaluated for kernel, milling, and bread baking quality against the check variety Glenn. Wheat samples were submitted through the Wheat Quality Council and processed and milled at the USDA-ARS Hard Red Spring...

  5. Transcript-specific, single-nucleotide polymorphism discovery and linkage analysis in hexaploid bread wheat (Triticum aestivum L.).

    Science.gov (United States)

    Allen, Alexandra M; Barker, Gary L A; Berry, Simon T; Coghill, Jane A; Gwilliam, Rhian; Kirby, Susan; Robinson, Phil; Brenchley, Rachel C; D'Amore, Rosalinda; McKenzie, Neil; Waite, Darren; Hall, Anthony; Bevan, Michael; Hall, Neil; Edwards, Keith J

    2011-12-01

    Food security is a global concern and substantial yield increases in cereal crops are required to feed the growing world population. Wheat is one of the three most important crops for human and livestock feed. However, the complexity of the genome coupled with a decline in genetic diversity within modern elite cultivars has hindered the application of marker-assisted selection (MAS) in breeding programmes. A crucial step in the successful application of MAS in breeding programmes is the development of cheap and easy to use molecular markers, such as single-nucleotide polymorphisms. To mine selected elite wheat germplasm for intervarietal single-nucleotide polymorphisms, we have used expressed sequence tags derived from public sequencing programmes and next-generation sequencing of normalized wheat complementary DNA libraries, in combination with a novel sequence alignment and assembly approach. Here, we describe the development and validation of a panel of 1114 single-nucleotide polymorphisms in hexaploid bread wheat using competitive allele-specific polymerase chain reaction genotyping technology. We report the genotyping results of these markers on 23 wheat varieties, selected to represent a broad cross-section of wheat germplasm including a number of elite UK varieties. Finally, we show that, using relatively simple technology, it is possible to rapidly generate a linkage map containing several hundred single-nucleotide polymorphism markers in the doubled haploid mapping population of Avalon × Cadenza. © 2011 The Authors. Plant Biotechnology Journal © 2011 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd.

  6. Urease inhibitor (NBPT and efficiency of single or split application of urea in wheat crop

    Directory of Open Access Journals (Sweden)

    Marcelo Curitiba Espindula

    2014-04-01

    Full Text Available NBPT (N-(n-butyl thiophosphoric triamide, a urease inhibitor, has been reported as one of the most promising compounds to maximize urea nitrogen use in agricultural systems. The objective of this study was to evaluate the performance of irrigated wheat fertilized with urea or urea + NBPT as single or split application. The experiment was conducted from June to October 2006 in Viçosa, MG, Brazil. The experimental design followed a 2×2 factorial scheme, in which urea or urea + NBPT were combined with two modes of application: full dose at sowing (60kg ha-1 or split (20kg ha-1 at sowing + 40kg ha-1 as topdressing at tillering, in randomized blocks with ten replications. The split application of nitrogen fertilization does not improve the yield wheat under used conditions. The use of urease inhibitor improves the grain yield of wheat crop when urea is applied in topdressing at tillering, but its use does not promote difference when urea is applied in the furrow at planting.

  7. A scalable single-chip multi-processor architecture with on-chip RTOS kernel

    NARCIS (Netherlands)

    Theelen, B.D.; Verschueren, A.C.; Reyes Suarez, V.V.; Stevens, M.P.J.; Nunez, A.

    2003-01-01

    Now that system-on-chip technology is emerging, single-chip multi-processors are becoming feasible. A key problem of designing such systems is the complexity of their on-chip interconnects and memory architecture. It is furthermore unclear at what level software should be integrated. An example of a

  8. Wheat related allergy – A retrospective single-centre study of 156 patient

    DEFF Research Database (Denmark)

    Junker Christensen, Morten

    2014-01-01

    Background Allergy to wheat can manifest in different forms: sensitization to ingested wheat via the gastrointestinal tract can cause traditional food allergy or in combination with exercise, Wheat-Dependent Exercise-Induced Anaphylaxis (WDEIA). Sensitization to inhaled wheat flour may lead to oc...

  9. Analysis of Quality-Related Parameters in Mature Kernels of Polygalacturonase Inhibiting Protein (PGIP) Transgenic Bread Wheat Infected with Fusarium graminearum.

    Science.gov (United States)

    Masci, Stefania; Laino, Paolo; Janni, Michela; Botticella, Ermelinda; Di Carli, Mariasole; Benvenuto, Eugenio; Danieli, Pier Paolo; Lilley, Kathryn S; Lafiandra, Domenico; D'Ovidio, Renato

    2015-04-22

    Fusarium head blight, caused by the fungus Fusarium graminearum, has a detrimental effect on both productivity and qualitative properties of wheat. To evaluate its impact on wheat flour, we compared its effect on quality-related parameters between a transgenic bread wheat line expressing a bean polygalacturonase inhibiting protein (PGIP) and its control line. We have compared metabolic proteins, the amounts of gluten proteins and their relative ratios, starch content, yield, extent of pathogen contamination, and deoxynivalenol (DON) accumulation. These comparisons showed that Fusarium significantly decreases the amount of starch in infected control plants, but not in infected PGIP plants. The flour of PGIP plants contained also a lower amount of pathogen biomass and DON accumulation. Conversely, both gluten and metabolic proteins were not significantly influenced either by the transgene or by fungal infection. These results indicate that the transgenic PGIP expression reduces the level of infection, without changing significantly the wheat seed proteome and other quality-related parameters.

  10. Single-kernel analysis of fumonisins and other fungal metabolites in maize from South African subsistence farmers

    DEFF Research Database (Denmark)

    Mogensen, Jesper Mølgaard; Sørensen, S.M.; Sulyok, M.

    2011-01-01

    Fumonisins are important Fusarium mycotoxins mainly found in maize and derived products. This study analysed maize from five subsistence farmers in the former Transkei region of South Africa. Farmers had sorted kernels into good and mouldy quality. A total of 400 kernels from 10 batches were...... analysed; of these 100 were visually characterised as uninfected and 300 as infected. Of the 400 kernels, 15% were contaminated with 1.84-1428 mg kg(-1) fumonisins, and 4% (n = 15) had a fumonisin content above 100 mg kg(-1). None of the visually uninfected maize had detectable amounts of fumonisins....... The total fumonisin concentration was 0.28-1.1 mg kg(-1) for good-quality batches and 0.03-6.2 mg kg(-1) for mouldy-quality batches. The high fumonisin content in the batches was apparently caused by a small number (4%) of highly contaminated kernels, and removal of these reduced the average fumonisin...

  11. Frequency and spectrum of mutations induced by gamma irradiation in single, double and triple dwarf wheats

    International Nuclear Information System (INIS)

    Dhonukshe, B.L.

    1981-01-01

    Induced mutation studies were carried with three dwarf wheat varieties viz., ''Sonalika'', ''Chhoti Lerma'' and ''Hira'', considered to be single, double and trible dwarfs, respectively. Gamma-rays were used as a source of irradiation. Frequency of chlorophyll mutations were comparatively low and the spectrum was narrow. Chlorophyll mutations were altogether absent in the variety ''Sonalika''. A very wide spectrum of viable mutations affecting stem, leaf, ear growth habit, maturity and fertility characteristics was observed in the M 2 . The cumulative frequency of all the mutants together was quite high, which varied with the varieties. There were varietal differences in the composition and width of the spectrum induced by gamma-rays. The dwarf mutants having desirable leaf and spike characters were isolated in all the three varieties. (author)

  12. Kernel Machine SNP-set Testing under Multiple Candidate Kernels

    Science.gov (United States)

    Wu, Michael C.; Maity, Arnab; Lee, Seunggeun; Simmons, Elizabeth M.; Harmon, Quaker E.; Lin, Xinyi; Engel, Stephanie M.; Molldrem, Jeffrey J.; Armistead, Paul M.

    2013-01-01

    Joint testing for the cumulative effect of multiple single nucleotide polymorphisms grouped on the basis of prior biological knowledge has become a popular and powerful strategy for the analysis of large scale genetic association studies. The kernel machine (KM) testing framework is a useful approach that has been proposed for testing associations between multiple genetic variants and many different types of complex traits by comparing pairwise similarity in phenotype between subjects to pairwise similarity in genotype, with similarity in genotype defined via a kernel function. An advantage of the KM framework is its flexibility: choosing different kernel functions allows for different assumptions concerning the underlying model and can allow for improved power. In practice, it is difficult to know which kernel to use a priori since this depends on the unknown underlying trait architecture and selecting the kernel which gives the lowest p-value can lead to inflated type I error. Therefore, we propose practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures. We demonstrate through simulations and real data applications that the procedures protect the type I error rate and can lead to substantially improved power over poor choices of kernels and only modest differences in power versus using the best candidate kernel. PMID:23471868

  13. Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt Seed Viability with Multivariate Data Analysis

    Directory of Open Access Journals (Sweden)

    Guangjun Qiu

    2018-03-01

    Full Text Available The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR spectroscopy with a wavelength range of 1000–2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

  14. Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis.

    Science.gov (United States)

    Qiu, Guangjun; Lü, Enli; Lu, Huazhong; Xu, Sai; Zeng, Fanguo; Shui, Qin

    2018-03-28

    The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR) spectroscopy with a wavelength range of 1000-2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA) were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

  15. Progressive Pearling of Barley Kernel: Chemical Characterization of Pearling Fractions and Effect of Their Inclusion on the Nutritional and Technological Properties of Wheat Bread.

    Science.gov (United States)

    Blandino, Massimo; Locatelli, Monica; Sovrani, Valentina; Coïsson, Jean Daniel; Rolle, Luca; Travaglia, Fabiano; Giacosa, Simone; Bordiga, Matteo; Scarpino, Valentina; Reyneri, Amedeo; Arlorio, Marco

    2015-07-01

    Two hulled barley varieties have been sequentially pearled for one to eight cycles, each with 5% removal. The derived fractions were analyzed for their bioactive compound content. The dietary fiber (DF) decreased from the external to the internal layers, whereas β-glucans showed an inverse trend. Deoxynivalenol contamination was concentrated in the outer layers. The total antioxidant activity (TAA) was higher in the 15-25% fractions, which were used to prepare bread. Five mixtures of refined wheat flour, with an increasing replacement of this pearled barley fraction, were compared with a control for the bioactive compound content, as well as for the rheological and physical bread properties. The inclusion of pearled fractions with up to a 10% substitution leads to a clear enhancement of the DF and TAA, with only minor detrimental effects on the physical parameters. Selected byproducts of barley pearling could be proposed as functional ingredients for bakery products rich in DF and TAA.

  16. Single-copy genes define a conserved order between rice and wheat for understanding differences caused by duplication, deletion, and transposition of genes.

    Science.gov (United States)

    Singh, Nagendra K; Dalal, Vivek; Batra, Kamlesh; Singh, Binay K; Chitra, G; Singh, Archana; Ghazi, Irfan A; Yadav, Mahavir; Pandit, Awadhesh; Dixit, Rekha; Singh, Pradeep K; Singh, Harvinder; Koundal, Kirpa R; Gaikwad, Kishor; Mohapatra, Trilochan; Sharma, Tilak R

    2007-01-01

    The high-quality rice genome sequence is serving as a reference for comparative genome analysis in crop plants, especially cereals. However, early comparisons with bread wheat showed complex patterns of conserved synteny (gene content) and colinearity (gene order). Here, we show the presence of ancient duplicated segments in the progenitor of wheat, which were first identified in the rice genome. We also show that single-copy (SC) rice genes, those representing unique matches with wheat expressed sequence tag (EST) unigene contigs in the whole rice genome, show more than twice the proportion of genes mapping to syntenic wheat chromosome as compared to the multicopy (MC) or duplicated rice genes. While 58.7% of the 1,244 mapped SC rice genes were located in single syntenic wheat chromosome groups, the remaining 41.3% were distributed randomly to the other six non-syntenic wheat groups. This could only be explained by a background dispersal of genes in the genome through transposition or other unknown mechanism. The breakdown of rice-wheat synteny due to such transpositions was much greater near the wheat centromeres. Furthermore, the SC rice genes revealed a conserved primordial gene order that gives clues to the origin of rice and wheat chromosomes from a common ancestor through polyploidy, aneuploidy, centromeric fusions, and translocations. Apart from the bin-mapped wheat EST contigs, we also compared 56,298 predicted rice genes with 39,813 wheat EST contigs assembled from 409,765 EST sequences and identified 7,241 SC rice gene homologs of wheat. Based on the conserved colinearity of 1,063 mapped SC rice genes across the bins of individual wheat chromosomes, we predicted the wheat bin location of 6,178 unmapped SC rice gene homologs and validated the location of 213 of these in the telomeric bins of 21 wheat chromosomes with 35.4% initial success. This opens up the possibility of directed mapping of a large number of conserved SC rice gene homologs in wheat

  17. Method: a single nucleotide polymorphism genotyping method for Wheat streak mosaic virus

    Science.gov (United States)

    2012-01-01

    Background The September 11, 2001 attacks on the World Trade Center and the Pentagon increased the concern about the potential for terrorist attacks on many vulnerable sectors of the US, including agriculture. The concentrated nature of crops, easily obtainable biological agents, and highly detrimental impacts make agroterrorism a potential threat. Although procedures for an effective criminal investigation and attribution following such an attack are available, important enhancements are still needed, one of which is the capability for fine discrimination among pathogen strains. The purpose of this study was to develop a molecular typing assay for use in a forensic investigation, using Wheat streak mosaic virus (WSMV) as a model plant virus. Method This genotyping technique utilizes single base primer extension to generate a genetic fingerprint. Fifteen single nucleotide polymorphisms (SNPs) within the coat protein and helper component-protease genes were selected as the genetic markers for this assay. Assay optimization and sensitivity testing was conducted using synthetic targets. WSMV strains and field isolates were collected from regions around the world and used to evaluate the assay for discrimination. The assay specificity was tested against a panel of near-neighbors consisting of genetic and environmental near-neighbors. Result Each WSMV strain or field isolate tested produced a unique SNP fingerprint, with the exception of three isolates collected within the same geographic location that produced indistinguishable fingerprints. The results were consistent among replicates, demonstrating the reproducibility of the assay. No SNP fingerprints were generated from organisms included in the near-neighbor panel, suggesting the assay is specific for WSMV. Using synthetic targets, a complete profile could be generated from as low as 7.15 fmoles of cDNA. Conclusion The molecular typing method presented is one tool that could be incorporated into the forensic

  18. Method: a single nucleotide polymorphism genotyping method for Wheat streak mosaic virus.

    Science.gov (United States)

    Rogers, Stephanie M; Payton, Mark; Allen, Robert W; Melcher, Ulrich; Carver, Jesse; Fletcher, Jacqueline

    2012-05-17

    The September 11, 2001 attacks on the World Trade Center and the Pentagon increased the concern about the potential for terrorist attacks on many vulnerable sectors of the US, including agriculture. The concentrated nature of crops, easily obtainable biological agents, and highly detrimental impacts make agroterrorism a potential threat. Although procedures for an effective criminal investigation and attribution following such an attack are available, important enhancements are still needed, one of which is the capability for fine discrimination among pathogen strains. The purpose of this study was to develop a molecular typing assay for use in a forensic investigation, using Wheat streak mosaic virus (WSMV) as a model plant virus. This genotyping technique utilizes single base primer extension to generate a genetic fingerprint. Fifteen single nucleotide polymorphisms (SNPs) within the coat protein and helper component-protease genes were selected as the genetic markers for this assay. Assay optimization and sensitivity testing was conducted using synthetic targets. WSMV strains and field isolates were collected from regions around the world and used to evaluate the assay for discrimination. The assay specificity was tested against a panel of near-neighbors consisting of genetic and environmental near-neighbors. Each WSMV strain or field isolate tested produced a unique SNP fingerprint, with the exception of three isolates collected within the same geographic location that produced indistinguishable fingerprints. The results were consistent among replicates, demonstrating the reproducibility of the assay. No SNP fingerprints were generated from organisms included in the near-neighbor panel, suggesting the assay is specific for WSMV. Using synthetic targets, a complete profile could be generated from as low as 7.15 fmoles of cDNA. The molecular typing method presented is one tool that could be incorporated into the forensic science tool box after a thorough

  19. Self-Organized Crystallization Patterns from Evaporating Droplets of Common Wheat Grain Leakages as a Potential Tool for Quality Analysis

    Directory of Open Access Journals (Sweden)

    Maria Olga Kokornaczyk

    2011-01-01

    Full Text Available We studied the evaporation-induced pattern formation in droplets of common wheat kernel leakages prepared out of ancient and modern wheat cultivars as a possible tool for wheat quality analysis. The experiments showed that the substances which passed into the water during the soaking of the kernels created crystalline structures with different degrees of complexity while the droplets were evaporating. The forms ranged from spots and simple structures with single ramifications, through dendrites, up to highly organized hexagonal shapes and fractal-like structures. The patterns were observed and photographed using dark field microscopy in small magnifications. The evaluation of the patterns was performed both visually and by means of the fractal dimension analysis. From the results, it can be inferred that the wheat cultivars differed in their pattern-forming capacities. Two of the analyzed wheat cultivars showed poor pattern formation, whereas another two created well-formed and complex patterns. Additionally, the wheat cultivars were analyzed for their vigor by means of the germination test and measurement of the electrical conductivity of the grain leakages. The results showed that the more vigorous cultivars also created more complex patterns, whereas the weaker cultivars created predominantly poor forms. This observation suggests a correlation between the wheat seed quality and droplet evaporation patterns.

  20. Phytotoxicity of Alachlor, Bromacil and Diuron as single or mixed herbicides applied to wheat, melon, and molokhia.

    Science.gov (United States)

    El-Nahhal, Yasser; Hamdona, Nisreen

    2015-01-01

    This study investigated the phytotoxicity of herbicides applied singly or as mixtures to different crops under greenhouse conditions. Growth inhibition of the crops was taken as an indicator of phytotoxicity. Phytotoxicity of mixtures was estimated by calculating EC50 value in toxic units. EC50 (mg/kg soil) of Alachlor, Bromacil and/or Diuron were: 11.37, 4.77, 1.64, respectively, on melon; 0.11, 0.08, 0.24, respectively, on molokhia, and 3.91, 3.08, 1.83, respectively, on wheat. EC50 values of binary mixture tests of (Alachlor + Bromacil), (Alachlor + Diuron), and (Bromacil + Diuron) were 12.21, 5.84, 10.22 on melon, 0.982, 925.4, 38.1 on molokhia, and 0.673, 1.34, 0.644 on wheat. Tertiary mixture tests showed EC50 values (TU/kg soil) of (Alachlor + Bromacil + Diuron) was 633.9 on melon, 3.02 on molokhia and 32.174 on wheat. Diuron was more toxic than Alachlor and Bromacil to the tested crops based on individual tests. Molokhia was the most sensitive crop to herbicides. Binary mixtures showed a synergistic effect as compared to the tertiary mixtures.

  1. Application of calibrations to hyperspectral images of food grains: example for wheat falling number

    Directory of Open Access Journals (Sweden)

    Nicola Caporaso

    2017-04-01

    Full Text Available The presence of a few kernels with sprouting problems in a batch of wheat can result in enzymatic activity sufficient to compromise flour functionality and bread quality. This is commonly assessed using the Hagberg Falling Number (HFN method, which is a batch analysis. Hyperspectral imaging (HSI can provide analysis at the single grain level with potential for improved performance. The present paper deals with the development and application of calibrations obtained using an HSI system working in the near infrared (NIR region (~900–2500 nm and reference measurements of HFN. A partial least squares regression calibration has been built using 425 wheat samples with a HFN range of 62–318 s, including field and laboratory pre-germinated samples placed under wet conditions. Two different approaches were tested to apply calibrations: i application of the calibration to each pixel, followed by calculation of the average of the resulting values for each object (kernel; ii calculation of the average spectrum for each object, followed by application of the calibration to the mean spectrum. The calibration performance achieved for HFN (R2 = 0.6; RMSEC ~ 50 s; RMSEP ~ 63 s compares favourably with other studies using NIR spectroscopy. Linear spectral pre-treatments lead to similar results when applying the two methods, while non-linear treatments such as standard normal variate showed obvious differences between these approaches. A classification model based on linear discriminant analysis (LDA was also applied to segregate wheat kernels into low (250 s HFN groups. LDA correctly classified 86.4% of the samples, with a classification accuracy of 97.9% when using an HFN threshold of 150 s. These results are promising in terms of wheat quality assessment using a rapid and non-destructive technique which is able to analyse wheat properties on a single-kernel basis, and to classify samples as acceptable or unacceptable for flour production.

  2. Functional features of a single chromosome arm in wheat (1AL) determined from its structure

    Czech Academy of Sciences Publication Activity Database

    Lucas, S. J.; Šimková, Hana; Šafář, Jan; Jurman, I.; Cattonaro, F.; Vautrin, S.; Bellec, A.; Berges, H.; Doležel, Jaroslav; Budak, H.

    2012-01-01

    Roč. 12, č. 1 (2012), s. 173-182 ISSN 1438-793X Institutional research plan: CEZ:AV0Z50380511 Keywords : Wheat * A genome * BAC end sequencing Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.292, year: 2012

  3. Phytotoxicity of Alachlor, Bromacil and Diuron as single or mixed herbicides applied to wheat, melon, and molokhia

    OpenAIRE

    El-Nahhal, Yasser; Hamdona, Nisreen

    2015-01-01

    This study investigated the phytotoxicity of herbicides applied singly or as mixtures to different crops under greenhouse conditions. Growth inhibition of the crops was taken as an indicator of phytotoxicity. Phytotoxicity of mixtures was estimated by calculating EC50 value in toxic units. EC50 (mg/kg soil) of Alachlor, Bromacil and/or Diuron were: 11.37, 4.77, 1.64, respectively, on melon; 0.11, 0.08, 0.24, respectively, on molokhia, and 3.91, 3.08, 1.83, respectively, on wheat. EC50 values ...

  4. Association of yield-related traits in founder genotypes and derivatives of common wheat (Triticum aestivum L.

    Directory of Open Access Journals (Sweden)

    Jie Guo

    2018-02-01

    Full Text Available Abstract Background Yield improvement is an ever-important objective of wheat breeding. Studying and understanding the phenotypes and genotypes of yield-related traits has potential for genetic improvement of crops. Results The genotypes of 215 wheat cultivars including 11 founder parents and 106 derivatives were analyzed by the 9 K wheat SNP iSelect assay. A total of 4138 polymorphic single nucleotide polymorphism (SNP loci were detected on 21 chromosomes, of which 3792 were mapped to single chromosome locations. All genotypes were phenotyped for six yield-related traits including plant height (PH, spike length (SL, spikelet number per spike (SNPS, kernel number per spike (KNPS, kernel weight per spike (KWPS, and thousand kernel weight (TKW in six irrigated environments. Genome-wide association analysis detected 117 significant associations of 76 SNPs on 15 chromosomes with phenotypic explanation rates (R 2 ranging from 2.03 to 12.76%. In comparing allelic variation between founder parents and their derivatives (106 and other cultivars (98 using the 76 associated SNPs, we found that the region 116.0–133.2 cM on chromosome 5A in founder parents and derivatives carried alleles positively influencing kernel weight per spike (KWPS, rarely found in other cultivars. Conclusion The identified favorable alleles could mark important chromosome regions in derivatives that were inherited from founder parents. Our results unravel the genetic of yield in founder genotypes, and provide tools for marker-assisted selection for yield improvement.

  5. Influence of wheat type and pretreatment on fungal growth in solid-state fermentation

    NARCIS (Netherlands)

    Hoogschagen, M.; Zhu, Y.; As, H. van; Tramper, J.; Rinzema, A.

    2001-01-01

    The respiration kinetics of Aspergillus oryzae on different varieties of whole wheat kernels were studied. Six wheat varieties were pretreated in two different ways. Five of the six substrates fermented similarly and independently of the pretreatment method. However, pretreatment affected

  6. Effects of climate change, CO2 and O3 on wheat productivity in Eastern China, singly and in combination

    Science.gov (United States)

    Tao, Fulu; Feng, Zhaozhong; Tang, Haoye; Chen, Yi; Kobayashi, Kazuhiko

    2017-03-01

    Air pollution and climate change are increasing threats to agricultural production and food security. Extensive studies have focused on the effect of climate change, but the interactive effects of multiple global change factors are poorly understood. Here, we incorporate the interactions between climate change, carbon dioxide (CO2) and ozone (O3) into an eco-physiological mechanistic model based on three years of O3 Free-Air Concentration Elevation (O3-FACE) experiments. We then investigate the effects of climate change, elevated CO2 concentration ([CO2]) and rising O3 concentration ([O3]) on wheat growth and productivity in eastern China in 1996-2005 (2000s) and 2016-2025 (2020s) under two climate change scenarios, singly and in combination. We find the interactive effects of climate change, CO2 and O3 on wheat productivity have spatially explicit patterns; the effect of climate change dominates the general pattern, which is however subject to the large uncertainties of climate change scenarios. Wheat productivity is estimated to increase by 2.8-9.0% due to elevated [CO2] however decline by 2.8-11.7% due to rising [O3] in the 2020s, relative to the 2000s. The combined effects of CO2 and O3 are less than that of O3 only, on average by 4.6-5.2%, however with O3 damage outweighing CO2 benefit in most of the region. This study demonstrates a more biologically meaningful and appropriate approach for assessing the interactive effects of climate change, CO2 and O3 on crop growth and productivity. Our findings promote the understanding on the interactive effects of multiple global change factors across contrasting climate conditions, cast doubt on the potential of CO2 fertilization effect in offsetting possible negative effect of climate change on crop productivity as suggested by many previous studies.

  7. HS-SPME-GC-MS/MS Method for the Rapid and Sensitive Quantitation of 2-Acetyl-1-pyrroline in Single Rice Kernels.

    Science.gov (United States)

    Hopfer, Helene; Jodari, Farman; Negre-Zakharov, Florence; Wylie, Phillip L; Ebeler, Susan E

    2016-05-25

    Demand for aromatic rice varieties (e.g., Basmati) is increasing in the US. Aromatic varieties typically have elevated levels of the aroma compound 2-acetyl-1-pyrroline (2AP). Due to its very low aroma threshold, analysis of 2AP provides a useful screening tool for rice breeders. Methods for 2AP analysis in rice should quantitate 2AP at or below sensory threshold level, avoid artifactual 2AP generation, and be able to analyze single rice kernels in cases where only small sample quantities are available (e.g., breeding trials). We combined headspace solid phase microextraction with gas chromatography tandem mass spectrometry (HS-SPME-GC-MS/MS) for analysis of 2AP, using an extraction temperature of 40 °C and a stable isotopologue as internal standard. 2AP calibrations were linear between the concentrations of 53 and 5380 pg/g, with detection limits below the sensory threshold of 2AP. Forty-eight aromatic and nonaromatic, milled rice samples from three harvest years were screened with the method for their 2AP content, and overall reproducibility, observed for all samples, ranged from 5% for experimental aromatic lines to 33% for nonaromatic lines.

  8. Identification and validation of single nucleotide polymorphic markers linked to Ug99 stem rust resistance in spring wheat

    Science.gov (United States)

    Wheat stem rust (Puccinia graminis f. sp. tritici Eriks. and E. Henn.) is one of the most destructive diseases world-wide. Races belonging to Ug99 (or TTKSK) continue to cause crop losses in East Africa and threaten global wheat production. Developing and deploying wheat varieties with multiple race...

  9. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

    Science.gov (United States)

    Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

    2016-01-01

    The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

  10. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

    Directory of Open Access Journals (Sweden)

    Jaime Cuevas

    2017-01-01

    Full Text Available The phenomenon of genotype × environment (G × E interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects ( u that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP and Gaussian (Gaussian kernel, GK. The other model has the same genetic component as the first model ( u plus an extra component, f, that captures random effects between environments that were not captured by the random effects u . We used five CIMMYT data sets (one maize and four wheat that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u   and   f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u .

  11. Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

    Science.gov (United States)

    Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

    2017-01-05

    The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

  12. The carotenoid biosynthetic and catabolic genes in wheat and their association with yellow pigments.

    Science.gov (United States)

    Colasuonno, Pasqualina; Lozito, Maria Luisa; Marcotuli, Ilaria; Nigro, Domenica; Giancaspro, Angelica; Mangini, Giacomo; De Vita, Pasquale; Mastrangelo, Anna Maria; Pecchioni, Nicola; Houston, Kelly; Simeone, Rosanna; Gadaleta, Agata; Blanco, Antonio

    2017-01-31

    In plants carotenoids play an important role in the photosynthetic process and photo-oxidative protection, and are the substrate for the synthesis of abscisic acid and strigolactones. In addition to their protective role as antioxidants and precursors of vitamin A, in wheat carotenoids are important as they influence the colour (whiteness vs. yellowness) of the grain. Understanding the genetic basis of grain yellow pigments, and identifying associated markers provide the basis for improving wheat quality by molecular breeding. Twenty-four candidate genes involved in the biosynthesis and catabolism of carotenoid compounds have been identified in wheat by comparative genomics. Single nucleotide polymorphisms (SNPs) found in the coding sequences of 19 candidate genes allowed their chromosomal location and accurate map position on two reference consensus maps to be determined. The genome-wide association study based on genotyping a tetraploid wheat collection with 81,587 gene-associated SNPs validated quantitative trait loci (QTLs) previously detected in biparental populations and discovered new QTLs for grain colour-related traits. Ten carotenoid genes mapped in chromosome regions underlying pigment content QTLs indicating possible functional relationships between candidate genes and the trait. The availability of linked, candidate gene-based markers can facilitate breeding wheat cultivars with desirable levels of carotenoids. Identifying QTLs linked to carotenoid pigmentation can contribute to understanding genes underlying carotenoid accumulation in the wheat kernels. Together these outputs can be combined to exploit the genetic variability of colour-related traits for the nutritional and commercial improvement of wheat products.

  13. Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

    OpenAIRE

    Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

    2016-01-01

    To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...

  14. Approximate kernel competitive learning.

    Science.gov (United States)

    Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

    2015-03-01

    Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Discrete element method as an approach to model the wheat milling process

    Science.gov (United States)

    It is a well-known phenomenon that break-release, particle size, and size distribution of wheat milling are functions of machine operational parameters and grain properties. Due to the non-uniformity of characteristics and properties of wheat kernels, the kernel physical and mechanical properties af...

  16. Effects of Sowing Date and Limited Irrigation on Yield and Yield Components of Five Rainfed Wheat Varieties in Maragheh Region

    Directory of Open Access Journals (Sweden)

    A. R. Tavakkoli

    2013-03-01

    Full Text Available In order to investigate the effects of sowing date (SD and single irrigation (SI amounts on yield and yield components of rainfed wheat varieties, a field experiment was conducted as split-split plots arranged in a randomized complete blocks design with three replications during 2002-2004 at main station of Dryland Agricultural Research Institute in Maragheh, Iran. Treatments included three sowing dates (early, normal and late, three levels of single irrigation (rainfed, 50 mm and 100 mm only at planting time and five wheat varieties (three numbered lines, Azar2 and double-cross Shahi. Results revealed that interactions of SD, SI and wheat varieties were significant for grain yield, number of kernels per spike and water productivity (P≤0.01. Single irrigation at normal planting time increased grain yield, straw, biomass, harvest index, and water productivity. Grain yield and water productivity were increased by 131% and 84.8%, respectively. Single irrigation at late planting time was not significant on agronomic traits and produced low water productivity. Regarding the reaction of wheat to planting date and single irrigation, results showed that normal single irrigation can improve yield, yield components and water productivity index. The effectiveness of single irrigation under dryland conditions can be observed in all wheat cultivars. Although this effectiveness on yield and yield components is observable, but it is necessary to select the time of irrigation properly.

  17. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  18. Optimized Kernel Entropy Components.

    Science.gov (United States)

    Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

    2017-06-01

    This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

  19. Subsampling Realised Kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    In a recent paper we have introduced the class of realised kernel estimators of the increments of quadratic variation in the presence of noise. We showed that this estimator is consistent and derived its limit distribution under various assumptions on the kernel weights. In this paper we extend our...... that subsampling is impotent, in the sense that subsampling has no effect on the asymptotic distribution. Perhaps surprisingly, for the efficient smooth kernels, such as the Parzen kernel, we show that subsampling is harmful as it increases the asymptotic variance. We also study the performance of subsampled...

  20. Single Nucleotide Polymorphisms in B-Genome Specific UDP-Glucosyl Transferases Associated with Fusarium Head Blight Resistance and Reduced Deoxynivalenol Accumulation in Wheat Grain.

    Science.gov (United States)

    Sharma, Pallavi; Gangola, Manu P; Huang, Chen; Kutcher, H Randy; Ganeshan, Seedhabadee; Chibbar, Ravindra N

    2018-01-01

    An in vitro spike culture method was optimized to evaluate Fusarium head blight (FHB) resistance in wheat (Triticum aestivum) and used to screen a population of ethyl methane sulfonate treated spike culture-derived variants (SCDV). Of the 134 SCDV evaluated, the disease severity score of 47 of the variants was ≤30%. Single nucleotide polymorphisms (SNP) in the UDP-glucosyltransferase (UGT) genes, TaUGT-2B, TaUGT-3B, and TaUGT-EST, differed between AC Nanda (an FHB-susceptible wheat variety) and Sumai-3 (an FHB-resistant wheat cultivar). SNP at 450 and 1,558 bp from the translation initiation site in TaUGT-2B and TaUGT-3B, respectively were negatively correlated with FHB severity in the SCDV population, whereas the SNP in TaUGT-EST was not associated with FHB severity. Fusarium graminearum strain M7-07-1 induced early expression of TaUGT-2B and TaUGT-3B in FHB-resistant SCDV lines, which were associated with deoxynivalenol accumulation and reduced FHB disease progression. At 8 days after inoculation, deoxynivalenol concentration varied from 767 ppm in FHB-resistant variants to 2,576 ppm in FHB-susceptible variants. The FHB-resistant SCDV identified can be used as new sources of FHB resistance in wheat improvement programs.

  1. The utility of flow sorting to identify chromosomes carrying a single copy transgene in wheat

    Czech Academy of Sciences Publication Activity Database

    Cápal, Petr; Endo, Takashi R.; Vrána, Jan; Kubaláková, Marie; Karafiátová, Miroslava; Komínková, Eva; Mora-Ramirez, I.; Weschke, W.; Doležel, Jaroslav

    2016-01-01

    Roč. 12, APR 25 (2016), s. 24 ISSN 1746-4811 R&D Projects: GA MŠk(CZ) LO1204; GA ČR GBP501/12/G090 Institutional support: RVO:61389030 Keywords : Transgene localization * Flow cytometric sorting * Single chromosome amplification Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.510, year: 2016

  2. Iterative software kernels

    Energy Technology Data Exchange (ETDEWEB)

    Duff, I.

    1994-12-31

    This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.

  3. Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP

    Directory of Open Access Journals (Sweden)

    Jeffrey B. Endelman

    2011-11-01

    Full Text Available Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR, which is equivalent to best linear unbiased prediction (BLUP when the genetic covariance between lines is proportional to their similarity in genotype space. This additive model can be broadened to include epistatic effects by using other kernels, such as the Gaussian, which represent inner products in a complex feature space. To facilitate the use of RR and nonadditive kernels in plant breeding, a new software package for R called rrBLUP has been developed. At its core is a fast maximum-likelihood algorithm for mixed models with a single variance component besides the residual error, which allows for efficient prediction with unreplicated training data. Use of the rrBLUP software is demonstrated through several examples, including the identification of optimal crosses based on superior progeny value. In cross-validation tests, the prediction accuracy with nonadditive kernels was significantly higher than RR for wheat ( L. grain yield but equivalent for several maize ( L. traits.

  4. Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

    Science.gov (United States)

    Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

    2018-01-01

    In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

  5. Classification With Truncated Distance Kernel.

    Science.gov (United States)

    Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

    2018-05-01

    This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

  6. High-Throughput Phenotyping of Wheat and Barley Plants Grown in Single or Few Rows in Small Plots Using Active and Passive Spectral Proximal Sensing

    OpenAIRE

    Barmeier, Gero;Schmidhalter, Urs

    2017-01-01

    In the early stages of plant breeding, breeders evaluate a large number of varieties. Due to limited availability of seeds and space, plot sizes may range from one to four rows. Spectral proximal sensors can be used in place of labour-intensive methods to estimate specific plant traits. The aim of this study was to test the performance of active and passive sensing to assess single and multiple rows in a breeding nursery. A field trial with single cultivars of winter barley and winter wheat w...

