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Sample records for single kernel wheat

  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

    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...... 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...

  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 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...... indicating that protein metabolism is influenced by multiple drought events, the H-1 NMR spectra of the methanol extracts of flour from mature grains revealed that the amount of fumaric acid is particularly sensitive to water deficits....

  3. 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...

  4. 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.

  5. 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.

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

    Indian Academy of Sciences (India)

    2011-12-02

    Dec 2, 2011 ... Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level? FA CUI1, 2†, ANMING DING1†, JUN LI1, 3†, CHUNHUA ZHAO1†, XINGFENG LI1, DESHUN FENG1,. XIUQIN WANG4, LIN WANG1, 5, JURONG GAO1 and HONGGANG WANG1∗. 1State Key Laboratory of Crop ...

  7. Pest development possibility in storage on the kernels and spikes of spelt wheat (Triticum spelta)

    OpenAIRE

    Almaši, Radmila; Poslončec, Danijela

    2012-01-01

    Storing the spelt wheat (Triticum spelta) depends of the type of storage. If we stored spikes, which contains two kernel of spelt tightly wrapped with tailings, development and reproduction of the most important pests is limited or impossible. Great impacts on the stored pests progeny and percentage of damaged kernels have the number of available kernel and the way of storage (kernels-spikes). Grain moth (Sitotroga cerealella Oliv.) developed more numerous progeny when spelt wheat stores in k...

  8. Wheat curl mite (Acari: Eriophyidae) dispersal and its relationship with kernel red streaking in maize.

    Science.gov (United States)

    Liu, J; Lee, E A; Sears, M K; Schaafsma, A W

    2005-10-01

    Wheat curl mites, Aceria tosichella Keifer, dispersing from wheat (Triticum spp.) to nearby corn (Zea mays L.) fields play a role in the development of kernel red streaking in corn. These studies were undertaken to verify the relationship of wheat curl mite to kernel red streaking, to determine whether wheat is the main source of curl mites dispersing into corn and to determine whether planting corn in temporal or spatial isolation of wheat is a valid management strategy. These studies were conducted on farm fields using sticky traps to monitor mites, followed by sampling mature grain for kernel streaking in southwestern Ontario from 1999 to 2002. The dominant source mites were winter wheat. Mite dispersal occurred during the first 3 wk of winter wheat maturation after the wheat had reached Zadoks stage 87. Mite dispersal corresponded to prevailing winds in the area with the lowest number of mites and the lowest severity of kernel red streaking occurring 60 m from wheat fields planted to the north, south, and east of cornfields and 90 m from wheat fields planted to the west of cornfields. The severity of kernel red streaking was positively correlated with the density of wheat curl mites in corn; however, the correlation was weak and kernel red streaking was still high in many cornfields when few or no mites were present. These findings suggest that wheat curl mite migration into corn is not entirely predictive of the incidence and severity of kernel red streaking.

  9. 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 ...

  10. 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...

  11. 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...

  12. 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 ...

  13. VARIABILITY OF NUMBER OF KERNELS PER SPIKE IN WHEAT CULTIVARS (Triticum aestivum L.

    Directory of Open Access Journals (Sweden)

    Desimir KNEZEVIC

    2012-09-01

    Full Text Available In this paper was analyzed number of kernels per spike in 20 genetically divergent wheat cultivars originated from different breeding centers in Serbia. Investigation conducted during two seasons which characterized different climatic condition. For analysis used samples of 60 wheat plants (20 plants in 3 replications which were harvested in full maturity stage. The differences in average values for number of kernels per spike in studied cultivars were determined. The variability of number of kernels per spike was established. In average, number of kernels per spike for all cultivars was higher in second year 72.22 than in first experimental year 68.73. The highest number of kernels/spike in both year expressed Tanjugovka cultivar and the lowest Yugoslavia cultivar. Average value of coefficientvariation for all cultivars varied from 14.19 in first year to 12.92 in second year. Average number of kernels per spike for both year of growing, varied from 54.56 in cultivar Yugoslavia to 77.83 in cultivar Tanjugovka. Significant differences for number of kernels/spike were found among cultivars in both years as well between years. Heritability in wide sense for number of kernels/spike was 79.13%.

  14. Evaluation of visco-elastic properties of conditioned wheat kernels and their doughs using a compression test under small strain.

    Science.gov (United States)

    Ponce-García, Néstor; Ramírez-Wong, Benjamín; Torres-Chávez, Patricia I; Figueroa-Cárdenas, Juan de Dios; Serna-Saldívar, Sergio O; Cortez-Rocha, Mario O; Escalante-Aburto, Anayansi

    2017-03-01

    The aim of this research was to evaluate the visco-elastic properties of conditioned wheat kernels and their doughs by applying the compression test under a small strain. Conditioned wheat kernels and their doughs, from soft and hard wheat classes were evaluated for total work (W t ), elastic work (W e ) and plastic work (W p ). Soft wheat kernels showed lower W e than W p , while the hard wheat kernels had a W e that was higher than W p . Regarding dough visco-elasticity, cultivars from soft and hard wheat showed higher W p than W e . The degree of elasticity (DE%) of the conditioned wheat kernel related to its dough decreased ∼46% in both wheat classes. The W t , W e and W p from the soft wheat kernel and dough correlated with physico-chemical and farinographic flour tests. The W t , W p and the maximum compression force (F max ) of the dough from hard wheat class presented highly significant negative correlations with wet gluten. The visco-elasticity parameters from compression test presented significant differences among conditioned wheat classes and their doughs. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

  15. THE EFFECT OF INSECT DAMAGED KERNELS (IDK AND SPROUTED WHEAT KERNELS (SWK PARAMETERS ON BAKERY PROPERTIES OF SOME ROMANIAN WHEAT SAMPLES

    Directory of Open Access Journals (Sweden)

    Ciprian-Nicolae Popa

    2017-07-01

    Full Text Available It had been analyzed the impact of two key parameters, namely insect damaged kernels (IDK and sprouted wheat kernels (SWK, on quality parameters of Romanian wheat samples from 2016 harvest. The results showed that IDK had a significant influence on all the quality parameters of wheat, with the exception of Falling Number. The increase of IDK very significant decreased the values of: Hectolitric mass (r = - 0.407 ***, Moisture (r = - 0.263 **, Gluten Index (r = 0.297 ** and increased very significant the values of Protein content (r = 0.477 ***, Wet gluten (r = 0.398 *** and Gluten deformation index (r = 0.620 ***. SWK was correlated negative very significant with Falling Number (r = -0.602 *** and positive significant with Moisture (r = 0.294 *. Also, between IDK and SWK it was established a significant negative correlation (r = -0.337 *. The results showed that the two parameters had a notable influence on the enzymatic activity of wheat. Thus, IDK significantly influenced proteolytic activity, while SWK significantly influenced amylolytic activity. Higher values than 3% for IDK parameter and respectively 4.5% for SWK parameter led to gradual loss of the bakery qualities of analyzed wheat samples.

  16. 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/

  17. 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.  

  18. Soft kernel durum wheat -- a new bakery ingredient?

    Science.gov (United States)

    “Bread wheat”, also known as “common wheat” (Triticum aestivum L.), is a leading cereal that sustains humankind. Current worldwide production stands at over 700 million metric tons produced from around 220 million hectares. In contrast, durum wheat (Triticum turgidum subsp. durum) is grown on about ...

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

    Indian Academy of Sciences (India)

    2011-12-02

    Dec 2, 2011 ... Improvement Center, College of Agronomy, Shandong Agricultural University, Taian 271018, People's Republic of China. 2Center for Agricultural Resources Research, Institute of .... cultural Sciences, Shandong, China, in 2003; Jimai 20 and. Yannong 19, two superior quality wheat varieties, are multi-.

  20. 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, ...

  1. 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.

  2. 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...

  3. Microwave-based treatments of wheat kernels do not abolish gluten epitopes implicated in celiac disease.

    Science.gov (United States)

    Gianfrani, Carmen; Mamone, Gianfranco; la Gatta, Barbara; Camarca, Alessandra; Di Stasio, Luigia; Maurano, Francesco; Picascia, Stefania; Capozzi, Vito; Perna, Giuseppe; Picariello, Gianluca; Di Luccia, Aldo

    2017-03-01

    Microwave based treatment (MWT) of wet wheat kernels induced a striking reduction of gluten, up to gluten-free. In contrast, analysis of gluten peptides by G12 antibody-based ELISA, mass spectrometry-based proteomics and in vitro assay with T cells of celiac subjects, indicated no difference of antigenicity before and after MWT. SDS-PAGE analysis and Raman spectroscopy demonstrated that MWT simply induced conformational modifications, reducing alcohol solubility of gliadins and altering the access of R5-antibody to the gluten epitopes. Thus, MWT neither destroys gluten nor modifies chemically the toxic epitopes, contradicting the preliminary claims that MWT of wheat kernels detoxifies gluten. This study provides evidence that R5-antibody ELISA alone is not effective to determine gluten in thermally treated wheat products. Gluten epitopes in processed wheat should be monitored using strategies based on combined immunoassays with T cells from celiacs, G12-antibody ELISA after proteolysis and proper molecular characterization. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. 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

  5. Analysis of ergosterol in single kernel and ground grain by gas chromatography-mass spectrometry.

    Science.gov (United States)

    Dong, Yanhong; Steffenson, Brian J; Mirocha, Chester J

    2006-06-14

    A method for analyzing ergosterol in a single kernel and ground barley and wheat was developed using gas chromatography-mass spectrometry (GC-MS). Samples were saponified in methanolic KOH. Ergosterol was extracted by "one step" hexane extraction and subsequently silylated by N-trimethylsilylimidazole/trimethylchlorosilane (TMSI/TMCS) reagent at room temperature. The recoveries of ergosterol from ground barley were 96.6, 97.1, 97.1, 88.5, and 90.3% at the levels of 0.2, 1, 5, 10, and 20 microg/g (ppm), respectively. The recoveries from a single kernel were between 93.0 and 95.9%. The precision (coefficient of variance) of the method was in the range 0.8-12.3%. The method detection limit (MDL) and the method quantification limit (MQL) were 18.5 and 55.6 ng/g (ppb), respectively. The ergosterol analysis method developed can be used to handle 80 samples daily by one person, making it suitable for screening cereal cultivars for resistance to fungal infection. The ability for detecting low levels of ergosterol in a single kernel provides a tool to investigate early fungal invasion and to study mechanisms of resistance to fungal diseases.