  7. Density separation as a strategy to reduce the enzyme load of preharvest sprouted wheat and enhance its bread making quality.

    Science.gov (United States)

    Olaerts, Heleen; De Bondt, Yamina; Courtin, Christophe M

    2018-02-15

    As preharvest sprouting of wheat impairs its use in food applications, postharvest solutions for this problem are required. Due to the high kernel to kernel variability in enzyme activity in a batch of sprouted wheat, the potential of eliminating severely sprouted kernels based on density differences in NaCl solutions was evaluated. Compared to higher density kernels, lower density kernels displayed higher α-amylase, endoxylanase, and peptidase activities as well as signs of (incipient) protein, β-glucan and arabinoxylan breakdown. By discarding lower density kernels of mildly and severely sprouted wheat batches (11% and 16%, respectively), density separation increased flour FN of the batch from 280 to 345s and from 135 to 170s and increased RVA viscosity. This in turn improved dough handling, bread crumb texture and crust color. These data indicate that density separation is a powerful technique to increase the quality of a batch of sprouted wheat. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Kernels for structured data

    CERN Document Server

    Gärtner, Thomas

    2009-01-01

    This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by

  9. Locally linear approximation for Kernel methods : the Railway Kernel

    OpenAIRE

    Muñoz, Alberto; González, Javier

    2008-01-01

    In this paper we present a new kernel, the Railway Kernel, that works properly for general (nonlinear) classification problems, with the interesting property that acts locally as a linear kernel. In this way, we avoid potential problems due to the use of a general purpose kernel, like the RBF kernel, as the high dimension of the induced feature space. As a consequence, following our methodology the number of support vectors is much lower and, therefore, the generalization capab...

  10. Data-variant kernel analysis

    CERN Document Server

    Motai, Yuichi

    2015-01-01

    Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include

  11. Anatomy and Cytogenetic Identification of a Wheat-Psathyrostachys huashanica Keng Line with Early Maturation.

    Directory of Open Access Journals (Sweden)

    Liangming Wang

    Full Text Available In previous studies, our research team successfully transferred the Ns genome from Psathyrostachys huashanica Keng into Triticum aestivum (common wheat cv. 7182 using embryo culture. In the present study, one of these lines, i.e., hybrid progeny 25-10-3, which matured about 10-14 days earlier than its wheat parent, was assessed using sequenced characterized amplified region (SCAR analysis, EST-SSR and EST-STS molecular markers, and genomic in situ hybridization (GISH. We found that this was a stable wheat-P. huashanica disomic addition line (2n = 44 = 22 II and the results demonstrated that it was a 6Ns disomic chromosome addition line, but it exhibited many different features compared with previously characterized lines, i.e., a longer awn, early maturation, and no twin spikelets. It was considered to be an early-maturing variety based on the early stage of inflorescence initiation in field experiments and binocular microscope observations over three consecutive years. This characteristic was distinct, especially from the single ridge stage and double ridge stage until the glume stage. In addition, it had a higher photosynthesis rate and economic values than common wheat cv. 7182, i.e., more spikelets per spike, more florets per spikelet, more kernels per spike, and a higher thousand-grain weight. These results suggest that this material may comprise a genetic pool of beneficial genes or chromosome segments, which are suitable for introgression to improve the quality of common wheat.

  12. Analog forecasting with dynamics-adapted kernels

    Science.gov (United States)

    Zhao, Zhizhen; Giannakis, Dimitrios

    2016-09-01

    Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.

  13. Wheat Allergy

    Science.gov (United States)

    ... of reactions. Learn more here. Milk Egg Peanut Tree Nuts Soy Wheat Fish Shellfish Sesame Other Food ... federal law. Download our resource on how to identify wheat on food labels. Avoid foods that contain ...

  14. Efeitos da precipitação pluvial, da umidade relativa do ar e de excesso e déficit hídrico do solo no peso do hectolitro, no peso de mil grãos e no rendimento de grãos de trigo Effects of rainfall, relative humidity and water excess and deficit on test weight, thousand kernel weight, and grain yield of wheat

    Directory of Open Access Journals (Sweden)

    Eliana Maria Guarienti

    2005-09-01

    Full Text Available Cerca de 90% da produção de trigo no Brasil está localizada nos estados do Paraná, do Rio Grande do Sul e de Santa Catarina. Nesses estados, a variabilidade climática é muito expressiva, tornando a produção tritícola uma atividade de risco e fazendo com que o decréscimo da produção e da produtividade de trigo seja objeto de questionamento de grande número de investigadores. Este trabalho teve por objetivo verificar a influência da precipitação pluvial, da umidade relativa do ar e de excesso e déficit hídrico do solo no peso do hectolitro, peso de mil grãos e rendimento de grãos. Foram usados dados de experimentos com a cultivar de trigo Embrapa 16, conduzidos durante os anos de 1990 a 1998, em sete locais do Rio Grande do Sul e em quatro locais de Santa Catarina. A análise estatística realizada foi correlação múltipla. Verificou-se que: a a precipitação pluvial e o excesso hídrico do solo afetaram negativamente o peso do hectolitro, peso de mil grãos e rendimento de grãos, e a umidade relativa do ar influenciou tanto positiva quanto negativamente essas variáveis; b o déficit hídrico do solo afetou positivamente o peso do hectolitro, peso de mil grãos e rendimento de grãos após a maturação fisiológica, isto é, nos dez primeiros dias anteriores à colheita, e negativamente nos demais períodos.About 90% of the wheat production in Brazil is located in Paraná, Rio Grande do Sul and Santa Catarina states. In these states there is a considerable climatic variability and consequently wheat production becomes a risky activity. Therefore, the decrease of wheat production and grain yield has been analyzed by a great number of investigators. This work aimed to verify the influence of rainfall, relative humidity, and water excess and deficit on test weight, thousand kernel weight, and grain yield of wheat. Data of Embrapa 16 wheat cultivar, obtained during the 1990-98 period, in seven Rio Grande do Sul state

  15. An SVM model with hybrid kernels for hydrological time series

    Science.gov (United States)

    Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

    2017-12-01

    Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

  16. Dose point kernels for beta-emitting radioisotopes

    International Nuclear Information System (INIS)

    Prestwich, W.V.; Chan, L.B.; Kwok, C.S.; Wilson, B.

    1986-01-01

    Knowledge of the dose point kernel corresponding to a specific radionuclide is required to calculate the spatial dose distribution produced in a homogeneous medium by a distributed source. Dose point kernels for commonly used radionuclides have been calculated previously using as a basis monoenergetic dose point kernels derived by numerical integration of a model transport equation. The treatment neglects fluctuations in energy deposition, an effect which has been later incorporated in dose point kernels calculated using Monte Carlo methods. This work describes new calculations of dose point kernels using the Monte Carlo results as a basis. An analytic representation of the monoenergetic dose point kernels has been developed. This provides a convenient method both for calculating the dose point kernel associated with a given beta spectrum and for incorporating the effect of internal conversion. An algebraic expression for allowed beta spectra has been accomplished through an extension of the Bethe-Bacher approximation, and tested against the exact expression. Simplified expression for first-forbidden shape factors have also been developed. A comparison of the calculated dose point kernel for 32 P with experimental data indicates good agreement with a significant improvement over the earlier results in this respect. An analytic representation of the dose point kernel associated with the spectrum of a single beta group has been formulated. 9 references, 16 figures, 3 tables

  17. Realized kernels in practice

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, P. Reinhard; Lunde, Asger

    2009-01-01

    and find a remarkable level of agreement. We identify some features of the high-frequency data, which are challenging for realized kernels. They are when there are local trends in the data, over periods of around 10 minutes, where the prices and quotes are driven up or down. These can be associated......Realized kernels use high-frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same stock...

  18. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  19. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  20. Kernel methods for deep learning

    OpenAIRE

    Cho, Youngmin

    2012-01-01

    We introduce a new family of positive-definite kernels that mimic the computation in large neural networks. We derive the different members of this family by considering neural networks with different activation functions. Using these kernels as building blocks, we also show how to construct other positive-definite kernels by operations such as composition, multiplication, and averaging. We explore the use of these kernels in standard models of supervised learning, such as support vector mach...

  1. Soft Sensing of Key State Variables in Fermentation Process Based on Relevance Vector Machine with Hybrid Kernel Function

    Directory of Open Access Journals (Sweden)

    Xianglin ZHU

    2014-06-01

    Full Text Available To resolve the online detection difficulty of some important state variables in fermentation process with traditional instruments, a soft sensing modeling method based on relevance vector machine (RVM with a hybrid kernel function is presented. Based on the characteristic analysis of two commonly-used kernel functions, that is, local Gaussian kernel function and global polynomial kernel function, a hybrid kernel function combing merits of Gaussian kernel function and polynomial kernel function is constructed. To design optimal parameters of this kernel function, the particle swarm optimization (PSO algorithm is applied. The proposed modeling method is used to predict the value of cell concentration in the Lysine fermentation process. Simulation results show that the presented hybrid-kernel RVM model has a better accuracy and performance than the single kernel RVM model.

  2. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...

  3. Kernel bundle EPDiff

    DEFF Research Database (Denmark)

    Sommer, Stefan Horst; Lauze, Francois Bernard; Nielsen, Mads

    2011-01-01

    In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space...

  4. Kernel structures for Clouds

    Science.gov (United States)

    Spafford, Eugene H.; Mckendry, Martin S.

    1986-01-01

    An overview of the internal structure of the Clouds kernel was presented. An indication of how these structures will interact in the prototype Clouds implementation is given. Many specific details have yet to be determined and await experimentation with an actual working system.

  5. Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

    Directory of Open Access Journals (Sweden)

    Hailun Wang

    2017-01-01

    Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

  6. Reduced multiple empirical kernel learning machine.

    Science.gov (United States)

    Wang, Zhe; Lu, MingZhe; Gao, Daqi

    2015-02-01

    Multiple kernel learning (MKL) is demonstrated to be flexible and effective in depicting heterogeneous data sources since MKL can introduce multiple kernels rather than a single fixed kernel into applications. However, MKL would get a high time and space complexity in contrast to single kernel learning, which is not expected in real-world applications. Meanwhile, it is known that the kernel mapping ways of MKL generally have two forms including implicit kernel mapping and empirical kernel mapping (EKM), where the latter is less attracted. In this paper, we focus on the MKL with the EKM, and propose a reduced multiple empirical kernel learning machine named RMEKLM for short. To the best of our knowledge, it is the first to reduce both time and space complexity of the MKL with EKM. Different from the existing MKL, the proposed RMEKLM adopts the Gauss Elimination technique to extract a set of feature vectors, which is validated that doing so does not lose much information of the original feature space. Then RMEKLM adopts the extracted feature vectors to span a reduced orthonormal subspace of the feature space, which is visualized in terms of the geometry structure. It can be demonstrated that the spanned subspace is isomorphic to the original feature space, which means that the dot product of two vectors in the original feature space is equal to that of the two corresponding vectors in the generated orthonormal subspace. More importantly, the proposed RMEKLM brings a simpler computation and meanwhile needs a less storage space, especially in the processing of testing. Finally, the experimental results show that RMEKLM owns a much efficient and effective performance in terms of both complexity and classification. The contributions of this paper can be given as follows: (1) by mapping the input space into an orthonormal subspace, the geometry of the generated subspace is visualized; (2) this paper first reduces both the time and space complexity of the EKM-based MKL; (3

  7. Breeding value of primary synthetic wheat genotypes for grain yield

    Science.gov (United States)

    To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid wheat genotypes (SYN) were crossed to 20 spring bread wheat (BW) cultivars at the International Wheat and Maize Improvement Center. Modified single...

  8. Viscosity kernel of molecular fluids

    DEFF Research Database (Denmark)

    Puscasu, Ruslan; Todd, Billy; Daivis, Peter

    2010-01-01

    , temperature, and chain length dependencies of the reciprocal and real-space viscosity kernels are presented. We find that the density has a major effect on the shape of the kernel. The temperature range and chain lengths considered here have by contrast less impact on the overall normalized shape. Functional...... forms that fit the wave-vector-dependent kernel data over a large density and wave-vector range have also been tested. Finally, a structural normalization of the kernels in physical space is considered. Overall, the real-space viscosity kernel has a width of roughly 3–6 atomic diameters, which means...

  9. High-Throughput Phenotyping of Wheat and Barley Plants Grown in Single or Few Rows in Small Plots Using Active and Passive Spectral Proximal Sensing

    Directory of Open Access Journals (Sweden)

    Gero Barmeier

    2016-11-01

    Full Text Available In the early stages of plant breeding, breeders evaluate a large number of varieties. Due to limited availability of seeds and space, plot sizes may range from one to four rows. Spectral proximal sensors can be used in place of labour-intensive methods to estimate specific plant traits. The aim of this study was to test the performance of active and passive sensing to assess single and multiple rows in a breeding nursery. A field trial with single cultivars of winter barley and winter wheat with four plot designs (single-row, wide double-row, three rows, and four rows was conducted. A GreenSeeker RT100 and a passive bi-directional spectrometer were used to assess biomass fresh and dry weight, as well as aboveground nitrogen content and uptake. Generally, spectral passive sensing and active sensing performed comparably in both crops. Spectral passive sensing was enhanced by the availability of optimized ratio vegetation indices, as well as by an optimized field of view and by reduced distance dependence. Further improvements of both sensors in detecting the performance of plants in single rows can likely be obtained by optimization of sensor positioning or orientation. The results suggest that even in early selection cycles, enhanced high-throughput phenotyping might be able to assess plant performance within plots comprising single or multiple rows. This method has significant potential for advanced breeding.

  10. Modeling end-use quality in U. S. soft wheat germplasm

    Science.gov (United States)

    End-use quality in soft wheat (Triticum aestivum L.) can be assessed by a wide array of measurements, generally categorized into grain, milling, and baking characteristics. Samples were obtained from four regional nurseries. Selected parameters included: test weight, kernel hardness, kernel size, ke...

  11. The botanical integrity of wheat products influences the gastric distention and satiety in healthy subjects

    Directory of Open Access Journals (Sweden)

    Almér Lars-Olof

    2008-04-01

    Full Text Available Abstract Background Maintenance of the botanical integrity of cereal kernels and the addition of acetic acid (as vinegar in the product or meal has been shown to lower the postprandial blood glucose and insulin response and to increase satiety. However, the mechanism behind the benefits of acetic acid on blood glucose and satiety is not clear. We hypothesized that the gastric emptying rate could be involved. Thus, the aim of this study was to evaluate the possible influence of maintained botanical integrity of cereals and the presence of acetic acid (vinegar on gastric emptying rate (GER, postprandial blood glucose and satiety. Methods Fifteen healthy subjects were included in a blinded crossover trial, and thirteen of the subjects completed the study. Equicarbohydrate amounts of the following wheat-based meals were studied: white wheat bread, whole-kernel wheat bread or wholemeal wheat bread served with white wine vinegar. The results were compared with a reference meal consisting of white wheat bread without vinegar. The GER was measured with standardized real-time ultrasonography using normal fasting blood glucose Results The whole-kernel wheat bread with vinegar resulted in significantly higher ( Conclusion The present study shows higher satiety after a whole-kernel wheat bread meal with vinegar. This may be explained by increased antral distension after ingestion of intact cereal kernels but, in this study, not by a lower gastric emptying rate or higher postprandial blood glucose response. Trial registration NTR1116

  12. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng

    2016-07-06

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  13. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

    Directory of Open Access Journals (Sweden)

    Guozheng Liu

    Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  14. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  15. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    Science.gov (United States)

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

  16. Variable Kernel Density Estimation

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1992-01-01

    We investigate some of the possibilities for improvement of univariate and multivariate kernel density estimates by varying the window over the domain of estimation, pointwise and globally. Two general approaches are to vary the window width by the point of estimation and by point of the sample observation. The first possibility is shown to be of little efficacy in one variable. In particular, nearest-neighbor estimators in all versions perform poorly in one and two dimensions, but begin to b...

  17. Steerability of Hermite Kernel

    Czech Academy of Sciences Publication Activity Database

    Yang, Bo; Flusser, Jan; Suk, Tomáš

    2013-01-01

    Roč. 27, č. 4 (2013), 1354006-1-1354006-25 ISSN 0218-0014 R&D Projects: GA ČR GAP103/11/1552 Institutional support: RVO:67985556 Keywords : Hermite polynomials * Hermite kernel * steerability * adaptive filtering Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.558, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/yang-0394387. pdf

  18. Eat Wheat!

    Science.gov (United States)

    Idaho Wheat Commission, Boise.

    This pamphlet contains puzzles, games, and a recipe designed to teach elementary school pupils about wheat. It includes word games based on the U.S. Department of Agriculture Food Guide Pyramid and on foods made from wheat. The Food Guide Pyramid can be cut out of the pamphlet and assembled as a three-dimensional information source and food guide.…

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

    Science.gov (United States)

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

    2017-06-19

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

  20. Near infrared hyperspectral imaging of blends of conventional and waxy hard wheats

    Directory of Open Access Journals (Sweden)

    Stephen R. Delwiche

    2018-02-01

    Full Text Available Recent development of hard winter waxy (amylose-free wheat adapted to the North American climate has prompted the quest to find a rapid method that will determine mixture levels of conventional wheat in lots of identity preserved waxy wheat. Previous work documented the use of conventional near infrared (NIR reflectance spectroscopy to determine the mixture level of conventional wheat in waxy wheat, with an examined range, through binary sample mixture preparation, of 0–100% (weight conventional / weight total. The current study examines the ability of NIR hyperspectral imaging of intact kernels to determine mixture levels. Twenty-nine mixtures (0, 1, 2, 3, 4, 5, 10, 15, …, 95, 96, 97, 98, 99, 100% were formed from known genotypes of waxy and conventional wheat. Two-class partial least squares discriminant analysis (PLSDA and statistical pattern recognition classifier models were developed for identifying each kernel in the images as conventional or waxy. Along with these approaches, conventional PLS1 regression modelling was performed on means of kernel spectra within each mixture test sample. Results indicated close agreement between all three approaches, with standard errors of prediction for the better preprocess transformations (PLSDA models or better classifiers (pattern recognition models of approximately 9 percentage units. Although such error rates were slightly greater than ones previously published using non-imaging NIR analysis of bulk whole kernel wheat and wheat meal, the HSI technique offers an advantage of its potential use in sorting operations.

  1. The definition of kernel Oz

    OpenAIRE

    Smolka, Gert

    1994-01-01

    Oz is a concurrent language providing for functional, object-oriented, and constraint programming. This paper defines Kernel Oz, a semantically complete sublanguage of Oz. It was an important design requirement that Oz be definable by reduction to a lean kernel language. The definition of Kernel Oz introduces three essential abstractions: the Oz universe, the Oz calculus, and the actor model. The Oz universe is a first-order structure defining the values and constraints Oz computes with. The ...

  2. 7 CFR 981.7 - Edible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Edible kernel. 981.7 Section 981.7 Agriculture... Regulating Handling Definitions § 981.7 Edible kernel. Edible kernel means a kernel, piece, or particle of almond kernel that is not inedible. [41 FR 26852, June 30, 1976] ...

  3. 7 CFR 981.408 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.408 Section 981.408 Agriculture... Administrative Rules and Regulations § 981.408 Inedible kernel. Pursuant to § 981.8, the definition of inedible kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as...

  4. 7 CFR 981.8 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Inedible kernel. 981.8 Section 981.8 Agriculture... Regulating Handling Definitions § 981.8 Inedible kernel. Inedible kernel means a kernel, piece, or particle of almond kernel with any defect scored as serious damage, or damage due to mold, gum, shrivel, or...

  5. Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers.

    Science.gov (United States)

    Li, Faji; Wen, Weie; He, Zhonghu; Liu, Jindong; Jin, Hui; Cao, Shuanghe; Geng, Hongwei; Yan, Jun; Zhang, Pingzhi; Wan, Yingxiu; Xia, Xianchun

    2018-06-01

    We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay. Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai × Shi 4185 (D × S), Gaocheng 8901 × Zhoumai 16 (G × Z) and Linmai 2 × Zhong 892 (L × Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5-32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

  6. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  7. Clustering via Kernel Decomposition

    DEFF Research Database (Denmark)

    Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

    2006-01-01

    Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

  8. Multiple kernel boosting framework based on information measure for classification

    International Nuclear Information System (INIS)

    Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun

    2016-01-01

    The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.

  9. Global Polynomial Kernel Hazard Estimation

    DEFF Research Database (Denmark)

    Hiabu, Munir; Miranda, Maria Dolores Martínez; Nielsen, Jens Perch

    2015-01-01

    This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...

  10. Wheat: The Whole Story.

    Science.gov (United States)

    Oklahoma State Dept. of Education, Oklahoma City.

    This publication presents information on wheat. Wheat was originally a wild grass and not native to the United States. Wheat was not planted there until 1777 (and then only as a hobby crop). Wheat is grown on more acres than any other grain in this country. Soft wheats are grown east of the Mississippi River, and hard wheats are grown west of the…

  11. Characterization and glutenin diversity in tetraploid wheat varieties ...

    African Journals Online (AJOL)

    STORAGESEVER

    2008-11-19

    Nov 19, 2008 ... Important methods applied for the breeding of bread-quality wheat (Triticum durum L.) consist of small- scale bread-quality tests for the determination of the grain protein content, SDS-sedimentation volume, thousand weight kernel and ... marked as a x and y – type subunits, based on their electrophoretic ...

  12. Robotic intelligence kernel

    Science.gov (United States)

    Bruemmer, David J [Idaho Falls, ID

    2009-11-17

    A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

  13. Fusarium proliferatum and fumonisin B1 co-occur with Fusarium species causing Fusarium Head Blight in durum wheat in Italy

    OpenAIRE

    Amato, Barbara; Pfohl, Katharina; Tonti, Stefano; Nipoti, Paola; Dastjerdi, Raana; Pisi, Annamaria; Karlovsky, Petr; Prodi, Antonio

    2015-01-01

    Fusarium Head Blight caused by phytopathogenic Fusarium spp. with Fusarium graminearum as main causal agent is a major disease of durum wheat (Triticum durum Desf.). Mycotoxins in wheat are dominated by trichothecenes B. Fumonisins have only occasionally been reported from wheat; their occurrence was attributed to Fusarium proliferatum and Fusarium verticillioides. We investigated kernels of durum wheat grown in Italy in 2008 - 2010 for colonization with Fusarium spp. and for the content o...

  14. Mixture Density Mercer Kernels: A Method to Learn Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...

  15. Point kernels and superposition methods for scatter dose calculations in brachytherapy

    International Nuclear Information System (INIS)

    Carlsson, A.K.

    2000-01-01

    Point kernels have been generated and applied for calculation of scatter dose distributions around monoenergetic point sources for photon energies ranging from 28 to 662 keV. Three different approaches for dose calculations have been compared: a single-kernel superposition method, a single-kernel superposition method where the point kernels are approximated as isotropic and a novel 'successive-scattering' superposition method for improved modelling of the dose from multiply scattered photons. An extended version of the EGS4 Monte Carlo code was used for generating the kernels and for benchmarking the absorbed dose distributions calculated with the superposition methods. It is shown that dose calculation by superposition at and below 100 keV can be simplified by using isotropic point kernels. Compared to the assumption of full in-scattering made by algorithms currently in clinical use, the single-kernel superposition method improves dose calculations in a half-phantom consisting of air and water. Further improvements are obtained using the successive-scattering superposition method, which reduces the overestimates of dose close to the phantom surface usually associated with kernel superposition methods at brachytherapy photon energies. It is also shown that scatter dose point kernels can be parametrized to biexponential functions, making them suitable for use with an effective implementation of the collapsed cone superposition algorithm. (author)

  16. Unsupervised multiple kernel learning for heterogeneous data integration.

    Science.gov (United States)

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

    Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

  17. Laboratory-scale dry/wet-milling process for the extraction of starch and gluten from wheat

    NARCIS (Netherlands)

    Steeneken, P.A.M.; Helmens, H.J.

    2009-01-01

    A laboratory-scale process is presented for the manufacture of starch and gluten from wheat. Main feature of this process is that whole wheat kernels are crushed dry between smooth rolls prior to wet disintegration in excess water in such way that gluten formation is prevented and fibres can be

  18. Pushing Wheat

    DEFF Research Database (Denmark)

    Sharp, Paul Richard

    This paper documents the evolution of variables central to understanding the creation of an Atlantic Economy in wheat between the US and the UK in the nineteenth century. The cointegrated VAR model is then applied to the period 1838-1913 in order to find long-run relationships between these varia......This paper documents the evolution of variables central to understanding the creation of an Atlantic Economy in wheat between the US and the UK in the nineteenth century. The cointegrated VAR model is then applied to the period 1838-1913 in order to find long-run relationships between...

  19. 7 CFR 981.9 - Kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...

  20. 7 CFR 51.2295 - Half kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...

  1. Proteome analysis of the almond kernel (Prunus dulcis).

    Science.gov (United States)

    Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu

    2016-08-01

    Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  2. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    . Schölkopf et al. introduce kernel PCA. Shawe-Taylor and Cristianini is an excellent reference for kernel methods in general. Bishop and Press et al. describe kernel methods among many other subjects. Nielsen and Canty use kernel PCA to detect change in univariate airborne digital camera images. The kernel...... version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply kernel versions of PCA, maximum autocorrelation factor (MAF) analysis...

  3. kernel oil by lipolytic organisms

    African Journals Online (AJOL)

    USER

    2010-08-02

    Aug 2, 2010 ... Rancidity of extracted cashew oil was observed with cashew kernel stored at 70, 80 and 90% .... method of American Oil Chemist Society AOCS (1978) using glacial ..... changes occur and volatile products are formed that are.

  4. Multineuron spike train analysis with R-convolution linear combination kernel.

    Science.gov (United States)

    Tezuka, Taro

    2018-06-01

    A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  6. Notes on the gamma kernel

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole E.

    The density function of the gamma distribution is used as shift kernel in Brownian semistationary processes modelling the timewise behaviour of the velocity in turbulent regimes. This report presents exact and asymptotic properties of the second order structure function under such a model......, and relates these to results of von Karmann and Horwath. But first it is shown that the gamma kernel is interpretable as a Green’s function....

  7. A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

    DEFF Research Database (Denmark)

    Li, Gang; Guan, Wei; Sierszecki, Krzysztof

    2012-01-01

    Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints....... This paper presents a multi-core architecture incorporating a hardware kernel on FPGAs, intended for high performance applications in control engineering domain. First, the hardware kernel is investigated on the basis of a component-based real-time kernel HARTEX (Hard Real-Time Executive for Control Systems...

  8. Option Valuation with Volatility Components, Fat Tails, and Non-Monotonic Pricing Kernels

    DEFF Research Database (Denmark)

    Babaoglu, Kadir; Christoffersen, Peter; Heston, Steven L.

    We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A U-shaped pricing kernel is economically most im...

  9. Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

    OpenAIRE

    Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping

    2017-01-01

    Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. In addition, while the influence function (IF) of an estimator can characterize its robustness, asymptotic ...

  10. Kernel versions of some orthogonal transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    Kernel versions of orthogonal transformations such as principal components are based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced...... by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel...... function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA) and kernel minimum noise fraction (MNF) analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function...

  11. An Approximate Approach to Automatic Kernel Selection.

    Science.gov (United States)

    Ding, Lizhong; Liao, Shizhong

    2016-02-02

    Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

  12. Model Selection in Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    Kernel ridge regression is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts. This paper investigates the influence of the choice of kernel and the setting of tuning parameters on forecast accuracy. We review several popular kernels......, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. We interpret the latter two kernels in terms of their smoothing properties, and we relate the tuning parameters associated to all these kernels to smoothness measures of the prediction function and to the signal-to-noise ratio. Based...... on these interpretations, we provide guidelines for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study confirms the practical usefulness of these rules of thumb. Finally, the flexible and smooth functional forms provided by the Gaussian and Sinc kernels makes them widely...

  13. Integral equations with contrasting kernels

    Directory of Open Access Journals (Sweden)

    Theodore Burton

    2008-01-01

    Full Text Available In this paper we study integral equations of the form $x(t=a(t-\\int^t_0 C(t,sx(sds$ with sharply contrasting kernels typified by $C^*(t,s=\\ln (e+(t-s$ and $D^*(t,s=[1+(t-s]^{-1}$. The kernel assigns a weight to $x(s$ and these kernels have exactly opposite effects of weighting. Each type is well represented in the literature. Our first project is to show that for $a\\in L^2[0,\\infty$, then solutions are largely indistinguishable regardless of which kernel is used. This is a surprise and it leads us to study the essential differences. In fact, those differences become large as the magnitude of $a(t$ increases. The form of the kernel alone projects necessary conditions concerning the magnitude of $a(t$ which could result in bounded solutions. Thus, the next project is to determine how close we can come to proving that the necessary conditions are also sufficient. The third project is to show that solutions will be bounded for given conditions on $C$ regardless of whether $a$ is chosen large or small; this is important in real-world problems since we would like to have $a(t$ as the sum of a bounded, but badly behaved function, and a large well behaved function.

  14. Visual, instrumental, mycological and mycotoxicological characterization of wheat inoculated with and protected against Alternaria spp.

    Directory of Open Access Journals (Sweden)

    Janić-Hajnal Elizabet P.

    2016-01-01

    Full Text Available The aim of this work was to characterize visual properties, instrumentally measured colour properties, field fungi presence and Alternaria toxins levels in wheat samples grown under conditions aimed at inhibition and stimulation of wheat infection with fungi from the Alternaria genus. Experiment was carried out on the wheat treated by fungicide and wheat inoculated by Alternaria spp., while non treated wheat was used as a control. Statistically significant difference was observed between all three treatments using visual scale. Protected wheat samples were significantly different from other samples in terms of all measured colour parameters while inoculated and control wheat samples were significantly different in terms of lightness and dominant wavelength. Identification of field fungi in the all examined wheat samples showed that the dominant mycotoxigenic fungus was Alternaria spp., followed by Fusarium spp. The content of Alternaria toxins in samples of wheat hulls and dehulled kernels point out at higher concentrations of Alternaria toxins in hulls than in dehulled kernels. [Projekat Ministarstvo nauke Republike Srbije, br. III 46001 i br. III 46005

  15. Physical characteristics of some wheat genotypes cultivated in Lake District of Turkey

    Directory of Open Access Journals (Sweden)

    Hülya GÜL

    2012-12-01

    Full Text Available This study was carried out to determine the physical characteristics of wheat genotypes cultivated in lakes district of Turkey. The genotypes were collected from the center of Isparta and Burdur province, districts and selected five different villages in this district at harvest in 2011. Totaly 19 genotypes named as; Hard Wheat, Red Kazmalı Wheat, Lavanta, Red Wheat, Burgaz, Osmaniye and Yunak (Landraces, Kızıltan-91, İzmir 85, Bezostoya, Ankara 98, Sönmez 2001, Çeşit-1252, Hatay 86, Mirzabey, Kunduru-1149, Gerek-79, Gediz-75 and Cumhuriyet-75 (Wheat registered cultivars were collected from these districts. Physical characteristics of the wheat samples brought to laboratory were analyzed as completely randomized design with three replications. Foreign matters of wheats were determined according to TS 2974 standards. 4 genotypes were found at second degree, 5 genotypes were at third degree and remaining 10 genotypes were found out of these rating. Highest thousand kernel weight and hectoliter weight were determined on Mirzabey and Sönmez 2001 respectively in bread wheat varieties while highest thousand kernel weight and hectoliter weight were determeined on Kunduru 1149 and Burgaz respectively in durum wheat varieties.

  16. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  17. Model selection for Gaussian kernel PCA denoising

    DEFF Research Database (Denmark)

    Jørgensen, Kasper Winther; Hansen, Lars Kai

    2012-01-01

    We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

  18. Optimizing memory-bound SYMV kernel on GPU hardware accelerators

    KAUST Repository

    Abdelfattah, Ahmad; Dongarra, Jack; Keyes, David E.; Ltaief, Hatem

    2013-01-01

    and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double

  19. Batched Triangular Dense Linear Algebra Kernels for Very Small Matrix Sizes on GPUs

    KAUST Repository

    Charara, Ali; Keyes, David E.; Ltaief, Hatem

    2017-01-01

    Batched dense linear algebra kernels are becoming ubiquitous in scientific applications, ranging from tensor contractions in deep learning to data compression in hierarchical low-rank matrix approximation. Within a single API call, these kernels are capable of simultaneously launching up to thousands of similar matrix computations, removing the expensive overhead of multiple API calls while increasing the occupancy of the underlying hardware. A challenge is that for the existing hardware landscape (x86, GPUs, etc.), only a subset of the required batched operations is implemented by the vendors, with limited support for very small problem sizes. We describe the design and performance of a new class of batched triangular dense linear algebra kernels on very small data sizes using single and multiple GPUs. By deploying two-sided recursive formulations, stressing the register usage, maintaining data locality, reducing threads synchronization and fusing successive kernel calls, the new batched kernels outperform existing state-of-the-art implementations.

  20. Batched Triangular Dense Linear Algebra Kernels for Very Small Matrix Sizes on GPUs

    KAUST Repository

    Charara, Ali

    2017-03-06

    Batched dense linear algebra kernels are becoming ubiquitous in scientific applications, ranging from tensor contractions in deep learning to data compression in hierarchical low-rank matrix approximation. Within a single API call, these kernels are capable of simultaneously launching up to thousands of similar matrix computations, removing the expensive overhead of multiple API calls while increasing the occupancy of the underlying hardware. A challenge is that for the existing hardware landscape (x86, GPUs, etc.), only a subset of the required batched operations is implemented by the vendors, with limited support for very small problem sizes. We describe the design and performance of a new class of batched triangular dense linear algebra kernels on very small data sizes using single and multiple GPUs. By deploying two-sided recursive formulations, stressing the register usage, maintaining data locality, reducing threads synchronization and fusing successive kernel calls, the new batched kernels outperform existing state-of-the-art implementations.

  1. Genetic evolution and utilization of wheat germplasm resources in Huanghuai winter wheat region of China

    International Nuclear Information System (INIS)

    Xiyong, C.; Haixia, X.U.; Feng, C.

    2011-01-01

    To determine the genetic variation of wheat germplasm resources and improve their use in wheat breeding, 215 wheat cultivars and advanced lines from the Huanghuai Wheat Region of China were used to identify 14 agronomic traits and 7 quality traits, as well as the evolution and utilization of high molecular weight glutenin subunits (HMW-GS) and low molecular weight-glutenin subunits (LMW-GS). From land race cultivars to current cultivars there had been significant increases in grain numbers spike/sip -1/, grain weight spike/sup -1/, 1000-kernel weight, grain weight plant/sup -1/, spikelet number spike/sup -1/, sterile spikelet numbers spike/sup -1/, flag leaf width, and flag leaf area. There had been significant decreases in spike number plant/sup -1/, plant height, the first inter node length, flag leaf length, kernel protein content and wet gluten content. Based on Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) results, a novel HMW-GS combination 20/8 was identified in 1B chromosome of Chinese landrace cultivar Heputou. Subunits 22, 20/8, 2.2+12, and GluB3a were only found in cultivars before the 1960s, and subunits 6+8, 13+16, 3+12, and 4+12 were only found in the cultivars after the 1980s. The average diversity index of 21 traits and allele variance of HMW-GS showed a decreasing-increasing-decreasing tendency. HMW-GS and LMW-GS combination-type cultivars showed an increasing-decreasing tendency. Before the 1980s, most parental strains were from foreign cultivars and landrace cultivars, while after the 1980s, most parental strains were from released cultivars and germplasm created by distant hybridization. This study provided useful information for improvement of wheat breeding in Huanghuai winter wheat region. (author)

  2. RTOS kernel in portable electrocardiograph

    Science.gov (United States)

    Centeno, C. A.; Voos, J. A.; Riva, G. G.; Zerbini, C.; Gonzalez, E. A.

    2011-12-01

    This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

  3. RTOS kernel in portable electrocardiograph

    International Nuclear Information System (INIS)

    Centeno, C A; Voos, J A; Riva, G G; Zerbini, C; Gonzalez, E A

    2011-01-01

    This paper presents the use of a Real Time Operating System (RTOS) on a portable electrocardiograph based on a microcontroller platform. All medical device digital functions are performed by the microcontroller. The electrocardiograph CPU is based on the 18F4550 microcontroller, in which an uCOS-II RTOS can be embedded. The decision associated with the kernel use is based on its benefits, the license for educational use and its intrinsic time control and peripherals management. The feasibility of its use on the electrocardiograph is evaluated based on the minimum memory requirements due to the kernel structure. The kernel's own tools were used for time estimation and evaluation of resources used by each process. After this feasibility analysis, the migration from cyclic code to a structure based on separate processes or tasks able to synchronize events is used; resulting in an electrocardiograph running on one Central Processing Unit (CPU) based on RTOS.

  4. Semi-Supervised Kernel PCA

    DEFF Research Database (Denmark)

    Walder, Christian; Henao, Ricardo; Mørup, Morten

    We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least...... squares regression and kernel PCA. The final LR-KPCA is an iteratively reweighted version of the previous which achieves a sigmoid loss function on the labeled points. We provide a theoretical risk bound as well as illustrative experiments on real and toy data sets....

  5. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

    Kernel ridge regression is a technique to perform ridge regression with a potentially infinite number of nonlinear transformations of the independent variables as regressors. This method is gaining popularity as a data-rich nonlinear forecasting tool, which is applicable in many different contexts....... The influence of the choice of kernel and the setting of tuning parameters on forecast accuracy is investigated. Several popular kernels are reviewed, including polynomial kernels, the Gaussian kernel, and the Sinc kernel. The latter two kernels are interpreted in terms of their smoothing properties......, and the tuning parameters associated to all these kernels are related to smoothness measures of the prediction function and to the signal-to-noise ratio. Based on these interpretations, guidelines are provided for selecting the tuning parameters from small grids using cross-validation. A Monte Carlo study...

  6. Resistance to Wheat Curl Mite in Arthropod-Resistant Rye-Wheat Translocation Lines

    Directory of Open Access Journals (Sweden)

    Lina Maria Aguirre-Rojas

    2017-11-01

    Full Text Available The wheat curl mite, Aceria toschiella (Keifer, and a complex of viruses vectored by A. toschiella substantially reduce wheat yields in every wheat-producing continent in the world. The development of A. toschiella-resistant wheat cultivars is a proven economically and ecologically viable method of controlling this pest. This study assessed A. toschiella resistance in wheat genotypes containing the H13, H21, H25, H26, H18 and Hdic genes for resistance to the Hessian fly, Mayetiola destructor (Say and in 94M370 wheat, which contains the Dn7 gene for resistance to the Russian wheat aphid, Diuraphis noxia (Kurdjumov. A. toschiella populations produced on plants containing Dn7 and H21 were significantly lower than those on plants of the susceptible control and no different than those on the resistant control. Dn7 resistance to D. noxia and H21 resistance to M. destructor resulted from translocations of chromatin from rye into wheat (H21—2BS/2RL, Dn7—1BL/1RS. These results provide new wheat pest management information, indicating that Dn7 and H21 constitute resources that can be used to reduce yield losses caused by A. toschiella, M. destructor, D. noxia, and wheat streak mosaic virus infection by transferring multi-pest resistance to single sources of germplasm.

  7. Impact of Triticum mosaic virus infection on hard winter wheat milling and bread baking quality.

    Science.gov (United States)

    Miller, Rebecca A; Martin, T Joe; Seifers, Dallas L

    2012-03-15

    Triticum mosaic virus (TriMV) is a newly discovered wheat virus. Information regarding the effect of wheat viruses on milling and baking quality is limited. The objective of this study was to determine the impact of TriMV infection on the kernel characteristics, milling yield and bread baking quality of wheat. Commercial hard winter varieties evaluated included RonL, Danby and Jagalene. The TriMV resistance of RonL is low, while that of Danby and Jagalene is unknown. KS96HW10-3, a germplasm with high TriMV resistance, was included as a control. Plots of each variety were inoculated with TriMV at the two- to three-leaf stage. Trials were conducted at two locations in two crop years. TriMV infection had no effect on the kernel characteristics, flour yield or baking properties of KS96HW10-3. The effect of TriMV on the kernel characteristics of RonL, Danby and Jagalene was not consistent between crop years and presumably an environmental effect. The flour milling and bread baking properties of these three varieties were not significantly affected by TriMV infection. TriMV infection of wheat plants did not affect harvested wheat kernel characteristics, flour milling properties or white pan bread baking quality. Copyright © 2011 Society of Chemical Industry.

  8. Multiple Kernel Learning with Data Augmentation

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:49–64, 2016 ACML 2016 Multiple Kernel Learning with Data Augmentation Khanh Nguyen nkhanh@deakin.edu.au...University, Australia Editors: Robert J. Durrant and Kee-Eung Kim Abstract The motivations of multiple kernel learning (MKL) approach are to increase... kernel expres- siveness capacity and to avoid the expensive grid search over a wide spectrum of kernels . A large amount of work has been proposed to

  9. A kernel version of multivariate alteration detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2013-01-01

    Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....

  10. A novel adaptive kernel method with kernel centers determined by a support vector regression approach

    NARCIS (Netherlands)

    Sun, L.G.; De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

    2012-01-01

    The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an

  11. Complex use of cottonseed kernels

    Energy Technology Data Exchange (ETDEWEB)

    Glushenkova, A I

    1977-01-01

    A review with 41 references is made on the manufacture of oil, protein, and other products from cottonseed, the effects of gossypol on protein yield and quality and technology of gossypol removal. A process eliminating thermal treatment of the kernels and permitting the production of oil, proteins, phytin, gossypol, sugar, sterols, phosphatides, tocopherols, and residual shells and baggase is described.

  12. Kernel regression with functional response

    OpenAIRE

    Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe

    2011-01-01

    We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.

  13. GRIM : Leveraging GPUs for Kernel integrity monitoring

    NARCIS (Netherlands)

    Koromilas, Lazaros; Vasiliadis, Giorgos; Athanasopoulos, Ilias; Ioannidis, Sotiris

    2016-01-01

    Kernel rootkits can exploit an operating system and enable future accessibility and control, despite all recent advances in software protection. A promising defense mechanism against rootkits is Kernel Integrity Monitor (KIM) systems, which inspect the kernel text and data to discover any malicious

  14. Paramecium: An Extensible Object-Based Kernel

    NARCIS (Netherlands)

    van Doorn, L.; Homburg, P.; Tanenbaum, A.S.

    1995-01-01

    In this paper we describe the design of an extensible kernel, called Paramecium. This kernel uses an object-based software architecture which together with instance naming, late binding and explicit overrides enables easy reconfiguration. Determining which components reside in the kernel protection

  15. Local Observed-Score Kernel Equating

    Science.gov (United States)

    Wiberg, Marie; van der Linden, Wim J.; von Davier, Alina A.

    2014-01-01

    Three local observed-score kernel equating methods that integrate methods from the local equating and kernel equating frameworks are proposed. The new methods were compared with their earlier counterparts with respect to such measures as bias--as defined by Lord's criterion of equity--and percent relative error. The local kernel item response…

  16. Veto-Consensus Multiple Kernel Learning

    NARCIS (Netherlands)

    Zhou, Y.; Hu, N.; Spanos, C.J.

    2016-01-01

    We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The

  17. Improved wheat for baking.

    Science.gov (United States)

    Faridi, H; Finley, J W

    1989-01-01

    To bakers, wheat quality means the performance characteristics of the flour milled from the wheat when used in specific wheat products. The tremendous increase in the number of wheat cultivars grown in the U.S. in recent years, along with the unusual climate, new advances in milling technology, and increased automation of baking lines, have resulted in bakery production problems partly attributed to wheat flour quality. In this review various factors affecting wheat quality are explained. Concerns of bread and cookie/cracker manufacturers on deterioration of the wheat quality are discussed, and, finally, some solutions are proposed.

  18. Screening for resistance to Fusarium head blight in spring wheat cultivars

    OpenAIRE

    Scholten, Dr. Olga E.; Steenhuis-Broers, Greet; Osman, Aart; Bremer, Esther

    2006-01-01

    Fusarium fungi cause Fusarium head blight in wheat. This disease is a problem that occurs both in organic and conventional farming systems. As Fusarium fungi produce mycotoxins in wheat kernels they are a threat to human and animal health. Breeding for disease resistance is the only way to prevent or reduce the occurrence of the disease. The aim of the current research project is to identify different mechanisms of resistance in cultivars and breeding lines to be used in further breeding pro...

  19. An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel

    Directory of Open Access Journals (Sweden)

    Senyue Zhang

    2016-01-01

    Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.

  20. Higher Fusarium Toxin Accumulation in Grain of Winter Triticale Lines Inoculated with Fusarium culmorum as Compared with Wheat.

    Science.gov (United States)

    Góral, Tomasz; Wiśniewska, Halina; Ochodzki, Piotr; Walentyn-Góral, Dorota

    2016-10-18

    Resistance to Fusarium head blight in 32 winter triticale and 34 winter wheat accessions was evaluated. Triticale and wheat were sown in field experiments in two locations. At the time of flowering, heads were inoculated with three Fusarium culmorum isolates. Fusarium head blight index was scored and after the harvest percentage of Fusarium damaged kernels was assessed. Grain was analysed for type B trichothecenes (deoxynivalenol and derivatives, nivalenol) and zearalenone (ZEN) content. The average Fusarium head blight indexes were 28.0% for wheat and 19.2% for triticale accessions. The percentage of Fusarium damaged kernels was also higher for wheat and came to 55.6%, while for triticale this figure was 40.2%. The average content of deoxynivalenol (DON) for wheat amounted to 11.65 mg/kg and was lower than the result for triticale which was 14.12 mg/kg. The average contents of nivalenol were similar in both cereals: 4.13 mg/kg and 5.19 mg/kg for wheat and triticale respectively. Considerable amounts of DON derivatives in the cereals were also detected. The ZEN content in the grain was 0.60 mg/kg for wheat and 0.66 mg/kg for triticale. Relationships between Fusarium head blight index, Fusarium damaged kernels and mycotoxin contents were statistically significant for wheat and mostly insignificant for triticale. Triticale proved to have less infected heads and kernels than wheat. However, the content of type B trichothecenes was higher in triticale grain than in wheat grain.

  1. Higher Fusarium Toxin Accumulation in Grain of Winter Triticale Lines Inoculated with Fusarium culmorum as Compared with Wheat

    Science.gov (United States)

    Góral, Tomasz; Wiśniewska, Halina; Ochodzki, Piotr; Walentyn-Góral, Dorota

    2016-01-01

    Resistance to Fusarium head blight in 32 winter triticale and 34 winter wheat accessions was evaluated. Triticale and wheat were sown in field experiments in two locations. At the time of flowering, heads were inoculated with three Fusarium culmorum isolates. Fusarium head blight index was scored and after the harvest percentage of Fusarium damaged kernels was assessed. Grain was analysed for type B trichothecenes (deoxynivalenol and derivatives, nivalenol) and zearalenone (ZEN) content. The average Fusarium head blight indexes were 28.0% for wheat and 19.2% for triticale accessions. The percentage of Fusarium damaged kernels was also higher for wheat and came to 55.6%, while for triticale this figure was 40.2%. The average content of deoxynivalenol (DON) for wheat amounted to 11.65 mg/kg and was lower than the result for triticale which was 14.12 mg/kg. The average contents of nivalenol were similar in both cereals: 4.13 mg/kg and 5.19 mg/kg for wheat and triticale respectively. Considerable amounts of DON derivatives in the cereals were also detected. The ZEN content in the grain was 0.60 mg/kg for wheat and 0.66 mg/kg for triticale. Relationships between Fusarium head blight index, Fusarium damaged kernels and mycotoxin contents were statistically significant for wheat and mostly insignificant for triticale. Triticale proved to have less infected heads and kernels than wheat. However, the content of type B trichothecenes was higher in triticale grain than in wheat grain. PMID:27763547

  2. Consistent Valuation across Curves Using Pricing Kernels

    Directory of Open Access Journals (Sweden)

    Andrea Macrina

    2018-03-01

    Full Text Available The general problem of asset pricing when the discount rate differs from the rate at which an asset’s cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets. As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised and single-curve models extended. In another application, inflation-linked, currency-based and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

  3. Pareto-path multitask multiple kernel learning.

    Science.gov (United States)

    Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

    2015-01-01

    A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.

  4. Prolamin proteins alteration in durum wheat by species of the genus Eurygaster and Aelia (Insecta, Hemiptera)

    Energy Technology Data Exchange (ETDEWEB)

    Salis, L.; Goula, M.; Valero, J.; Gordun, E.

    2010-07-01

    Wheat bugs are widely distributed in various areas of Europe, Asia and North Africa. Species belonging to the genus Eurygaster and Aelia pierce wheat kernels affecting protein quality. The effects of these insects feeding activity have been studied mainly in bread wheat (Triticum aestivum L.). This study provides information on the degradation of prolamin proteins (glutenins and gliadins) of bug-damaged durum wheat (Triticum turgidum L. var durum) in six cultivars grown in Sardinia (Italy). Samples of whole flour mixture of 70% sound wheat and 30% damaged wheat were hydrated and incubated at two temperatures (45 and 4 degree centigrade), for different periods of time (0, 1 and 3 h). Glutenin and gliadin content was analysed using free zone capillary electrophoresis. The presence of bug-damaged kernels had influence on the quality of durum wheat proteins. Glutenins were rapidly degraded independently to incubation temperature. Gliadin degradation, however, took place with dependence on temperature and incubation time. Therefore glutenin degradation was possibly not due solely to the activity of proteolytic enzymes but also to some other as yet unknown factor linked to wheat bugs feeding activity. (Author) 35 refs.

  5. Prolamin proteins alteration in durum wheat by species of the genus Eurygaster and Aelia (Insecta, Hemiptera)

    International Nuclear Information System (INIS)

    Salis, L.; Goula, M.; Valero, J.; Gordun, E.

    2010-01-01

    Wheat bugs are widely distributed in various areas of Europe, Asia and North Africa. Species belonging to the genus Eurygaster and Aelia pierce wheat kernels affecting protein quality. The effects of these insects feeding activity have been studied mainly in bread wheat (Triticum aestivum L.). This study provides information on the degradation of prolamin proteins (glutenins and gliadins) of bug-damaged durum wheat (Triticum turgidum L. var durum) in six cultivars grown in Sardinia (Italy). Samples of whole flour mixture of 70% sound wheat and 30% damaged wheat were hydrated and incubated at two temperatures (45 and 4 degree centigrade), for different periods of time (0, 1 and 3 h). Glutenin and gliadin content was analysed using free zone capillary electrophoresis. The presence of bug-damaged kernels had influence on the quality of durum wheat proteins. Glutenins were rapidly degraded independently to incubation temperature. Gliadin degradation, however, took place with dependence on temperature and incubation time. Therefore glutenin degradation was possibly not due solely to the activity of proteolytic enzymes but also to some other as yet unknown factor linked to wheat bugs feeding activity. (Author) 35 refs.

  6. Composite population kernels in ytterbium-buffer collisions studied by means of laser-saturated absorption

    International Nuclear Information System (INIS)

    Zhu, X.

    1986-01-01

    We present a systematic study of composite population kernels for 174 Yb collisions with He, Ar, and Xe buffer gases, using laser-saturation spectroscopy. 174 Yb is chosen as the active species because of the simple structure of its 1 S 0 - 3 P 1 resonance transition (lambda = 556 nm). Elastic collisions are modeled by means of a composite collision kernel, an expression of which is explicitly derived based on arguments of a hard-sphere potential and two-category collisions. The corresponding coupled population-rate equations are solved by iteration to obtain an expression for the saturated-absorption line shape. This expression is fit to the data to obtain information about the composite kernel, along with reasonable values for other parameters. The results confirm that a composite kernel is more general and realistic than a single-component kernel, and the generality in principle and the practical necessity of the former are discussed

  7. Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

    Science.gov (United States)

    Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

    2018-05-01

    With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Wigner functions defined with Laplace transform kernels.

    Science.gov (United States)

    Oh, Se Baek; Petruccelli, Jonathan C; Tian, Lei; Barbastathis, George

    2011-10-24

    We propose a new Wigner-type phase-space function using Laplace transform kernels--Laplace kernel Wigner function. Whereas momentum variables are real in the traditional Wigner function, the Laplace kernel Wigner function may have complex momentum variables. Due to the property of the Laplace transform, a broader range of signals can be represented in complex phase-space. We show that the Laplace kernel Wigner function exhibits similar properties in the marginals as the traditional Wigner function. As an example, we use the Laplace kernel Wigner function to analyze evanescent waves supported by surface plasmon polariton. © 2011 Optical Society of America

  9. Credit scoring analysis using kernel discriminant

    Science.gov (United States)

    Widiharih, T.; Mukid, M. A.; Mustafid

    2018-05-01

    Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

  10. Testing Infrastructure for Operating System Kernel Development

    DEFF Research Database (Denmark)

    Walter, Maxwell; Karlsson, Sven

    2014-01-01

    Testing is an important part of system development, and to test effectively we require knowledge of the internal state of the system under test. Testing an operating system kernel is a challenge as it is the operating system that typically provides access to this internal state information. Multi......-core kernels pose an even greater challenge due to concurrency and their shared kernel state. In this paper, we present a testing framework that addresses these challenges by running the operating system in a virtual machine, and using virtual machine introspection to both communicate with the kernel...... and obtain information about the system. We have also developed an in-kernel testing API that we can use to develop a suite of unit tests in the kernel. We are using our framework for for the development of our own multi-core research kernel....

  11. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    kernel PCA. Shawe-Taylor and Cristianini [4] is an excellent reference for kernel methods in general. Bishop [5] and Press et al. [6] describe kernel methods among many other subjects. The kernel version of PCA handles nonlinearities by implicitly transforming data into high (even infinite) dimensional...... feature space via the kernel function and then performing a linear analysis in that space. In this paper we shall apply a kernel version of maximum autocorrelation factor (MAF) [7, 8] analysis to irregularly sampled stream sediment geochemistry data from South Greenland and illustrate the dependence...... of the kernel width. The 2,097 samples each covering on average 5 km2 are analyzed chemically for the content of 41 elements....

  12. Sina and Sinb genes in triticale do not determine grain hardness contrary to their orthologs Pina and Pinb in wheat.

    Science.gov (United States)

    Gasparis, Sebastian; Orczyk, Waclaw; Nadolska-Orczyk, Anna

    2013-11-26

    Secaloindoline a (Sina) and secaloindoline b (Sinb) genes of hexaploid triticale (x Triticosecale Wittmack) are orthologs of puroindoline a (Pina) and puroindoline b (Pinb) in hexaploid wheat (Triticum aestivum L.). It has already been proven that RNA interference (RNAi)-based silencing of Pina and Pinb genes significantly decreased the puroindoline a and puroindoline b proteins in wheat and essentially increased grain hardness (J Exp Bot 62:4025-4036, 2011). The function of Sina and Sinb in triticale was tested by means of RNAi silencing and compared to wheat. Novel Sina and Sinb alleles in wild-type plants of cv. Wanad were identified and their expression profiles characterized. Alignment with wheat Pina-D1a and Pinb-D1a alleles showed 95% and 93.3% homology with Sina and Sinb coding sequences. Twenty transgenic lines transformed with two hpRNA silencing cassettes directed to silence Sina or Sinb were obtained by the Agrobacterium-mediated method. A significant decrease of expression of both Sin genes in segregating progeny of tested T1 lines was observed independent of the silencing cassette used. The silencing was transmitted to the T4 kernel generation. The relative transcript level was reduced by up to 99% in T3 progeny with the mean for the sublines being around 90%. Silencing of the Sin genes resulted in a substantial decrease of secaloindoline a and secaloindoline b content. The identity of SIN peptides was confirmed by mass spectrometry. The hardness index, measured by the SKCS (Single Kernel Characterization System) method, ranged from 22 to 56 in silent lines and from 37 to 49 in the control, and the mean values were insignificantly lower in the silent ones, proving increased softness. Additionally, the mean total seed protein content of silenced lines was about 6% lower compared with control lines. Correlation coefficients between hardness and transcript level were weakly positive. We documented that RNAi-based silencing of Sin genes resulted in

  13. Segregation distortion in homozygous lines obtained via anther culture and maize doubled haploid methods in comparison to single seed descent in wheat (Triticum aestivum L.)

    OpenAIRE

    Adamski,Tadeusz; Krystkowiak,Karolina; Kuczynska,Anetta; Mikolajczak,Krzysztof; Ogrodowicz,Piotr; Ponitka,Aleksandra; Surma,Maria; Slusarkiewicz-Jarzina,Aurelia

    2014-01-01

    Background: The quality of wheat grain depends on several characteristics, among which the composition of high molecular weight glutenin subunits, encoded by Glu-1 loci, are the most important. Application of biotechnological tools to accelerate the attainment of homozygous lines may influence the proportion of segregated genotypes. The objective was to determine, whether the selection pressure generated by the methods based on in vitro cultures, may cause a loss of genotypes with desirable G...

  14. 90Sr and 137Cs contamination of wheat produced in Japan. Survey and analysis during the years 1959 through 1995 including the Chernobyl accident

    International Nuclear Information System (INIS)

    Komamura, Misako; Tsumura, Akito; Kihou, Nobuharu; Kodaira, Kiyoshi

    2002-01-01

    This paper attempts to discuss the influences of global-scale radioactive fallout on wheat produced in Japan. For this purpose, a set of wheat samples was collected annually from sixteen National and Prefectural Experimental Farms during the years from 1959 to 1995. According to the graph presenting year-to-year variations in the nationwide averages of 90 Sr and 137 Cs contents (mBq/kg) in wheat kernels, the sharp peak was first marked in 1963 with 12300 for 90 Sr and 43600 for 137 Cs. In 1966, however, the nuclide contents dropped drastically to 2360 for 90 Sr and 2870 for 137 Cs respectively. In the years following, both nuclides continued to decrease slowly although there were minor fluctuations. It is noticeable that low-level 137 Cs contamination was caused in Japan's wheat in 1981, the year after the nuclear testing in China. It is also noticeable that 137 Cs contents in wheat kernels increased to 5960 in 1986 when the Chernobyl nuclear power plant accident happened, although it dropped back to its normal level of 40 in the year after. The following are also discussed in this paper: Year to year variations in the ratio of 90 Sr to 137 Cs contents in wheat kernels and wheat flour. Regional differences in 90 Sr and 137 Cs contents in wheat kernels. Comparison of 90 Sr and 137 Cs contents in wheat kernels and unpolished rice. Direct and indirect pathways of 90 Sr and 137 Cs that contaminate wheat. Influence of the Chernobyl power plant accident. Suggestions about the ways of estimating the level of 137 Cs contamination in case of nuclear accidents, if any. (author)

  15. An endogenous reference gene of common and durum wheat for detection of genetically modified wheat.

    Science.gov (United States)

    Imai, Shinjiro; Tanaka, Keiko; Nishitsuji, Yasuyuki; Kikuchi, Yosuke; Matsuoka, Yasuyuki; Arami, Shin-Ichiro; Sato, Megumi; Haraguchi, Hiroyuki; Kurimoto, Youichi; Mano, Junichi; Furui, Satoshi; Kitta, Kazumi

    2012-01-01

    To develop a method for detecting GM wheat that may be marketed in the near future, we evaluated the proline-rich protein (PRP) gene as an endogenous reference gene of common wheat (Triticum aestivum L.) and durum wheat (Triticum durum L.). Real-time PCR analysis showed that only DNA of wheat was amplified and no amplification product was observed for phylogenetically related cereals, indicating that the PRP detection system is specific to wheat. The intensities of the amplification products and Ct values among all wheat samples used in this study were very similar, with no nonspecific or additional amplification, indicating that the PRP detection system has high sequence stability. The limit of detection was estimated at 5 haploid genome copies. The PRP region was demonstrated to be present as a single or double copy in the common wheat haploid genome. Furthermore, the PRP detection system showed a highly linear relationship between Ct values and the amount of plasmid DNA, indicating that an appropriate calibration curve could be constructed for quantitative detection of GM wheat. All these results indicate that the PRP gene is a suitable endogenous reference gene for PCR-based detection of GM wheat.

  16. Validation of Born Traveltime Kernels

    Science.gov (United States)

    Baig, A. M.; Dahlen, F. A.; Hung, S.

    2001-12-01

    Most inversions for Earth structure using seismic traveltimes rely on linear ray theory to translate observed traveltime anomalies into seismic velocity anomalies distributed throughout the mantle. However, ray theory is not an appropriate tool to use when velocity anomalies have scale lengths less than the width of the Fresnel zone. In the presence of these structures, we need to turn to a scattering theory in order to adequately describe all of the features observed in the waveform. By coupling the Born approximation to ray theory, the first order dependence of heterogeneity on the cross-correlated traveltimes (described by the Fréchet derivative or, more colourfully, the banana-doughnut kernel) may be determined. To determine for what range of parameters these banana-doughnut kernels outperform linear ray theory, we generate several random media specified by their statistical properties, namely the RMS slowness perturbation and the scale length of the heterogeneity. Acoustic waves are numerically generated from a point source using a 3-D pseudo-spectral wave propagation code. These waves are then recorded at a variety of propagation distances from the source introducing a third parameter to the problem: the number of wavelengths traversed by the wave. When all of the heterogeneity has scale lengths larger than the width of the Fresnel zone, ray theory does as good a job at predicting the cross-correlated traveltime as the banana-doughnut kernels do. Below this limit, wavefront healing becomes a significant effect and ray theory ceases to be effective even though the kernels remain relatively accurate provided the heterogeneity is weak. The study of wave propagation in random media is of a more general interest and we will also show our measurements of the velocity shift and the variance of traveltime compare to various theoretical predictions in a given regime.

  17. RKRD: Runtime Kernel Rootkit Detection

    Science.gov (United States)

    Grover, Satyajit; Khosravi, Hormuzd; Kolar, Divya; Moffat, Samuel; Kounavis, Michael E.

    In this paper we address the problem of protecting computer systems against stealth malware. The problem is important because the number of known types of stealth malware increases exponentially. Existing approaches have some advantages for ensuring system integrity but sophisticated techniques utilized by stealthy malware can thwart them. We propose Runtime Kernel Rootkit Detection (RKRD), a hardware-based, event-driven, secure and inclusionary approach to kernel integrity that addresses some of the limitations of the state of the art. Our solution is based on the principles of using virtualization hardware for isolation, verifying signatures coming from trusted code as opposed to malware for scalability and performing system checks driven by events. Our RKRD implementation is guided by our goals of strong isolation, no modifications to target guest OS kernels, easy deployment, minimal infra-structure impact, and minimal performance overhead. We developed a system prototype and conducted a number of experiments which show that the per-formance impact of our solution is negligible.

  18. Kernel Bayesian ART and ARTMAP.

    Science.gov (United States)

    Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan

    2018-02-01

    Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Natural variation in grain composition of wheat and related cereals.

    Science.gov (United States)

    Shewry, Peter R; Hawkesford, Malcolm J; Piironen, Vieno; Lampi, Ann-Maija; Gebruers, Kurt; Boros, Danuta; Andersson, Annica A M; Åman, Per; Rakszegi, Mariann; Bedo, Zoltan; Ward, Jane L

    2013-09-04

    The wheat grain comprises three groups of major components, starch, protein, and cell wall polysaccharides (dietary fiber), and a range of minor components that may confer benefits to human health. Detailed analyses of dietary fiber and other bioactive components were carried out under the EU FP6 HEALTHGRAIN program on 150 bread wheat lines grown on a single site, 50 lines of other wheat species and other cereals grown on the same site, and 23-26 bread wheat lines grown in six environments. Principal component analysis allowed the 150 bread wheat lines to be classified on the basis of differences in their contents of bioactive components and wheat species (bread, durum, spelt, emmer, and einkorn wheats) to be clearly separated from related cereals (barley, rye, and oats). Such multivariate analyses could be used to define substantial equivalence when novel (including transgenic) cereals are considered.

  20. Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

    Science.gov (United States)

    Zhang, Zhanhui; Wu, Xiangyuan; Shi, Chaonan; Wang, Rongna; Li, Shengfei; Wang, Zhaohui; Liu, Zonghua; Xue, Yadong; Tang, Guiliang; Tang, Jihua

    2016-02-01

    Kernel development is an important dynamic trait that determines the final grain yield in maize. To dissect the genetic basis of maize kernel development process, a conditional quantitative trait locus (QTL) analysis was conducted using an immortalized F2 (IF2) population comprising 243 single crosses at two locations over 2 years. Volume (KV) and density (KD) of dried developing kernels, together with kernel weight (KW) at different developmental stages, were used to describe dynamic changes during kernel development. Phenotypic analysis revealed that final KW and KD were determined at DAP22 and KV at DAP29. Unconditional QTL mapping for KW, KV and KD uncovered 97 QTLs at different kernel development stages, of which qKW6b, qKW7a, qKW7b, qKW10b, qKW10c, qKV10a, qKV10b and qKV7 were identified under multiple kernel developmental stages and environments. Among the 26 QTLs detected by conditional QTL mapping, conqKW7a, conqKV7a, conqKV10a, conqKD2, conqKD7 and conqKD8a were conserved between the two mapping methodologies. Furthermore, most of these QTLs were consistent with QTLs and genes for kernel development/grain filling reported in previous studies. These QTLs probably contain major genes associated with the kernel development process, and can be used to improve grain yield and quality through marker-assisted selection.

  1. A framework for dense triangular matrix kernels on various manycore architectures

    KAUST Repository

    Charara, Ali

    2017-06-06

    We present a new high-performance framework for dense triangular Basic Linear Algebra Subroutines (BLAS) kernels, ie, triangular matrix-matrix multiplication (TRMM) and triangular solve (TRSM), on various manycore architectures. This is an extension of a previous work on a single GPU by the same authors, presented at the EuroPar\\'16 conference, in which we demonstrated the effectiveness of recursive formulations in enhancing the performance of these kernels. In this paper, the performance of triangular BLAS kernels on a single GPU is further enhanced by implementing customized in-place CUDA kernels for TRMM and TRSM, which are called at the bottom of the recursion. In addition, a multi-GPU implementation of TRMM and TRSM is proposed and we show an almost linear performance scaling, as the number of GPUs increases. Finally, the algorithmic recursive formulation of these triangular BLAS kernels is in fact oblivious to the targeted hardware architecture. We, therefore, port these recursive kernels to homogeneous x86 hardware architectures by relying on the vendor optimized BLAS implementations. Results reported on various hardware architectures highlight a significant performance improvement against state-of-the-art implementations. These new kernels are freely available in the KAUST BLAS (KBLAS) open-source library at https://github.com/ecrc/kblas.

  2. A framework for dense triangular matrix kernels on various manycore architectures

    KAUST Repository

    Charara, Ali; Keyes, David E.; Ltaief, Hatem

    2017-01-01

    We present a new high-performance framework for dense triangular Basic Linear Algebra Subroutines (BLAS) kernels, ie, triangular matrix-matrix multiplication (TRMM) and triangular solve (TRSM), on various manycore architectures. This is an extension of a previous work on a single GPU by the same authors, presented at the EuroPar'16 conference, in which we demonstrated the effectiveness of recursive formulations in enhancing the performance of these kernels. In this paper, the performance of triangular BLAS kernels on a single GPU is further enhanced by implementing customized in-place CUDA kernels for TRMM and TRSM, which are called at the bottom of the recursion. In addition, a multi-GPU implementation of TRMM and TRSM is proposed and we show an almost linear performance scaling, as the number of GPUs increases. Finally, the algorithmic recursive formulation of these triangular BLAS kernels is in fact oblivious to the targeted hardware architecture. We, therefore, port these recursive kernels to homogeneous x86 hardware architectures by relying on the vendor optimized BLAS implementations. Results reported on various hardware architectures highlight a significant performance improvement against state-of-the-art implementations. These new kernels are freely available in the KAUST BLAS (KBLAS) open-source library at https://github.com/ecrc/kblas.

  3. A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

    DEFF Research Database (Denmark)

    Li, Gang; Guan, Wei; Sierszecki, Krzysztof

    2012-01-01

    Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints. This pa......Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints......). Second, a heterogeneous multi-core architecture is investigated, focusing on its performance in relation to hard real-time constraints and predictable behavior. Third, the hardware implementation of HARTEX is designated to support the heterogeneous multi-core architecture. This hardware kernel has...... several advantages over a similar kernel implemented in software: higher-speed processing capability, parallel computation, and separation between the kernel itself and the applications being run. A microbenchmark has been used to compare the hardware kernel with the software kernel, and compare...

  4. Association Mapping and Nucleotide Sequence Variation in Five Drought Tolerance Candidate Genes in Spring Wheat

    Directory of Open Access Journals (Sweden)

    Erena A. Edae

    2013-07-01

    Full Text Available Functional markers are needed for key genes involved in drought tolerance to improve selection for crop yield under moisture stress conditions. The objectives of this study were to (i characterize five drought tolerance candidate genes, namely dehydration responsive element binding 1A (, enhanced response to abscisic acid ( and , and fructan 1-exohydrolase ( and , in wheat ( L. for nucleotide and haplotype diversity, Tajima’s D value, and linkage disequilibrium (LD and (ii associate within-gene single nucleotide polymorphisms (SNPs with phenotypic traits in a spring wheat association mapping panel ( = 126. Field trials were grown under contrasting moisture regimes in Greeley, CO, and Melkassa, Ethiopia, in 2010 and 2011. Genome-specific amplification and DNA sequence analysis of the genes identified SNPs and revealed differences in nucleotide and haplotype diversity, Tajima’s D, and patterns of LD. showed associations (false discovery rate adjusted probability value = 0.1 with normalized difference vegetation index, heading date, biomass, and spikelet number. Both and were associated with harvest index, flag leaf width, and leaf senescence. was associated with grain yield, and was associated with thousand kernel weight and test weight. If validated in relevant genetic backgrounds, the identified marker–trait associations may be applied to functional marker-assisted selection.

  5. Optimizing Multiple Kernel Learning for the Classification of UAV Data

    Directory of Open Access Journals (Sweden)

    Caroline M. Gevaert

    2016-12-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing high-quality orthoimagery and 3D information in the form of point clouds at a relatively low cost. Their increasing popularity stresses the necessity of understanding which algorithms are especially suited for processing the data obtained from UAVs. The features that are extracted from the point cloud and imagery have different statistical characteristics and can be considered as heterogeneous, which motivates the use of Multiple Kernel Learning (MKL for classification problems. In this paper, we illustrate the utility of applying MKL for the classification of heterogeneous features obtained from UAV data through a case study of an informal settlement in Kigali, Rwanda. Results indicate that MKL can achieve a classification accuracy of 90.6%, a 5.2% increase over a standard single-kernel Support Vector Machine (SVM. A comparison of seven MKL methods indicates that linearly-weighted kernel combinations based on simple heuristics are competitive with respect to computationally-complex, non-linear kernel combination methods. We further underline the importance of utilizing appropriate feature grouping strategies for MKL, which has not been directly addressed in the literature, and we propose a novel, automated feature grouping method that achieves a high classification accuracy for various MKL methods.

  6. Characterisation and final disposal behaviour of theoria-based fuel kernels in aqueous phases

    International Nuclear Information System (INIS)

    Titov, M.