  6. Impact of genetic and climatic factors on parameters of breadmaking quality of wheat kernel and flour starch component

    Directory of Open Access Journals (Sweden)

    Živančev Dragan

    2017-01-01

    Full Text Available This study investigates how genetic and climatic factors affect parameters of breadmaking quality of wheat kernel and flour starch component. Nine wheat cultivars with different combinations of HMW-GS were grown in three production years. Various rheological devices such as Falling Number (FN, Farinograph, Amylograph, Mixolab and SDmatic were used for characterization of milled wheat samples. The most results showed that climatic factors affected parameters of breadmaking quality of wheat kernel and flour starch component more than HMW-GS composition. However, some results of the bread making quality parameters that are considered to be very reliable indicators of changes in starch component of wheat in wet years, such as FN and maximum peak of viscosity by Amylograph, were dependent of HMW-GS composition.

  7. Single aflatoxin contaminated corn kernel analysis with fluorescence hyperspectral image

    Science.gov (United States)

    Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Ononye, Ambrose; Brown, Robert L.; Cleveland, Thomas E.

    2010-04-01

    Aflatoxins are toxic secondary metabolites of the fungi Aspergillus flavus and Aspergillus parasiticus, among others. Aflatoxin contaminated corn is toxic to domestic animals when ingested in feed and is a known carcinogen associated with liver and lung cancer in humans. Consequently, aflatoxin levels in food and feed are regulated by the Food and Drug Administration (FDA) in the US, allowing 20 ppb (parts per billion) limits in food and 100 ppb in feed for interstate commerce. Currently, aflatoxin detection and quantification methods are based on analytical tests including thin-layer chromatography (TCL) and high performance liquid chromatography (HPLC). These analytical tests require the destruction of samples, and are costly and time consuming. Thus, the ability to detect aflatoxin in a rapid, nondestructive way is crucial to the grain industry, particularly to corn industry. Hyperspectral imaging technology offers a non-invasive approach toward screening for food safety inspection and quality control based on its spectral signature. The focus of this paper is to classify aflatoxin contaminated single corn kernels using fluorescence hyperspectral imagery. Field inoculated corn kernels were used in the study. Contaminated and control kernels under long wavelength ultraviolet excitation were imaged using a visible near-infrared (VNIR) hyperspectral camera. The imaged kernels were chemically analyzed to provide reference information for image analysis. This paper describes a procedure to process corn kernels located in different images for statistical training and classification. Two classification algorithms, Maximum Likelihood and Binary Encoding, were used to classify each corn kernel into "control" or "contaminated" through pixel classification. The Binary Encoding approach had a slightly better performance with accuracy equals to 87% or 88% when 20 ppb or 100 ppb was used as classification threshold, respectively.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. [Effects of sprinkler irrigation on the plant nitrogen accumulation and translocation and kernel protein content of winter wheat].

    Science.gov (United States)

    Yao, Su-mei; Kang, Yue-hu; Ru, Zhen-gang; Liu, Ming-jiu; Yang, Wen-ping; Li, Gan

    2013-08-01

    Taking wheat cultivar Bainong AK58 as test material, a field experiment was conducted to study the plant nitrogen accumulation and translocation and kernel protein content of winter wheat under sprinkler irrigation and surface irrigation, aimed to understand the differences in the nitrogen metabolism characteristics of winter wheat under different irrigation regimes. At booting stage, no significant difference was observed in the total amount of plant nitrogen accumulation between sprinkler irrigation and surface irrigation; while from booting stage to maturing stage, the total amount of plant nitrogen accumulation under sprinkler irrigation was significantly higher. Under sprinkler irrigation, the translocation amount and contribution rate of the nitrogen stored in leaf, glume, stem and sheath at pre-anthesis to the kernel increased, while the contribution rate of the assimilated nitrogen after anthesis to the kernel nitrogen declined. Both the relative protein content and the total protein yield in the kernel increased significantly under sprinkler irrigation. In conclusion, sprinkler irrigation could significantly regulate the nitrogen translocation and kernel protein accumulation of winter wheat.

  10. 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.

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

    African Journals Online (AJOL)

    Also, source levels were manipulated through 50% spikelet removal at anthesis to evaluate cultivar source/sink limitations to kernel growth. The results depicted that grain yield, kernel number per spike and 1000 kernel weight were reduced by 24.1%, 9.2% and 23.7% in warmer environment, respectively. Hence, kernel ...

  12. Factors affecting laboratory bioassays with diatomaceous earth on stored wheat: effect of insect density, grain quantity, and cracked kernel containment.

    Science.gov (United States)

    Kavallieratos, Nickolas G; Athanassiou, Christos G; Mpakou, Flora D; Mpassoukou, Argyro E

    2007-10-01

    Laboratory bioassays were carried out to evaluate the effect of insect density (10, 30, 60, and 100 adults), wheat quantity (10, 30, 60, and 100 g), and cracked kernel containment (5, 15, 30, and 50%) on the efficacy of diatomaceous earth (DE). Three beetle species, Sitophilus oryzae (L.), Rhyzopertha dominica (F.), and Tribolium confusum Jacquelin du Val, as well as two DE formulations, Insecto and SilicoSec, and one DE enhanced with pyrethrum, PyriSec (all commercially available) were tested. In the first two series of bioassays, the three DE formulations were applied at three dose rates, 500, 1000 and 1,500 ppm. In the third series, the dose rates used were 500 and 1,000 ppm. Dead adults were counted 14 d later. For insect density, wheat quantity, and cracked kernel containment, significant differences were noted in mortality levels of the tested species among the three DE formulations and among doses. No significant differences were noted in the mortality levels among the four adult densities of any of the insects tested. The increase of wheat quantity used in the bioassays increased significantly adult mortality of T. confusum. The increase of cracked wheat containment decreased significantly adult mortality of S. oryzae.

  13. 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

  14. Feasibility of detecting Aflatoxin B1 in single maize kernels using hyperspectral imaging

    Science.gov (United States)

    The feasibility of detecting Aflatoxin B1 (AFB1) in single maize kernel inoculated with Aspergillus flavus conidia in the field, as well as its spatial distribution in the kernels, was assessed using near-infrared hyperspectral imaging (HSI) technique. Firstly, an image mask was applied to a pixel-b...

  15. 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 ...

  16. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    easily implemented and is suitable for large data sets, like those in data mining appli- cations. Experimental results show that, with a small loss of quality, the proposed method can significantly reduce the time taken than the conventional kernel k-means cluster- ing method. The proposed method is also compared with other ...

  17. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    This approach has reduced both time complexity and memory requirements. However, the clustering result of this method will be very much deviated form that obtained using the conventional kernel k-means method. This is because of the fact that pseudo cluster centers in the input space may not represent the exact cluster ...

  18. Does cyclic water stress damage wheat yield more than a single stress?

    Science.gov (United States)

    Ding, Jinfeng; Huang, Zhengjin; Zhu, Min; Li, Chunyan; Zhu, Xinkai; Guo, Wenshan

    2018-01-01

    The occurrence of water stress during wheat growth is more frequent due to climate change. Three experiments (cyclic drought, cyclic waterlogging, and cyclic drought plus waterlogging) were conducted to investigate the effects of mild and severe cyclic/single water stress at elongation and heading stages on winter wheat (Triticum aestivum L.) yield. The effect of either mild drought at elongation or mild waterlogging at heading on wheat yield was not significant; however, significance did occur under other single water stresses. As the stress becomes more severe, the yield loss significantly increases. Extreme drought/waterlogging treatment at elongation caused a greater yield penalty than stress at heading stage. Except the combination of mild drought and mild waterlogging treatment, cyclic water stress significantly decreased wheat yields. The decrease in wheat yield under cyclic severe drought and waterlogging was significantly higher than any other treatment, with percentage decreases of 71.52 and 73.51%, respectively. In general, a yield reduction from mild cyclic water stress did not indicate more severe damage than single treatments; in contrast, grain yield suffered more when water stress occurred again after severe drought and waterlogging. Drought during elongation significantly decreased kernel number, whereas drought at heading/waterlogging during elongation and heading decreased the spike weight, which might be the main reason for the yield penalty. Furthermore, water stress caused variation in the decrease of total biomass and/or harvest index. The present study indicates comprehensive understanding of the types, degree, and stages of water stress are essential for assessing the impact of multiple water stresses on wheat yield.

  19. 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 2 O gasification than WS and PS biochars. A longer residence time and addition of steam were found to be beneficial during PKS biochar gasification.