    2005-08-01

    Two high-temperature reactors (AVR and THTR) operated in Germany have produced about 1 million spent fuel elements. The nuclear fuel in these reactors consists mainly of thorium-uranium mixed oxides, but also pure uranium dioxide and carbide fuels were tested. One of the possible solutions of utilising spent HTR fuel is the direct disposal in deep geological formations. Under such circumstances, the properties of fuel kernels, and especially their leaching behaviour in aqueous phases, have to be investigated for safety assessments of the final repository. In the present work, unirradiated ThO 2 , (Th 0.906 ,U 0.094 )O 2 , (Th 0.834 ,U 0.166 )O 2 and UO 2 fuel kernels were investigated. The composition, crystal structure and surface of the kernels were investigated by traditional methods. Furthermore, a new method was developed for testing the mechanical properties of ceramic kernels. The method was successfully used for the examination of mechanical properties of oxide kernels and for monitoring their evolution during contact with aqueous phases. The leaching behaviour of thoria-based oxide kernels and powders was investigated in repository-relevant salt solutions, as well as in artificial leachates. The influence of different experimental parameters on the kernel leaching stability was investigated. It was shown that thoria-based fuel kernels possess high chemical stability and are indifferent to presence of oxidative and radiolytic species in solution. The dissolution rate of thoria-based materials is typically several orders of magnitude lower than of conventional UO 2 fuel kernels. The life time of a single intact (Th,U)O 2 kernel under aggressive conditions of salt repository was estimated as about hundred thousand years. The importance of grain boundary quality on the leaching stability was demonstrated. Numerical Monte Carlo simulations were performed in order to explain the results of leaching experiments. (orig.)

  7. Impact of bran components on the quality of whole wheat bread

    Science.gov (United States)

    Whole grains contain components, such as dietary fiber, starch, fat, antioxidant nutrients, minerals, vitamin, lignans, and phenolic compounds, which are beneficial to human health. Most of the beneficial components are found in the germ and bran as part of a wheat kernel, which are reduced in the ...

  8. Bread Wheat Quality: Some Physical, Chemical and Rheological Characteristics of Syrian and English Bread Wheat Samples

    Directory of Open Access Journals (Sweden)

    Abboud Al-Saleh

    2012-11-01

    Full Text Available The relationships between breadmaking quality, kernel properties (physical and chemical, and dough rheology were investigated using flours from six genotypes of Syrian wheat lines, comprising both commercially grown cultivars and advanced breeding lines. Genotypes were grown in 2008/2009 season in irrigated plots in the Eastern part of Syria. Grain samples were evaluated for vitreousness, test weight, 1000-kernel weight and then milled and tested for protein content, ash, and water content. Dough rheology of the samples was studied by the determination of the mixing time, stability, weakness, resistance and the extensibility of the dough. Loaf baking quality was evaluated by the measurement of the specific weight, resilience and firmness in addition to the sensory analysis. A comparative study between the six Syrian wheat genotypes and two English flour samples was conducted. Significant differences were observed among Syrian genotypes in vitreousness (69.3%–95.0%, 1000-kernel weight (35.2–46.9 g and the test weight (82.2–88.0 kg/hL. All samples exhibited high falling numbers (346 to 417 s for the Syrian samples and 285 and 305 s for the English flours. A significant positive correlation was exhibited between the protein content of the flour and its absorption of water (r = 0.84 **, as well as with the vitreousness of the kernel (r = 0.54 *. Protein content was also correlated with dough stability (r = 0.86 **, extensibility (r = 0.8 **, and negatively correlated with dough weakness (r = −0.69 **. Bread firmness and dough weakness were positively correlated (r = 0.66 **. Sensory analysis indicated Doumah-2 was the best appreciated whilst Doumah 40765 and 46055 were the least appreciated which may suggest their suitability for biscuit preparation rather than bread making.

  9. Bread Wheat Quality: Some Physical, Chemical and Rheological Characteristics of Syrian and English Bread Wheat Samples.

    Science.gov (United States)

    Al-Saleh, Abboud; Brennan, Charles S

    2012-11-22

    The relationships between breadmaking quality, kernel properties (physical and chemical), and dough rheology were investigated using flours from six genotypes of Syrian wheat lines, comprising both commercially grown cultivars and advanced breeding lines. Genotypes were grown in 2008/2009 season in irrigated plots in the Eastern part of Syria. Grain samples were evaluated for vitreousness, test weight, 1000-kernel weight and then milled and tested for protein content, ash, and water content. Dough rheology of the samples was studied by the determination of the mixing time, stability, weakness, resistance and the extensibility of the dough. Loaf baking quality was evaluated by the measurement of the specific weight, resilience and firmness in addition to the sensory analysis. A comparative study between the six Syrian wheat genotypes and two English flour samples was conducted. Significant differences were observed among Syrian genotypes in vitreousness (69.3%-95.0%), 1000-kernel weight (35.2-46.9 g) and the test weight (82.2-88.0 kg/hL). All samples exhibited high falling numbers (346 to 417 s for the Syrian samples and 285 and 305 s for the English flours). A significant positive correlation was exhibited between the protein content of the flour and its absorption of water (r = 0.84 **), as well as with the vitreousness of the kernel (r = 0.54 *). Protein content was also correlated with dough stability (r = 0.86 **), extensibility (r = 0.8 **), and negatively correlated with dough weakness (r = -0.69 **). Bread firmness and dough weakness were positively correlated (r = 0.66 **). Sensory analysis indicated Doumah-2 was the best appreciated whilst Doumah 40765 and 46055 were the least appreciated which may suggest their suitability for biscuit preparation rather than bread making.

  10. Theory of reproducing kernels and applications

    CERN Document Server

    Saitoh, Saburou

    2016-01-01

    This book provides a large extension of the general theory of reproducing kernels published by N. Aronszajn in 1950, with many concrete applications. In Chapter 1, many concrete reproducing kernels are first introduced with detailed information. Chapter 2 presents a general and global theory of reproducing kernels with basic applications in a self-contained way. Many fundamental operations among reproducing kernel Hilbert spaces are dealt with. Chapter 2 is the heart of this book. Chapter 3 is devoted to the Tikhonov regularization using the theory of reproducing kernels with applications to numerical and practical solutions of bounded linear operator equations. In Chapter 4, the numerical real inversion formulas of the Laplace transform are presented by applying the Tikhonov regularization, where the reproducing kernels play a key role in the results. Chapter 5 deals with ordinary differential equations; Chapter 6 includes many concrete results for various fundamental partial differential equations. In Chapt...

  11. Segregation distortion in homozygous lines obtained via anther culture and maize doubled haploid methods in comparison to single seed descent in wheat (Triticum aestivum L.

    Directory of Open Access Journals (Sweden)

    Tadeusz Adamski

    2014-01-01

    Conclusions: Segregation distortion in DH-AC populations was caused by the development of more than one plant of the same genotype from one callus. This distortion was minimized if only one plant per callus was included in the population. Selection of haploid wheat plants before chromosome doubling based on allele-specific markers allows us to choose genotypes that possess desirable Glu-1 alleles and to reduce the number of plants in the next steps of DH production. The SSD technique appeared to be the most advantageous in terms of Mendelian segregation, thus the occurrence of residual heterozygosity can be minimized by continuous selfing beyond the F6 generation.

  12. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří

    2016-02-12

    We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

  13. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří ; Barton, Michael

    2016-01-01

    We investigate the close correspondence between barycentric coordinates and barycentric kernels from the point of view of the limit process when finer and finer polygons converge to a smooth convex domain. We show that any barycentric kernel is the limit of a set of barycentric coordinates and prove that the convergence rate is quadratic. Our convergence analysis extends naturally to barycentric interpolants and mappings induced by barycentric coordinates and kernels. We verify our theoretical convergence results numerically on several examples.

  14. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

    region acquired at two different time points. If change over time does not dominate the scene, the projection of the original two bands onto the second eigenvector will show change over time. In this paper a kernel version of PCA is used to carry out the analysis. Unlike ordinary PCA, kernel PCA...... with a Gaussian kernel successfully finds the change observations in a case where nonlinearities are introduced artificially....

  15. The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice.

    Science.gov (United States)

    Liu, Jie; Huang, Juan; Guo, Huan; Lan, Liu; Wang, Hongze; Xu, Yuancheng; Yang, Xiaohong; Li, Wenqiang; Tong, Hao; Xiao, Yingjie; Pan, Qingchun; Qiao, Feng; Raihan, Mohammad Sharif; Liu, Haijun; Zhang, Xuehai; Yang, Ning; Wang, Xiaqing; Deng, Min; Jin, Minliang; Zhao, Lijun; Luo, Xin; Zhou, Yang; Li, Xiang; Zhan, Wei; Liu, Nannan; Wang, Hong; Chen, Gengshen; Li, Qing; Yan, Jianbing

    2017-10-01

    Maize ( Zea mays ) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice ( Oryza sativa ) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1 , a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis ( Arabidopsis thaliana ) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1 ). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis. © 2017 American Society of Plant Biologists. All Rights Reserved.

  16. Partial Deconvolution with Inaccurate Blur Kernel.

    Science.gov (United States)

    Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei

    2017-10-17

    Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning

  17. Process for producing metal oxide kernels and kernels so obtained

    International Nuclear Information System (INIS)

    Lelievre, Bernard; Feugier, Andre.

    1974-01-01

    The process desbribed is for producing fissile or fertile metal oxide kernels used in the fabrication of fuels for high temperature nuclear reactors. This process consists in adding to an aqueous solution of at least one metallic salt, particularly actinide nitrates, at least one chemical compound capable of releasing ammonia, in dispersing drop by drop the solution thus obtained into a hot organic phase to gel the drops and transform them into solid particles. These particles are then washed, dried and treated to turn them into oxide kernels. The organic phase used for the gel reaction is formed of a mixture composed of two organic liquids, one acting as solvent and the other being a product capable of extracting the anions from the metallic salt of the drop at the time of gelling. Preferably an amine is used as product capable of extracting the anions. Additionally, an alcohol that causes a part dehydration of the drops can be employed as solvent, thus helping to increase the resistance of the particles [fr

  18. Hilbertian kernels and spline functions

    CERN Document Server

    Atteia, M

    1992-01-01

    In this monograph, which is an extensive study of Hilbertian approximation, the emphasis is placed on spline functions theory. The origin of the book was an effort to show that spline theory parallels Hilbertian Kernel theory, not only for splines derived from minimization of a quadratic functional but more generally for splines considered as piecewise functions type. Being as far as possible self-contained, the book may be used as a reference, with information about developments in linear approximation, convex optimization, mechanics and partial differential equations.

  19. Rising Temperatures Reduce Global Wheat Production

    Science.gov (United States)

    Asseng, S.; Ewert, F.; Martre, P.; Rötter, R. P.; Lobell, D. B.; Cammarano, D.; Kimball, B. A.; Ottman, M. J.; Wall, G. W.; White, J. W.; hide

    2015-01-01

    Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32? degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time.

  20. Dense Medium Machine Processing Method for Palm Kernel/ Shell ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Cracked palm kernel is a mixture of kernels, broken shells, dusts and other impurities. In ... machine processing method using dense medium, a separator, a shell collector and a kernel .... efficiency, ease of maintenance and uniformity of.

  1. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge; Schuster, Gerard T.

    2012-01-01

    The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently

  2. The Response of Durum Wheat to the Preceding Crop in a Mediterranean Environment

    Directory of Open Access Journals (Sweden)

    Laura Ercoli

    2014-01-01

    Full Text Available Crop sequence is an important management practice that may affect durum wheat (Triticum durum Desf. production. Field research was conducted in 2007-2008 and 2008-2009 seasons in a rain-fed cold Mediterranean environment to examine the impact of the preceding crops alfalfa (Medicago sativa L., maize (Zea mays L., sunflower (Helianthus annuus L., and bread wheat (Triticum aestivum L. on yield and N uptake of four durum wheat varieties. The response of grain yield of durum wheat to the preceding crop was high in 2007-2008 and was absent in the 2008-2009 season, because of the heavy rainfall that negatively impacted establishment, vegetative growth, and grain yield of durum wheat due to waterlogging. In the first season, durum wheat grain yield was highest following alfalfa, and was 33% lower following wheat. The yield increase of durum wheat following alfalfa was mainly due to an increased number of spikes per unit area and number of kernels per spike, while the yield decrease following wheat was mainly due to a reduction of spike number per unit area. Variety growth habit and performance did not affect the response to preceding crop and varieties ranked in the order Levante > Saragolla = Svevo > Normanno.

  3. Hydration kinetics of some durum and bread wheat varieties grown in south-eastern region of turkey

    International Nuclear Information System (INIS)

    Yildirm, A.

    2017-01-01

    Hydration kinetics of wheat varieties grown in South-Eastern Region of Turkey, covering a temperature range from 25 to 50 degree C was examined. Peleg's model together with Arrhenius relationship were successfully used to evaluate water uptake of some Durum (Local names; Zenit and BurgosBurgos) and Bread (Local names; Dariyel and Karatopak) wheat varieties during soaking at a temperature range of 25-50 degree C. Model was found to be suitable for describing the soaking behaviour of wheat kernels with a coefficient of determination (R2) and Root mean square error (RMSE) greater than 0.9805, and less than 0.051, respectively. The Peleg rate and capacity constants, K1 and K2, were affected by temperature and wheat varieties. Activation energy values of Zenit, BurgosBurgos, Dariyel and Karatopak wheats were found as 39.94, 38.03, 36.25 and 29.54 kJ mol-1, respectively. Zenit wheat was the least hydrated while Karatopak was the most hydrated one due to kernel size and protein content. General equations to describe the water uptake of wheat varieties as a function of soaking time, temperature and initial moisture content were developed. These derived equations can be used for wheat operations such as tempering, mixing, knedding etc. (author)

  4. Ranking Support Vector Machine with Kernel Approximation

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2017-01-01

    Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  5. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

    Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  6. Sentiment classification with interpolated information diffusion kernels

    NARCIS (Netherlands)

    Raaijmakers, S.

    2007-01-01

    Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of

  7. Evolution kernel for the Dirac field

    International Nuclear Information System (INIS)

    Baaquie, B.E.

    1982-06-01

    The evolution kernel for the free Dirac field is calculated using the Wilson lattice fermions. We discuss the difficulties due to which this calculation has not been previously performed in the continuum theory. The continuum limit is taken, and the complete energy eigenfunctions as well as the propagator are then evaluated in a new manner using the kernel. (author)

  8. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  9. Improving the Bandwidth Selection in Kernel Equating

    Science.gov (United States)

    Andersson, Björn; von Davier, Alina A.

    2014-01-01

    We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

  10. Kernel Korner : The Linux keyboard driver

    NARCIS (Netherlands)

    Brouwer, A.E.

    1995-01-01

    Our Kernel Korner series continues with an article describing the Linux keyboard driver. This article is not for "Kernel Hackers" only--in fact, it will be most useful to those who wish to use their own keyboard to its fullest potential, and those who want to write programs to take advantage of the

  11. Multiple kernel SVR based on the MRE for remote sensing water depth fusion detection

    Science.gov (United States)

    Wang, Jinjin; Ma, Yi; Zhang, Jingyu

    2018-03-01

    Remote sensing has an important means of water depth detection in coastal shallow waters and reefs. Support vector regression (SVR) is a machine learning method which is widely used in data regression. In this paper, SVR is used to remote sensing multispectral bathymetry. Aiming at the problem that the single-kernel SVR method has a large error in shallow water depth inversion, the mean relative error (MRE) of different water depth is retrieved as a decision fusion factor with single kernel SVR method, a multi kernel SVR fusion method based on the MRE is put forward. And taking the North Island of the Xisha Islands in China as an experimentation area, the comparison experiments with the single kernel SVR method and the traditional multi-bands bathymetric method are carried out. The results show that: 1) In range of 0 to 25 meters, the mean absolute error(MAE)of the multi kernel SVR fusion method is 1.5m,the MRE is 13.2%; 2) Compared to the 4 single kernel SVR method, the MRE of the fusion method reduced 1.2% (1.9%) 3.4% (1.8%), and compared to traditional multi-bands method, the MRE reduced 1.9%; 3) In 0-5m depth section, compared to the single kernel method and the multi-bands method, the MRE of fusion method reduced 13.5% to 44.4%, and the distribution of points is more concentrated relative to y=x.

  12. Metabolic network prediction through pairwise rational kernels.

    Science.gov (United States)

    Roche-Lima, Abiel; Domaratzki, Michael; Fristensky, Brian

    2014-09-26

    Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to another reaction. Many pathways remain incompletely characterized. One of the major challenges of computational biology is to obtain better models of metabolic pathways. Existing models are dependent on the annotation of the genes. This propagates error accumulation when the pathways are predicted by incorrectly annotated genes. Pairwise classification methods are supervised learning methods used to classify new pair of entities. Some of these classification methods, e.g., Pairwise Support Vector Machines (SVMs), use pairwise kernels. Pairwise kernels describe similarity measures between two pairs of entities. Using pairwise kernels to handle sequence data requires long processing times and large storage. Rational kernels are kernels based on weighted finite-state transducers that represent similarity measures between sequences or automata. They have been effectively used in problems that handle large amount of sequence information such as protein essentiality, natural language processing and machine translations. We create a new family of pairwise kernels using weighted finite-state transducers (called Pairwise Rational Kernel (PRK)) to predict metabolic pathways from a variety of biological data. PRKs take advantage of the simpler representations and faster algorithms of transducers. Because raw sequence data can be used, the predictor model avoids the errors introduced by incorrect gene annotations. We then developed several experiments with PRKs and Pairwise SVM to validate our methods using the metabolic network of Saccharomyces cerevisiae. As a result, when PRKs are used, our method executes faster in comparison with other pairwise kernels. Also, when we use PRKs combined with other simple kernels that include evolutionary information, the accuracy

  13. Natural Variation in Grain Composition of Wheat and Related Cereals

    OpenAIRE

    Shewry, Peter R; Hawkesford, Malcolm J; Piironen, Vieno; Lampi, Anna-Maija; Gebruers, Kurt; Boros, Danuta; Andersson, Annica AM; Åman, Per; Rakszegi, Mariann; Bedo, Zoltan; Ward, Jane L

    2013-01-01

    The wheat grain comprises three groups of major components, starch, protein, and cell wall polysaccharides (dietary fiber), and a range of minor components that may confer benefits to human health. Detailed analyses of dietary fiber and other bioactive components were carried out under the EU FP6 HEALTHGRAIN program on 150 bread wheat lines grown on a single site, 50 lines of other wheat species and other cereals grown on the same site, and 23−26 bread wheat lines grown in six environments. P...

  14. Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

    Directory of Open Access Journals (Sweden)

    Chunmei Liu

    2016-01-01

    Full Text Available This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour.

  15. Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

    Science.gov (United States)

    2016-01-01

    This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

  16. GWAS for plant growth stages and yield components in spring wheat (Triticum aestivum L.) harvested in three regions of Kazakhstan.

    Science.gov (United States)

    Turuspekov, Yerlan; Baibulatova, Aida; Yermekbayev, Kanat; Tokhetova, Laura; Chudinov, Vladimir; Sereda, Grigoriy; Ganal, Martin; Griffiths, Simon; Abugalieva, Saule

    2017-11-14

    Spring wheat is the largest agricultural crop grown in Kazakhstan with an annual sowing area of 12 million hectares in 2016. Annually, the country harvests around 15 million tons of high quality grain. Despite environmental stress factors it is predicted that the use of new technologies may lead to increases in productivity from current levels of 1.5 to up to 3 tons per hectare. One way of improving wheat productivity is by the application of new genomic oriented approaches in plant breeding projects. Genome wide association studies (GWAS) are emerging as powerful tools for the understanding of the inheritance of complex traits via utilization of high throughput genotyping technologies and phenotypic assessments of plant collections. In this study, phenotyping and genotyping data on 194 spring wheat accessions from Kazakhstan, Russia, Europe, and CIMMYT were assessed for the identification of marker-trait associations (MTA) of agronomic traits by using GWAS. Field trials in Northern, Central and Southern regions of Kazakhstan using 194 spring wheat accessions revealed strong correlations of yield with booting date, plant height, biomass, number of spikes per plant, and number of kernels per spike. The accessions from Europe and CIMMYT showed high breeding potential for Southern and Central regions of the country in comparison with the performance of the local varieties. The GGE biplot method, using average yield per plant, suggested a clear separation of accessions into their three breeding origins in relationship to the three environments in which they were evaluated. The genetic variation in the three groups of accessions was further studied using 3245 polymorphic SNP (single nucleotide polymorphism) markers. The application of Principal Coordinate analysis clearly grouped the 194 accessions into three clades according to their breeding origins. GWAS on data from nine field trials allowed the identification of 114 MTAs for 12 different agronomic traits. Field

  17. Starch facilitates enzymatic wheat gluten hydrolysis

    NARCIS (Netherlands)

    Hardt, N.A.; Boom, R.M.; Goot, van der A.J.

    2015-01-01

    Wheat gluten can be hydrolyzed by either using (vital) wheat gluten or directly from wheat flour. This study investigates the influence of the presence of starch, the main component of wheat, on enzymatic wheat gluten hydrolysis. Wheat gluten present in wheat flour (WFG) and vital wheat gluten (VWG)

  18. Evidence of isolate-specificity in non-hypersensitive resistance in spring wheat (Triticum aestivum) to wheat leaf rust

    NARCIS (Netherlands)

    Qamar, Maqsood; Niks, R.E.

    2007-01-01

    Isolate-specific aspect of non-hypersensitive resistance in wheat to wheat leaf rust was studied at seedling stage in the green house. Isolate-specific response of non-hypersensitive resistance was assessed from latency period (LP) and infection frequency (IF) of two single-pustule isolates of

  19. Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

    Science.gov (United States)

    Karmeshu; Gupta, Varun; Kadambari, K V

    2011-06-01

    A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

  20. Bayesian Kernel Mixtures for Counts.

    Science.gov (United States)

    Canale, Antonio; Dunson, David B

    2011-12-01

    Although Bayesian nonparametric mixture models for continuous data are well developed, there is a limited literature on related approaches for count data. A common strategy is to use a mixture of Poissons, which unfortunately is quite restrictive in not accounting for distributions having variance less than the mean. Other approaches include mixing multinomials, which requires finite support, and using a Dirichlet process prior with a Poisson base measure, which does not allow smooth deviations from the Poisson. As a broad class of alternative models, we propose to use nonparametric mixtures of rounded continuous kernels. An efficient Gibbs sampler is developed for posterior computation, and a simulation study is performed to assess performance. Focusing on the rounded Gaussian case, we generalize the modeling framework to account for multivariate count data, joint modeling with continuous and categorical variables, and other complications. The methods are illustrated through applications to a developmental toxicity study and marketing data. This article has supplementary material online.

  1. Putting Priors in Mixture Density Mercer Kernels

    Science.gov (United States)

    Srivastava, Ashok N.; Schumann, Johann; Fischer, Bernd

    2004-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. We describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using predefined kernels. These data adaptive kernels can en- code prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS). The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains template for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic- algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code. The results show that the Mixture Density Mercer-Kernel described here outperforms tree-based classification in distinguishing high-redshift galaxies from low- redshift galaxies by approximately 16% on test data, bagged trees by approximately 7%, and bagged trees built on a much larger sample of data by approximately 2%.

  2. Anisotropic hydrodynamics with a scalar collisional kernel

    Science.gov (United States)

    Almaalol, Dekrayat; Strickland, Michael

    2018-04-01

    Prior studies of nonequilibrium dynamics using anisotropic hydrodynamics have used the relativistic Anderson-Witting scattering kernel or some variant thereof. In this paper, we make the first study of the impact of using a more realistic scattering kernel. For this purpose, we consider a conformal system undergoing transversally homogenous and boost-invariant Bjorken expansion and take the collisional kernel to be given by the leading order 2 ↔2 scattering kernel in scalar λ ϕ4 . We consider both classical and quantum statistics to assess the impact of Bose enhancement on the dynamics. We also determine the anisotropic nonequilibrium attractor of a system subject to this collisional kernel. We find that, when the near-equilibrium relaxation-times in the Anderson-Witting and scalar collisional kernels are matched, the scalar kernel results in a higher degree of momentum-space anisotropy during the system's evolution, given the same initial conditions. Additionally, we find that taking into account Bose enhancement further increases the dynamically generated momentum-space anisotropy.

  3. A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

    KAUST Repository

    Rosen, Paul

    2013-06-01

    We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

  4. A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

    KAUST Repository

    Rosen, Paul

    2013-01-01

    We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

  5. Wheat biotechnology: A minireview

    OpenAIRE

    Patnaik, Debasis; Khurana, Paramjit

    2001-01-01

    Due to the inherent difficulties associated with gene delivery into regenerable explants and recovery of plantlets with the introduced transgene, wheat was the last among cereals to be genetically transformed. This review attempts to summarize different efforts in the direction of achieving genetic transformation of wheat by various methods. Particle bombardment is the most widely employed procedure for the introduction of marker genes and also for the generation of transformed wheat with int...

  6. Optimizing memory-bound SYMV kernel on GPU hardware accelerators

    KAUST Repository

    Abdelfattah, Ahmad

    2013-01-01

    Hardware accelerators are becoming ubiquitous high performance scientific computing. They are capable of delivering an unprecedented level of concurrent execution contexts. High-level programming language extensions (e.g., CUDA), profiling tools (e.g., PAPI-CUDA, CUDA Profiler) are paramount to improve productivity, while effectively exploiting the underlying hardware. We present an optimized numerical kernel for computing the symmetric matrix-vector product on nVidia Fermi GPUs. Due to its inherent memory-bound nature, this kernel is very critical in the tridiagonalization of a symmetric dense matrix, which is a preprocessing step to calculate the eigenpairs. Using a novel design to address the irregular memory accesses by hiding latency and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double precision arithmetics, respectively. © 2013 Springer-Verlag.

  7. The use of near infrared transmittance kernel sorting technology to salvage high quality grain from grain downgraded due to Fusarium damage

    Directory of Open Access Journals (Sweden)

    Michael E. Kautzman

    2015-03-01

    Full Text Available The mycotoxins associated with specific Fusarium fungal infections of grains are a threat to global food and feed security. These fungal infestations are referred to as Fusarium Head Blight (FHB and lead to Fusarium Damaged Kernels (FDK. Incidence of FDK >0.25% will lower the grade, with a tolerance of 5% FDK for export feed grain. During infestation, the fungi can produce a variety of mycotoxins, the most common being deoxynivalenol (DON. Fusarium Damaged Kernels have been associated with reduced crude protein (CP, lowering nutritional, functional and grade value. New technology has been developed using Near Infrared Transmittance (NIT spectra that estimate CP of individual kernels of wheat, barley and durum. Our objective is to evaluate the technology's capability to reduce FDK and DON of downgraded wheat and ability to salvage high quality safe kernels. In five FDK downgraded sources of wheat, the lowest 20% CP kernels had significantly increased FDK and DON with the high CP fractions having decreased FDK and DON, thousand kernel weights (TKW and bushel weight (Bu. Strong positive correlations were observed between FDK and DON (r = 0.90; FDK and grade (r = 0.62 and DON and grade (r = 0.62. Negative correlations were observed between FDK and DON with CP (r = −0.27 and −0.32; TKW (r = −0.45 and −0.54 and Bu (r = −0.79 and −0.74. Results show improved quality and value of Fusarium downgraded grain using this technology.

  8. Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

    African Journals Online (AJOL)

    In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...

  9. NLO corrections to the Kernel of the BKP-equations

    Energy Technology Data Exchange (ETDEWEB)

    Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fadin, V.S. [Budker Institute of Nuclear Physics, Novosibirsk (Russian Federation); Novosibirskij Gosudarstvennyj Univ., Novosibirsk (Russian Federation); Lipatov, L.N. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg (Russian Federation); Vacca, G.P. [INFN, Sezione di Bologna (Italy)

    2012-10-02

    We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3{yields}3 kernel, computed in the tree approximation.

  10. Adaptive Kernel in Meshsize Boosting Algorithm in KDE ...

    African Journals Online (AJOL)

    This paper proposes the use of adaptive kernel in a meshsize boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

  11. Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...

    African Journals Online (AJOL)

    This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

  12. Kernel maximum autocorrelation factor and minimum noise fraction transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...

  13. 7 CFR 51.1441 - Half-kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Half-kernel. 51.1441 Section 51.1441 Agriculture... Standards for Grades of Shelled Pecans Definitions § 51.1441 Half-kernel. Half-kernel means one of the separated halves of an entire pecan kernel with not more than one-eighth of its original volume missing...

  14. 7 CFR 51.2296 - Three-fourths half kernel.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...

  15. 7 CFR 981.401 - Adjusted kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Adjusted kernel weight. 981.401 Section 981.401... Administrative Rules and Regulations § 981.401 Adjusted kernel weight. (a) Definition. Adjusted kernel weight... kernels in excess of five percent; less shells, if applicable; less processing loss of one percent for...

  16. 7 CFR 51.1403 - Kernel color classification.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

  17. The Linux kernel as flexible product-line architecture

    NARCIS (Netherlands)

    M. de Jonge (Merijn)

    2002-01-01

    textabstractThe Linux kernel source tree is huge ($>$ 125 MB) and inflexible (because it is difficult to add new kernel components). We propose to make this architecture more flexible by assembling kernel source trees dynamically from individual kernel components. Users then, can select what

  18. IDENTIFICATION AND MAPPING OF A GENE FOR RICE SLENDER KERNEL USING Oryza glumaepatula INTROGRESSION LINES

    Directory of Open Access Journals (Sweden)

    Sobrizal Sobrizal

    2016-10-01

    Full Text Available World demand for superior rice grain quality tends to increase. One of the  criteria of appearance quality of rice grain is grain shape. Rice consumers  exhibit wide preferences for grain shape, but most Indonesian rice consumers prefer long and slender grain. The objectives of this study were to identify and map a gene for rice slender kernel trait using Oryza  glumaepatula introgression lines with O. sativa cv. Taichung 65 genetic background. A segregation analysis of BC4F2 population derived from backcrosses of a donor parent O. glumaepatula into a recurrent parent Taichung 65 showed that the slender kernel was controlled by a single recessive gene. This new identified gene was designated as sk1 (slender kernel 1. Moreover, based on the RFLP analyses using 14 RFLP markers located on chromosomes 2, 8, 9, and 10 in which the O. glumaepatula chromosomal segments were retained in BC4F2 population, the sk1 was located between RFLP markers C679 and C560 on the long arm of chromosome 2, with map distances of 2.8 and 1.5 cM, respectively. The wild rice O. glumaepatula carried a recessive allele for slender kernel. This allele may be useful in breeding of rice with slender kernel types. In addition, the development of plant materials and RFLP map associated with slender kernel in this study is the preliminary works in the effort to isolate this important grain shape gene.

  19. SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement

    International Nuclear Information System (INIS)

    Chamberlain, S; French, S; Nazareth, D

    2016-01-01

    Purpose: Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method. Methods: A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3 × 10"6 to 3 × 10"7); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 10"6 was established as the lower range because it provided the minimal accuracy level. Results: As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single-processor run, to 0.30 hours for the 100-processor run. Conclusion: Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 10"6 have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.

  20. Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

    Directory of Open Access Journals (Sweden)

    Peter S. Kristensen

    2018-02-01

    Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

  1. Digital signal processing with kernel methods

    CERN Document Server

    Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

    2018-01-01

    A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

  2. Parsimonious Wavelet Kernel Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Wang Qin

    2015-11-01

    Full Text Available In this study, a parsimonious scheme for wavelet kernel extreme learning machine (named PWKELM was introduced by combining wavelet theory and a parsimonious algorithm into kernel extreme learning machine (KELM. In the wavelet analysis, bases that were localized in time and frequency to represent various signals effectively were used. Wavelet kernel extreme learning machine (WELM maximized its capability to capture the essential features in “frequency-rich” signals. The proposed parsimonious algorithm also incorporated significant wavelet kernel functions via iteration in virtue of Householder matrix, thus producing a sparse solution that eased the computational burden and improved numerical stability. The experimental results achieved from the synthetic dataset and a gas furnace instance demonstrated that the proposed PWKELM is efficient and feasible in terms of improving generalization accuracy and real time performance.

  3. Ensemble Approach to Building Mercer Kernels

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive...

  4. Control Transfer in Operating System Kernels

    Science.gov (United States)

    1994-05-13

    microkernel system that runs less code in the kernel address space. To realize the performance benefit of allocating stacks in unmapped kseg0 memory, the...review how I modified the Mach 3.0 kernel to use continuations. Because of Mach’s message-passing microkernel structure, interprocess communication was...critical control transfer paths, deeply- nested call chains are undesirable in any case because of the function call overhead. 4.1.3 Microkernel Operating

  5. Heterosis for yield and its components in bread wheat crosses among powdery mildew resistant and susceptible genotypes

    International Nuclear Information System (INIS)

    Ilker, E.; Tonk, F.A.; Tosun, M.

    2010-01-01

    The objective of this research was to investigate heterotic effects between five powdery mildew resistant wheat lines derived from CIMMYT and three susceptible commercial wheat varieties growing in Turkey and to determine mode of gene actions of the parents for yield characters in F1 generation. All 15 F1 crosses and their parents were planted in randomized complete block design in three replications. Measurements were done for plant height, pike length, spike let and kernel number per spike, grain weight per spike and 1000-kernel weight. Promising findings of the crosses 72 x Golia, 70 x Golia, 70 x Basribey, 48 x Basribey, 48 x Atilla-12 and 72 x Atilla12 were obtained to breed new varieties or pure lines having shorter plant height and taller spike length, more number of spike let and kernel per spike, besides higher grain yield than their mid or better parents to improve powdery mildew resistant varieties. (author)

  6. Genetic variability, path-coefficient and correlation studies in twenty elite bread-wheat (triticum aestivum L.) lines

    International Nuclear Information System (INIS)

    Mujahid, M.Y.; Asif, M.; Ahmad, I.; Kisana, N.A.; Ahmad, Z.; Asim, M.

    2005-01-01

    Twenty bread-wheat elite lines of diverse origin, developed by various research institutes in the country, were tested and evaluated at National Agricultural Research Centre (NARC) under optimum irrigated conditions. Significant variation was observed for all the traits studied viz: days to heading, days to maturity, kernel weight, test weight and grain yield. Genotypic and phenotypic correlations were computed and the direct and indirect contributions of each trait towards grain-yield were determined. Grain-yield showed significant association with test weight and kernel weight. Direct positive effects of kernel weight and test weight towards grain-yield suggest the effectiveness of these traits to select and identify the desirable wheat- genotypes for a target environment. (author)

  7. Mutation induction in durum wheat

    International Nuclear Information System (INIS)

    Senay, A.; Sekerci, S.

    2009-01-01

    The aim of this research was to determine the separate and combine effects of different doses of gamma rays and EMS concentrations on some characteristics of M1 plants of durum wheat, cv. Kunduru 1149. The seeds of durum wheat, cv. Kunduru 1149 which were irradiated with 50 Gy, 150 Gy and 250 Gy gamma rays and/or treated EMS for 6 hours at 30 C in 0,2 % and 0,4 % concentrated. According to the results of this research; separate and combine treatments of different doses of gamma rays and EMS have shown significant difference all of the observed traits at M1 plants of durum wheat cv. Kunduru 1149. The negative effects of increasing doses of mutagens on all plant characteristics for M1 plants were found statistically significant. Combined treatments were found to be more efficient than the sum of effects of the single treatments. In followed generation 3 mutant lines were selected according to plant height, spike height, number of seed, leaf relative water lost, and some quality traits. In M6 generation 3 desirable lines have been sown for preliminary field yield tests.

  8. Uranium kernel formation via internal gelation

    International Nuclear Information System (INIS)

    Hunt, R.D.; Collins, J.L.

    2004-01-01

    In the 1970s and 1980s, U.S. Department of Energy (DOE) conducted numerous studies on the fabrication of nuclear fuel particles using the internal gelation process. These amorphous kernels were prone to flaking or breaking when gases tried to escape from the kernels during calcination and sintering. These earlier kernels would not meet today's proposed specifications for reactor fuel. In the interim, the internal gelation process has been used to create hydrous metal oxide microspheres for the treatment of nuclear waste. With the renewed interest in advanced nuclear fuel by the DOE, the lessons learned from the nuclear waste studies were recently applied to the fabrication of uranium kernels, which will become tri-isotropic (TRISO) fuel particles. These process improvements included equipment modifications, small changes to the feed formulations, and a new temperature profile for the calcination and sintering. The modifications to the laboratory-scale equipment and its operation as well as small changes to the feed composition increased the product yield from 60% to 80%-99%. The new kernels were substantially less glassy, and no evidence of flaking was found. Finally, key process parameters were identified, and their effects on the uranium microspheres and kernels are discussed. (orig.)

  9. Quantum tomography, phase-space observables and generalized Markov kernels

    International Nuclear Information System (INIS)

    Pellonpaeae, Juha-Pekka

    2009-01-01

    We construct a generalized Markov kernel which transforms the observable associated with the homodyne tomography into a covariant phase-space observable with a regular kernel state. Illustrative examples are given in the cases of a 'Schroedinger cat' kernel state and the Cahill-Glauber s-parametrized distributions. Also we consider an example of a kernel state when the generalized Markov kernel cannot be constructed.

  10. Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.

    Directory of Open Access Journals (Sweden)

    Silvano O Assanga

    Full Text Available Stable quantitative trait loci (QTL are important for deployment in marker assisted selection in wheat (Triticum aestivum L. and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading and yield related traits (test weight, thousand kernel weight, harvest index. The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1

  11. Penetuan Bilangan Iodin pada Hydrogenated Palm Kernel Oil (HPKO) dan Refined Bleached Deodorized Palm Kernel Oil (RBDPKO)

    OpenAIRE

    Sitompul, Monica Angelina

    2015-01-01

    Have been conducted Determination of Iodin Value by method titration to some Hydrogenated Palm Kernel Oil (HPKO) and Refined Bleached Deodorized Palm Kernel Oil (RBDPKO). The result of analysis obtained the Iodin Value in Hydrogenated Palm Kernel Oil (A) = 0,16 gr I2/100gr, Hydrogenated Palm Kernel Oil (B) = 0,20 gr I2/100gr, Hydrogenated Palm Kernel Oil (C) = 0,24 gr I2/100gr. And in Refined Bleached Deodorized Palm Kernel Oil (A) = 17,51 gr I2/100gr, Refined Bleached Deodorized Palm Kernel ...

  12. Colonisation of winter wheat grain by Fusarium spp. and mycotoxin content as dependent on a wheat variety, crop rotation, a crop management system and weather conditions.

    Science.gov (United States)

    Czaban, Janusz; Wróblewska, Barbara; Sułek, Alicja; Mikos, Marzena; Boguszewska, Edyta; Podolska, Grażyna; Nieróbca, Anna

    2015-01-01

    Field experiments were conducted during three consecutive growing seasons (2007/08, 2008/09 and 2009/10) with four winter wheat (Triticum aestivum L.) cultivars - 'Bogatka', 'Kris', 'Satyna' and 'Tonacja' - grown on fields with a three-field crop rotation (winter triticale, spring barley, winter wheat) and in a four-field crop rotation experiment (spring wheat, spring cereals, winter rapeseed, winter wheat). After the harvest, kernels were surface disinfected with 2% NaOCl and then analysed for the internal infection by different species of Fusarium. Fusaria were isolated on Czapek-Dox iprodione dichloran agar medium and identified on the basis of macro- and micro-morphology on potato dextrose agar and synthetic nutrient agar media. The total wheat grain infection by Fusarium depended mainly on relative humidity (RH) and a rainfall during the flowering stage. Intensive rainfall and high RH in 2009 and 2010 in the period meant the proportions of infected kernels by the fungi were much higher than those in 2008 (lack of precipitation during anthesis). Weather conditions during the post-anthesis period changed the species composition of Fusarium communities internally colonising winter wheat grain. The cultivars significantly varied in the proportion of infected kernels by Fusarium spp. The growing season and type of crop rotation had a distinct effect on species composition of Fusarium communities colonising the grain inside. A trend of a higher percentage of the colonised kernels by the fungi in the grain from the systems using more fertilisers and pesticides as well as the buried straw could be perceived. The most frequent species in the grain were F. avenaceum, F. tricinctum and F. poae in 2008, and F. avenaceum, F. graminearum, F. tricinctum and F. poae in 2009 and 2010. The contents of deoxynivalenol and zearalenon in the grain were correlated with the percentage of kernels colonised by F. graminearum and were the highest in 2009 in the grain from the four

  13. 21 CFR 137.195 - Crushed wheat.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Crushed wheat. 137.195 Section 137.195 Food and... Related Products § 137.195 Crushed wheat. Crushed wheat, coarse ground wheat, is the food prepared by so crushing cleaned wheat other than durum wheat and red durum wheat that, when tested by the method...

  14. The pangenome of hexaploid bread wheat

    Czech Academy of Sciences Publication Activity Database

    Montenegro, J. D.; Golicz, A. A.; Bayer, P.E.; Hurgobin, B.; Lee, H. T.; Chan, C. K. K.; Visendi, P.; Lai, K.; Doležel, Jaroslav; Batley, J.; Edwards, D.

    2017-01-01

    Roč. 90, č. 5 (2017), s. 1007-1013 ISSN 0960-7412 R&D Projects: GA MŠk(CZ) LO1204 Institutional support: RVO:61389030 Keywords : database * diversity * genome * pangenome * single nucleotide polymorphisms * Triticum aestivum * wheat Subject RIV: EB - Genetics ; Molecular Biology OBOR OECD: Plant sciences, botany Impact factor: 5.901, year: 2016

  15. QTLs associated with agronomic traits in the Attila × CDC Go spring wheat population evaluated under conventional management.

    Directory of Open Access Journals (Sweden)

    Jun Zou

    Full Text Available Recently, we investigated the effect of the wheat 90K single nucleotide polymorphic (SNP array and three gene-specific (Ppd-D1, Vrn-A1 and Rht-B1 markers on quantitative trait loci (QTL detection in a recombinant inbred lines (RILs population derived from a cross between two spring wheat (Triticum aestivum L. cultivars, 'Attila' and 'CDC Go', and evaluated for eight agronomic traits at three environments under organic management. The objectives of the present study were to investigate the effect of conventional management on QTL detection in the same mapping population using the same set of markers as the organic management and compare the results with organic management. Here, we evaluated 167 RILs for number of tillers (tillering, flowering time, maturity, plant height, test weight (grain volume weight, 1000 kernel weight, grain yield, and grain protein content at seven conventionally managed environments from 2008 to 2014. Using inclusive composite interval mapping (ICIM on phenotypic data averaged across seven environments and a subset of 1203 informative markers (1200 SNPs and 3 gene specific markers, we identified a total of 14 QTLs associated with flowering time (1, maturity (2, plant height (1, grain yield (1, test weight (2, kernel weight (4, tillering (1 and grain protein content (2. Each QTL individually explained from 6.1 to 18.4% of the phenotypic variance. Overall, the QTLs associated with each trait explained from 9.7 to 35.4% of the phenotypic and from 22.1 to 90.8% of the genetic variance. Three chromosomal regions on chromosomes 2D (61-66 cM, 4B (80-82 cM and 5A (296-297 cM harbored clusters of QTLs associated with two to three traits. The coincidental region on chromosome 5A harbored QTL clusters for both flowering and maturity time, and mapped about 2 cM proximal to the Vrn-A1 gene, which was in high linkage disequilibrium (0.70 ≤ r2 ≤ 0.75 with SNP markers that mapped within the QTL confidence interval. Six of the 14

  16. TaGW2, a Good Reflection of Wheat Polyploidization and Evolution.

    Science.gov (United States)

    Qin, Lin; Zhao, Junjie; Li, Tian; Hou, Jian; Zhang, Xueyong; Hao, Chenyang

    2017-01-01

    Hexaploid wheat consists of three subgenomes, namely, A, B, and D. These well-characterized ancestral genomes also exist at the diploid and tetraploid levels, thereby rendering wheat as a good model species for studying polyploidization. Here, we performed intra- and inter-species comparative analyses of wheat and its relatives to dissect polymorphism and differentiation of the TaGW2 genes. Our results showed that genetic diversity of TaGW2 decreased with progression from the diploids to tetraploids and hexaploids. The strongest selection occurred in the promoter regions of TaGW2-6A and TaGW2-6B . Phylogenetic trees clearly indicated that Triticum urartu and Ae. speltoides were the donors of the A and B genomes in tetraploid and hexaploid wheats. Haplotypes detected among hexaploid genotypes traced back to the tetraploid level. Fst and π values revealed that the strongest selection on TaGW2 occurred at the tetraploid level rather than in hexaploid wheat. This infers that grain size enlargement, especially increased kernel width, mainly occurred in tetraploid genotypes. In addition, relative expression levels of TaGW2s significantly declined from the diploid level to tetraploids and hexaploids, further indicating that these genes negatively regulate kernel size. Our results also revealed that the polyploidization events possibly caused much stronger differentiation than domestication and breeding.

  17. Agronomic traits and deoxynivalenol contamination of two tetraploid wheat species (Triticum turgidum spp. durum, Triticum turgidum spp. turanicum grown strictly under low input conditions

    Directory of Open Access Journals (Sweden)

    Giovanni Dinelli

    2014-09-01

    Full Text Available An evaluation of the agronomic performance of two tetraploid wheat varieties (Triticum turgidum spp. durum, Claudio; Triticum turgidum spp. turanicum, Kamut® grown strictly under low input conditions was carried out over three consecutive cropping years. The study reported grain yield values ranging from 1.8 to 2.6 t ha-1. Productivity showed to be primarily affected by environmental conditions, while no differences were observed between the two genotypes. The study of the yield components highlighted that the durum wheat variety had a higher plant density than Kamut®, but this discrepancy was offset by a greater number of kernels per spike and the kernel weight of khorasan wheat. The investigated wheat genotypes were also analysed to assess the mycotoxin (DON levels of wholegrain semolina and the efficiency of cleaning treatments to reduce contamination. Results showed that both wheat varieties had a good hygienic and sanitary quality with a DON content ranging from 0.35 to 1.31 mg kg-1, which was lower than the maximum acceptable level set by the European regulation at 1.75 mg kg-1. In addition, our research work investigated the effects of premilling cleaning procedures, such as water washing and brushing, on mycotoxin levels, which yielded interesting results in terms of decontamination efficiency. These methods were particularly efficient with Kamut® semolina (46-93% DON reduction, suggesting that mycotoxins accumulate in this variety at more superficial levels than in the durum wheat variety. On the whole, our study provided additional knowledge on the traits to be further improved to respond to low input requirements and to enhance the potential adaptability of wheat genotypes to organic agriculture. Our results emphasized the need to develop wheat varieties that can provide adequate performance without high levels of nitrogen inputs by selecting specific traits, such as kernel weight, spike length and kernel/spike. This may help

  18. The pangenome of hexaploid bread wheat.

    Science.gov (United States)

    Montenegro, Juan D; Golicz, Agnieszka A; Bayer, Philipp E; Hurgobin, Bhavna; Lee, HueyTyng; Chan, Chon-Kit Kenneth; Visendi, Paul; Lai, Kaitao; Doležel, Jaroslav; Batley, Jacqueline; Edwards, David

    2017-06-01

    There is an increasing understanding that variation in gene presence-absence plays an important role in the heritability of agronomic traits; however, there have been relatively few studies on variation in gene presence-absence in crop species. Hexaploid wheat is one of the most important food crops in the world and intensive breeding has reduced the genetic diversity of elite cultivars. Major efforts have produced draft genome assemblies for the cultivar Chinese Spring, but it is unknown how well this represents the genome diversity found in current modern elite cultivars. In this study we build an improved reference for Chinese Spring and explore gene diversity across 18 wheat cultivars. We predict a pangenome size of 140 500 ± 102 genes, a core genome of 81 070 ± 1631 genes and an average of 128 656 genes in each cultivar. Functional annotation of the variable gene set suggests that it is enriched for genes that may be associated with important agronomic traits. In addition to variation in gene presence, more than 36 million intervarietal single nucleotide polymorphisms were identified across the pangenome. This study of the wheat pangenome provides insight into genome diversity in elite wheat as a basis for genomics-based improvement of this important crop. A wheat pangenome, GBrowse, is available at http://appliedbioinformatics.com.au/cgi-bin/gb2/gbrowse/WheatPan/, and data are available to download from http://wheatgenome.info/wheat_genome_databases.php. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  19. Exact Heat Kernel on a Hypersphere and Its Applications in Kernel SVM

    Directory of Open Access Journals (Sweden)

    Chenchao Zhao

    2018-01-01

    Full Text Available Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by Lafferty and Lebanon [1], demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.

  20. Development of new iraqi wheat varieties induced by gamma rays

    International Nuclear Information System (INIS)

    Ibrahim, I.F.; Al-Janabi, K.K.; Al-Maaroof, E.M.; Al-Aubaidi, M.O.; Mahmoud, A.H.; Al-Janabi, A.A.

    1991-01-01

    The aim of the present investigation is to study agronomic traits of three wheat mutants induced by gamma rays and compared with their origin 'Saber Beg' during M 8 - M 11 generations. These mutants showed a moderate resistance to leaf rust and lodging, while the origin was susceptible. Also, these mutants surpassed their origin in seed weight of 100 spikes, weight of 1000 kernels and protein yield per unit area. Chemical and physical analyses of mutant flours indicated that it could be used for bread making successfully.2 fig.,4 tab

  1. OP-16 DIETARY INTERVENTION USING THE LOW FODMAP DIET VERSUS THE "MILK, EGG, WHEAT AND SOYA FREE" DIET FOR TREATMENT OF FUNCTIONAL GUT DISORDERS A SINGLE CENTRE EXPERIENCE.

    Science.gov (United States)

    Keetarut, K; Kiparissi, F; McCartney, S; Murray, C

    2015-10-01

    The adolescent clinic is a tertiary referral clinic including patients with a wide variety of complex gastroenterology conditions predominantly tertiary referrals fromGreat Ormond Street Hospital transition clinic. To assess the benefit of the low FODMAP diet versus the "Milk, egg, wheat and soya" (MEWS) free diet for symptom control in patients with functional gut disorders and/or food allergy from June 2013 to June 2015. A total of 436 patients were seen during this time period for dietetic advice and the age range varied from 13-21 years old with 43terms of diagnosis used. These included the broad categories of inflammatory bowel disease, food allergy, functional gut conditions, congenital gut disorders, autoimmune disorders and oncology conditions. For functional gut disorders/food allergy there were 14 terms used which varied from "Functional gut disorder" to "Irritable bowel syndrome" and also included patients with delayed gastric emptying. For patients with food allergy the terms "multiple food allergy" or EosinophilicOesophagitis or Colitis were used. A total of 40 patients with functional gut disorders were referred for the MEWS or low FODMAP diet. The efficacy of the diet was measured using a symptom scale pre and post dietary intervention assessing if patients symptoms changed from nil/mild/moderate tosignificant. The results indicate whether the presenting predominant symptom e.g., bloating, constipation or abdominal pain improved following the dietary intervention. A total of 29 patients were seen for the "MEWS" free diet.These were 17 functional, 3 food allergy, 6 IBS, 2 EosinophilicOesophagitis, 1 oncology patient. The age ranged from 14 to 21 and average ageat treatment was 16.6 years old with 11 males and 18 females. 13 patients were referred for the low FODMAP diet. The patients referred for the low FODMAP diet were 7 with a functional gut disorder, 5Irritable Bowel Syndrome and1 EosinophilicColitis.The age range was 14 to 19 years old with

  2. Aflatoxin contamination of developing corn kernels.

    Science.gov (United States)

    Amer, M A

    2005-01-01

    Preharvest of corn and its contamination with aflatoxin is a serious problem. Some environmental and cultural factors responsible for infection and subsequent aflatoxin production were investigated in this study. Stage of growth and location of kernels on corn ears were found to be one of the important factors in the process of kernel infection with A. flavus & A. parasiticus. The results showed positive correlation between the stage of growth and kernel infection. Treatment of corn with aflatoxin reduced germination, protein and total nitrogen contents. Total and reducing soluble sugar was increase in corn kernels as response to infection. Sucrose and protein content were reduced in case of both pathogens. Shoot system length, seeding fresh weigh and seedling dry weigh was also affected. Both pathogens induced reduction of starch content. Healthy corn seedlings treated with aflatoxin solution were badly affected. Their leaves became yellow then, turned brown with further incubation. Moreover, their total chlorophyll and protein contents showed pronounced decrease. On the other hand, total phenolic compounds were increased. Histopathological studies indicated that A. flavus & A. parasiticus could colonize corn silks and invade developing kernels. Germination of A. flavus spores was occurred and hyphae spread rapidly across the silk, producing extensive growth and lateral branching. Conidiophores and conidia had formed in and on the corn silk. Temperature and relative humidity greatly influenced the growth of A. flavus & A. parasiticus and aflatoxin production.

  3. Genetic Variation and Biological Control of Fusarium graminearum Isolated from Wheat in Assiut-Egypt

    Directory of Open Access Journals (Sweden)

    Amer F. Mahmoud

    2016-04-01

    Full Text Available Fusarium graminearum Schwabe causes Fusarium head blight (FHB, a devastating disease that leads to extensive yield and quality loss of wheat and other cereal crops. Twelve isolates of F. graminearum were collected from naturally infected spikes of wheat from Assiut Egypt. These isolates were compared using SRAP. The results indicated distinct genetic groups exist within F. graminearum, and demonstrated that these groups have different biological properties, especially with respect to their pathogenicity on wheat. There were biologically significant differences between the groups; with group (B isolates being more aggressive towards wheat than groups (A and (C. Furthermore, Trichoderma harzianum (Rifai and Bacillus subtilis (Ehrenberg which isolated from wheat kernels were screened for antagonistic activity against F. graminearum. They significantly reduced the growth of F. graminearum colonies in culture. In order to gain insight into biological control effect in situ, highly antagonistic isolates of T. harzianum and B. subtilis were selected, based on their in vitro effectiveness, for greenhouse test. It was revealed that T. harzianum and B. subtilis significantly reduced FHB severity. The obtained results indicated that T. harzianum and B. subtilis are very effective biocontrol agents that offer potential benefit in FHB and should be harnessed for further biocontrol applications. The accurate analysis of genetic variation and studies of population structures have significant implications for understanding the genetic traits and disease control programs in wheat. This is the first known report of the distribution and genetic variation of F. graminearum on wheat spikes in Assiut Egypt.

  4. Effect of seeding rate on grain quality of winter wheat

    Directory of Open Access Journals (Sweden)

    Veselinka Zecevic

    2014-03-01

    Full Text Available Planting density is important factor which influence yield and quality of wheat (Triticum aestivum L. For this reason, in scientific investigations is constantly investigated optimization of plant number per unit area. The objective of this study was to determine the influence of seeding rate in grain quality of winter wheat cultivars. The experiment was conducted with four winter wheat genotypes ('Ana Morava', 'Vizija', 'L-3027', and 'Perla' at the Small Grains Research Centre of Kragujevac, Serbia, in 3 yr at two seeding rates (SR1 = 500 and SR2 = 650 germinating seeds m-2. The 1000-kernel weight, Zeleny sedimentation, and wet gluten content in divergent wheat genotypes were investigated depending on the seeding rate and ecological factors. Significant differences in quality components were established between investigated seeding rates. The highest values of all investigated quality traits were established in SR2 variant when applied 650 seeds m-2. Genotypes reacted differently to seeding rate. 'Perla' in average had the highest mean sedimentation value (42.2 mL and wet gluten content (33.76% in SR2 variant and this cultivar responded the best to seeding rate. Significant differences for sedimentation value and wet gluten content were found among cultivars, years, seeding rate, and for all their interactions. Also, ANOVA for 1000-kernel weight showed highly significant differences among investigated varieties, seeding rate and growing seasons, but all their interactions were not significant. In all investigated genotypes, better quality was established in SR2 variant when applied 650 seeds m-2.

  5. Genetic gains in wheat in Turkey: Winter wheat for dryland conditions

    Directory of Open Access Journals (Sweden)

    Mesut Keser

    2017-12-01

    Full Text Available Wheat breeders in Turkey have been developing new varieties since the 1920s, but few studies have evaluated the rates of genetic improvement. This study determined wheat genetic gains by evaluating 22 winter/facultative varieties released for rainfed conditions between 1931 and 2006. The study was conducted at three locations in Turkey during 2008–2012, with a total of 21 test sites. The experimental design was a randomized complete block with four replicates in 2008 and 2009 and three replicates in 2010–2012. Regression analysis was conducted to determine genetic progress over time. Mean yield across all 21 locations was 3.34 t ha−1, but varied from 1.11 t ha−1 to 6.02 t ha−1 and was highly affected by moisture stress. Annual genetic gain was 0.50% compared to Ak-702, or 0.30% compared to the first modern landmark varieties. The genetic gains in drought-affected sites were 0.75% compared to Ak-702 and 0.66% compared to the landmark varieties. Modern varieties had both improved yield potential and tolerance to moisture stress. Rht genes and rye translocations were largely absent in the varieties studied. The number of spikes per unit area decreased by 10% over the study period, but grains spike−1 and 1000-kernel weight increased by 10%. There were no significant increases in harvest index, grain size, or spike fertility, and no significant decrease in quality over time. Future use of Rht genes and rye translocations in breeding programs may increase yield under rainfed conditions. Keywords: Genetic gain, Rainfed wheat production, Winter wheat, Yield

  6. OS X and iOS Kernel Programming

    CERN Document Server

    Halvorsen, Ole Henry

    2011-01-01

    OS X and iOS Kernel Programming combines essential operating system and kernel architecture knowledge with a highly practical approach that will help you write effective kernel-level code. You'll learn fundamental concepts such as memory management and thread synchronization, as well as the I/O Kit framework. You'll also learn how to write your own kernel-level extensions, such as device drivers for USB and Thunderbolt devices, including networking, storage and audio drivers. OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, i

  7. The Classification of Diabetes Mellitus Using Kernel k-means

    Science.gov (United States)

    Alamsyah, M.; Nafisah, Z.; Prayitno, E.; Afida, A. M.; Imah, E. M.

    2018-01-01

    Diabetes Mellitus is a metabolic disorder which is characterized by chronicle hypertensive glucose. Automatics detection of diabetes mellitus is still challenging. This study detected diabetes mellitus by using kernel k-Means algorithm. Kernel k-means is an algorithm which was developed from k-means algorithm. Kernel k-means used kernel learning that is able to handle non linear separable data; where it differs with a common k-means. The performance of kernel k-means in detecting diabetes mellitus is also compared with SOM algorithms. The experiment result shows that kernel k-means has good performance and a way much better than SOM.

  8. Object classification and detection with context kernel descriptors

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2014-01-01

    Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...

  9. Option Valuation with Volatility Components, Fat Tails, and Nonlinear Pricing Kernels

    DEFF Research Database (Denmark)

    Babaoglu, Kadir Gokhan; Christoffersen, Peter; Heston, Steven

    We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A second volatility factor is economically most i...

  10. Eucalyptus-Palm Kernel Oil Blends: A Complete Elimination of Diesel in a 4-Stroke VCR Diesel Engine

    Directory of Open Access Journals (Sweden)

    Srinivas Kommana

    2015-01-01

    Full Text Available Fuels derived from biomass are mostly preferred as alternative fuels for IC engines as they are abundantly available and renewable in nature. The objective of the study is to identify the parameters that influence gross indicated fuel conversion efficiency and how they are affected by the use of biodiesel relative to petroleum diesel. Important physicochemical properties of palm kernel oil and eucalyptus blend were experimentally evaluated and found within acceptable limits of relevant standards. As most of vegetable oils are edible, growing concern for trying nonedible and waste fats as alternative to petrodiesel has emerged. In present study diesel fuel is completely replaced by biofuels, namely, methyl ester of palm kernel oil and eucalyptus oil in various blends. Different blends of palm kernel oil and eucalyptus oil are prepared on volume basis and used as operating fuel in single cylinder 4-stroke variable compression ratio diesel engine. Performance and emission characteristics of these blends are studied by varying the compression ratio. In the present experiment methyl ester extracted from palm kernel oil is considered as ignition improver and eucalyptus oil is considered as the fuel. The blends taken are PKE05 (palm kernel oil 95 + eucalyptus 05, PKE10 (palm kernel oil 90 + eucalyptus 10, and PKE15 (palm kernel 85 + eucalyptus 15. The results obtained by operating with these fuels are compared with results of pure diesel; finally the most preferable combination and the preferred compression ratio are identified.

  11. The effect of feeding wheat with purple pericarp on the growth of carp

    Directory of Open Access Journals (Sweden)

    Jan Mareš

    2015-08-01

    Full Text Available This study assessed and compared the influence of feeding wheat with purple pericarp (variety Konini and standard coloured wheat (red variety Bohemia on the growth characteristics of fingerling carp (Cyprinus carpio L. of the "Amurský lysec" line. The total content of anthocyanins converted to cyanidin 3-glucoside in the control Bohemia wheat was 24.95 mg.kg-1 and in the Konini purple wheat 41.70 mg.kg-1. Two experimental variants for feed were evaluated: dipped wheat grain and crushed wheat grain. The feed dose for wheat was 1.5% of the fish stock weight and for natural food (frozen Chironomid larvae was 0.2% of fish stock weight to all variants. Growth parameters (body length, body weight, Fulton's condition factor and feed conversion ratio of the fish were evaluated after one month of administration. The feed consumption and physico-chemical parameters (temperature, oxygen saturation, pH, N-NH4 +, N-NO2-, N-NO3- and Cl- of the environment were observed. During the feeding test, no major differences in food consumption among variations feeding on either wheat and on Chironomid larvae were noted. Satisfying results for mas and length gain were achieved in V2 wheat with purple pericarp (Konini variety - dipped grain, where the average total body length was 156.56 mm and the average unit mass was 60.81 g. In this variant, higher values of the parameters were achieved compared to the control group (100.6%, resp. 104.2%. A positive impact of wheat with purple pericarp on the evaluated parameter of fish condition factor was demonstrated. This trend was confirmed in all variants. No effect was demonstrated for mechanical disruption of kernels on the level of utilization of nutrients. In further experiments on growth characteristics we would like to determine antioxidant parameters in the blood and liver of fry.

  12. Glycine betaine and salicylic acid induced modification in productivity of two different cultivars of wheat grown under water stress

    Directory of Open Access Journals (Sweden)

    Heshmat S. Aldesuquy

    2012-05-01

    Full Text Available A pot experiment was conducted to evaluate the beneficial effect of foliar application of glycine betaine (10mM, grain presoaking in salicylic acid (0.05 M and their interaction on drought tolerance of two wheat (Triticum aestivum L. cultivars (sensitive, Sakha 94 and resistant, Sakha 93. Water stress decreased wheat yield components (spike length, number of spikelets / main spike, 100 kernel weight, grain number / spike, grain yield / spike, grain yield / plant, straw yield / plant, crop yield / plant, harvest, mobilization and crop indices and the biochemical aspects of grains(grain biomass, carbohydrates, total protein, total phosphorus, ions content and amino acids in both wheat cultivars. The applied chemicals appeared to alleviate the negative effects of water stress on wheat productivity (particularly the sensitive one and the biochemical aspects of yielded grains. The effect was more pronounced with GB+SA treatment. This improvement would result from the repairing effect of the provided chemicals on growth and metabolism of wheat plants grown under water deficit condition. In response to the applied water stress and the used chemicals, the grain yield of the sensitive and resistant wheat cultivars was strongly correlated with all the estimated yield components (shoot length, spike length, plant height, main spike weight, number of spikelets per main spike, 100 kernel weight, grain number per spike, grain weight per plant, straw weight per plant, crop yield per plant, harvest, mobilization and crop indices.

  13. Alterations and abnormal mitosis of wheat chromosomes induced by wheat-rye monosomic addition lines.

    Directory of Open Access Journals (Sweden)

    Shulan Fu

    Full Text Available BACKGROUND: Wheat-rye addition lines are an old topic. However, the alterations and abnormal mitotic behaviours of wheat chromosomes caused by wheat-rye monosomic addition lines are seldom reported. METHODOLOGY/PRINCIPAL FINDINGS: Octoploid triticale was derived from common wheat T. aestivum L. 'Mianyang11'×rye S. cereale L. 'Kustro' and some progeny were obtained by the controlled backcrossing of triticale with 'Mianyang11' followed by self-fertilization. Genomic in situ hybridization (GISH using rye genomic DNA and fluorescence in situ hybridization (FISH using repetitive sequences pAs1 and pSc119.2 as probes were used to analyze the mitotic chromosomes of these progeny. Strong pSc119.2 FISH signals could be observed at the telomeric regions of 3DS arms in 'Mianyang11'. However, the pSc119.2 FISH signals were disappeared from the selfed progeny of 4R monosomic addition line and the changed 3D chromosomes could be transmitted to next generation stably. In one of the selfed progeny of 7R monosomic addition line, one 2D chromosome was broken and three 4A chromosomes were observed. In the selfed progeny of 6R monosomic addition line, structural variation and abnormal mitotic behaviour of 3D chromosome were detected. Additionally, 1A and 4B chromosomes were eliminated from some of the progeny of 6R monosomic addition line. CONCLUSIONS/SIGNIFICANCE: These results indicated that single rye chromosome added to wheat might cause alterations and abnormal mitotic behaviours of wheat chromosomes and it is possible that the stress caused by single alien chromosome might be one of the factors that induced karyotype alteration of wheat.

  14. Alterations and Abnormal Mitosis of Wheat Chromosomes Induced by Wheat-Rye Monosomic Addition Lines

    Science.gov (United States)

    Fu, Shulan; Yang, Manyu; Fei, Yunyan; Tan, Feiquan; Ren, Zhenglong; Yan, Benju; Zhang, Huaiyu; Tang, Zongxiang

    2013-01-01

    Background Wheat-rye addition lines are an old topic. However, the alterations and abnormal mitotic behaviours of wheat chromosomes caused by wheat-rye monosomic addition lines are seldom reported. Methodology/Principal Findings Octoploid triticale was derived from common wheat T. aestivum L. ‘Mianyang11’×rye S. cereale L. ‘Kustro’ and some progeny were obtained by the controlled backcrossing of triticale with ‘Mianyang11’ followed by self-fertilization. Genomic in situ hybridization (GISH) using rye genomic DNA and fluorescence in situ hybridization (FISH) using repetitive sequences pAs1 and pSc119.2 as probes were used to analyze the mitotic chromosomes of these progeny. Strong pSc119.2 FISH signals could be observed at the telomeric regions of 3DS arms in ‘Mianyang11’. However, the pSc119.2 FISH signals were disappeared from the selfed progeny of 4R monosomic addition line and the changed 3D chromosomes could be transmitted to next generation stably. In one of the selfed progeny of 7R monosomic addition line, one 2D chromosome was broken and three 4A chromosomes were observed. In the selfed progeny of 6R monosomic addition line, structural variation and abnormal mitotic behaviour of 3D chromosome were detected. Additionally, 1A and 4B chromosomes were eliminated from some of the progeny of 6R monosomic addition line. Conclusions/Significance These results indicated that single rye chromosome added to wheat might cause alterations and abnormal mitotic behaviours of wheat chromosomes and it is possible that the stress caused by single alien chromosome might be one of the factors that induced karyotype alteration of wheat. PMID:23936213

  15. Reproducing kernel method with Taylor expansion for linear Volterra integro-differential equations

    Directory of Open Access Journals (Sweden)

    Azizallah Alvandi

    2017-06-01

    Full Text Available This research aims of the present a new and single algorithm for linear integro-differential equations (LIDE. To apply the reproducing Hilbert kernel method, there is made an equivalent transformation by using Taylor series for solving LIDEs. Shown in series form is the analytical solution in the reproducing kernel space and the approximate solution $ u_{N} $ is constructed by truncating the series to $ N $ terms. It is easy to prove the convergence of $ u_{N} $ to the analytical solution. The numerical solutions from the proposed method indicate that this approach can be implemented easily which shows attractive features.

  16. Induced spherococcoid hard wheat

    International Nuclear Information System (INIS)

    Yanev, Sh.

    1981-01-01

    A mutant has been obtained - a spheroccocoid line -through irradiation of hard wheat seed with fast neutrons. It is distinguished by semispherical glumes and smaller grain; the plants have low stem with erect leaves but with shorter spikes and with lesser number of spikelets than those of the initial cultivar. Good productive tillering and resistance to lodging contributed to 23.5% higher yield. The line was superior to the standard and the initial cultivars by 14.2% as regards protein content, and by up to 22.8% - as to flour gluten. It has been successfully used in hybridization producing high-yielding hard wheat lines resistant to lodging, with good technological and other indicators. The possibility stated is of obtaining a spherococcoid mutant in tetraploid (hard) wheat out of the D-genome as well as its being suited to hard wheat breeding to enhance protein content, resistance to lodging, etc. (author)

  17. Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

    Science.gov (United States)

    Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

    2017-12-15

    Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

  18. Kernel abortion in maize. II. Distribution of 14C among kernel carboydrates

    International Nuclear Information System (INIS)

    Hanft, J.M.; Jones, R.J.

    1986-01-01

    This study was designed to compare the uptake and distribution of 14 C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 309 and 35 0 C were transferred to [ 14 C]sucrose media 10 days after pollination. Kernels cultured at 35 0 C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on atlageled media. After 8 days in culture on [ 14 C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35 0 C, respectively. Of the total carbohydrates, a higher percentage of label was associated with sucrose and lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35 0 C compared to kernels cultured at 30 0 C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35 0 C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30 0 C (89%). Kernels cultured at 35 0 C had a correspondingly higher proportion of 14 C in endosperm fructose, glucose, and sucrose

  19. Fluidization calculation on nuclear fuel kernel coating

    International Nuclear Information System (INIS)

    Sukarsono; Wardaya; Indra-Suryawan

    1996-01-01

    The fluidization of nuclear fuel kernel coating was calculated. The bottom of the reactor was in the from of cone on top of the cone there was a cylinder, the diameter of the cylinder for fluidization was 2 cm and at the upper part of the cylinder was 3 cm. Fluidization took place in the cone and the first cylinder. The maximum and the minimum velocity of the gas of varied kernel diameter, the porosity and bed height of varied stream gas velocity were calculated. The calculation was done by basic program

  20. Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

    KAUST Repository

    Leach, Lindsey J; Belfield, Eric J; Jiang, Caifu; Brown, Carly; Mithani, Aziz; Harberd, Nicholas P

    2014-01-01

    BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution 'nullisomic-tetrasomic' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

  1. Patterns of homoeologous gene expression shown by RNA sequencing in hexaploid bread wheat.

    KAUST Repository

    Leach, Lindsey J

    2014-04-11

    BACKGROUND: Bread wheat (Triticum aestivum) has a large, complex and hexaploid genome consisting of A, B and D homoeologous chromosome sets. Therefore each wheat gene potentially exists as a trio of A, B and D homoeoloci, each of which may contribute differentially to wheat phenotypes. We describe a novel approach combining wheat cytogenetic resources (chromosome substitution \\'nullisomic-tetrasomic\\' lines) with next generation deep sequencing of gene transcripts (RNA-Seq), to directly and accurately identify homoeologue-specific single nucleotide variants and quantify the relative contribution of individual homoeoloci to gene expression. RESULTS: We discover, based on a sample comprising ~5-10% of the total wheat gene content, that at least 45% of wheat genes are expressed from all three distinct homoeoloci. Most of these genes show strikingly biased expression patterns in which expression is dominated by a single homoeolocus. The remaining ~55% of wheat genes are expressed from either one or two homoeoloci only, through a combination of extensive transcriptional silencing and homoeolocus loss. CONCLUSIONS: We conclude that wheat is tending towards functional diploidy, through a variety of mechanisms causing single homoeoloci to become the predominant source of gene transcripts. This discovery has profound consequences for wheat breeding and our understanding of wheat evolution.