  20. 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)

  1. Denoising of brain DW-MR data by single and multiple diffusion kernels Denoising of brain DW-MR data by single and multiple diffusion kernels

    Directory of Open Access Journals (Sweden)

    Manzar Ashtari

    2012-02-01

    Full Text Available Las imágenes por resonancia magnética pesadas en difusión son ampliamente utilizadaspara el estudio de las estructuras cerebrales dentro de la materia blanca del cerebro. Sinembargo, recuperar las orientaciones de los axones puede ser susceptible a errores por elruido dentro de la señal. Una regularización espacial puede mejorar la estimación, perodebe ser realizada cuidadosamente dado que puede remover información espacial ó introducirfalsas orientaciones. En este trabajo se investigaron las ventajas de aplicar un filtroanisotrópico basado en simples y múltiples kerneles de orientación de manojos de axones.Para esto, hemos calculado kerneles locales de difusión basados en modelos de tensoresde difusión y multi tensores de difusión. Mostraremos los beneficios de nuestra propuestaen 3 tipos diferentes de imágenes obtenidas por resonancia magnética pesada en difusión:Datos sintéticos, imágenes humanas tomadas en vivo, y datos obtenidos de un fantasmasimulador de difusión.Diffusion Weighted Magnetic Resonance Imaging is widely used to study the structure ofthe fiber pathways of white matter in the brain. However, the recovered axon orientationscan be prone to error because of the low signal to noise ratio. Spatial regularization canreduce the error, but it must be done carefully so that real spatial information is not removedand false orientations are not introduced. In this paper we investigate the advantagesof applying an anisotropic filter based on single and multiple axon bundle orientation kernels.To this end, we compute local diffusion kernels based on Diffusion Tensor and multiDiffusion Tensor models. We show the benefits of our approach to three different types ofDW-MRI data: synthetic, in vivo human, and acquired from a diffusion phantom.

  2. 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).

  3. Single determinant N-representability and the kernel energy method applied to water clusters.

    Science.gov (United States)

    Polkosnik, Walter; Massa, Lou

    2017-10-24

    The Kernel energy method (KEM) is a quantum chemical calculation method that has been shown to provide accurate energies for large molecules. KEM performs calculations on subsets of a molecule (called kernels) and so the computational difficulty of KEM calculations scales more softly than full molecule methods. Although KEM provides accurate energies those energies are not required to satisfy the variational theorem. In this article, KEM is extended to provide a full molecule single-determinant N-representable one-body density matrix. A kernel expansion for the one-body density matrix analogous to the kernel expansion for energy is defined. This matrix is converted to a normalized projector by an algorithm due to Clinton. The resulting single-determinant N-representable density matrix maps to a quantum mechanically valid wavefunction which satisfies the variational theorem. The process is demonstrated on clusters of three to twenty water molecules. The resulting energies are more accurate than the straightforward KEM energy results and all violations of the variational theorem are resolved. The N-representability studied in this article is applicable to the study of quantum crystallography. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. Fungal flora and aflatoxin contamination in Pakistani wheat kernels (Triticum aestivum L. and their attribution in seed germination

    Directory of Open Access Journals (Sweden)

    Muhammad Asif Asghar

    2016-07-01

    . Germination rates in healthy and contaminated wheat kernels were 84.6% and 45.2%, respectively. Based on the obtained results, it was concluded that the levels of fungal pathogen and AF contamination in Pakistani-grown wheat are not a potential threat to consumer health. However, control procedures along with a strict monitoring policy are mandatory to further minimize the prevalence of fungal carriers and the potency of AFs in crops cultivated in Pakistan.

  5. 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.

  6. Single-Feature Polymorphism Mapping in Bread Wheat

    Directory of Open Access Journals (Sweden)

    Travis W. Banks

    2009-07-01

    Full Text Available Probe hybridization data from the Affymetrix GeneChip platform can be used to identify genetic polymorphisms. Developed from gene expression data, these single-feature polymorphism (SFP markers are located in or are tightly associated with gene sequences. Using two different methods to identify SFPs, 1035 and 875 SFPs were mapped in a segregating population of 64 doubled haploid lines from the L. cross RL4452 × ‘AC Domain’. Statistical associations between the SFP maps and the rice ( L. ssp. genome were in agreement with known cereal syntenic blocks, and the mapping data were corroborated by previously established physical locations for wheat expressed sequence tags. This approach allowed the rapid identification of markers from the genic regions of the complex hexaploid wheat genome.

  7. 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.

  8. 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.

  9. Single image super-resolution via an iterative reproducing kernel Hilbert space method.

    Science.gov (United States)

    Deng, Liang-Jian; Guo, Weihong; Huang, Ting-Zhu

    2016-11-01

    Image super-resolution, a process to enhance image resolution, has important applications in satellite imaging, high definition television, medical imaging, etc. Many existing approaches use multiple low-resolution images to recover one high-resolution image. In this paper, we present an iterative scheme to solve single image super-resolution problems. It recovers a high quality high-resolution image from solely one low-resolution image without using a training data set. We solve the problem from image intensity function estimation perspective and assume the image contains smooth and edge components. We model the smooth components of an image using a thin-plate reproducing kernel Hilbert space (RKHS) and the edges using approximated Heaviside functions. The proposed method is applied to image patches, aiming to reduce computation and storage. Visual and quantitative comparisons with some competitive approaches show the effectiveness of the proposed method.

  10. FUSED KERNEL-SPLINE SMOOTHING FOR REPEATEDLY MEASURED OUTCOMES IN A GENERALIZED PARTIALLY LINEAR MODEL WITH FUNCTIONAL SINGLE INDEX.

    Science.gov (United States)

    Jiang, Fei; Ma, Yanyuan; Wang, Yuanjia

    We propose a generalized partially linear functional single index risk score model for repeatedly measured outcomes where the index itself is a function of time. We fuse the nonparametric kernel method and regression spline method, and modify the generalized estimating equation to facilitate estimation and inference. We use local smoothing kernel to estimate the unspecified coefficient functions of time, and use B-splines to estimate the unspecified function of the single index component. The covariance structure is taken into account via a working model, which provides valid estimation and inference procedure whether or not it captures the true covariance. The estimation method is applicable to both continuous and discrete outcomes. We derive large sample properties of the estimation procedure and show different convergence rate of each component of the model. The asymptotic properties when the kernel and regression spline methods are combined in a nested fashion has not been studied prior to this work even in the independent data case.

  11. 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...

  12. 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.

  13. 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

  14. Impact of gluten-friendly™ technology on wheat kernel endosperm and gluten protein structure in seeds by light and electron microscopy.

    Science.gov (United States)

    Landriscina, L; D'Agnello, P; Bevilacqua, A; Corbo, M R; Sinigaglia, M; Lamacchia, C

    2017-04-15

    The main aim of this paper was to assess the impact of Gluten-Friendly™ (GF) technology (Italian priority patent n° 102015000084813 filed on 17th December 2015) on wheat kernel endosperm morphology and gluten protein structure, using SEM, light and immunofluorescent microscopy. Microscopy was combined with immunodetection with specific antibodies for gliadins, γ-gliadins, LMW subunits and antigenic epitopes to gain a better understanding of the technology at a molecular level. The results showed significant changes to gluten proteins after GF treatment; cross-reactivity towards the antibodies recognizing almost the entire range of gluten proteins as well as the antigenic epitopes through the sequences QQSF, QQSY, PEQPFPQGC and QQPFP was significantly reduced. The present study confirms the results from our previous work and shows, for the first time, the mechanism by which a chemical-physical treatment abolishes the antigenic capacity of gluten. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. 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...

  16. 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.

  17. 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.

  18. 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…

  19. Discriminating oat and groat kernels from other grains using near infrared spectroscopy

    Science.gov (United States)

    Oat and groats can be discriminated from other grains such as barley, wheat, rye, and triticale (non-oats) using near infrared spectroscopy. The two instruments tested were the manual version of the ARS-USDA Single Kernel Near Infrared (SKNIR) and the automated QualySense QSorter Explorer high-speed...

  20. Near-Infrared Absorption and Scattering Separated by Extended Inverted Signal Correction (EISC): Analysis of Near-Infrared Transmittance Spectra of Single Wheat Seeds

    DEFF Research Database (Denmark)

    Pedersen, Dorthe Kjær; Martens, Harald; Pram Nielsen, Jesper

    2002-01-01

    A new extended method for separating, e.g., scattering from absorbance in spectroscopic measurements, extended inverted signal correction (EISC), is presented and compared to multiplicative signal correction (MSC) and existing modiŽ cations of this. EISC preprocessing is applied to near-infrared...... transmittance (NIT) spectra of single wheat kernels with the aim of improving the multivariate calibration for protein content by partial least-squares regression (PLSR). The primary justiŽ cation of the EISC method is to facilitate removal of spectral artifacts and interferences that are uncorrelated to target...... of the EISC was found to be comparable to a more complex dual-transformation model obtained by Ž rst calculating the second derivative NIT spectra followed by MSC. The calibration model based on EISC preprocessing performed better than models based on the raw data, second derivatives, MSC, and MSC followed...

  1. Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays

    Directory of Open Access Journals (Sweden)

    Hu Shengwa

    2009-05-01

    Full Text Available Abstract Background Wheat (Triticum aestivum L. is a staple food crop worldwide. The wheat genome has not yet been sequenced due to its huge genome size (~17,000 Mb and high levels of repetitive sequences; the whole genome sequence may not be expected in the near future. Available linkage maps have low marker density due to limitation in available markers; therefore new technologies that detect genome-wide polymorphisms are still needed to discover a large number of new markers for construction of high-resolution maps. A high-resolution map is a critical tool for gene isolation, molecular breeding and genomic research. Single feature polymorphism (SFP is a new microarray-based type of marker that is detected by hybridization of DNA or cRNA to oligonucleotide probes. This study was conducted to explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome. Results Six wheat varieties of diverse origins (Ning 7840, Clark, Jagger, Encruzilhada, Chinese Spring, and Opata 85 were analyzed for significant probe by variety interactions and 396 probe sets with SFPs were identified. A subset of 164 unigenes was sequenced and 54% showed polymorphism within probes. Microarray analysis of 71 recombinant inbred lines from the cross Ning 7840/Clark identified 955 SFPs and 877 of them were mapped together with 269 simple sequence repeat markers. The SFPs were randomly distributed within a chromosome but were unevenly distributed among different genomes. The B genome had the most SFPs, and the D genome had the least. Map positions of a selected set of SFPs were validated by mapping single nucleotide polymorphism using SNaPshot and comparing with expressed sequence tags mapping data. Conclusion The Affymetrix array is a cost-effective platform for SFP discovery and SFP mapping in wheat. The new high-density map constructed in this study will be a useful tool for genetic and genomic research in wheat.

  2. 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 ...

  3. 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...

  4. 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.

  5. 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...

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

    African Journals Online (AJOL)

    Important methods applied for the breeding of bread-quality wheat (Triticum durum L.) consist of smallscale bread-quality tests for the determination of the grain protein content, SDS-sedimentation volume, thousand weight kernel and kernel diameter. Wheat grains of six varieties were analyzed. The thousand weight kernel, ...

  7. 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.

  8. 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.

  9. Genetic Diversity Revealed by Single Nucleotide Polymorphism Markers in a Worldwide Germplasm Collection of Durum Wheat

    Directory of Open Access Journals (Sweden)

    Ming-Cheng Luo

    2013-03-01

    Full Text Available Evaluation of genetic diversity and genetic structure in crops has important implications for plant breeding programs and the conservation of genetic resources. Newly developed single nucleotide polymorphism (SNP markers are effective in detecting genetic diversity. In the present study, a worldwide durum wheat collection consisting of 150 accessions was used. Genetic diversity and genetic structure were investigated using 946 polymorphic SNP markers covering the whole genome of tetraploid wheat. Genetic structure was greatly impacted by multiple factors, such as environmental conditions, breeding methods reflected by release periods of varieties, and gene flows via human activities. A loss of genetic diversity was observed from landraces and old cultivars to the modern cultivars released during periods of the Early Green Revolution, but an increase in cultivars released during the Post Green Revolution. Furthermore, a comparative analysis of genetic diversity among the 10 mega ecogeographical regions indicated that South America, North America, and Europe possessed the richest genetic variability, while the Middle East showed moderate levels of genetic diversity.

  10. 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)

  11. Empirical rheology and pasting properties of soft-textured durum wheat (Triticum turgidum ssp. durum) and hard-textured common wheat (T. aestivum)

    Science.gov (United States)

    Puroindoline (PIN) proteins are the molecular basis for wheat kernel texture classification and affect flour milling performance. This study aimed at investigating the effect of PINs on kernel physical characteristics and dough rheological properties of common wheat (Alpowa cv, soft wheat) and durum...

  12. 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

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

    Directory of Open Access Journals (Sweden)

    Long-Xi Yu

    Full Text Available 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-specific genes or complex adult plant resistance is necessary to achieve durability. In the present study, we applied genome-wide association studies (GWAS for identifying loci associated with the Ug99 stem rust resistance (SR in a panel of wheat lines developed at the International Maize and Wheat Improvement Center (CIMMYT. Genotyping was carried out using the wheat 9K iSelect single nucleotide polymorphism (SNP chip. Phenotyping was done in the field in Kenya by infection of Puccinia graminis f. sp. tritici race TTKST, the Sr24-virulent variant of Ug99. Marker-trait association identified 12 SNP markers significantly associated with resistance. Among them, 7 were mapped on five chromosomes. Markers located on chromosomes 4A and 4B overlapped with the location of the Ug99 resistance genes SrND643 and Sr37, respectively. Markers identified on 7DL were collocated with Sr25. Additional significant markers were located in the regions where no Sr gene has been reported. The chromosome location for five of the SNP markers was unknown. A BLASTN search of the NCBI database using the flanking sequences of the SNPs associated with Ug99 resistance revealed that several markers were linked to plant disease resistance analogues, while others were linked to regulatory factors or metabolic enzymes. A KASP (Kompetitive Allele Specific PCR assay was used for validating six marker loci linked to genes with resistance to Ug99. Of those, four co-segregated with the Sr25-pathotypes while the rest identified unknown resistance genes. With further investigation, these markers can be used for marker-assisted selection in breeding for Ug99 stem rust resistance in wheat.

  14. Self-organized crystallization patterns from evaporating droplets of common wheat grain leakages as a potential tool for quality analysis.

    Science.gov (United States)

    Kokornaczyk, Maria Olga; Dinelli, Giovanni; Marotti, Ilaria; Benedettelli, Stefano; Nani, Daniele; Betti, Lucietta

    2011-01-01

    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.

  15. 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.

  16. 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.

  17. 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.

  18. Exploiting the Repetitive Fraction of the Wheat Genome for High-Throughput Single-Nucleotide Polymorphism Discovery and Genotyping

    Directory of Open Access Journals (Sweden)

    Nelly Cubizolles

    2016-03-01

    Full Text Available Transposable elements (TEs account for more than 80% of the wheat genome. Although they represent a major obstacle for genomic studies, TEs are also a source of polymorphism and consequently of molecular markers such as insertion site-based polymorphism (ISBP markers. Insertion site-based polymorphisms have been found to be a great source of genome-specific single-nucleotide polymorphism (SNPs in the hexaploid wheat ( L. genome. Here, we report on the development of a high-throughput SNP discovery approach based on sequence capture of ISBP markers. By applying this approach to the reference sequence of chromosome 3B from hexaploid wheat, we designed 39,077 SNPs that are evenly distributed along the chromosome. We demonstrate that these SNPs can be efficiently scored with the KASPar (Kompetitive allele-specific polymerase chain reaction genotyping technology. Finally, through genetic diversity and genome-wide association studies, we also demonstrate that ISBP-derived SNPs can be used in marker-assisted breeding programs.

  19. Biochemical and molecular characterization of Avena indolines and their role in kernel texture.

    Science.gov (United States)

    Gazza, Laura; Taddei, Federica; Conti, Salvatore; Gazzelloni, Gloria; Muccilli, Vera; Janni, Michela; D'Ovidio, Renato; Alfieri, Michela; Redaelli, Rita; Pogna, Norberto E

    2015-02-01

    Among cereals, Avena sativa is characterized by an extremely soft endosperm texture, which leads to some negative agronomic and technological traits. On the basis of the well-known softening effect of puroindolines in wheat kernel texture, in this study, indolines and their encoding genes are investigated in Avena species at different ploidy levels. Three novel 14 kDa proteins, showing a central hydrophobic domain with four tryptophan residues and here named vromindoline (VIN)-1,2 and 3, were identified. Each VIN protein in diploid oat species was found to be synthesized by a single Vin gene whereas, in hexaploid A. sativa, three Vin-1, three Vin-2 and two Vin-3 genes coding for VIN-1, VIN-2 and VIN-3, respectively, were described and assigned to the A, C or D genomes based on similarity to their counterparts in diploid species. Expression of oat vromindoline transgenes in the extra-hard durum wheat led to accumulation of vromindolines in the endosperm and caused an approximate 50 % reduction of grain hardness, suggesting a central role for vromindolines in causing the extra-soft texture of oat grain. Further, hexaploid oats showed three orthologous genes coding for avenoindolines A and B, with five or three tryptophan residues, respectively, but very low amounts of avenoindolines were found in mature kernels. The present results identify a novel protein family affecting cereal kernel texture and would further elucidate the phylogenetic evolution of Avena genus.

  20. 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

  1. 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 ...

  2. 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.

  3. 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

  4. 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 .

  5. 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.

  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. 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...

  8. 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.

  9. 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.

  10. QTLs Associated with Agronomic Traits in the Cutler × AC Barrie Spring Wheat Mapping Population Using Single Nucleotide Polymorphic Markers

    Science.gov (United States)

    Perez-Lara, Enid; Semagn, Kassa; Chen, Hua; Iqbal, Muhammad; N’Diaye, Amidou; Kamran, Atif; Navabi, Alireza; Pozniak, Curtis; Spaner, Dean

    2016-01-01

    We recently reported three earliness per se quantitative trait loci (QTL) associated with flowering and maturity in a recombinant inbred lines (RILs) population derived from a cross between the spring wheat (Triticum aestivum L.) cultivars ‘Cutler’ and ‘AC Barrie’ using 488 microsatellite and diversity arrays technology (DArT) markers. Here, we present QTLs associated with flowering time, maturity, plant height, and grain yield using high density single nucleotide polymorphic (SNP) markers in the same population. A mapping population of 158 RILs and the two parents were evaluated at five environments for flowering, maturity, plant height and grain yield under field conditions, at two greenhouse environments for flowering, and genotyped with a subset of 1809 SNPs out of the 90K SNP array and 2 functional markers (Ppd-D1 and Rht-D1). Using composite interval mapping on the combined phenotype data across all environments, we identified a total of 19 QTLs associated with flowering time in greenhouse (5), and field (6) conditions, maturity (5), grain yield (2) and plant height (1). We mapped these QTLs on 8 chromosomes and they individually explained between 6.3 and 37.8% of the phenotypic variation. Four of the 19 QTLs were associated with multiple traits, including a QTL on 2D associated with flowering, maturity and grain yield; two QTLs on 4A and 7A associated with flowering and maturity, and another QTL on 4D associated with maturity and plant height. However, only the QTLs on both 2D and 4D had major effects, and they mapped adjacent to well-known photoperiod response Ppd-D1 and height reducing Rht-D1 genes, respectively. The QTL on 2D reduced flowering and maturity time up to 5 days with a yield penalty of 436 kg ha-1, while the QTL on 4D reduced plant height by 13 cm, but increased maturity by 2 days. The high density SNPs allowed us to map eight moderate effect, two major effect, and nine minor effect QTLs that were not identified in our previous study

  11. 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`.

  12. 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.