  2. Method for calculating anisotropic neutron transport using scattering kernel without polynomial expansion

    International Nuclear Information System (INIS)

    Takahashi, Akito; Yamamoto, Junji; Ebisuya, Mituo; Sumita, Kenji

    1979-01-01

    A new method for calculating the anisotropic neutron transport is proposed for the angular spectral analysis of D-T fusion reactor neutronics. The method is based on the transport equation with new type of anisotropic scattering kernels formulated by a single function I sub(i) (μ', μ) instead of polynomial expansion, for instance, Legendre polynomials. In the calculation of angular flux spectra by using scattering kernels with the Legendre polynomial expansion, we often observe the oscillation with negative flux. But in principle this oscillation disappears by this new method. In this work, we discussed anisotropic scattering kernels of the elastic scattering and the inelastic scatterings which excite discrete energy levels. The other scatterings were included in isotropic scattering kernels. An approximation method, with use of the first collision source written by the I sub(i) (μ', μ) function, was introduced to attenuate the ''oscillations'' when we are obliged to use the scattering kernels with the Legendre polynomial expansion. Calculated results with this approximation showed remarkable improvement for the analysis of the angular flux spectra in a slab system of lithium metal with the D-T neutron source. (author)

  3. Wheat (Triticum aestivum L.) transformation using immature embryos.

    Science.gov (United States)

    Ishida, Yuji; Tsunashima, Masako; Hiei, Yukoh; Komari, Toshihiko

    2015-01-01

    Wheat may now be transformed very efficiently by Agrobacterium tumefaciens. Under the protocol hereby described, immature embryos of healthy plants of wheat cultivar Fielder grown in a well-conditioned greenhouse were pretreated with centrifuging and cocultivated with A. tumefaciens. Transgenic wheat plants were obtained routinely from between 40 and 90 % of the immature embryos, thus infected in our tests. All regenerants were normal in morphology and fully fertile. About half of the transformed plants carried single copy of the transgene, which are inherited by the progeny in a Mendelian fashion.

  4. Effect of fungal colonization of wheat grains with Fusarium spp. on food choice, weight gain and mortality of meal beetle larvae (Tenebrio molitor.

    Directory of Open Access Journals (Sweden)

    Zhiqing Guo

    Full Text Available Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin

  5. Effect of Fungal Colonization of Wheat Grains with Fusarium spp. on Food Choice, Weight Gain and Mortality of Meal Beetle Larvae (Tenebrio molitor)

    Science.gov (United States)

    Guo, Zhiqing; Döll, Katharina; Dastjerdi, Raana; Karlovsky, Petr; Dehne, Heinz-Wilhelm; Altincicek, Boran

    2014-01-01

    Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F

  6. Effect of fungal colonization of wheat grains with Fusarium spp. on food choice, weight gain and mortality of meal beetle larvae (Tenebrio molitor).

    Science.gov (United States)

    Guo, Zhiqing; Döll, Katharina; Dastjerdi, Raana; Karlovsky, Petr; Dehne, Heinz-Wilhelm; Altincicek, Boran

    2014-01-01

    Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F

  7. QTL Mapping of Kernel Number-Related Traits and Validation of One Major QTL for Ear Length in Maize.

    Science.gov (United States)

    Huo, Dongao; Ning, Qiang; Shen, Xiaomeng; Liu, Lei; Zhang, Zuxin

    2016-01-01

    The kernel number is a grain yield component and an important maize breeding goal. Ear length, kernel number per row and ear row number are highly correlated with the kernel number per ear, which eventually determines the ear weight and grain yield. In this study, two sets of F2:3 families developed from two bi-parental crosses sharing one inbred line were used to identify quantitative trait loci (QTL) for four kernel number-related traits: ear length, kernel number per row, ear row number and ear weight. A total of 39 QTLs for the four traits were identified in the two populations. The phenotypic variance explained by a single QTL ranged from 0.4% to 29.5%. Additionally, 14 overlapping QTLs formed 5 QTL clusters on chromosomes 1, 4, 5, 7, and 10. Intriguingly, six QTLs for ear length and kernel number per row overlapped in a region on chromosome 1. This region was designated qEL1.10 and was validated as being simultaneously responsible for ear length, kernel number per row and ear weight in a near isogenic line-derived population, suggesting that qEL1.10 was a pleiotropic QTL with large effects. Furthermore, the performance of hybrids generated by crossing 6 elite inbred lines with two near isogenic lines at qEL1.10 showed the breeding value of qEL1.10 for the improvement of the kernel number and grain yield of maize hybrids. This study provides a basis for further fine mapping, molecular marker-aided breeding and functional studies of kernel number-related traits in maize.

  8. 21 CFR 137.190 - Cracked wheat.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Cracked wheat. 137.190 Section 137.190 Food and... Related Products § 137.190 Cracked wheat. Cracked wheat is the food prepared by so cracking or cutting into angular fragments cleaned wheat other than durum wheat and red durum wheat that, when tested by...

  9. Comparative Analysis of Kernel Methods for Statistical Shape Learning

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

    2006-01-01

    .... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...

  10. Variable kernel density estimation in high-dimensional feature spaces

    CSIR Research Space (South Africa)

    Van der Walt, Christiaan M

    2017-02-01

    Full Text Available Estimating the joint probability density function of a dataset is a central task in many machine learning applications. In this work we address the fundamental problem of kernel bandwidth estimation for variable kernel density estimation in high...

  11. Influence of differently processed mango seed kernel meal on ...

    African Journals Online (AJOL)

    Influence of differently processed mango seed kernel meal on performance response of west African ... and TD( consisted spear grass and parboiled mango seed kernel meal with concentrate diet in a ratio of 35:30:35). ... HOW TO USE AJOL.

  12. On methods to increase the security of the Linux kernel

    International Nuclear Information System (INIS)

    Matvejchikov, I.V.

    2014-01-01

    Methods to increase the security of the Linux kernel for the implementation of imposed protection tools have been examined. The methods of incorporation into various subsystems of the kernel on the x86 architecture have been described [ru

  13. Linear and kernel methods for multi- and hypervariate change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

    . Principal component analysis (PCA) as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (which are nonlinear), may further enhance change signals relative to no-change background. The kernel versions are based on a dual...... formulation, also termed Q-mode analysis, in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution......, also known as the kernel trick, these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of the kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component...

  14. Kernel methods in orthogonalization of multi- and hypervariate data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

    A kernel version of maximum autocorrelation factor (MAF) analysis is described very briefly and applied to change detection in remotely sensed hyperspectral image (HyMap) data. The kernel version is based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis...... via inner products in the Gram matrix only. In the kernel version the inner products are replaced by inner products between nonlinear mappings into higher dimensional feature space of the original data. Via kernel substitution also known as the kernel trick these inner products between the mappings...... are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MAF analysis handle nonlinearities by implicitly transforming data into high (even infinite...

  15. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge

    2012-01-01

    The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.

  16. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    Science.gov (United States)

    2016-01-05

    SECURITY CLASSIFICATION OF: The research objective of this proposal was to develop a predictive Bayesian kernel approach to model count data based on...several predictive variables. Such an approach, which we refer to as the Poisson Bayesian kernel model, is able to model the rate of occurrence of... kernel methods made use of: (i) the Bayesian property of improving predictive accuracy as data are dynamically obtained, and (ii) the kernel function

  17. Relationship between attenuation coefficients and dose-spread kernels

    International Nuclear Information System (INIS)

    Boyer, A.L.

    1988-01-01

    Dose-spread kernels can be used to calculate the dose distribution in a photon beam by convolving the kernel with the primary fluence distribution. The theoretical relationships between various types and components of dose-spread kernels relative to photon attenuation coefficients are explored. These relations can be valuable as checks on the conservation of energy by dose-spread kernels calculated by analytic or Monte Carlo methods

  18. Fabrication of Uranium Oxycarbide Kernels for HTR Fuel

    International Nuclear Information System (INIS)

    Barnes, Charles; Richardson, Clay; Nagley, Scott; Hunn, John; Shaber, Eric

    2010-01-01

    Babcock and Wilcox (B and W) has been producing high quality uranium oxycarbide (UCO) kernels for Advanced Gas Reactor (AGR) fuel tests at the Idaho National Laboratory. In 2005, 350-(micro)m, 19.7% 235U-enriched UCO kernels were produced for the AGR-1 test fuel. Following coating of these kernels and forming the coated-particles into compacts, this fuel was irradiated in the Advanced Test Reactor (ATR) from December 2006 until November 2009. B and W produced 425-(micro)m, 14% enriched UCO kernels in 2008, and these kernels were used to produce fuel for the AGR-2 experiment that was inserted in ATR in 2010. B and W also produced 500-(micro)m, 9.6% enriched UO2 kernels for the AGR-2 experiments. Kernels of the same size and enrichment as AGR-1 were also produced for the AGR-3/4 experiment. In addition to fabricating enriched UCO and UO2 kernels, B and W has produced more than 100 kg of natural uranium UCO kernels which are being used in coating development tests. Successive lots of kernels have demonstrated consistent high quality and also allowed for fabrication process improvements. Improvements in kernel forming were made subsequent to AGR-1 kernel production. Following fabrication of AGR-2 kernels, incremental increases in sintering furnace charge size have been demonstrated. Recently small scale sintering tests using a small development furnace equipped with a residual gas analyzer (RGA) has increased understanding of how kernel sintering parameters affect sintered kernel properties. The steps taken to increase throughput and process knowledge have reduced kernel production costs. Studies have been performed of additional modifications toward the goal of increasing capacity of the current fabrication line to use for production of first core fuel for the Next Generation Nuclear Plant (NGNP) and providing a basis for the design of a full scale fuel fabrication facility.

  19. Consistent Estimation of Pricing Kernels from Noisy Price Data

    OpenAIRE

    Vladislav Kargin

    2003-01-01

    If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.

  20. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

    Heunen, C.; Jacobs, B.P.F.

    2009-01-01

    This paper investigates quantum logic from the perspective of categorical logic, and starts from minimal assumptions, namely the existence of involutions/daggers and kernels. The resulting structures turn out to (1) encompass many examples of interest, such as categories of relations, partial

  1. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

    Heunen, C.; Jacobs, B.P.F.; Coecke, B.; Panangaden, P.; Selinger, P.

    2011-01-01

    This paper investigates quantum logic from the perspective of categorical logic, and starts from minimal assumptions, namely the existence of involutions/daggers and kernels. The resulting structures turn out to (1) encompass many examples of interest, such as categories of relations, partial

  2. Symbol recognition with kernel density matching.

    Science.gov (United States)

    Zhang, Wan; Wenyin, Liu; Zhang, Kun

    2006-12-01

    We propose a novel approach to similarity assessment for graphic symbols. Symbols are represented as 2D kernel densities and their similarity is measured by the Kullback-Leibler divergence. Symbol orientation is found by gradient-based angle searching or independent component analysis. Experimental results show the outstanding performance of this approach in various situations.

  3. Flexible Scheduling in Multimedia Kernels: An Overview

    NARCIS (Netherlands)

    Jansen, P.G.; Scholten, Johan; Laan, Rene; Chow, W.S.

    1999-01-01

    Current Hard Real-Time (HRT) kernels have their timely behaviour guaranteed on the cost of a rather restrictive use of the available resources. This makes current HRT scheduling techniques inadequate for use in a multimedia environment where we can make a considerable profit by a better and more

  4. Reproducing kernel Hilbert spaces of Gaussian priors

    NARCIS (Netherlands)

    Vaart, van der A.W.; Zanten, van J.H.; Clarke, B.; Ghosal, S.

    2008-01-01

    We review definitions and properties of reproducing kernel Hilbert spaces attached to Gaussian variables and processes, with a view to applications in nonparametric Bayesian statistics using Gaussian priors. The rate of contraction of posterior distributions based on Gaussian priors can be described

  5. A synthesis of empirical plant dispersal kernels

    Czech Academy of Sciences Publication Activity Database

    Bullock, J. M.; González, L. M.; Tamme, R.; Götzenberger, Lars; White, S. M.; Pärtel, M.; Hooftman, D. A. P.

    2017-01-01

    Roč. 105, č. 1 (2017), s. 6-19 ISSN 0022-0477 Institutional support: RVO:67985939 Keywords : dispersal kernel * dispersal mode * probability density function Subject RIV: EH - Ecology, Behaviour OBOR OECD: Ecology Impact factor: 5.813, year: 2016

  6. Analytic continuation of weighted Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

    Roč. 94, č. 6 (2010), s. 622-650 ISSN 0021-7824 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * analytic continuation * Toeplitz operator Subject RIV: BA - General Mathematics Impact factor: 1.450, year: 2010 http://www.sciencedirect.com/science/article/pii/S0021782410000942

  7. On convergence of kernel learning estimators

    NARCIS (Netherlands)

    Norkin, V.I.; Keyzer, M.A.

    2009-01-01

    The paper studies convex stochastic optimization problems in a reproducing kernel Hilbert space (RKHS). The objective (risk) functional depends on functions from this RKHS and takes the form of a mathematical expectation (integral) of a nonnegative integrand (loss function) over a probability

  8. Analytic properties of the Virasoro modular kernel

    Energy Technology Data Exchange (ETDEWEB)

    Nemkov, Nikita [Moscow Institute of Physics and Technology (MIPT), Dolgoprudny (Russian Federation); Institute for Theoretical and Experimental Physics (ITEP), Moscow (Russian Federation); National University of Science and Technology MISIS, The Laboratory of Superconducting metamaterials, Moscow (Russian Federation)

    2017-06-15

    On the space of generic conformal blocks the modular transformation of the underlying surface is realized as a linear integral transformation. We show that the analytic properties of conformal block implied by Zamolodchikov's formula are shared by the kernel of the modular transformation and illustrate this by explicit computation in the case of the one-point toric conformal block. (orig.)

  9. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...

  10. Kernel Temporal Differences for Neural Decoding

    Science.gov (United States)

    Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2015-01-01

    We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504

  11. Scattering kernels and cross sections working group

    International Nuclear Information System (INIS)

    Russell, G.; MacFarlane, B.; Brun, T.

    1998-01-01

    Topics addressed by this working group are: (1) immediate needs of the cold-moderator community and how to fill them; (2) synthetic scattering kernels; (3) very simple synthetic scattering functions; (4) measurements of interest; and (5) general issues. Brief summaries are given for each of these topics

  12. Predictive Model Equations for Palm Kernel (Elaeis guneensis J ...

    African Journals Online (AJOL)

    Estimated error of ± 0.18 and ± 0.2 are envisaged while applying the models for predicting palm kernel and sesame oil colours respectively. Keywords: Palm kernel, Sesame, Palm kernel, Oil Colour, Process Parameters, Model. Journal of Applied Science, Engineering and Technology Vol. 6 (1) 2006 pp. 34-38 ...

  13. Stable Kernel Representations as Nonlinear Left Coprime Factorizations

    NARCIS (Netherlands)

    Paice, A.D.B.; Schaft, A.J. van der

    1994-01-01

    A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel

  14. 7 CFR 981.60 - Determination of kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Determination of kernel weight. 981.60 Section 981.60... Regulating Handling Volume Regulation § 981.60 Determination of kernel weight. (a) Almonds for which settlement is made on kernel weight. All lots of almonds, whether shelled or unshelled, for which settlement...

  15. 21 CFR 176.350 - Tamarind seed kernel powder.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

  16. Heat kernel analysis for Bessel operators on symmetric cones

    DEFF Research Database (Denmark)

    Möllers, Jan

    2014-01-01

    . The heat kernel is explicitly given in terms of a multivariable $I$-Bessel function on $Ω$. Its corresponding heat kernel transform defines a continuous linear operator between $L^p$-spaces. The unitary image of the $L^2$-space under the heat kernel transform is characterized as a weighted Bergmann space...

  17. A Fast and Simple Graph Kernel for RDF

    NARCIS (Netherlands)

    de Vries, G.K.D.; de Rooij, S.

    2013-01-01

    In this paper we study a graph kernel for RDF based on constructing a tree for each instance and counting the number of paths in that tree. In our experiments this kernel shows comparable classification performance to the previously introduced intersection subtree kernel, but is significantly faster

  18. 7 CFR 981.61 - Redetermination of kernel weight.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Redetermination of kernel weight. 981.61 Section 981... GROWN IN CALIFORNIA Order Regulating Handling Volume Regulation § 981.61 Redetermination of kernel weight. The Board, on the basis of reports by handlers, shall redetermine the kernel weight of almonds...

  19. Prediction of protein subcellular localization using support vector machine with the choice of proper kernel

    Directory of Open Access Journals (Sweden)

    Al Mehedi Hasan

    2017-07-01

    subcellular localization prediction to find out which kernel is the best for SVM. We have evaluated our system on a combined dataset containing 5447 single-localized proteins (originally published as part of the Höglund dataset and 3056 multi-localized proteins (originally published as part of the DBMLoc set. This dataset was used by Briesemeister et al. in their extensive comparison of multilocalization prediction system. The experimental results indicate that the system based on SVM with the Laplace kernel, termed LKLoc, not only achieves a higher accuracy than the system using other kernels but also shows significantly better results than those obtained from other top systems (MDLoc, BNCs, YLoc+. The source code of this prediction system is available upon request.

  20. Learning a peptide-protein binding affinity predictor with kernel ridge regression

    Science.gov (United States)

    2013-01-01

    Background The cellular function of a vast majority of proteins is performed through physical interactions with other biomolecules, which, most of the time, are other proteins. Peptides represent templates of choice for mimicking a secondary structure in order to modulate protein-protein interaction. They are thus an interesting class of therapeutics since they also display strong activity, high selectivity, low toxicity and few drug-drug interactions. Furthermore, predicting peptides that would bind to a specific MHC alleles would be of tremendous benefit to improve vaccine based therapy and possibly generate antibodies with greater affinity. Modern computational methods have the potential to accelerate and lower the cost of drug and vaccine discovery by selecting potential compounds for testing in silico prior to biological validation. Results We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalizes eight kernels, comprised of the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it’s approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of predicting the binding affinity of any peptide to any protein with reasonable accuracy. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. Conclusion On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting

  1. Quasi-Dual-Packed-Kerneled Au49 (2,4-DMBT)27 Nanoclusters and the Influence of Kernel Packing on the Electrochemical Gap.

    Science.gov (United States)

    Liao, Lingwen; Zhuang, Shengli; Wang, Pu; Xu, Yanan; Yan, Nan; Dong, Hongwei; Wang, Chengming; Zhao, Yan; Xia, Nan; Li, Jin; Deng, Haiteng; Pei, Yong; Tian, Shi-Kai; Wu, Zhikun

    2017-10-02

    Although face-centered cubic (fcc), body-centered cubic (bcc), hexagonal close-packed (hcp), and other structured gold nanoclusters have been reported, it was unclear whether gold nanoclusters with mix-packed (fcc and non-fcc) kernels exist, and the correlation between kernel packing and the properties of gold nanoclusters is unknown. A Au 49 (2,4-DMBT) 27 nanocluster with a shell electron count of 22 has now been been synthesized and structurally resolved by single-crystal X-ray crystallography, which revealed that Au 49 (2,4-DMBT) 27 contains a unique Au 34 kernel consisting of one quasi-fcc-structured Au 21 and one non-fcc-structured Au 13 unit (where 2,4-DMBTH=2,4-dimethylbenzenethiol). Further experiments revealed that the kernel packing greatly influences the electrochemical gap (EG) and the fcc structure has a larger EG than the investigated non-fcc structure. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Systemic Growth of F. graminearum in Wheat Plants and Related Accumulation of Deoxynivalenol

    Directory of Open Access Journals (Sweden)

    Antonio Moretti

    2014-04-01

    Full Text Available Fusarium head blight (FHB is an important disease of wheat worldwide caused mainly by Fusarium graminearum (syn. Gibberella zeae. This fungus can be highly aggressive and can produce several mycotoxins such as deoxynivalenol (DON, a well known harmful metabolite for humans, animals, and plants. The fungus can survive overwinter on wheat residues and on the soil, and can usually attack the wheat plant at their point of flowering, being able to infect the heads and to contaminate the kernels at the maturity. Contaminated kernels can be sometimes used as seeds for the cultivation of the following year. Poor knowledge on the ability of the strains of F. graminearum occurring on wheat seeds to be transmitted to the plant and to contribute to the final DON contamination of kernels is available. Therefore, this study had the goals of evaluating: (a the capability of F. graminearum causing FHB of wheat to be transmitted from the seeds or soil to the kernels at maturity and the progress of the fungus within the plant at different growth stages; (b the levels of DON contamination in both plant tissues and kernels. The study has been carried out for two years in a climatic chamber. The F. gramineraum strain selected for the inoculation was followed within the plant by using Vegetative Compatibility technique, and quantified by Real-Time PCR. Chemical analyses of DON were carried out by using immunoaffinity cleanup and HPLC/UV/DAD. The study showed that F. graminearum originated from seeds or soil can grow systemically in the plant tissues, with the exception of kernels and heads. There seems to be a barrier that inhibits the colonization of the heads by the fungus. High levels of DON and F. graminearum were found in crowns, stems, and straw, whereas low levels of DON and no detectable levels of F. graminearum were found in both heads and kernels. Finally, in all parts of the plant (heads, crowns, and stems at milk and vitreous ripening stages, and straw at

  3. Characterization of Brazilian wheat cultivars for specific technological applications

    Directory of Open Access Journals (Sweden)

    Patrícia Matos Scheuer

    2011-09-01

    Full Text Available Functional and technological properties of wheat depend on its chemical composition, which together with structural and microscopic characteristics, define flour quality. The aim of the present study was to characterize four Brazilian wheat cultivars (BRS Louro, BRS Timbauva, BRS Guamirim and BRS Pardela and their respective flours in order to indicate specific technological applications. Kernels were analyzed for test weight, thousand kernel weight, hardness, moisture, and water activity. Flours were analyzed for water activity, color, centesimal composition, total dietary fiber, amylose content and identification of high molecular weight glutenins. The rheological properties of the flours were estimated by farinography, extensography, falling number, rapid visco amylography, and glutomatic and glutork equipment. Baking tests and scanning electron microscopy were also performed. The data were subjected to analysis of variance and principal component analysis. BRS Timbauva and BRS Guamirim presented results that did not allow for specific technological application. On the other hand, BRS Louro presented suitable characteristics for the elaboration of products with low dough strength such as cakes, pies and biscuits, while BRS Pardela seemed suitable for bread and pasta products.

  4. Scuba: scalable kernel-based gene prioritization.

    Science.gov (United States)

    Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

    2018-01-25

    The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

  5. Genetic rearrangements of six wheat-agropyron cristatum 6P addition lines revealed by molecular markers.

    Directory of Open Access Journals (Sweden)

    Haiming Han

    Full Text Available Agropyron cristatum (L. Gaertn. (2n = 4x = 28, PPPP not only is cultivated as pasture fodder but also could provide many desirable genes for wheat improvement. It is critical to obtain common wheat-A. cristatum alien disomic addition lines to locate the desired genes on the P genome chromosomes. Comparative analysis of the homoeologous relationships between the P genome chromosome and wheat genome chromosomes is a key step in transferring different desirable genes into common wheat and producing the desired alien translocation line while compensating for the loss of wheat chromatin. In this study, six common wheat-A. cristatum disomic addition lines were produced and analyzed by phenotypic examination, genomic in situ hybridization (GISH, SSR markers from the ABD genomes and STS markers from the P genome. Comparative maps, six in total, were generated and demonstrated that all six addition lines belonged to homoeologous group 6. However, chromosome 6P had undergone obvious rearrangements in different addition lines compared with the wheat chromosome, indicating that to obtain a genetic compensating alien translocation line, one should recombine alien chromosomal regions with homoeologous wheat chromosomes. Indeed, these addition lines were classified into four types based on the comparative mapping: 6PI, 6PII, 6PIII, and 6PIV. The different types of chromosome 6P possessed different desirable genes. For example, the 6PI type, containing three addition lines, carried genes conferring high numbers of kernels per spike and resistance to powdery mildew, important traits for wheat improvement. These results may prove valuable for promoting the development of conventional chromosome engineering techniques toward molecular chromosome engineering.

  6. Study on Spectrum Estimation in Biophoton Emission Signal Analysis of Wheat Varieties

    Directory of Open Access Journals (Sweden)

    Yitao Liang

    2014-01-01

    Full Text Available The photon emission signal in visible range (380 nm–630 nm was measured from various wheat kernels by means of a low noise photomultiplier system. To study the features of the photon emission signal, the spectrum estimation method of the photon emission signal is described for the first time. The biophoton emission signal, belonging to four varieties of wheat, is analyzed in time domain and frequency domain. It shows that the intensity of the biophoton emission signal for four varieties of wheat kernels is relatively weak and has dramatic changes over time. Mean and mean square value are obviously different in four varieties; the range was, respectively, 3.7837 and 74.8819. The difference of variance is not significant. The range is 1.1764. The results of power spectrum estimation deduced that the biophoton emission signal is a low frequency signal, and its power spectrum is mostly distributed in the frequency less than 0.1 Hz. Then three parameters, which are spectral edge frequency, spectral gravity frequency, and power spectral entropy, are adopted to explain the features of the kernels’ spontaneous biophoton emission signal. It shows that the parameters of the spontaneous biophoton emission signal for different varieties of wheat are similar.

  7. Landslide Susceptibility Mapping Based on Particle Swarm Optimization of Multiple Kernel Relevance Vector Machines: Case of a Low Hill Area in Sichuan Province, China

    Directory of Open Access Journals (Sweden)

    Yongliang Lin

    2016-10-01

    Full Text Available In this paper, we propose a multiple kernel relevance vector machine (RVM method based on the adaptive cloud particle swarm optimization (PSO algorithm to map landslide susceptibility in the low hill area of Sichuan Province, China. In the multi-kernel structure, the kernel selection problem can be solved by adjusting the kernel weight, which determines the single kernel contribution of the final kernel mapping. The weights and parameters of the multi-kernel function were optimized using the PSO algorithm. In addition, the convergence speed of the PSO algorithm was increased using cloud theory. To ensure the stability of the prediction model, the result of a five-fold cross-validation method was used as the fitness of the PSO algorithm. To verify the results, receiver operating characteristic curves (ROC and landslide dot density (LDD were used. The results show that the model that used a heterogeneous kernel (a combination of two different kernel functions had a larger area under the ROC curve (0.7616 and a lower prediction error ratio (0.28% than did the other types of kernel models employed in this study. In addition, both the sum of two high susceptibility zone LDDs (6.71/100 km2 and the sum of two low susceptibility zone LDDs (0.82/100 km2 demonstrated that the landslide susceptibility map based on the heterogeneous kernel model was closest to the historical landslide distribution. In conclusion, the results obtained in this study can provide very useful information for disaster prevention and land-use planning in the study area.

  8. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    function and all quantities needed in the analysis are expressed in terms of this kernel function. This means that we need not know the nonlinear mappings explicitly. Kernel PCA and MNF analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via...... analysis all 126 spectral bands of the HyMap are included. Changes on the ground are most likely due to harvest having taken place between the two acquisitions and solar effects (both solar elevation and azimuth have changed). Both types of kernel analysis emphasize change and unlike kernel PCA, kernel MNF...

  9. A laser optical method for detecting corn kernel defects

    Energy Technology Data Exchange (ETDEWEB)

    Gunasekaran, S.; Paulsen, M. R.; Shove, G. C.

    1984-01-01

    An opto-electronic instrument was developed to examine individual corn kernels and detect various kernel defects according to reflectance differences. A low power helium-neon (He-Ne) laser (632.8 nm, red light) was used as the light source in the instrument. Reflectance from good and defective parts of corn kernel surfaces differed by approximately 40%. Broken, chipped, and starch-cracked kernels were detected with nearly 100% accuracy; while surface-split kernels were detected with about 80% accuracy. (author)

  10. Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws

    Directory of Open Access Journals (Sweden)

    Mohammed D. ABDULMALIK

    2008-06-01

    Full Text Available Microsoft has made substantial enhancements to the kernel of the Microsoft Windows Vista operating system. Kernel improvements are significant because the kernel provides low-level operating system functions, including thread scheduling, interrupt and exception dispatching, multiprocessor synchronization, and a set of routines and basic objects.This paper describes some of the kernel security enhancements for 64-bit edition of Windows Vista. We also point out some weakness areas (flaws that can be attacked by malicious leading to compromising the kernel.

  11. Difference between standard and quasi-conformal BFKL kernels

    International Nuclear Information System (INIS)

    Fadin, V.S.; Fiore, R.; Papa, A.

    2012-01-01

    As it was recently shown, the colour singlet BFKL kernel, taken in Möbius representation in the space of impact parameters, can be written in quasi-conformal shape, which is unbelievably simple compared with the conventional form of the BFKL kernel in momentum space. It was also proved that the total kernel is completely defined by its Möbius representation. In this paper we calculated the difference between standard and quasi-conformal BFKL kernels in momentum space and discovered that it is rather simple. Therefore we come to the conclusion that the simplicity of the quasi-conformal kernel is caused mainly by using the impact parameter space.

  12. Introgression of novel traits from a wild wheat relative improves drought adaptation in wheat.

    Science.gov (United States)

    Placido, Dante F; Campbell, Malachy T; Folsom, Jing J; Cui, Xinping; Kruger, Greg R; Baenziger, P Stephen; Walia, Harkamal

    2013-04-01

    Root architecture traits are an important component for improving water stress adaptation. However, selection for aboveground traits under favorable environments in modern cultivars may have led to an inadvertent loss of genes and novel alleles beneficial for adapting to environments with limited water. In this study, we elucidate the physiological and molecular consequences of introgressing an alien chromosome segment (7DL) from a wild wheat relative species (Agropyron elongatum) into cultivated wheat (Triticum aestivum). The wheat translocation line had improved water stress adaptation and higher root and shoot biomass compared with the control genotypes, which showed significant drops in root and shoot biomass during stress. Enhanced access to water due to higher root biomass enabled the translocation line to maintain more favorable gas-exchange and carbon assimilation levels relative to the wild-type wheat genotypes during water stress. Transcriptome analysis identified candidate genes associated with root development. Two of these candidate genes mapped to the site of translocation on chromosome 7DL based on single-feature polymorphism analysis. A brassinosteroid signaling pathway was predicted to be involved in the novel root responses observed in the A. elongatum translocation line, based on the coexpression-based gene network generated by seeding the network with the candidate genes. We present an effective and highly integrated approach that combines root phenotyping, whole-plant physiology, and functional genomics to discover novel root traits and the underlying genes from a wild related species to improve drought adaptation in cultivated wheat.

  13. Assessment of chapatti quality of wheat varieties based on physicochemical, rheological and sensory traits.

    Science.gov (United States)

    Kundu, Manju; Khatkar, Bhupendar Singh; Gulia, Neelam

    2017-07-01

    Fifty wheat varieties were assessed for chapatti quality using grain characteristics, dough rheological properties and pasting characteristics. Results revealed that 88% of wheat varieties studied were medium-hard to hard based on kernel texture. Water absorption and damaged starch were found to be important parameters for chapatti quality as both parameters had significant positive effect on the pliability and puffing height of chapatti. Protein content and gluten strength parameters like SDS sedimentation volume, dough stability and gluten index were found to have a negative impact on chapatti quality. Based on chapatti quality assessment the wheat varieties were classified into four distinct clusters viz. good, acceptable, fair and poor for chapatti making. It was elucidated that 46% of the varieties studied were good to acceptable for chapatti making, while 54% resulted in fair or poor chapatti quality thereby clearly indicating the need to establish and substantiate the development of product-specific varieties. Copyright © 2016. Published by Elsevier Ltd.

  14. Difference in postprandial GLP-1 response despite similar glucose kinetics after consumption of wheat breads with different particle size in healthy men.

    Science.gov (United States)

    Eelderink, Coby; Noort, Martijn W J; Sozer, Nesli; Koehorst, Martijn; Holst, Jens J; Deacon, Carolyn F; Rehfeld, Jens F; Poutanen, Kaisa; Vonk, Roel J; Oudhuis, Lizette; Priebe, Marion G

    2017-04-01

    Underlying mechanisms of the beneficial health effects of low glycemic index starchy foods are not fully elucidated yet. We varied the wheat particle size to obtain fiber-rich breads with a high and low glycemic response and investigated the differences in postprandial glucose kinetics and metabolic response after their consumption. Ten healthy male volunteers participated in a randomized, crossover study, consuming 13 C-enriched breads with different structures; a control bread (CB) made from wheat flour combined with wheat bran, and a kernel bread (KB) where 85 % of flour was substituted with broken wheat kernels. The structure of the breads was characterized extensively. The use of stable isotopes enabled calculation of glucose kinetics: rate of appearance of exogenous glucose, endogenous glucose production, and glucose clearance rate. Additionally, postprandial plasma concentrations of glucose, insulin, glucagon, incretins, cholecystokinin, and bile acids were analyzed. Despite the attempt to obtain a bread with a low glycemic response by replacing flour by broken kernels, the glycemic response and glucose kinetics were quite similar after consumption of CB and KB. Interestingly, the glucagon-like peptide-1 (GLP-1) response was much lower after KB compared to CB (iAUC, P bread did not result in a difference in glucose response and kinetics, but in a pronounced difference in GLP-1 response. Thus, changing the processing conditions of wheat for baking bread can influence the metabolic response beyond glycemia and may therefore influence health.

  15. Combined Kernel-Based BDT-SMO Classification of Hyperspectral Fused Images

    Directory of Open Access Journals (Sweden)

    Fenghua Huang

    2014-01-01

    Full Text Available To solve the poor generalization and flexibility problems that single kernel SVM classifiers have while classifying combined spectral and spatial features, this paper proposed a solution to improve the classification accuracy and efficiency of hyperspectral fused images: (1 different radial basis kernel functions (RBFs are employed for spectral and textural features, and a new combined radial basis kernel function (CRBF is proposed by combining them in a weighted manner; (2 the binary decision tree-based multiclass SMO (BDT-SMO is used in the classification of hyperspectral fused images; (3 experiments are carried out, where the single radial basis function- (SRBF- based BDT-SMO classifier and the CRBF-based BDT-SMO classifier are used, respectively, to classify the land usages of hyperspectral fused images, and genetic algorithms (GA are used to optimize the kernel parameters of the classifiers. The results show that, compared with SRBF, CRBF-based BDT-SMO classifiers display greater classification accuracy and efficiency.

  16. Heat tolerance in wheat

    DEFF Research Database (Denmark)

    Sharma, Dew Kumari

    As a consequence of global climate change, heat stress together with other abiotic stresses will remain an important determinant of future food security. Wheat (Triticum aestivum L.) is the third most important crop of the world feeding one third of the world population. Being a crop of temperate...... climate, wheat is sensitive to heat stress. We need to understand how our crops will perform in these changing climatic conditions and how we can develop varieties, which are more tolerant. The PhD study focussed on understanding heat tolerance in wheat with a combined approach of plant physiology...... and quantitative genetics in particular, plant phenotyping based quantitative trait loci (QTL) discovery for a physiological trait under heat stress. Chlorophyll a fluorescence trait, Fv/Fm was used as a phenotyping tool, as it reflects the effect of heat stress on maximum photochemical efficiency of photosystem...

  17. Kernel Tuning and Nonuniform Influence on Optical and Electrochemical Gaps of Bimetal Nanoclusters.

    Science.gov (United States)

    He, Lizhong; Yuan, Jinyun; Xia, Nan; Liao, Lingwen; Liu, Xu; Gan, Zibao; Wang, Chengming; Yang, Jinlong; Wu, Zhikun

    2018-03-14

    Fine tuning nanoparticles with atomic precision is exciting and challenging and is critical for tuning the properties, understanding the structure-property correlation and determining the practical applications of nanoparticles. Some ultrasmall thiolated metal nanoparticles (metal nanoclusters) have been shown to be precisely doped, and even the protecting staple metal atom could be precisely reduced. However, the precise addition or reduction of the kernel atom while the other metal atoms in the nanocluster remain the same has not been successful until now, to the best of our knowledge. Here, by carefully selecting the protecting ligand with adequate steric hindrance, we synthesized a novel nanocluster in which the kernel can be regarded as that formed by the addition of two silver atoms to both ends of the Pt@Ag 12 icosohedral kernel of the Ag 24 Pt(SR) 18 (SR: thiolate) nanocluster, as revealed by single crystal X-ray crystallography. Interestingly, compared with the previously reported Ag 24 Pt(SR) 18 nanocluster, the as-obtained novel bimetal nanocluster exhibits a similar absorption but a different electrochemical gap. One possible explanation for this result is that the kernel tuning does not essentially change the electronic structure, but obviously influences the charge on the Pt@Ag 12 kernel, as demonstrated by natural population analysis, thus possibly resulting in the large electrochemical gap difference between the two nanoclusters. This work not only provides a novel strategy to tune metal nanoclusters but also reveals that the kernel change does not necessarily alter the optical and electrochemical gaps in a uniform manner, which has important implications for the structure-property correlation of nanoparticles.