  13. 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

  14. 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

  15. The development and evaluation of single cell suspension from wheat and barley as a model system; a first step towards functional genomics application

    DEFF Research Database (Denmark)

    Dong, Jing; Bowra, Steve; Vincze, Éva

    2010-01-01

    Background The overall research objective was to develop single cell plant cultures as a model system to facilitate functional genomics of monocots, in particular wheat and barley. The essential first step towards achieving the stated objective was the development of a robust, viable single cell...... suspension culture from both species. Results We established growth conditions to allow routine culturing of somatic cells in 24 well microtiter plate format. Evaluation of the wheat and barley cell suspension as model cell system is a multi step process. As an initial step in the evaluation procedure we...... level of genes (P5CS, P5CR) under various treatments and we suggest that the cells can be used as a model host system to study gene expression and regulation in monocots....

  16. 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

  17. Linux Kernel in a Nutshell

    CERN Document Server

    Kroah-Hartman, Greg

    2009-01-01

    Linux Kernel in a Nutshell covers the entire range of kernel tasks, starting with downloading the source and making sure that the kernel is in sync with the versions of the tools you need. In addition to configuration and installation steps, the book offers reference material and discussions of related topics such as control of kernel options at runtime.

  18. The distal portion of the short arm of wheat (Triticum aestivum L.) chromosome 5D controls endosperm vitreosity and grain hardness.

    Science.gov (United States)

    Morris, Craig F; Beecher, Brian S

    2012-07-01

    Kernel vitreosity is an important trait of wheat grain, but its developmental control is not completely known. We developed back-cross seven (BC(7)) near-isogenic lines in the soft white spring wheat cultivar Alpowa that lack the distal portion of chromosome 5D short arm. From the final back-cross, 46 BC(7)F(2) plants were isolated. These plants exhibited a complete and perfect association between kernel vitreosity (i.e. vitreous, non-vitreous or mixed) and Single Kernel Characterization System (SKCS) hardness. Observed segregation of 10:28:7 fit a 1:2:1 Chi-square. BC(7)F(2) plants classified as heterozygous for both SKCS hardness and kernel vitreosity (n = 29) were selected and a single vitreous and non-vitreous kernel were selected, and grown to maturity and subjected to SKCS analysis. The resultant phenotypic ratios were, from non-vitreous kernels, 23:6:0, and from vitreous kernels, 0:1:28, soft:heterozygous:hard, respectively. Three of these BC(7)F(2) heterozygous plants were selected and 40 kernels each drawn at random, grown to maturity and subjected to SKCS analysis. Phenotypic segregation ratios were 7:27:6, 11:20:9, and 3:28:9, soft:heterozygous:hard. Chi-square analysis supported a 1:2:1 segregation for one plant but not the other two, in which cases the two homozygous classes were under-represented. Twenty-two paired BC(7)F(2):F(3) full sibs were compared for kernel hardness, weight, size, density and protein content. SKCS hardness index differed markedly, 29.4 for the lines with a complete 5DS, and 88.6 for the lines possessing the deletion. The soft non-vitreous kernels were on average significantly heavier, by nearly 20%, and were slightly larger. Density and protein contents were similar, however. The results provide strong genetic evidence that gene(s) on distal 5DS control not only kernel hardness but also the manner in which the endosperm develops, viz. whether it is vitreous or non-vitreous.

  19. 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

  20. [Study of genetic models of maize kernel traits].

    Science.gov (United States)

    Zhang, H W; Kong, F L

    2000-01-01

    Two sets of NCII mating design including 21 different maize inbreds were used to study the genetic models of five maize kernel traits--kernel length, width, ratio of kernel length and width, kernel thickness and weight per 100 kernels. Ten generations including P1, P2, F1, F2, B1, B2 and their reciprocal crosses RF1, RF2, RB1, RB2 were obtained. Three years' data were obtained and analyzed using mainly two methods: (1) precision identification for single cross and (2) mixed liner model MINQUE approach for diallel design. Method 1 showed that kernel traits were primarily controlled by maternal dominance, endosperm additive and dominance effect (maternal dominance > endosperm additive > endosperm dominance). Cytoplasmic effect was detected in one of the two crosses studied. Method 2 revealed that in the total variance of kernel traits, maternal genotypic effect contributed more than 60%, endosperm genotypic effect contributed less than 40%. Cytoplasmic effect only existed in kernel length and 100 kernel weight, with the range of 10% to 30%. The results indicated that kernel genetic performance was quite largely controlled by maternal genotypic effect.

  1. 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.

  2. 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...

  3. 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

  4. Robust visual tracking via speedup multiple kernel ridge regression

    Science.gov (United States)

    Qian, Cheng; Breckon, Toby P.; Li, Hui

    2015-09-01

    Most of the tracking methods attempt to build up feature spaces to represent the appearance of a target. However, limited by the complex structure of the distribution of features, the feature spaces constructed in a linear manner cannot characterize the nonlinear structure well. We propose an appearance model based on kernel ridge regression for visual tracking. Dense sampling is fulfilled around the target image patches to collect the training samples. In order to obtain a kernel space in favor of describing the target appearance, multiple kernel learning is introduced into the selection of kernels. Under the framework, instead of a single kernel, a linear combination of kernels is learned from the training samples to create a kernel space. Resorting to the circulant property of a kernel matrix, a fast interpolate iterative algorithm is developed to seek coefficients that are assigned to these kernels so as to give an optimal combination. After the regression function is learned, all candidate image patches gathered are taken as the input of the function, and the candidate with the maximal response is regarded as the object image patch. Extensive experimental results demonstrate that the proposed method outperforms other state-of-the-art tracking methods.

  5. Multidimensional kernel estimation

    CERN Document Server

    Milosevic, Vukasin

    2015-01-01

    Kernel estimation is one of the non-parametric methods used for estimation of probability density function. Its first ROOT implementation, as part of RooFit package, has one major issue, its evaluation time is extremely slow making in almost unusable. The goal of this project was to create a new class (TKNDTree) which will follow the original idea of kernel estimation, greatly improve the evaluation time (using the TKTree class for storing the data and creating different user-controlled modes of evaluation) and add the interpolation option, for 2D case, with the help of the new Delaunnay2D class.

  6. 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...

  7. 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...

  8. 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

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

    Science.gov (United States)

    Du, Wanli; Jing, Fan; Wang, Zhonghua; Wu, Jun; Chen, Xinhong

    2015-01-01

    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. PMID:26461884

  10. 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.

  11. Realized kernels in practice

    DEFF Research Database (Denmark)

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

    2009-01-01

    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...

  12. 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.

  13. The development and evaluation of single cell suspension from wheat and barley as a model system; a first step towards functional genomics application.

    Science.gov (United States)

    Dong, Jing; Bowra, Steve; Vincze, Eva

    2010-11-05

    The overall research objective was to develop single cell plant cultures as a model system to facilitate functional genomics of monocots, in particular wheat and barley. The essential first step towards achieving the stated objective was the development of a robust, viable single cell suspension culture from both species. We established growth conditions to allow routine culturing of somatic cells in 24 well microtiter plate format. Evaluation of the wheat and barley cell suspension as model cell system is a multi step process. As an initial step in the evaluation procedure we chose to study the impact of selected abiotic stress elicitors at the physiological, biochemical and molecular level. We report the results of osmotic stress imposed by NaCl and PEG. As proline is an important osmoprotectant of the cereal cells, colorimetric assay for proline detection was developed for small volumes (200 μl). We performed RT-PCR experiments to study the change in the expression of the genes encoding Δ1-pyrroline-5-carboxylate synthetase (P5CS) and Δ1-pyrroline-5-carboxylate reductase (PC5R) in response to abiotic stress. We found differences between the wheat and barley suspension cultures, barley being more tolerant to the applied osmotic stresses. We suggested a model to explain the obtained differences in stress tolerance between the two species. The suspension cell cultures have proven useful for determining changes in proline concentration and expression level of genes (P5CS, P5CR) under various treatments and we suggest that the cells can be used as a model host system to study gene expression and regulation in monocots.

  14. 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...... returns measured over 5 or 10 minutes intervals. We show the new estimator is substantially more precise....

  15. 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...... returns measured over 5 or 10 min intervals. We show that the new estimator is substantially more precise....

  16. 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

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

    Directory of Open Access Journals (Sweden)

    Yulin Jian

    2017-06-01

    Full Text Available 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.

  18. 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.

  19. The impact of single nucleotide polymorphism in monomeric alpha-amylase inhibitor genes from wild emmer wheat, primarily from Israel and Golan

    Directory of Open Access Journals (Sweden)

    Yan Ze-Hong

    2010-06-01

    Full Text Available Abstract Background Various enzyme inhibitors act on key insect gut digestive hydrolases, including alpha-amylases and proteinases. Alpha-amylase inhibitors have been widely investigated for their possible use in strengthening a plant's defense against insects that are highly dependent on starch as an energy source. We attempted to unravel the diversity of monomeric alpha-amylase inhibitor genes of Israeli and Golan Heights' wild emmer wheat with different ecological factors (e.g., geography, water, and temperature. Population methods that analyze the nature and frequency of allele diversity within a species and the codon analysis method (comparing patterns of synonymous and non-synonymous changes in protein coding sequences were used to detect natural selection. Results Three hundred and forty-eight sequences encoding monomeric alpha-amylase inhibitors (WMAI were obtained from 14 populations of wild emmer wheat. The frequency of SNPs in WMAI genes was 1 out of 16.3 bases, where 28 SNPs were detected in the coding sequence. The results of purifying and the positive selection hypothesis (p Conclusions Great diversity at the WMAI locus, both between and within populations, was detected in the populations of wild emmer wheat. It was revealed that WMAI were naturally selected for across populations by a ratio of dN/dS as expected. Ecological factors, singly or in combination, explained a significant proportion of the variations in the SNPs. A sharp genetic divergence over very short geographic distances compared to a small genetic divergence between large geographic distances also suggested that the SNPs were subjected to natural selection, and ecological factors had an important evolutionary role in polymorphisms at this locus. According to population and codon analysis, these results suggested that monomeric alpha-amylase inhibitors are adaptively selected under different environmental conditions.

  20. 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 ...

  1. Composition Kernel: A Software Solution for Constructing a Multi-OS Embedded System

    Directory of Open Access Journals (Sweden)

    Kinebuchi Yuki

    2010-01-01

    Full Text Available Abstract Modern high-end embedded systems require both predictable real-time scheduling and high-level abstraction interface to their OS kernels. Since these features are difficult to be balanced by a single OS, some methods that accommodate multiple different versions of OS kernels, typically real-time OS and general purpose OS, into a single device have been proposed. The hybrid kernel, one of those methods, executes a general purpose OS kernel as a task of real-time OS which can support those features with reasonable engineering effort. However when adapting the approach to various combinations of OS kernels, which is required in the real-world embedded system design, the engineering effort of modifying the kernel becomes not negligible. This article introduce a method called a composition kernel which uses a thin abstraction layer for accommodating kernels without making direct dependencies between them. The authors developed the abstraction layer on an SH-4A processor and executed kernels on top of it. The amount of modifications to the kernels was significantly smaller than that in related work, while introducing only negligible verhead to the performance of the kernels.

  2. 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...... information to be automatically incorporated in registrations and promises to improve the standard framework in several aspects. We present the mathematical foundations of LDDKBM and derive the KB-EPDiff evolution equations, which provide optimal warps in this new framework. To illustrate the resulting...

  3. 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....

  4. 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.

  5. 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.

  6. 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

  7. 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.

  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. Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

    Science.gov (United States)

    Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

    2016-08-01

    This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

  10. 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...

  11. Classification Using the Zipfian Kernel

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2015-01-01

    Roč. 32, č. 2 (2015), s. 305-326 ISSN 0176-4268 R&D Projects: GA TA ČR TA01010490 Institutional support: RVO:67985807 Keywords : kernel machine * Zipfian kernel * multivariate data * correlation dimension * harmonic series * classification Subject RIV: JC - Computer Hardware ; Software Impact factor: 1.147, year: 2015

  12. Model Selection in Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    , 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...... applicable, and we recommend their use instead of the popular polynomial kernels in general settings, in which no information on the data-generating process is available....

  13. Viscosity kernel of molecular fluids

    DEFF Research Database (Denmark)

    Puscasu, Ruslan; Todd, Billy; Daivis, Peter

    2010-01-01

    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......The wave-vector dependent shear viscosities for butane and freely jointed chains have been determined. The transverse momentum density and stress autocorrelation functions have been determined by equilibrium molecular dynamics in both atomic and molecular hydrodynamic formalisms. The density......, 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...

  14. 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.

  15. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

    . 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...... 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 applicable. Therefore, their use is recommended instead of the popular polynomial kernels in general settings, where no information...

  16. Implementation of kernels on the Maestro processor

    Science.gov (United States)

    Suh, Jinwoo; Kang, D. I. D.; Crago, S. P.

    Currently, most microprocessors use multiple cores to increase performance while limiting power usage. Some processors use not just a few cores, but tens of cores or even 100 cores. One such many-core microprocessor is the Maestro processor, which is based on Tilera's TILE64 processor. The Maestro chip is a 49-core, general-purpose, radiation-hardened processor designed for space applications. The Maestro processor, unlike the TILE64, has a floating point unit (FPU) in each core for improved floating point performance. The Maestro processor runs at 342 MHz clock frequency. On the Maestro processor, we implemented several widely used kernels: matrix multiplication, vector add, FIR filter, and FFT. We measured and analyzed the performance of these kernels. The achieved performance was up to 5.7 GFLOPS, and the speedup compared to single tile was up to 49 using 49 tiles.

  17. 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.…

  18. 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.

  19. Optimizing single irrigation scheme to improve water use efficiency by manipulating winter wheat sink-source relationships in Northern China Plain.

    Science.gov (United States)

    Xu, Xuexin; Zhang, Yinghua; Li, Jinpeng; Zhang, Meng; Zhou, Xiaonan; Zhou, Shunli; Wang, Zhimin

    2018-01-01

    Improving winter wheat grain yield and water use efficiency (WUE) with minimum irrigation is very important for ensuring agricultural and ecological sustainability in the Northern China Plain (NCP). A three-year field experiment was conducted to determine how single irrigation can improve grain yield and WUE by manipulating the "sink-source" relationships. To achieve this, no-irrigation after sowing (W0) as a control, and five single irrigation treatments after sowing (75 mm of each irrigation) were established. They included irrigation at upstanding (WU), irrigation at jointing (WJ), irrigation at booting (WB), irrigation at anthesis (WA) and irrigation at medium milk (WM). Results showed that compared with no-irrigation after sowing (W0), WU, WJ, WB, WA and WM significantly improved mean grain yield by 14.1%, 19.9%, 17.9%, 11.6%, and 7.5%, respectively. WJ achieved the highest grain yield (8653.1 kg ha-1) and WUE (20.3 kg ha-1 mm-1), and WB observed the same level of grain yield and WUE as WJ. In comparison to WU, WJ and WB coordinated pre- and post-anthesis water use while reducing pre-anthesis and total evapotranspiration (ET). They also retained higher soil water content above 180 cm soil layers at anthesis, increased post-anthesis water use, and ultimately increased WUE. WJ and WB optimized population quantity and individual leaf size, delayed leaf senescence, extended grain-filling duration, improved post-anthesis biomass and biomass remobilization (source supply capacity) as well as post-anthesis biomass per unit anthesis leaf area (PostBA-leaf ratio). WJ also optimized the allocation of assimilation, increased the spike partitioning index (SPI, spike biomass/biomass at anthesis) and grain production efficiency (GPE, the ratio of grain number to biomass at anthesis), thus improved mean sink capacity by 28.1%, 5.7%, 21.9%, and 26.7% in comparison to W0, WU, WA and WM, respectively. Compared with WA and WM, WJ and WB also increased sink capacity, post

  20. 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...

  1. Signaling in Early Maize Kernel Development.

    Science.gov (United States)

    Doll, Nicolas M; Depège-Fargeix, Nathalie; Rogowsky, Peter M; Widiez, Thomas

    2017-03-06

    Developing the next plant generation within the seed requires the coordination of complex programs driving pattern formation, growth, and differentiation of the three main seed compartments: the embryo (future plant), the endosperm (storage compartment), representing the two filial tissues, and the surrounding maternal tissues. This review focuses on the signaling pathways and molecular players involved in early maize kernel development. In the 2 weeks following pollination, functional tissues are shaped from single cells, readying the kernel for filling with storage compounds. Although the overall picture of the signaling pathways regulating embryo and endosperm development remains fragmentary, several types of molecular actors, such as hormones, sugars, or peptides, have been shown to be involved in particular aspects of these developmental processes. These molecular actors are likely to be components of signaling pathways that lead to transcriptional programming mediated by transcriptional factors. Through the integrated action of these components, multiple types of information received by cells or tissues lead to the correct differentiation and patterning of kernel compartments. In this review, recent advances regarding the four types of molecular actors (hormones, sugars, peptides/receptors, and transcription factors) involved in early maize development are presented. Copyright © 2017 The Author. Published by Elsevier Inc. All rights reserved.

  2. 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.

  3. 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...

  4. 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.

  5. Heat kernels and critical limits

    OpenAIRE

    Pickrell, Doug

    2007-01-01

    This paper is an exposition of several questions linking heat kernel measures on infinite dimensional Lie groups, limits associated with critical Sobolev exponents, and Feynmann-Kac measures for sigma models.

  6. Wheat Allergy

    Science.gov (United States)

    ... Watery eyes Wheat allergy Symptoms & causes Diagnosis & treatment Advertisement Mayo Clinic does not endorse companies or products. ... a Job Site Map About This Site Twitter Facebook Google YouTube Pinterest Mayo Clinic is a not- ...

  7. 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.

  8. 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…

  9. 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...

  10. 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...

  11. Small kernel2

    Science.gov (United States)

    Yang, Yan-Zhuo; Ding, Shuo; Wang, Yong; Li, Cui-Ling; Shen, Yun; Meeley, Robert; McCarty, Donald R; Tan, Bao-Cai

    2017-06-01

    Vitamin B 6 , an essential cofactor for a range of biochemical reactions and a potent antioxidant, plays important roles in plant growth, development, and stress tolerance. Vitamin B 6 deficiency causes embryo lethality in Arabidopsis ( Arabidopsis thaliana ), but the specific role of vitamin B 6 biosynthesis in endosperm development has not been fully addressed, especially in monocot crops, where endosperm constitutes the major portion of the grain. Through molecular characterization of a small kernel2 ( smk2 ) mutant in maize, we reveal that vitamin B 6 has differential effects on embryogenesis and endosperm development in maize. The B 6 vitamer pyridoxal 5'-phosphate (PLP) is drastically reduced in both the smk2 embryo and the endosperm. However, whereas embryogenesis of the smk2 mutant is arrested at the transition stage, endosperm formation is nearly normal. Cloning reveals that Smk2 encodes the glutaminase subunit of the PLP synthase complex involved in vitamin B 6 biosynthesis de novo. Smk2 partially complements the Arabidopsis vitamin B 6 -deficient mutant pdx2.1 and Saccharomyces cerevisiae pyridoxine auxotrophic mutant MML21. Smk2 is constitutively expressed in the maize plant, including developing embryos. Analysis of B 6 vitamers indicates that the endosperm accumulates a large amount of pyridoxamine 5'-phosphate (PMP). These results indicate that vitamin B 6 is essential to embryogenesis but has a reduced role in endosperm development in maize. The vitamin B 6 required for seed development is synthesized in the seed, and the endosperm accumulates PMP probably as a storage form of vitamin B 6 . © 2017 American Society of Plant Biologists. All Rights Reserved.