  18. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... Department of Computer Science and Engineering, Srinivasa Ramanujan Institute of Technology, Anantapur 515701, India; Department of Computer Science and Engineering, Rajeev Gandhi Memorial College of Engineering and Technology, Nandyal 518501, India; Department of Computer Science and ...

  19. Biolistics Transformation of Wheat

    Science.gov (United States)

    Sparks, Caroline A.; Jones, Huw D.

    We present a complete, step-by-step guide to the production of transformed wheat plants using a particle bombardment device to deliver plasmid DNA into immature embryos and the regeneration of transgenic plants via somatic embryogenesis. Currently, this is the most commonly used method for transforming wheat and it offers some advantages. However, it will be interesting to see whether this position is challenged as facile methods are developed for delivering DNA by Agrobacterium tumefaciens or by the production of transformants via a germ-line process (see other chapters in this book).

  20. Analytic scattering kernels for neutron thermalization studies

    International Nuclear Information System (INIS)

    Sears, V.F.

    1990-01-01

    Current plans call for the inclusion of a liquid hydrogen or deuterium cold source in the NRU replacement vessel. This report is part of an ongoing study of neutron thermalization in such a cold source. Here, we develop a simple analytical model for the scattering kernel of monatomic and diatomic liquids. We also present the results of extensive numerical calculations based on this model for liquid hydrogen, liquid deuterium, and mixtures of the two. These calculations demonstrate the dependence of the scattering kernel on the incident and scattered-neutron energies, the behavior near rotational thresholds, the dependence on the centre-of-mass pair correlations, the dependence on the ortho concentration, and the dependence on the deuterium concentration in H 2 /D 2 mixtures. The total scattering cross sections are also calculated and compared with available experimental results

  1. Quantized kernel least mean square algorithm.

    Science.gov (United States)

    Chen, Badong; Zhao, Songlin; Zhu, Pingping; Príncipe, José C

    2012-01-01

    In this paper, we propose a quantization approach, as an alternative of sparsification, to curb the growth of the radial basis function structure in kernel adaptive filtering. The basic idea behind this method is to quantize and hence compress the input (or feature) space. Different from sparsification, the new approach uses the "redundant" data to update the coefficient of the closest center. In particular, a quantized kernel least mean square (QKLMS) algorithm is developed, which is based on a simple online vector quantization method. The analytical study of the mean square convergence has been carried out. The energy conservation relation for QKLMS is established, and on this basis we arrive at a sufficient condition for mean square convergence, and a lower and upper bound on the theoretical value of the steady-state excess mean square error. Static function estimation and short-term chaotic time-series prediction examples are presented to demonstrate the excellent performance.

  2. Kernel-based tests for joint independence

    DEFF Research Database (Denmark)

    Pfister, Niklas; Bühlmann, Peter; Schölkopf, Bernhard

    2018-01-01

    if the $d$ variables are jointly independent, as long as the kernel is characteristic. Based on an empirical estimate of dHSIC, we define three different non-parametric hypothesis tests: a permutation test, a bootstrap test and a test based on a Gamma approximation. We prove that the permutation test......We investigate the problem of testing whether $d$ random variables, which may or may not be continuous, are jointly (or mutually) independent. Our method builds on ideas of the two variable Hilbert-Schmidt independence criterion (HSIC) but allows for an arbitrary number of variables. We embed...... the $d$-dimensional joint distribution and the product of the marginals into a reproducing kernel Hilbert space and define the $d$-variable Hilbert-Schmidt independence criterion (dHSIC) as the squared distance between the embeddings. In the population case, the value of dHSIC is zero if and only...

  3. Wilson Dslash Kernel From Lattice QCD Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Joo, Balint [Jefferson Lab, Newport News, VA; Smelyanskiy, Mikhail [Parallel Computing Lab, Intel Corporation, California, USA; Kalamkar, Dhiraj D. [Parallel Computing Lab, Intel Corporation, India; Vaidyanathan, Karthikeyan [Parallel Computing Lab, Intel Corporation, India

    2015-07-01

    Lattice Quantum Chromodynamics (LQCD) is a numerical technique used for calculations in Theoretical Nuclear and High Energy Physics. LQCD is traditionally one of the first applications ported to many new high performance computing architectures and indeed LQCD practitioners have been known to design and build custom LQCD computers. Lattice QCD kernels are frequently used as benchmarks (e.g. 168.wupwise in the SPEC suite) and are generally well understood, and as such are ideal to illustrate several optimization techniques. In this chapter we will detail our work in optimizing the Wilson-Dslash kernels for Intel Xeon Phi, however, as we will show the technique gives excellent performance on regular Xeon Architecture as well.

  4. The Relationship between Black Point and Fungi Species and Effects of Black Point on Seed Germination Properties in Bread Wheat

    OpenAIRE

    TOKLU, Faruk; AKGÜL, Davut Soner; BİÇİCİ, Mehmet; KARAKÖY, Tolga

    2014-01-01

    This study was undertaken to investigate the relationship between some fungi species and black point incidence and the effect of black point on seed weight, germination percentage, seedling emergence, seedling establishment, number of embryonic roots, and coleoptile length under field conditions in bread wheat. In this research, black-pointed and black point-free kernel samples of 5 bread wheat cultivars, namely Ceyhan-99, Doğankent-1, Yüreğir-89, Seyhan-95, and Adana-99 - commonly grown unde...

  5. A Kernel for Protein Secondary Structure Prediction

    OpenAIRE

    Guermeur , Yann; Lifchitz , Alain; Vert , Régis

    2004-01-01

    http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...

  6. Scalar contribution to the BFKL kernel

    International Nuclear Information System (INIS)

    Gerasimov, R. E.; Fadin, V. S.

    2010-01-01

    The contribution of scalar particles to the kernel of the Balitsky-Fadin-Kuraev-Lipatov (BFKL) equation is calculated. A great cancellation between the virtual and real parts of this contribution, analogous to the cancellation in the quark contribution in QCD, is observed. The reason of this cancellation is discovered. This reason has a common nature for particles with any spin. Understanding of this reason permits to obtain the total contribution without the complicated calculations, which are necessary for finding separate pieces.

  7. Weighted Bergman Kernels for Logarithmic Weights

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2010-01-01

    Roč. 6, č. 3 (2010), s. 781-813 ISSN 1558-8599 R&D Projects: GA AV ČR IAA100190802 Keywords : Bergman kernel * Toeplitz operator * logarithmic weight * pseudodifferential operator Subject RIV: BA - General Mathematics Impact factor: 0.462, year: 2010 http://www.intlpress.com/site/pub/pages/journals/items/pamq/content/vols/0006/0003/a008/

  8. Heat kernels and zeta functions on fractals

    International Nuclear Information System (INIS)

    Dunne, Gerald V

    2012-01-01

    On fractals, spectral functions such as heat kernels and zeta functions exhibit novel features, very different from their behaviour on regular smooth manifolds, and these can have important physical consequences for both classical and quantum physics in systems having fractal properties. This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical in honour of Stuart Dowker's 75th birthday devoted to ‘Applications of zeta functions and other spectral functions in mathematics and physics’. (paper)

  9. Exploiting graph kernels for high performance biomedical relation extraction.

    Science.gov (United States)

    Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

    2018-01-30

    Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM

  10. Registration of 'Tiger' wheat

    Science.gov (United States)

    ‘Tiger’ hard white winter wheat (Triticum aestivum L.) was developed at Research Center-Hays, Kansas State University and released by Kansas Agricultural Experiment Station in 2010. Tiger was selected from a three-way cross KS98H245/’Trego’//KS98HW518 made in 1999 at Hays, KS. The objective of this ...

  11. 21 CFR 184.1322 - Wheat gluten.

    Science.gov (United States)

    2010-04-01

    ... 21 Food and Drugs 3 2010-04-01 2009-04-01 true Wheat gluten. 184.1322 Section 184.1322 Food and... Substances Affirmed as GRAS § 184.1322 Wheat gluten. (a) Wheat gluten (CAS Reg. No. 8002-80-0) is the principal protein component of wheat and consists mainly of gliadin and glutenin. Wheat gluten is obtained...

  12. Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

    Science.gov (United States)

    Kwak, Nojun

    2016-05-20

    Recently, the nonlinear projection trick (NPT) was introduced enabling direct computation of coordinates of samples in a reproducing kernel Hilbert space. With NPT, any machine learning algorithm can be extended to a kernel version without relying on the so called kernel trick. However, NPT is inherently difficult to be implemented incrementally because an ever increasing kernel matrix should be treated as additional training samples are introduced. In this paper, an incremental version of the NPT (INPT) is proposed based on the observation that the centerization step in NPT is unnecessary. Because the proposed INPT does not change the coordinates of the old data, the coordinates obtained by INPT can directly be used in any incremental methods to implement a kernel version of the incremental methods. The effectiveness of the INPT is shown by applying it to implement incremental versions of kernel methods such as, kernel singular value decomposition, kernel principal component analysis, and kernel discriminant analysis which are utilized for problems of kernel matrix reconstruction, letter classification, and face image retrieval, respectively.

  13. Identification of leaf rust resistant gene Lr10 in Pakistani wheat ...

    African Journals Online (AJOL)

    Leaf (brown) rust is the major disease of wheat in Pakistan and other countries. The disease is more effectively controlled when several rust resistance genes are pyramided into a single line. Molecular survey was conducted to screen 25 Pakistan wheat germplasm for the presence of leaf rust resistance gene Lr10 using ...

  14. Sensitivity kernels for viscoelastic loading based on adjoint methods

    Science.gov (United States)

    Al-Attar, David; Tromp, Jeroen

    2014-01-01

    Observations of glacial isostatic adjustment (GIA) allow for inferences to be made about mantle viscosity, ice sheet history and other related parameters. Typically, this inverse problem can be formulated as minimizing the misfit between the given observations and a corresponding set of synthetic data. When the number of parameters is large, solution of such optimization problems can be computationally challenging. A practical, albeit non-ideal, solution is to use gradient-based optimization. Although the gradient of the misfit required in such methods could be calculated approximately using finite differences, the necessary computation time grows linearly with the number of model parameters, and so this is often infeasible. A far better approach is to apply the `adjoint method', which allows the exact gradient to be calculated from a single solution of the forward problem, along with one solution of the associated adjoint problem. As a first step towards applying the adjoint method to the GIA inverse problem, we consider its application to a simpler viscoelastic loading problem in which gravitationally self-consistent ocean loading is neglected. The earth model considered is non-rotating, self-gravitating, compressible, hydrostatically pre-stressed, laterally heterogeneous and possesses a Maxwell solid rheology. We determine adjoint equations and Fréchet kernels for this problem based on a Lagrange multiplier method. Given an objective functional J defined in terms of the surface deformation fields, we show that its first-order perturbation can be written δ J = int _{MS}K_{η }δ ln η dV +int _{t0}^{t1}int _{partial M}K_{dot{σ }} δ dot{σ } dS dt, where δ ln η = δη/η denotes relative viscosity variations in solid regions MS, dV is the volume element, δ dot{σ } is the perturbation to the time derivative of the surface load which is defined on the earth model's surface ∂M and for times [t0, t1] and dS is the surface element on ∂M. The `viscosity

  15. A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

    Science.gov (United States)

    Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

    2015-09-01

    Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

  16. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

    Science.gov (United States)

    Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

    2017-06-07

    Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

  17. Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

    Directory of Open Access Journals (Sweden)

    Massaine Bandeira e Sousa

    2017-06-01

    Full Text Available Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1 single-environment, main genotypic effect model (SM; (2 multi-environment, main genotypic effects model (MM; (3 multi-environment, single variance G×E deviation model (MDs; and (4 multi-environment, environment-specific variance G×E deviation model (MDe. Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB, and a nonlinear kernel Gaussian kernel (GK. The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets, having different numbers of maize hybrids evaluated in different environments for grain yield (GY, plant height (PH, and ear height (EH. Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied.

  18. A SNP-Based Molecular Barcode for Characterization of Common Wheat.

    Directory of Open Access Journals (Sweden)

    LiFeng Gao

    Full Text Available Wheat is grown as a staple crop worldwide. It is important to develop an effective genotyping tool for this cereal grain both to identify germplasm diversity and to protect the rights of breeders. Single-nucleotide polymorphism (SNP genotyping provides a means for developing a practical, rapid, inexpensive and high-throughput assay. Here, we investigated SNPs as robust markers of genetic variation for typing wheat cultivars. We identified SNPs from an array of 9000 across a collection of 429 well-known wheat cultivars grown in China, of which 43 SNP markers with high minor allele frequency and variations discriminated the selected wheat varieties and their wild ancestors. This SNP-based barcode will allow for the rapid and precise identification of wheat germplasm resources and newly released varieties and will further assist in the wheat breeding program.

  19. Kernel based subspace projection of near infrared hyperspectral images of maize kernels

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben

    2009-01-01

    In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods ......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data.......In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so...

  20. Effects of nitrogen and irrigation on gluten protein composition and their relationship to yellow berry disorder in wheat (triticum aestivum)

    International Nuclear Information System (INIS)

    Wong, B.R.; Felix, F.R.; Chavez, T

    2014-01-01

    In Mexico and the rest of the world, the presence of yellow berry (YB) in wheat grains (Triticum aestivum) has been related with poor quality, this defect is associated with low protein content in the grains. However, the quality of the wheat depends not only on the protein content, but also on the composition of the gluten proteins. The effect of the various agronomic factors on the composition of wheat gluten has been a subject of study worldwide. However, in Mexico, wheat quality still remains an issue, as there is a lack of knowledge regarding the optimal agronomic conditions to produce wheat with good-quality gluten. For this reason, the effects of nitrogen (N) rates and irrigations on the amount of gliadin subclasses, glutenin subunits (two main groups) and grain protein content as well as the relation of these proteins to the YB content in wheat grains were investigated. The experiment was conducted on arable farmland in the Valley of Empalme, Sonora, Mexico (27 degree 58' N, 110 degree 49' W; 10 m altitude), during the fall-winter period of 2009-2010. Tarachi, the hard wheat cultivar studied, was selected for its relative susceptibility to the presence of elevated YB content in mature wheat kernels. Three levels of N (75, 150 or 250 kg ha-1) and three levels of irrigation (1, 2 or 3 auxiliary irrigations) were studied. Using a N rate of 150 kg ha-1 with 3 auxiliary irrigations, wheat with good-quality gluten was obtained. The results suggest that the YB disorder is primarily related to the amount of protein in the wheat grain. (author)

  1. A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

    Science.gov (United States)

    Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2014-01-01

    Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

  2. LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

    Science.gov (United States)

    Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

    2018-05-07

    Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

  3. Kernel based eigenvalue-decomposition methods for analysing ham

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming

    2010-01-01

    methods, such as PCA, MAF or MNF. We therefore investigated the applicability of kernel based versions of these transformation. This meant implementing the kernel based methods and developing new theory, since kernel based MAF and MNF is not described in the literature yet. The traditional methods only...... have two factors that are useful for segmentation and none of them can be used to segment the two types of meat. The kernel based methods have a lot of useful factors and they are able to capture the subtle differences in the images. This is illustrated in Figure 1. You can see a comparison of the most...... useful factor of PCA and kernel based PCA respectively in Figure 2. The factor of the kernel based PCA turned out to be able to segment the two types of meat and in general that factor is much more distinct, compared to the traditional factor. After the orthogonal transformation a simple thresholding...

  4. Classification of maize kernels using NIR hyperspectral imaging

    DEFF Research Database (Denmark)

    Williams, Paul; Kucheryavskiy, Sergey V.

    2016-01-01

    NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....

  5. Ideal gas scattering kernel for energy dependent cross-sections

    International Nuclear Information System (INIS)

    Rothenstein, W.; Dagan, R.

    1998-01-01

    A third, and final, paper on the calculation of the joint kernel for neutron scattering by an ideal gas in thermal agitation is presented, when the scattering cross-section is energy dependent. The kernel is a function of the neutron energy after scattering, and of the cosine of the scattering angle, as in the case of the ideal gas kernel for a constant bound atom scattering cross-section. The final expression is suitable for numerical calculations

  6. Aphid-parasitoid community structure on genetically modified wheat.

    Science.gov (United States)

    von Burg, Simone; van Veen, Frank J F; Álvarez-Alfageme, Fernando; Romeis, Jörg

    2011-06-23

    Since the introduction of genetically modified (GM) plants, one of the main concerns has been their potential effect on non-target insects. Many studies have looked at GM plant effects on single non-target herbivore species or on simple herbivore-natural enemy food chains. Agro-ecosystems, however, are characterized by numerous insect species which are involved in complex interactions, forming food webs. In this study, we looked at transgenic disease-resistant wheat (Triticum aestivum) and its effect on aphid-parasitoid food webs. We hypothesized that the GM of the wheat lines directly or indirectly affect aphids and that these effects cascade up to change the structure of the associated food webs. Over 2 years, we studied different experimental wheat lines under semi-field conditions. We constructed quantitative food webs to compare their properties on GM lines with the properties on corresponding non-transgenic controls. We found significant effects of the different wheat lines on insect community structure up to the fourth trophic level. However, the observed effects were inconsistent between study years and the variation between wheat varieties was as big as between GM plants and their controls. This suggests that the impact of our powdery mildew-resistant GM wheat plants on food web structure may be negligible and potential ecological effects on non-target insects limited.

  7. Analysis and Implementation of Particle-to-Particle (P2P) Graphics Processor Unit (GPU) Kernel for Black-Box Adaptive Fast Multipole Method

    Science.gov (United States)

    2015-06-01

    implementation of the direct interaction called particle-to-particle kernel for a shared-memory single GPU device using the Compute Unified Device Architecture ...GPU-defined P2P kernel we developed using the Compute Unified Device Architecture (CUDA).9 A brief outline of the rest of this work follows. The...Employed The computing environment used for this work is a 64-node heterogeneous cluster consisting of 48 IBM dx360M4 nodes, each with one Intel Phi

  8. Embedded real-time operating system micro kernel design

    Science.gov (United States)

    Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

    2005-12-01

    Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

  9. Hadamard Kernel SVM with applications for breast cancer outcome predictions.

    Science.gov (United States)

    Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

    2017-12-21

    Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

  10. Parameter optimization in the regularized kernel minimum noise fraction transformation

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2012-01-01

    Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....

  11. Analysis of Advanced Fuel Kernel Technology

    International Nuclear Information System (INIS)

    Oh, Seung Chul; Jeong, Kyung Chai; Kim, Yeon Ku; Kim, Young Min; Kim, Woong Ki; Lee, Young Woo; Cho, Moon Sung

    2010-03-01

    The reference fuel for prismatic reactor concepts is based on use of an LEU UCO TRISO fissile particle. This fuel form was selected in the early 1980s for large high-temperature gas-cooled reactor (HTGR) concepts using LEU, and the selection was reconfirmed for modular designs in the mid-1980s. Limited existing irradiation data on LEU UCO TRISO fuel indicate the need for a substantial improvement in performance with regard to in-pile gaseous fission product release. Existing accident testing data on LEU UCO TRISO fuel are extremely limited, but it is generally expected that performance would be similar to that of LEU UO 2 TRISO fuel if performance under irradiation were successfully improved. Initial HTGR fuel technology was based on carbide fuel forms. In the early 1980s, as HTGR technology was transitioning from high-enriched uranium (HEU) fuel to LEU fuel. An initial effort focused on LEU prismatic design for large HTGRs resulted in the selection of UCO kernels for the fissile particles and thorium oxide (ThO 2 ) for the fertile particles. The primary reason for selection of the UCO kernel over UO 2 was reduced CO pressure, allowing higher burnup for equivalent coating thicknesses and reduced potential for kernel migration, an important failure mechanism in earlier fuels. A subsequent assessment in the mid-1980s considering modular HTGR concepts again reached agreement on UCO for the fissile particle for a prismatic design. In the early 1990s, plant cost-reduction studies led to a decision to change the fertile material from thorium to natural uranium, primarily because of a lower long-term decay heat level for the natural uranium fissile particles. Ongoing economic optimization in combination with anticipated capabilities of the UCO particles resulted in peak fissile particle burnup projection of 26% FIMA in steam cycle and gas turbine concepts

  12. Effects of Milling and Cooking Processes on the Deoxynivalenol Content in Wheat

    Directory of Open Access Journals (Sweden)

    Masayo Kushiro

    2008-11-01

    Full Text Available Deoxynivalenol (DON, vomitoxin is a natural-occuring mycotoxin mainly produced by Fusarium graminearum, a food-borne fungi widely distributed in crops and it is one of the most important mycotoxins in wheat and wheat-based foods and feeds. DON affects animal and human health causing diarrhea, vomiting, gastro-intestinal inflammation, and immunomodulation. Since the rate of the occurrence of DON in wheat is high, effective procedures to remove or eliminate DON from food products is essential to minimize exposures in those who consume large amounts of wheat. Cleaning prior to milling reduced to some extent the concentration of DON in final products. Since DON is distributed throughout the kernels, with higher content in the outer skin, milling is also effective in reducing the DON levels of wheat-based foods if bran and shorts are removed before thermal cooking. DON is water-soluble and cooking with larger amounts of water lowers DON content in products such as spaghetti and noodles. During baking or heating, DON is partially degraded to DON-related chemicals, whose toxicological effects are not studied well. This paper reviews the researches on the effects of milling and cooking on the DON level and discusses the perspectives of further studies.

  13. Genetic variability and fumonisin production by Fusarium proliferatum isolated from durum wheat grains in Argentina.

    Science.gov (United States)

    Palacios, S A; Susca, A; Haidukowski, M; Stea, G; Cendoya, E; Ramírez, M L; Chulze, S N; Farnochi, M C; Moretti, A; Torres, A M

    2015-05-18

    Fusarium proliferatum is a member of the Fusarium fujikuroi species complex (FFSC) involved in the maize ear rot together with Fusarium verticillioides, which is a very closely related species. Recently, different studies have detected natural fumonisin contamination in wheat kernels and most of them have shown that the main species isolated was F. proliferatum. Fusarium strains obtained from freshly harvested durum wheat samples (2008 to 2011 harvest seasons) from Argentina were characterized through a phylogenetic analysis based on translation elongation factor-1 alpha (EF-1α) and calmodulin (CaM) genes, determination of mating type alleles, and evaluation of fumonisin production capability. The strains were identified as F. proliferatum (72%), F. verticillioides (24%) and other Fusarium species. The ratio of mating type alleles (MAT-1 and MAT-2) obtained for both main populations suggests possible occurrence of sexual reproduction in the wheat fields, although this seems more frequent in F. proliferatum. Phylogenetic analysis revealed greater nucleotide variability in F. proliferatum strains than in F. verticillioides, however this was not related to origin, host or harvest year. The fumonisin-producing ability was detected in 92% of the strains isolated from durum wheat grains. These results indicate that F. proliferatum and F. verticillioides, among the fumonisin producing species, frequently contaminate durum wheat grains in Argentina, presenting a high risk for human and animal health. Copyright © 2015 Elsevier B.V. All rights reserved.

  14. Learning Rotation for Kernel Correlation Filter

    KAUST Repository

    Hamdi, Abdullah

    2017-08-11

    Kernel Correlation Filters have shown a very promising scheme for visual tracking in terms of speed and accuracy on several benchmarks. However it suffers from problems that affect its performance like occlusion, rotation and scale change. This paper tries to tackle the problem of rotation by reformulating the optimization problem for learning the correlation filter. This modification (RKCF) includes learning rotation filter that utilizes circulant structure of HOG feature to guesstimate rotation from one frame to another and enhance the detection of KCF. Hence it gains boost in overall accuracy in many of OBT50 detest videos with minimal additional computation.

  15. Research of Performance Linux Kernel File Systems

    Directory of Open Access Journals (Sweden)

    Andrey Vladimirovich Ostroukh

    2015-10-01

    Full Text Available The article describes the most common Linux Kernel File Systems. The research was carried out on a personal computer, the characteristics of which are written in the article. The study was performed on a typical workstation running GNU/Linux with below characteristics. On a personal computer for measuring the file performance, has been installed the necessary software. Based on the results, conclusions and proposed recommendations for use of file systems. Identified and recommended by the best ways to store data.

  16. Fixed kernel regression for voltammogram feature extraction

    International Nuclear Information System (INIS)

    Acevedo Rodriguez, F J; López-Sastre, R J; Gil-Jiménez, P; Maldonado Bascón, S; Ruiz-Reyes, N

    2009-01-01

    Cyclic voltammetry is an electroanalytical technique for obtaining information about substances under analysis without the need for complex flow systems. However, classifying the information in voltammograms obtained using this technique is difficult. In this paper, we propose the use of fixed kernel regression as a method for extracting features from these voltammograms, reducing the information to a few coefficients. The proposed approach has been applied to a wine classification problem with accuracy rates of over 98%. Although the method is described here for extracting voltammogram information, it can be used for other types of signals

  17. Reciprocity relation for multichannel coupling kernels

    International Nuclear Information System (INIS)

    Cotanch, S.R.; Satchler, G.R.

    1981-01-01

    Assuming time-reversal invariance of the many-body Hamiltonian, it is proven that the kernels in a general coupled-channels formulation are symmetric, to within a specified spin-dependent phase, under the interchange of channel labels and coordinates. The theorem is valid for both Hermitian and suitably chosen non-Hermitian Hamiltonians which contain complex effective interactions. While of direct practical consequence for nuclear rearrangement reactions, the reciprocity relation is also appropriate for other areas of physics which involve coupled-channels analysis

  18. Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods

    DEFF Research Database (Denmark)

    Arenas-Garcia, J.; Petersen, K.; Camps-Valls, G.

    2013-01-01

    correlation analysis (CCA), and orthonormalized PLS (OPLS), as well as their nonlinear extensions derived by means of the theory of reproducing kernel Hilbert spaces (RKHSs). We also review their connections to other methods for classification and statistical dependence estimation and introduce some recent...

  19. Particle models for discrete element modeling of bulk grain properties of wheat kernels

    Science.gov (United States)

    Recent research has shown the potential of discrete element method (DEM) in simulating grain flow in bulk handling systems. Research has also revealed that simulation of grain flow with DEM requires establishment of appropriate particle models for each grain type. This research completes the three-p...

  20. Kernel learning at the first level of inference.

    Science.gov (United States)

    Cawley, Gavin C; Talbot, Nicola L C

    2014-05-01

    Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Flixweed is more competitive than winter wheat under ozone pollution: evidences from membrane lipid peroxidation, antioxidant enzymes and biomass.

    Directory of Open Access Journals (Sweden)

    Cai-Hong Li

    Full Text Available To investigate the effects of ozone on winter wheat and flixweed under competition, two species were exposed to ambient, elevated and high [O3] for 30 days, planted singly or in mixculture. Eco-physiological responses were examined at different [O3] and fumigating time. Ozone reduced the contents of chlorophyll, increased the accumulation of H2O2 and malondialdehyde in both wheat and flixweed. The effects of competition on chlorophyll content of wheat emerged at elevated and high [O3], while that of flixweed emerged only at high [O3]. The increase of H2O2 and malondialdehyde of flixweed was less than that of wheat under the same condition. Antioxidant enzyme activities of wheat and flixweed were seriously depressed by perennial and serious treatment using O3. However, short-term and moderate fumigation increased the activities of SOD and POD of wheat, and CAT of flixweed. The expression levels of antioxidant enzymes related genes provided explanation for these results. Furthermore, the increase of CAT expression of flixweed was much higher than that of SOD and POD expression of wheat. Ozone and competition resulted in significant reductions in biomass and grain yield in both winter wheat and flixweed. However, the negative effects on flixweed were less than wheat. Our results demonstrated that winter wheat is more sensitive to O3 and competition than flixweed, providing valuable data for further investigation on responses of winter wheat to ozone pollution, in particular combined with species competition.

  2. Wheat ferritins: Improving the iron content of the wheat grain

    DEFF Research Database (Denmark)

    Borg, Søren; Brinch-Pedersen, Henrik; Tauris, Birgitte

    2012-01-01

    The characterization of the full complement of wheat ferritins show that the modern hexaploid wheat genome contains two ferritin genes, TaFer1 and TaFer2, each represented by three homeoalleles and placed on chromosome 5 and 4, respectively. The two genes are differentially regulated and expresse...

  3. Assessment of annual effective dose from natural radioactivity intake through wheat grain produced in Faisalabad, Pakistan

    International Nuclear Information System (INIS)

    Tufail, M.; Sabiha-Javied; Akhtar, N.; Akhter, J.

    2010-01-01

    Wheat is staple food of the people of Pakistan. Phosphate fertilizers, used to increase the yield of wheat, enhance the natural radioactivity in the agricultural fields from where radionuclides are transferred to wheat grain. A study was, therefore, carried out to investigate the uptake of radioactivity by wheat grain and to determine radiation doses received by human beings from the intake of foodstuffs made of wheat grain. Wheat was grown in a highly fertilized agricultural research farm at the Nuclear Institute of Agriculture and Biology (NIAB), Faisalabad, Pakistan. The activity concentration of 40 K, 226 Ra and 232 Th was measured in soil, single superphosphate (SSP) fertilizer, and wheat grain using an HPGe-based gamma-ray spectrometer. Soil to wheat grain transfer factors determined for 40 K, 226 Ra and 232 Th were 0.118 ± 0.021, 0.022 ± 0.004 and 0.036 ± 0.007, respectively, and the annual effective dose received by an adult person from the intake of wheat products was estimated to be 217 μSv. (author)

  4. Comparative physical mapping between wheat chromosome arm 2BL and rice chromosome 4.

    Science.gov (United States)

    Lee, Tong Geon; Lee, Yong Jin; Kim, Dae Yeon; Seo, Yong Weon

    2010-12-01

    Physical maps of chromosomes provide a framework for organizing and integrating diverse genetic information. DNA microarrays are a valuable technique for physical mapping and can also be used to facilitate the discovery of single feature polymorphisms (SFPs). Wheat chromosome arm 2BL was physically mapped using a Wheat Genome Array onto near-isogenic lines (NILs) with the aid of wheat-rice synteny and mapped wheat EST information. Using high variance probe set (HVP) analysis, 314 HVPs constituting genes present on 2BL were identified. The 314 HVPs were grouped into 3 categories: HVPs that match only rice chromosome 4 (298 HVPs), those that match only wheat ESTs mapped on 2BL (1), and those that match both rice chromosome 4 and wheat ESTs mapped on 2BL (15). All HVPs were converted into gene sets, which represented either unique rice gene models or mapped wheat ESTs that matched identified HVPs. Comparative physical maps were constructed for 16 wheat gene sets and 271 rice gene sets. Of the 271 rice gene sets, 257 were mapped to the 18-35 Mb regions on rice chromosome 4. Based on HVP analysis and sequence similarity between the gene models in the rice chromosomes and mapped wheat ESTs, the outermost rice gene model that limits the translocation breakpoint to orthologous regions was identified.

  5. The Kernel Estimation in Biosystems Engineering

    Directory of Open Access Journals (Sweden)

    Esperanza Ayuga Téllez

    2008-04-01

    Full Text Available In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than "a priori" assumption of the global target function shape (e.g., linear or quadratic. In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

  6. Aligning Biomolecular Networks Using Modular Graph Kernels

    Science.gov (United States)

    Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

    Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

  7. Formal truncations of connected kernel equations

    International Nuclear Information System (INIS)

    Dixon, R.M.

    1977-01-01

    The Connected Kernel Equations (CKE) of Alt, Grassberger and Sandhas (AGS); Kouri, Levin and Tobocman (KLT); and Bencze, Redish and Sloan (BRS) are compared against reaction theory criteria after formal channel space and/or operator truncations have been introduced. The Channel Coupling Class concept is used to study the structure of these CKE's. The related wave function formalism of Sandhas, of L'Huillier, Redish and Tandy and of Kouri, Krueger and Levin are also presented. New N-body connected kernel equations which are generalizations of the Lovelace three-body equations are derived. A method for systematically constructing fewer body models from the N-body BRS and generalized Lovelace (GL) equations is developed. The formally truncated AGS, BRS, KLT and GL equations are analyzed by employing the criteria of reciprocity and two-cluster unitarity. Reciprocity considerations suggest that formal truncations of BRS, KLT and GL equations can lead to reciprocity-violating results. This study suggests that atomic problems should employ three-cluster connected truncations and that the two-cluster connected truncations should be a useful starting point for nuclear systems

  8. Scientific Computing Kernels on the Cell Processor

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Samuel W.; Shalf, John; Oliker, Leonid; Kamil, Shoaib; Husbands, Parry; Yelick, Katherine

    2007-04-04

    The slowing pace of commodity microprocessor performance improvements combined with ever-increasing chip power demands has become of utmost concern to computational scientists. As a result, the high performance computing community is examining alternative architectures that address the limitations of modern cache-based designs. In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results, as well as our own implementations on a 3.2GHz Cell blade. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different mappings of the kernels and demonstrates a simple and effective programming model for Cell's unique architecture. Finally, we propose modest microarchitectural modifications that could significantly increase the efficiency of double-precision calculations. Overall results demonstrate the tremendous potential of the Cell architecture for scientific computations in terms of both raw performance and power efficiency.

  9. Delimiting areas of endemism through kernel interpolation.

    Science.gov (United States)

    Oliveira, Ubirajara; Brescovit, Antonio D; Santos, Adalberto J

    2015-01-01

    We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE), based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

  10. Delimiting areas of endemism through kernel interpolation.

    Directory of Open Access Journals (Sweden)

    Ubirajara Oliveira

    Full Text Available We propose a new approach for identification of areas of endemism, the Geographical Interpolation of Endemism (GIE, based on kernel spatial interpolation. This method differs from others in being independent of grid cells. This new approach is based on estimating the overlap between the distribution of species through a kernel interpolation of centroids of species distribution and areas of influence defined from the distance between the centroid and the farthest point of occurrence of each species. We used this method to delimit areas of endemism of spiders from Brazil. To assess the effectiveness of GIE, we analyzed the same data using Parsimony Analysis of Endemism and NDM and compared the areas identified through each method. The analyses using GIE identified 101 areas of endemism of spiders in Brazil GIE demonstrated to be effective in identifying areas of endemism in multiple scales, with fuzzy edges and supported by more synendemic species than in the other methods. The areas of endemism identified with GIE were generally congruent with those identified for other taxonomic groups, suggesting that common processes can be responsible for the origin and maintenance of these biogeographic units.

  11. New spring wheat varieties ‘Panianka’ and ‘Diana’

    Directory of Open Access Journals (Sweden)

    О. А. Демидов

    2016-12-01

    Full Text Available Purpose. To create new competitive spring wheat varieties. Methods. Field study, laboratory test. Results. Based on the competitive variety trial, bread spring wheat line ‘Lutescens 07-26’ has been selected due to high values of such traits as resistance to fungal diseases, grain qua­lity(protein content accounted for 15.0%, 1000 kernel weight (44.6 g productivity (3.92 t/ha and lodging resistance (9 points. In 2011, it was submitted to the State variety testing as ‘Panianka’ variety. Durum spring wheat line ‘Leukurum 08-11’ was characterized by a number of positive traits: quite a high productivity (3.05 t/ha, short stem (79 cm, resistance to fungal diseases and lodging(9 points, and in 2011 it was submitted to the State variety testing as ‘Diana’ variety. According to the results of the State variety testing in 2012–2014, spring wheat varieties ‘Panianka’ and ‘Diana’ in 2015 were put on the State Register of plant varieties suitable for dissemination in Ukraine. Conclusions. For farms in Forest-Steppe and Polissia zones of Ukraine, bread and durum spring wheat varieties were bred by V. M.Remeslo Myronivka Institute of Wheat of NAAS of Ukraine that demonstrated rather high potential of productivity and adaptability to stress conditions. This goes to prove that cultivation of domestic spring wheat varieties will promote formation of high and quality grain yields.

  12. Characterization of a Wheat Breeders' Array suitable for high-throughput SNP genotyping of global accessions of hexaploid bread wheat (Triticum aestivum).