  12. 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...

  13. The distal portion of wheat (Triticum aestivum L.) chromosome 5D short arm controls endosperm vitreosity and grain hardness

    Science.gov (United States)

    Kernel vitreosity is an important trait of wheat grain, but its complete developmental control is not known. We developed back-cross seven (BC7) near isogenic lines in the soft white spring wheat cultivar Alpowa that possess or lack the distal portion of chromosome 5D short arm. This deletion was de...

  14. 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

  15. 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.

  16. 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...

  17. 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

  18. 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.

  19. 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.

  20. 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...

  1. 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 squ...... 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....

  2. Metabolisable energy values of whole palm kernel and palm kernel ...

    African Journals Online (AJOL)

    4.12 Kcal/kg DM. 4.36 and 4.13 Kcal/kg DM, respectively were the corresponding values for broiler chickens. No interaction between ingredients and birds was found but there were interactions among the bioavailable energy systems and the bird types. Keywords: Metabolisable energy, palm kernel layers, broilers.

  3. Spine labeling in axial magnetic resonance imaging via integral kernels.

    Science.gov (United States)

    Miles, Brandon; Ben Ayed, Ismail; Hojjat, Seyed-Parsa; Wang, Michael H; Li, Shuo; Fenster, Aaron; Garvin, Gregory J

    2016-12-01

    This study investigates a fast integral-kernel algorithm for classifying (labeling) the vertebra and disc structures in axial magnetic resonance images (MRI). The method is based on a hierarchy of feature levels, where pixel classifications via non-linear probability product kernels (PPKs) are followed by classifications of 2D slices, individual 3D structures and groups of 3D structures. The algorithm further embeds geometric priors based on anatomical measurements of the spine. Our classifier requires evaluations of computationally expensive integrals at each pixel, and direct evaluations of such integrals would be prohibitively time consuming. We propose an efficient computation of kernel density estimates and PPK evaluations for large images and arbitrary local window sizes via integral kernels. Our method requires a single user click for a whole 3D MRI volume, runs nearly in real-time, and does not require an intensive external training. Comprehensive evaluations over T1-weighted axial lumbar spine data sets from 32 patients demonstrate a competitive structure classification accuracy of 99%, along with a 2D slice classification accuracy of 88%. To the best of our knowledge, such a structure classification accuracy has not been reached by the existing spine labeling algorithms. Furthermore, we believe our work is the first to use integral kernels in the context of medical images. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Reducing Kernel Development Complexity in Distributed Environments

    OpenAIRE

    Lèbre , Adrien; Lottiaux , Renaud; Focht , Erich; Morin , Christine

    2008-01-01

    Setting up generic and fully transparent distributed services for clusters implies complex and tedious kernel developments. More flexible approaches such as user-space libraries are usually preferred with the drawback of requiring application recompilation. A second approach consists in using specific kernel modules (such as FUSE in Gnu/Linux system) to transfer kernel complexity into user space. In this paper, we present a new way to design and implement kernel distributed services for clust...

  5. Oops! What about a Million Kernel Oopses?

    OpenAIRE

    Guo , Lisong; Senna Tschudin , Peter; Kono , Kenji; Muller , Gilles; Lawall , Julia

    2013-01-01

    When a failure occurs in the Linux kernel, the kernel emits an "oops", summarizing the execution context of the failure. Kernel oopses describe real Linux errors, and thus can help prioritize debugging efforts and motivate the design of tools to improve the reliability of Linux code. Nevertheless, the information is only meaningful if it is representative and can be interpreted correctly. In this paper, we study a repository of kernel oopses collected over 8 months by Red Hat. We consider the...

  6. Derivative Kernels: Numerics and Applications.

    Science.gov (United States)

    Hosseini, Mahdi S; Plataniotis, Konstantinos N

    2017-10-01

    A generalized framework for numerical differentiation (ND) is proposed for constructing a finite impulse response (FIR) filter in closed form. The framework regulates the frequency response of ND filters for arbitrary derivative-order and cutoff frequency selected parameters relying on interpolating power polynomials and maximally flat design techniques. Compared with the state-of-the-art solutions, such as Gaussian kernels, the proposed ND filter is sharply localized in the Fourier domain with ripple-free artifacts. Here, we construct 2D MaxFlat kernels for image directional differentiation to calculate image differentials for arbitrary derivative order, cutoff level and steering angle. The resulted kernel library renders a new solution capable of delivering discrete approximation of gradients, Hessian, and higher-order tensors in numerous applications. We tested the utility of this library on three different imaging applications with main focus on the unsharp masking. The reported results highlight the high efficiency of the 2D MaxFlat kernel and its versatility with respect to robustness and parameter control accuracy.

  7. 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

  8. 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

  9. 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

  10. Rye kernel breakfast increases satiety in the afternoon - an effect of food structure

    Directory of Open Access Journals (Sweden)

    Fredriksson Helena

    2011-04-01

    Full Text Available Abstract Background The structure of whole grain cereals is maintained to varying degrees during processing and preparation of foods. Food structure can influence metabolism, including perceived hunger and satiety. A diet that enhances satiety per calorie may help to prevent excessive calorie intake. The objective of this work was to compare subjective appetite ratings after consumption of intact and milled rye kernels. Methods Two studies were performed using a randomized, cross-over design. Ratings for appetite (hunger, satiety and desire to eat were registered during an 8-h period after consumption of whole and milled rye kernels prepared as breads (study 1, n = 24 and porridges (study 2, n = 20. Sifted wheat bread was used as reference in both study parts and the products were eaten in iso-caloric portions with standardized additional breakfast foods. Breads and porridges were analyzed to determine whether structure (whole vs. milled kernels effected dietary fibre content and composition after preparation of the products. Statistical evaluation of the appetite ratings after intake of the different breakfasts was done by paired t-tests for morning and afternoon ratings separately, with subjects as random effect and type of breakfast and time points as fixed effects. Results All rye breakfasts resulted in higher satiety ratings in the morning and afternoon compared with the iso-caloric reference breakfast with sifted wheat bread. Rye bread with milled or whole kernels affected appetite equally, so no effect of structure was observed. In contrast, after consumption of the rye kernel breakfast, satiety was increased and hunger suppressed in the afternoon compared with the milled rye kernel porridge breakfast. This effect could be related to structural differences alone, because the products were equal in nutritional content including dietary fibre content and composition. Conclusions The study demonstrates that small changes in diet composition

  11. Rye kernel breakfast increases satiety in the afternoon - an effect of food structure.

    Science.gov (United States)

    Isaksson, Hanna; Rakha, Allah; Andersson, Roger; Fredriksson, Helena; Olsson, Johan; Aman, Per

    2011-04-11

    The structure of whole grain cereals is maintained to varying degrees during processing and preparation of foods. Food structure can influence metabolism, including perceived hunger and satiety. A diet that enhances satiety per calorie may help to prevent excessive calorie intake. The objective of this work was to compare subjective appetite ratings after consumption of intact and milled rye kernels. Two studies were performed using a randomized, cross-over design. Ratings for appetite (hunger, satiety and desire to eat) were registered during an 8-h period after consumption of whole and milled rye kernels prepared as breads (study 1, n = 24) and porridges (study 2, n = 20). Sifted wheat bread was used as reference in both study parts and the products were eaten in iso-caloric portions with standardized additional breakfast foods. Breads and porridges were analyzed to determine whether structure (whole vs. milled kernels) effected dietary fibre content and composition after preparation of the products. Statistical evaluation of the appetite ratings after intake of the different breakfasts was done by paired t-tests for morning and afternoon ratings separately, with subjects as random effect and type of breakfast and time points as fixed effects. All rye breakfasts resulted in higher satiety ratings in the morning and afternoon compared with the iso-caloric reference breakfast with sifted wheat bread. Rye bread with milled or whole kernels affected appetite equally, so no effect of structure was observed. In contrast, after consumption of the rye kernel breakfast, satiety was increased and hunger suppressed in the afternoon compared with the milled rye kernel porridge breakfast. This effect could be related to structural differences alone, because the products were equal in nutritional content including dietary fibre content and composition. The study demonstrates that small changes in diet composition such as cereal grain structure have the potential to effect

  12. Isolation and characterization of a Psathyrostachys huashanica Keng 6Ns chromosome addition in common wheat.

    Directory of Open Access Journals (Sweden)

    Wanli Du

    Full Text Available The development of alien addition lines is important for transferring useful genes from exotic species into common wheat. A hybrid of common wheat cv. 7182 (2n = 6x = 42, AABBDD and Psathyrostachys huashanica Keng (2n = 2x = 14, NsNs via embryo culture produced the novel intergeneric disomic addition line 59-11. The seed morphology of 59-11 resembled the parent 7182 and it exhibited extreme agronomic characteristics, i.e., twin stable spikelets, fertile florets, and multi-kernel clusters. Furthermore, 59-11 produced plump kernels with a high seed-setting percentage during the advanced maturation stage. The line was screened based on genomic in situ hybridization, EST-SSR, EST-STS, and gliadin to identify P. huashanica chromatin in the wheat background. The chromosome number and configuration of 59-11 was 2n = 44 = 22 II and we confirmed the 6Ns disomic chromosome additions based on A-PAGE analysis and molecular markers. The results suggested that the production of twin spikelets and multiple kernels per spike in the wheat-P. huashanica addition line was related to homologous group 6 in the wheat chromosome. This is the first report of the introduction of improved spike traits into common wheat from the alien species P. huashanica and it opens up the possibility of increasing the wheat yield based on this enlarged gene pool.

  13. 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.