    Science.gov (United States)

    Allen, Alexandra M; Winfield, Mark O; Burridge, Amanda J; Downie, Rowena C; Benbow, Harriet R; Barker, Gary L A; Wilkinson, Paul A; Coghill, Jane; Waterfall, Christy; Davassi, Alessandro; Scopes, Geoff; Pirani, Ali; Webster, Teresa; Brew, Fiona; Bloor, Claire; Griffiths, Simon; Bentley, Alison R; Alda, Mark; Jack, Peter; Phillips, Andrew L; Edwards, Keith J

    2017-03-01

    Targeted selection and inbreeding have resulted in a lack of genetic diversity in elite hexaploid bread wheat accessions. Reduced diversity can be a limiting factor in the breeding of high yielding varieties and crucially can mean reduced resilience in the face of changing climate and resource pressures. Recent technological advances have enabled the development of molecular markers for use in the assessment and utilization of genetic diversity in hexaploid wheat. Starting with a large collection of 819 571 previously characterized wheat markers, here we describe the identification of 35 143 single nucleotide polymorphism-based markers, which are highly suited to the genotyping of elite hexaploid wheat accessions. To assess their suitability, the markers have been validated using a commercial high-density Affymetrix Axiom ® genotyping array (the Wheat Breeders' Array), in a high-throughput 384 microplate configuration, to characterize a diverse global collection of wheat accessions including landraces and elite lines derived from commercial breeding communities. We demonstrate that the Wheat Breeders' Array is also suitable for generating high-density genetic maps of previously uncharacterized populations and for characterizing novel genetic diversity produced by mutagenesis. To facilitate the use of the array by the wheat community, the markers, the associated sequence and the genotype information have been made available through the interactive web site 'CerealsDB'. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  13. Difference in postprandial GLP-1 response despite similar glucose kinetics after consumption of wheat breads with different particle size in healthy men

    DEFF Research Database (Denmark)

    Eelderink, Coby; Noort, Martijn W J; Sozer, Nesli

    2017-01-01

    PURPOSE: Underlying mechanisms of the beneficial health effects of low glycemic index starchy foods are not fully elucidated yet. We varied the wheat particle size to obtain fiber-rich breads with a high and low glycemic response and investigated the differences in postprandial glucose kinetics...... and metabolic response after their consumption. METHODS: Ten healthy male volunteers participated in a randomized, crossover study, consuming (13)C-enriched breads with different structures; a control bread (CB) made from wheat flour combined with wheat bran, and a kernel bread (KB) where 85 % of flour...... in a difference in glucose response and kinetics, but in a pronounced difference in GLP-1 response. Thus, changing the processing conditions of wheat for baking bread can influence the metabolic response beyond glycemia and may therefore influence health....

  14. a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

    Science.gov (United States)

    Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

    2014-10-01

    In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

  15. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically

  16. Replacement Value of Palm Kernel Meal for Maize on Carcass ...

    African Journals Online (AJOL)

    This study was conducted to evaluate the effect of replacing maize with palm kernel meal on nutrient composition, fatty acid profile and sensory qualities of the meat of turkeys fed the dietary treatments. Six dietary treatments were formulated using palm kernel meal to replace maize at 0, 20, 40, 60, 80 and 100 percent.

  17. Effect of Palm Kernel Cake Replacement and Enzyme ...

    African Journals Online (AJOL)

    A feeding trial which lasted for twelve weeks was conducted to study the performance of finisher pigs fed five different levels of palm kernel cake replacement for maize (0%, 40%, 40%, 60%, 60%) in a maize-palm kernel cake based ration with or without enzyme supplementation. It was a completely randomized design ...

  18. Capturing option anomalies with a variance-dependent pricing kernel

    NARCIS (Netherlands)

    Christoffersen, P.; Heston, S.; Jacobs, K.

    2013-01-01

    We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

  19. Nonlinear Forecasting With Many Predictors Using Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter; Groenen, Patrick J.F.; Heij, Christiaan

    This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predi...

  20. Commutators of Integral Operators with Variable Kernels on Hardy ...

    Indian Academy of Sciences (India)

    Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 4. Commutators of Integral Operators with Variable Kernels on Hardy Spaces. Pu Zhang Kai Zhao. Volume 115 Issue 4 November 2005 pp 399-410 ... Keywords. Singular and fractional integrals; variable kernel; commutator; Hardy space.

  1. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

  2. Geodesic exponential kernels: When Curvature and Linearity Conflict

    DEFF Research Database (Denmark)

    Feragen, Aase; Lauze, François; Hauberg, Søren

    2015-01-01

    manifold, the geodesic Gaussian kernel is only positive definite if the Riemannian manifold is Euclidean. This implies that any attempt to design geodesic Gaussian kernels on curved Riemannian manifolds is futile. However, we show that for spaces with conditionally negative definite distances the geodesic...

  3. Denoising by semi-supervised kernel PCA preimaging

    DEFF Research Database (Denmark)

    Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai

    2014-01-01

    Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...

  4. Design and construction of palm kernel cracking and separation ...

    African Journals Online (AJOL)

    Design and construction of palm kernel cracking and separation machines. ... Username, Password, Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. Design and construction of palm kernel cracking and separation machines. JO Nordiana, K ...

  5. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

  6. Genetic relationship between plant growth, shoot and kernel sizes in ...

    African Journals Online (AJOL)

    Maize (Zea mays L.) ear vascular tissue transports nutrients that contribute to grain yield. To assess kernel heritabilities that govern ear development and plant growth, field studies were conducted to determine the combining abilities of parents that differed for kernel-size, grain-filling rates and shoot-size. Thirty two hybrids ...

  7. A relationship between Gel'fand-Levitan and Marchenko kernels

    International Nuclear Information System (INIS)

    Kirst, T.; Von Geramb, H.V.; Amos, K.A.

    1989-01-01

    An integral equation which relates the output kernels of the Gel'fand-Levitan and Marchenko inverse scattering equations is specified. Structural details of this integral equation are studied when the S-matrix is a rational function, and the output kernels are separable in terms of Bessel, Hankel and Jost solutions. 4 refs

  8. Boundary singularity of Poisson and harmonic Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2015-01-01

    Roč. 429, č. 1 (2015), s. 233-272 ISSN 0022-247X R&D Projects: GA AV ČR IAA100190802 Institutional support: RVO:67985840 Keywords : harmonic Bergman kernel * Poisson kernel * pseudodifferential boundary operators Subject RIV: BA - General Mathematics Impact factor: 1.014, year: 2015 http://www.sciencedirect.com/science/article/pii/S0022247X15003170

  9. Oven-drying reduces ruminal starch degradation in maize kernels

    NARCIS (Netherlands)

    Ali, M.; Cone, J.W.; Hendriks, W.H.; Struik, P.C.

    2014-01-01

    The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels

  10. Real time kernel performance monitoring with SystemTap

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    SystemTap is a dynamic method of monitoring and tracing the operation of a running Linux kernel. In this talk I will present a few practical use cases where SystemTap allowed me to turn otherwise complex userland monitoring tasks in simple kernel probes.

  11. Resolvent kernel for the Kohn Laplacian on Heisenberg groups

    Directory of Open Access Journals (Sweden)

    Neur Eddine Askour

    2002-07-01

    Full Text Available We present a formula that relates the Kohn Laplacian on Heisenberg groups and the magnetic Laplacian. Then we obtain the resolvent kernel for the Kohn Laplacian and find its spectral density. We conclude by obtaining the Green kernel for fractional powers of the Kohn Laplacian.

  12. Reproducing Kernels and Coherent States on Julia Sets

    Energy Technology Data Exchange (ETDEWEB)

    Thirulogasanthar, K., E-mail: santhar@cs.concordia.ca; Krzyzak, A. [Concordia University, Department of Computer Science and Software Engineering (Canada)], E-mail: krzyzak@cs.concordia.ca; Honnouvo, G. [Concordia University, Department of Mathematics and Statistics (Canada)], E-mail: g_honnouvo@yahoo.fr

    2007-11-15

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems.

  13. Reproducing Kernels and Coherent States on Julia Sets

    International Nuclear Information System (INIS)

    Thirulogasanthar, K.; Krzyzak, A.; Honnouvo, G.

    2007-01-01

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems

  14. A multi-scale kernel bundle for LDDMM

    DEFF Research Database (Denmark)

    Sommer, Stefan Horst; Nielsen, Mads; Lauze, Francois Bernard

    2011-01-01

    The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...

  15. Comparison of Kernel Equating and Item Response Theory Equating Methods

    Science.gov (United States)

    Meng, Yu

    2012-01-01

    The kernel method of test equating is a unified approach to test equating with some advantages over traditional equating methods. Therefore, it is important to evaluate in a comprehensive way the usefulness and appropriateness of the Kernel equating (KE) method, as well as its advantages and disadvantages compared with several popular item…

  16. An analysis of 1-D smoothed particle hydrodynamics kernels

    International Nuclear Information System (INIS)

    Fulk, D.A.; Quinn, D.W.

    1996-01-01

    In this paper, the smoothed particle hydrodynamics (SPH) kernel is analyzed, resulting in measures of merit for one-dimensional SPH. Various methods of obtaining an objective measure of the quality and accuracy of the SPH kernel are addressed. Since the kernel is the key element in the SPH methodology, this should be of primary concern to any user of SPH. The results of this work are two measures of merit, one for smooth data and one near shocks. The measure of merit for smooth data is shown to be quite accurate and a useful delineator of better and poorer kernels. The measure of merit for non-smooth data is not quite as accurate, but results indicate the kernel is much less important for these types of problems. In addition to the theory, 20 kernels are analyzed using the measure of merit demonstrating the general usefulness of the measure of merit and the individual kernels. In general, it was decided that bell-shaped kernels perform better than other shapes. 12 refs., 16 figs., 7 tabs

  17. Optimal Bandwidth Selection in Observed-Score Kernel Equating

    Science.gov (United States)

    Häggström, Jenny; Wiberg, Marie

    2014-01-01

    The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

  18. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, Jeroen

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  19. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, J.

    2002-01-01

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  20. (Neovossia indica ) resistance in wheat

    Indian Academy of Sciences (India)

    Unknown

    Screening and multiplication of different wheat varieties under laboratory conditions using in vitro culture techniques may speed up the resistance breeding programmes. Hence, the present investigations were planned to study the nature and magnitude of gene effects of inhibition zone formed by the wheat embryos, callus-.

  1. BRS 374 – Wheat cultivar

    Directory of Open Access Journals (Sweden)

    Eduardo Caierão

    2013-01-01

    Full Text Available BRS 374 is a wheat cultivar developed by Embrapa. It resulted from a cross between the F1 generation of PF 88618/Coker80.33 and Frontana/Karl. BRS 374 belongs to the soft wheat class, has a low plant height, a high potential grain yield, andwhite flour.

  2. Ultrafast convolution/superposition using tabulated and exponential kernels on GPU

    Energy Technology Data Exchange (ETDEWEB)

    Chen Quan; Chen Mingli; Lu Weiguo [TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 (United States)

    2011-03-15

    Purpose: Collapsed-cone convolution/superposition (CCCS) dose calculation is the workhorse for IMRT dose calculation. The authors present a novel algorithm for computing CCCS dose on the modern graphic processing unit (GPU). Methods: The GPU algorithm includes a novel TERMA calculation that has no write-conflicts and has linear computation complexity. The CCCS algorithm uses either tabulated or exponential cumulative-cumulative kernels (CCKs) as reported in literature. The authors have demonstrated that the use of exponential kernels can reduce the computation complexity by order of a dimension and achieve excellent accuracy. Special attentions are paid to the unique architecture of GPU, especially the memory accessing pattern, which increases performance by more than tenfold. Results: As a result, the tabulated kernel implementation in GPU is two to three times faster than other GPU implementations reported in literature. The implementation of CCCS showed significant speedup on GPU over single core CPU. On tabulated CCK, speedups as high as 70 are observed; on exponential CCK, speedups as high as 90 are observed. Conclusions: Overall, the GPU algorithm using exponential CCK is 1000-3000 times faster over a highly optimized single-threaded CPU implementation using tabulated CCK, while the dose differences are within 0.5% and 0.5 mm. This ultrafast CCCS algorithm will allow many time-sensitive applications to use accurate dose calculation.

  3. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, Ramzi

    2014-01-01

    The complications in anisotropic multi-parameter inversion lie in the trade-off between the different anisotropy parameters. We compute the tomographic waveform sensitivity kernels for a VTI acoustic medium perturbation as a tool to investigate this ambiguity between the different parameters. We use dynamic ray tracing to efficiently handle the expensive computational cost for 3-D anisotropic models. Ray tracing provides also the ray direction information necessary for conditioning the sensitivity kernels to handle anisotropy. The NMO velocity and η parameter kernels showed a maximum sensitivity for diving waves which results in a relevant choice of those parameters in wave equation tomography. The δ parameter kernel showed zero sensitivity; therefore it can serve as a secondary parameter to fit the amplitude in the acoustic anisotropic inversion. Considering the limited penetration depth of diving waves, migration velocity analysis based kernels are introduced to fix the depth ambiguity with reflections and compute sensitivity maps in the deeper parts of the model.

  4. Anatomically-aided PET reconstruction using the kernel method.

    Science.gov (United States)

    Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

    2016-09-21

    This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

  5. Open Problem: Kernel methods on manifolds and metric spaces

    DEFF Research Database (Denmark)

    Feragen, Aasa; Hauberg, Søren

    2016-01-01

    Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....

  6. Compactly Supported Basis Functions as Support Vector Kernels for Classification.

    Science.gov (United States)

    Wittek, Peter; Tan, Chew Lim

    2011-10-01

    Wavelet kernels have been introduced for both support vector regression and classification. Most of these wavelet kernels do not use the inner product of the embedding space, but use wavelets in a similar fashion to radial basis function kernels. Wavelet analysis is typically carried out on data with a temporal or spatial relation between consecutive data points. We argue that it is possible to order the features of a general data set so that consecutive features are statistically related to each other, thus enabling us to interpret the vector representation of an object as a series of equally or randomly spaced observations of a hypothetical continuous signal. By approximating the signal with compactly supported basis functions and employing the inner product of the embedding L2 space, we gain a new family of wavelet kernels. Empirical results show a clear advantage in favor of these kernels.

  7. Canola-Wheat Rotation versus Continuous Wheat for the Southern Plains

    OpenAIRE

    Duke, Jason C.; Epplin, Francis M.; Vitale, Jeffrey D.; Peeper, Thomas F.

    2009-01-01

    Crop rotations are not common in the wheat belt of the Southern Plains. After years of continuous wheat, weeds have become increasingly difficult and expensive to manage. Yield data were elicited from farmers and used to determine if canola-wheat-wheat rotations are economically competitive with continuous wheat in the region.

  8. THE IMPACT OF REFORMING WHEAT IMPORTING STATE-TRADING ENTERPRISES ON THE QUALITY OF WHEAT IMPORTED

    OpenAIRE

    Lavoie, Nathalie

    2003-01-01

    Recent surveys of wheat importers indicate that countries that import wheat via a state trader are less sensitive to quality issues in import decision making than countries that import wheat through private traders. This study examines conceptually and empirically the impact of the deregulation of wheat imports on the quality and source of wheat imports.

  9. Induced mutations of rust resistance genes in wheat

    International Nuclear Information System (INIS)

    McIntosh, R.A.

    1983-01-01

    Induced mutations are being used as a tool to study genes for resistance in wheat. It was found that Pm1 can be separated from Lr20 and Sr15, but these two react like a single pleiotropic gene. Mutants were further examined in crosses and backmutations have been attempted. (author)

  10. TEXTURE ANALYSIS OF EXTRUDED APPLE POMACE - WHEAT SEMOLINA BLENDS

    Directory of Open Access Journals (Sweden)

    Ivan Bakalov

    2016-03-01

    Full Text Available Apple pomace - wheat semolina blends were extruded in a laboratory single screw extruder (Brabender 20 DN, Germany. Effects apple pomace content, moisture content, screw speed, and temperature of final cooking zone on texture of extrudates were studied applying response surface methodology. The texture characteristics of the extrudates were measured using a TA.XT Plus Texture Analyser, Stable Micro Systems.

  11. Studies on productivity lodge resistance of radiation induced mutants of syrian local durum wheat

    Energy Technology Data Exchange (ETDEWEB)

    Elfares, A M; Ghazal, H M [Dep. of Radiation Agriculture, Syrian Atomic Energy Commision, Damascus, P.O. Box 6091, (Syrian Arab Republic)

    1995-10-01

    The aim of the research was to induce mutations characterized by lodging resistant and high yielding ability in two syrian local durum wheat land races. This research was carried out at two periods during 1983-1987 and from 1991-1993. At the first period, Kernels of Hourani and Senatore Cappelle were treated with 10, 15, 20, 25 and 30 K rad of gamma rays at the Laboratory of the commission of Syrian Atomic Energy to induce mutations. The treated Kernels were planted in 1983/1984 season. After that, selection were practicised on plants which characterized by good performance and lodging resistant. During the successive seasons, screening were made on mutant lines to keep out only lines which show adaptability to intensive cultivation. Second period includes testing of selected lines at two govern orates of syria (Raqqa and Aleppo) during three successive seasons; 1991/1992 and 1992/1993 under intensive cultivation conditions (fertilization, irrigation, stands, etc.).

  12. ADSORPTION OF COPPER FROM AQUEOUS SOLUTION BY ELAIS GUINEENSIS KERNEL ACTIVATED CARBON

    Directory of Open Access Journals (Sweden)

    NAJUA DELAILA TUMIN

    2008-08-01

    Full Text Available In this study, a series of batch laboratory experiments were conducted in order to investigate the feasibility of Elais Guineensis kernel or known as palm kernel shell (PKS-based activated carbon for the removal of copper from aqueous solution by the adsorption process. Investigation was carried out by studying the influence of initial solution pH, adsorbent dosage and initial concentration of copper. The particle size of PKS used was categorized as PKS–M. All batch experiments were carried out at a constant temperature of 30°C (±2°C using mechanical shaker that operated at 100 rpm. The single component equilibrium data was analyzed using Langmuir, Freundlich, Redlich-Peterson, Temkin and Toth adsorption isotherms.

  13. Higher-order predictions for splitting functions and coefficient functions from physical evolution kernels

    International Nuclear Information System (INIS)

    Vogt, A; Soar, G.; Vermaseren, J.A.M.

    2010-01-01

    We have studied the physical evolution kernels for nine non-singlet observables in deep-inelastic scattering (DIS), semi-inclusive e + e - annihilation and the Drell-Yan (DY) process, and for the flavour-singlet case of the photon- and heavy-top Higgs-exchange structure functions (F 2 , F φ ) in DIS. All known contributions to these kernels show an only single-logarithmic large-x enhancement at all powers of (1-x). Conjecturing that this behaviour persists to (all) higher orders, we have predicted the highest three (DY: two) double logarithms of the higher-order non-singlet coefficient functions and of the four-loop singlet splitting functions. The coefficient-function predictions can be written as exponentiations of 1/N-suppressed contributions in Mellin-N space which, however, are less predictive than the well-known exponentiation of the ln k N terms. (orig.)

  14. Performance and Emission of VCR-CI Engine with palm kernel and eucalyptus blends

    Directory of Open Access Journals (Sweden)

    Srinivas kommana

    2016-09-01

    Full Text Available This study aims at complete replacement of conventional diesel fuel by biodiesel. In order to achieve that, palm kernel oil and eucalyptus oil blend has been chosen. Eucalyptus oil was blended with methyl ester of palm kernel oil in 5%, 10% and 15% by volume. Tests were conducted with diesel fuel and blends on a 4 stroke VCR diesel engine for comparative analysis with 220 bar injection pressure and 19:1 compression ratio. All the test fuels were used in computerized 4 stroke single cylinder variable compression ratio engine at five different loads (0, 6, 12, 18 and 24 N m. Present investigation depicts the improved combustion and reduced emissions for the PKO85% + EuO15% blend when compared to diesel at full load conditions.

  15. Improved modeling of clinical data with kernel methods.

    Science.gov (United States)

    Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

    2012-02-01

    Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

  16. Durum wheat modeling

    DEFF Research Database (Denmark)

    Toscano, P.; Ranieri, R.; Matese, A.

    2012-01-01

    in predicting grain yield even before maturity for a wide range of growing conditions in the Mediterranean climate, governed by different annual weather patterns. The results were evaluated on the basis of regression and normalized root mean squared error with known crop yield statistics at regional level....... durum wheat during phenological development, at regional scale. We present an innovative system capable of predicting spatial yield variation and temporal yield fluctuation in long-term analysis, that are the main purposes of regional crop simulation study. The Delphi system was applied to simulate...

  17. A method for manufacturing kernels of metallic oxides and the thus obtained kernels

    International Nuclear Information System (INIS)

    Lelievre Bernard; Feugier, Andre.

    1973-01-01

    A method is described for manufacturing fissile or fertile metal oxide kernels, consisting in adding at least a chemical compound capable of releasing ammonia to an aqueous solution of actinide nitrates dispersing the thus obtained solution dropwise in a hot organic phase so as to gelify the drops and transform them into solid particles, washing drying and treating said particles so as to transform them into oxide kernels. Such a method is characterized in that the organic phase used in the gel-forming reactions comprises a mixture of two organic liquids, one of which acts as a solvent, whereas the other is a product capable of extracting the metal-salt anions from the drops while the gel forming reaction is taking place. This can be applied to the so-called high temperature nuclear reactors [fr

  18. Effects of location and year on grain yield and its components in wheat genotypes developed from seed irradiation treatment

    International Nuclear Information System (INIS)

    Amer, I.M.; El-Rassas, H.N.; Abdel-Aleem, M.M.

    1994-01-01

    Eight mutant lines derived from gamma ray treatments and their parental cultivar sokha 69 of bread wheat were evaluated for grain yield per feddan, straw yield per feddan, harvest index, spike length, spike yield and weight of 1000-kernels at two locations (El-Fayoum and Inshas) in two seasons, 1991/92 and 1992/93. Significant effects of location on yield and yield components were found and the year significantly affects all the studied traits except grain yield per feddan. A significant location genotype interaction was detected for spike length, 1000-kernel weight and straw yield per feddan. In addition, year genotype interaction was significant in weight of 1000-kernels, straw yield per feddan and harvest index. The statistical analysis showed a significant difference among genotypes over all environments for spike length, 1000-kernel weight, straw yield per feddan and harvest index. However, these did not reflect significant effect on grain yield per feddan over all environments because it has a highly compensation ability. Meanwhile, mutant L 1 2 -1 exhibited significantly higher straw yield than sokha 69, when averaged over two seasons at El-Fayoum. Mutant L 1 9 -1 gave higher weight of 1000-kernels, spike length and harvest index than the other genotypes at low-yielding location (Inshas). It seems to be stable over a wide range of environments. 3 tabs

  19. Learning molecular energies using localized graph kernels

    Science.gov (United States)

    Ferré, Grégoire; Haut, Terry; Barros, Kipton

    2017-03-01

    Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

  20. GABA Shunt in Durum Wheat

    Directory of Open Access Journals (Sweden)

    Petronia Carillo

    2018-02-01

    Full Text Available Plant responses to salinity are complex, especially when combined with other stresses, and involve many changes in gene expression and metabolic fluxes. Until now, plant stress studies have been mainly dealt only with a single stress approach. However, plants exposed to multiple stresses at the same time, a combinatorial approach reflecting real-world scenarios, show tailored responses completely different from the response to the individual stresses, due to the stress-related plasticity of plant genome and to specific metabolic modifications. In this view, recently it has been found that γ-aminobutyric acid (GABA but not glycine betaine (GB is accumulated in durum wheat plants under salinity only when it is combined with high nitrate and high light. In these conditions, plants show lower reactive oxygen species levels and higher photosynthetic efficiency than plants under salinity at low light. This is certainly relevant because the most of drought or salinity studies performed on cereal seedlings have been done in growth chambers under controlled culture conditions and artificial lighting set at low light. However, it is very difficult to interpret these data. To unravel the reason of GABA accumulation and its possible mode of action, in this review, all possible roles for GABA shunt under stress are considered, and an additional mechanism of action triggered by salinity and high light suggested.

  1. Stochastic subset selection for learning with kernel machines.

    Science.gov (United States)

    Rhinelander, Jason; Liu, Xiaoping P

    2012-06-01

    Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

  2. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Ling-Yu Duan

    2010-01-01

    Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  3. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Tian Yonghong

    2010-01-01

    Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  4. Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.

    Science.gov (United States)

    Han, Yina; Yang, Kunde; Ma, Yuanliang; Liu, Guizhong

    2014-01-01

    Our objective is to train support vector machines (SVM)-based localized multiple kernel learning (LMKL), using the alternating optimization between the standard SVM solvers with the local combination of base kernels and the sample-specific kernel weights. The advantage of alternating optimization developed from the state-of-the-art MKL is the SVM-tied overall complexity and the simultaneous optimization on both the kernel weights and the classifier. Unfortunately, in LMKL, the sample-specific character makes the updating of kernel weights a difficult quadratic nonconvex problem. In this paper, starting from a new primal-dual equivalence, the canonical objective on which state-of-the-art methods are based is first decomposed into an ensemble of objectives corresponding to each sample, namely, sample-wise objectives. Then, the associated sample-wise alternating optimization method is conducted, in which the localized kernel weights can be independently obtained by solving their exclusive sample-wise objectives, either linear programming (for l1-norm) or with closed-form solutions (for lp-norm). At test time, the learnt kernel weights for the training data are deployed based on the nearest-neighbor rule. Hence, to guarantee their generality among the test part, we introduce the neighborhood information and incorporate it into the empirical loss when deriving the sample-wise objectives. Extensive experiments on four benchmark machine learning datasets and two real-world computer vision datasets demonstrate the effectiveness and efficiency of the proposed algorithm.

  5. Deep Restricted Kernel Machines Using Conjugate Feature Duality.

    Science.gov (United States)

    Suykens, Johan A K

    2017-08-01

    The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

  6. Training Lp norm multiple kernel learning in the primal.

    Science.gov (United States)

    Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei

    2013-10-01

    Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. Effects of benzoic acid and cadmium toxicity on wheat seedlings

    Directory of Open Access Journals (Sweden)

    Kavita Yadav

    2013-06-01

    Full Text Available Benzoic acid (BA and Cd exhibit cumulative effects on plants due to their accumulation in the soil. The present study reports the effects of BA an allelochemical, Cd and their combinations on seed germination, seedling growth, biochemical parameters, and response of antioxidant enzymes in Triticum aestivum L. The experiment was conducted in sand supplemented with Hoagland nutrient solution. Benzoic acid was applied at concentrations of 0.5, 1.0, and 1.5 mM with or without Cd (7 mg L-1 to observe effects of allelochemical and Cd alone and in combination on wheat. Both stresses exhibited inhibitory effect on growth and metabolism of wheat seedlings. The allelochemical in single and combined treatments with Cd decreased seedling growth as compared to Cd stress. The two stresses significantly enhanced malondialdehyde content of wheat seedlings. The activity of other antioxidant enzymes, viz. superoxide dismutase (SOD, catalase (CAT, ascorbate peroxidase (APX, and guaiacol peroxidase (POX were also recorded. SOD increased in seedlings under the two stresses. CAT more prominently ameliorates the toxic effects of H2O2 as compared with APX and POX and protected wheat seedlings from oxidative stress. Allelochemical buttressed the toxic effect of Cd on wheat seedlings.

  8. Dual purpose wheat production with different levels of nitrogen topdressing

    Directory of Open Access Journals (Sweden)

    Éderson Luis Henz

    2016-04-01

    Full Text Available Currently, the practice of Crop-Livestock Integration is stimulated as a way of increasing the generation of foreign exchange for Brazil. Integrated systems improve land use efficiency as well as preserve, recover and increment or soil fertility. The aim of this research was to evaluate how different doses of nitrogen fertilization can affect production and quality of dual purpose wheat submitted to grazing. The experimental designed was randomized block with five treatments (0, 75, 150, 225 and 300 Kg N ha-1, like ammonium nitrate and four repetitions. The forage yield, the percentage crude protein (P=.0001 and acid detergent insoluble protein (P=.0054 had a linear increased because of the nitrogen addition doses. The crude protein percentage changed the estimate of all soluble carbohydrates (P=.0001 and non-fibrous carbohydrates (P=.0186, but did not influence the, nitrogen detergent fiber corrected with ash and proteins percentage contributing for content cell. The crops production (P=.0001 and the number of kernels per ear (P=.0001 showed significantly difference because of the nitrogen additions dose, increasing the number of fertile flowers. The nitrogen topdressing alters forage production, the chemical composition and the production of dual purpose wheat grains subjected to grazing.

  9. Mutation induction of protein variability in wheat and rice

    International Nuclear Information System (INIS)

    Narahari, P.; Bhatia, C.R.; Gopalakrishna, T.; Mitra, R.K.

    1976-01-01

    No high protein mutants of wheat have been obtained without depression of grain yield after screening a few thousand lines. The best wheat mutant identified in our programme so far is an erectoid mutant that has consistently shown about 1.5-2% points increase in protein over Kalyan sona for the last four years. Grain yield of the mutant is about 89% of the parent. No significant variation in amino composition is noted in the mutant. Preliminary analysis of over 200 macro mutants in three varieties of rice has resulted in identification of mutants with high protein content (10-22%) compared with 8.0 to 8.5% in the high yielding controls. The amino-acid composition of some of the mutant kernels do not show great deviation from the controls. All the high protein percentage mutants are lower in grain yield. Despite very high F 1 sterility in a cross involving the high protein genotype GMPR-51 and high yielding IR-8, several fertile F 2 plants resembling IR-8 have been isolated which on preliminary analysis have shown still higher protein content than GMPR-51, suggesting a transgressive mode of inheritance of this trait. (author)

  10. Genetic differentiation of the wheat leaf rust fungus Puccinia triticina in Pakistan and genetic relationship to other worldwide populations

    Science.gov (United States)

    Collections of Puccinia triticina, the wheat leaf rust pathogen, were obtained from Pakistan in 2008, 2010, 2011, 2013, and 2014. Collections were also obtained from Bhutan in 2013. Single uredinial isolates were derived and tested for virulence phenotype to 20 lines of Thatcher wheat that differ fo...

  11. Gradient-based adaptation of general gaussian kernels.

    Science.gov (United States)

    Glasmachers, Tobias; Igel, Christian

    2005-10-01

    Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

  12. On weights which admit the reproducing kernel of Bergman type

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    Zbigniew Pasternak-Winiarski

    1992-01-01

    Full Text Available In this paper we consider (1 the weights of integration for which the reproducing kernel of the Bergman type can be defined, i.e., the admissible weights, and (2 the kernels defined by such weights. It is verified that the weighted Bergman kernel has the analogous properties as the classical one. We prove several sufficient conditions and necessary and sufficient conditions for a weight to be an admissible weight. We give also an example of a weight which is not of this class. As a positive example we consider the weight μ(z=(Imz2 defined on the unit disk in ℂ.

  13. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus...... on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...

  14. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  15. Explicit signal to noise ratio in reproducing kernel Hilbert spaces

    DEFF Research Database (Denmark)

    Gomez-Chova, Luis; Nielsen, Allan Aasbjerg; Camps-Valls, Gustavo

    2011-01-01

    This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose...... an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted...

  16. Effects of Cd2+ on chlorophyll content in flag and grain yield of wheats

    International Nuclear Information System (INIS)

    Zhu Zhiyong; Li Youjun; Liu Yingjie; Duan Youqiang; Li Qiang; Hao Yufen; Guo Jia

    2011-01-01

    A field experiment was conducted with wheat cultivars Luohan 6 and Yumai 18 to investigate the effects of Cd 2+ stress on chlorophyll contents in flag leaves, flag leave area, thousand kernel weight, kernel filling velocity and yield of wheat. Results indicated that, under low Cd 2+ stress (10 mg/kg), the average contents of chlorophyll a + b of Luohan 6 reduced by 1.6%, however, its average area of flag leave and yield increased by 3.8% and 1.6%, respectively. At the same time, the average content of chlorophyll a + b, area of flag leave yield of Yumai 18 reduced 8.0%, 9.6% and 5.4%. Under high Cd 2+ stress (100 mg/kg), the average contents of chlorophyll a + b, areas of flag leaves and yields of Luohan 6 and Yumai 18 reduced by 29.2% and 30.5%, 6.3% and 17.4%, 16.7% and 36.7%, respectively. The results demonstrated that Cd 2+ restrained synthesis and accumulation of chlorophyll and its components. This study even showed that within a range of Cd 2+ concentration could promote the growth of flag leaves, and it also had an equal positive effect on yield of wheat if the Cd 2+ concentration in grains were not out of limit. The growth of flag leave and yield of wheat would be limited when Cd 2+ concentration exceed that range. Overall, Yumai 18 bore more poison from Cd 2+ than Luohan 6. (authors)

  17. Analysis of heterosis and quantitative trait loci for kernel shape related traits using triple testcross population in maize.

    Directory of Open Access Journals (Sweden)

    Lu Jiang

    Full Text Available Kernel shape related traits (KSRTs have been shown to have important influences on grain yield. The previous studies that emphasize kernel length (KL and kernel width (KW lack a comprehensive evaluation of characters affecting kernel shape. In this study, materials of the basic generations (B73, Mo17, and B73 × Mo17, 82 intermated B73 × Mo17 (IBM individuals, and the corresponding triple testcross (TTC populations were used to evaluate heterosis, investigate correlations, and characterize the quantitative trait loci (QTL for six KSRTs: KL, KW, length to width ratio (LWR, perimeter length (PL, kernel area (KA, and circularity (CS. The results showed that the mid-parent heterosis (MPH for most of the KSRTs was moderate. The performance of KL, KW, PL, and KA exhibited significant positive correlation with heterozygosity but their Pearson's R values were low. Among KSRTs, the strongest significant correlation was found between PL and KA with R values was up to 0.964. In addition, KW, PL, KA, and CS were shown to be significant positive correlation with 100-kernel weight (HKW. 28 QTLs were detected for KSRTs in which nine were augmented additive, 13 were augmented dominant, and six were dominance × additive epistatic. The contribution of a single QTL to total phenotypic variation ranged from 2.1% to 32.9%. Furthermore, 19 additive × additive digenic epistatic interactions were detected for all KSRTs with the highest total R2 for KW (78.8%, and nine dominance × dominance digenic epistatic interactions detected for KL, LWR, and CS with the highest total R2 (55.3%. Among significant digenic interactions, most occurred between genomic regions not mapped with main-effect QTLs. These findings display the complexity of the genetic basis for KSRTs and enhance our understanding on heterosis of KSRTs from the quantitative genetic perspective.

  18. IDENTIFICATION OF TECHNOLOGICALLY IMPORTANT GENES AND THEIR PRODUCTS IN THE COLLECTION OF BREAD WHEAT GENOTYPES

    Directory of Open Access Journals (Sweden)

    Milan Chňapek

    2015-02-01

    Full Text Available Wheat is the second most cultivated crop on the world and is very important plant for feed not only mankind but also animals. Because of this is necessary to develop new varieties with better properties. Bread making quality of wheat grain is one of the most important paramaters for quality evaluation. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE of wheat storage proteins and allelic specific polymerase chain reaction (AS-PCR are analysis suitable for identification, differentiation and characterization of bread wheat (Triticum aestivum L.. There were analysed 16 genotypes of new varieties of bread wheat in our work by SDS-PAGE and obtained results were verified by AS-PCR. Analysed genotypes of bread wheat genotypes were homogenous and single line with very good bread making quality. Our results confirmed hypothesis, that cultivated bread wheat genotypes are uniformed with high production and quality but there is a risk of sensitivity to environmental conditions. SDS-PAGE analyses of wheat grain proteins are fast and not very expensive technique, which provide us information of bread making quality of grains. However, there is possibility of environmental influence on protein synthesis and because of this is necessary to couple these analysis with analysis of DNA.

  19. Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

    Science.gov (United States)

    Cid, Jaime A; von Davier, Alina A

    2015-05-01

    Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

  20. Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

    Science.gov (United States)

    Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

    Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.