  14. ESTs analysis in maize developing kernels exposed to single and combined water and heat stresses Análise de ESTs de espigas de milho em desenvolvimento expostas a estresse simples e combinado de água e calor

    Directory of Open Access Journals (Sweden)

    Violeta Andjelković

    2011-06-01

    Full Text Available Molecular and metabolic response of plants to a combination of two abiotic stresses is unique and cannot be directly extrapolated from the response of plants to each of the stresses individually. cDNA macroarray has become a useful tool to analyze expression profiles and compare the similarities and differences of various expression patterns. A macroarray of approximately 2,500 maize (Zea mays L. cDNAs was used for transcriptome profiling in response to single and simultaneous application of water and high temperature stress of maize developing kernels at 15 days after pollination. All stress treatments (water stress-WS, heat stress-HS and their combined application-CS induced changes in expression of 106 transcripts with 54 up-regulated and 52 down-regulated. There were 11 up-regulated and 15 down-regulated transcripts in common for all three stresses. Although these common transcripts showed existence of a mutual mechanism in stress response, the 23 transcripts induced only in CS indicate that plants responded in a different manner when exposed to simultaneous effects of both stresses. A glimpse of functions regulated under WS, HS and CS is provided, and also the common and different responses between individual and simultaneous stresses.A resposta molecular e metabólica de plantas a uma combinação de dois estresses abióticos é singular, e não pode ser diretamente extrapolada da resposta das plantas a cada um dos estresses individualmente. O macroarranjo do cDNA, tornou-se uma ferramenta útil para analisar os perfís de expressão e comparar as similaridades e diferenças de vários padrões de expressão. Um macroarranjo de 2.500 cDNAs de milho (Zea mays L. foi usado para traçar um perfil de transcriptoma em resposta ao stress ocasionado por uma única e simultânea aplicação de água e alta temperatura em espigas em desenvolvimento, 15 dias após a polinização. Todos os tratamentos de stress (stress de água - SA, stress de calor

  15. 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.

  16. 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

  17. 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.

  18. Three-Dimensional Sensitivity Kernels of Z/H Amplitude Ratios of Surface and Body Waves

    Science.gov (United States)

    Bao, X.; Shen, Y.

    2017-12-01

    The ellipticity of Rayleigh wave particle motion, or Z/H amplitude ratio, has received increasing attention in inversion for shallow Earth structures. Previous studies of the Z/H ratio assumed one-dimensional (1D) velocity structures beneath the receiver, ignoring the effects of three-dimensional (3D) heterogeneities on wave amplitudes. This simplification may introduce bias in the resulting models. Here we present 3D sensitivity kernels of the Z/H ratio to Vs, Vp, and density perturbations, based on finite-difference modeling of wave propagation in 3D structures and the scattering-integral method. Our full-wave approach overcomes two main issues in previous studies of Rayleigh wave ellipticity: (1) the finite-frequency effects of wave propagation in 3D Earth structures, and (2) isolation of the fundamental mode Rayleigh waves from Rayleigh wave overtones and converted Love waves. In contrast to the 1D depth sensitivity kernels in previous studies, our 3D sensitivity kernels exhibit patterns that vary with azimuths and distances to the receiver. The laterally-summed 3D sensitivity kernels and 1D depth sensitivity kernels, based on the same homogeneous reference model, are nearly identical with small differences that are attributable to the single period of the 1D kernels and a finite period range of the 3D kernels. We further verify the 3D sensitivity kernels by comparing the predictions from the kernels with the measurements from numerical simulations of wave propagation for models with various small-scale perturbations. We also calculate and verify the amplitude kernels for P waves. This study shows that both Rayleigh and body wave Z/H ratios provide vertical and lateral constraints on the structure near the receiver. With seismic arrays, the 3D kernels afford a powerful tool to use the Z/H ratios to obtain accurate and high-resolution Earth models.

  19. 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....

  20. 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.

  1. Color of whole-wheat foods prepared from a bright-white hard winter wheat and the phenolic acids in its coarse bran.

    Science.gov (United States)

    Jiang, Hongxin; Martin, Joe; Okot-Kotber, Moses; Seib, Paul A

    2011-08-01

    The color of wheat kernels often impacts the color and thereby the value of wheat-based foods. A line of hard white winter wheat (B-W HW) with bright appearing kernels has been developed at the Kansas State Agricultural Research Center. The objective of this study was to compare the color of several foods made from the B-W HW wheat with those of 2 hard white wheat cultivars, Trego and Lakin. The B-W HW kernels showed higher lightness (L*, 57.6) than Trego (55.5) and Lakin (56.8), and the increased lightness was carried over to its bran and whole-wheat flour. Alkaline noodle and bread crumb made from the B-W HW whole-wheat flour showed slightly higher lightness (L*) than those made from Trego and Lakin. The sum of soluble and bound phenolics extracted from the 3 wheat brans, which had not been preextracted to remove lipids, was found to be 17.22 to 18.98 mg/g. The soluble phenolic acids in the brans were principally vanillic, ferulic, and syringic. The bound phenolic acids in the brans were dominated by ferulic, which accounted for 50.1% to 82.2% of total identified bound phenolic acids. Other bound phenolic acids were protocatechuic, caffeic, syringic, trans-cinnamic, p-hydroxybenzoic, p-coumaric, and vanillic. The lightness (L*) values of coarse wheat brans correlated positively with their levels of bound protocatechuic (r = 0.72, P < 0.01) and p-hydroxybenzoic acids (r = 0.75, P < 0.01). © 2011 Institute of Food Technologists®

  2. 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.

  3. 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.

  4. Concentrated Arabinoxylan but Not Concentrated Beta-Glucan in Wheat Bread Has Similar Effects on Postprandial Insulin as Whole-Grain Rye in Porto-arterial Catheterized Pigs

    DEFF Research Database (Denmark)

    Christensen, Kirstine Lykke; Hedemann, Mette Skou; Lærke, Helle Nygaard

    2013-01-01

    The acute glycemic effects of concentrated dietary fibers (DF) versus whole-grain rye were studied in portoarterial catheterized pigs. Two white wheat breads with wheat arabinoxylan (AX) or oat beta-glucan (BG), two rye breads with intact rye kernels (RK) or milled rye (GR), and a low DF white wh...

  5. Effect of prothioconazole-based fungicides on Fusarium head blight, grain yield and deoxynivalenol accumulation in wheat under field conditions

    Directory of Open Access Journals (Sweden)

    Miriam HAIDUKOWSKI

    2012-05-01

    Full Text Available The effect of triazole-based treatments on Fusarium head blight (FHB, grain yields and the accumulation of deoxynivalenol (DON in harvested wheat kernels was evaluated by means of twenty multi-site field experiments performed during five consecutive growing seasons (from 2004‒2005 to 2008‒2009 in Italy. Fungicide treatments were carried out on different cultivars of common wheat (cv. Serio, Blasco, Genio and Savio and durum wheat (cv. Orobel, Saragolla, San Carlo, Levante, Duilio, Karur and Derrik after artificial inoculation with a mixture of toxigenic Fusarium graminearum and F. culmorum strains. The application of fungicides containing prothioconazole (Proline® or Prosaro® at the beginning of anthesis (BBCH 61 resulted in a consistent reduction of FHB disease severity (by between 39 and 93% and DON levels in wheat kernels (by between 40 and 91% and increased wheat yields (from 0.4 to 5.6 t ha-1, average 2.2 t ha-1, as compared to the untreated/inoculated control. Fungicides containing tebuconazole (Folicur® SE and cyproconazole plus prochloraz (Tiptor® Xcell showed a reduced effectiveness compared with prothioconazole-based treatments. All fungicide treatments were more effective in reducing DON and increasing grain yields of common wheat than durum wheat. Results showed that the application of fungicides containing prothioconazole at the beginning of anthesis provided a strong reduction of FHB disease, allowing both an increase in grain yields and a considerable reduction of DON content in wheat kernels.

  6. Nonlinear Deep Kernel Learning for Image Annotation.

    Science.gov (United States)

    Jiu, Mingyuan; Sahbi, Hichem

    2017-02-08

    Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. kFOIL: Learning simple relational kernels

    OpenAIRE

    Landwehr, Niels; Passerini, Andrea; De Raedt, Luc; Frasconi, Paolo

    2006-01-01

    A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FOIL with kernel methods. The feature space is constructed by leveraging FOIL search for a set of relevant clauses. The search is driven by the performance obtained by a support vector machine based on the resulting kernel. In this way, kFOIL implements a dynamic propositionalization approach. Both classification an...

  15. 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.

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

    Science.gov (United States)

    2013-01-01

    Background 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. Results 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. Conclusions We documented that RNAi-based silencing

  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. 7 CFR 51.1403 - Kernel color classification.

    Science.gov (United States)

    2010-01-01

    ... models of pecan kernels, illustrate the color intensities implied by the terms “golden,” “light brown... Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...

  20. 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 ...

  1. 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

  2. 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.

  3. 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)

  4. Modelling Issues in Kernel Ridge Regression

    NARCIS (Netherlands)

    P. Exterkate (Peter)

    2011-01-01

    textabstractKernel 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

  5. 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.

  6. 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.

  7. Kernel method for corrections to scaling.

    Science.gov (United States)

    Harada, Kenji

    2015-07-01

    Scaling analysis, in which one infers scaling exponents and a scaling function in a scaling law from given data, is a powerful tool for determining universal properties of critical phenomena in many fields of science. However, there are corrections to scaling in many cases, and then the inference problem becomes ill-posed by an uncontrollable irrelevant scaling variable. We propose a new kernel method based on Gaussian process regression to fix this problem generally. We test the performance of the new kernel method for some example cases. In all cases, when the precision of the example data increases, inference results of the new kernel method correctly converge. Because there is no limitation in the new kernel method for the scaling function even with corrections to scaling, unlike in the conventional method, the new kernel method can be widely applied to real data in critical phenomena.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Wheat and gluten intolerance

    NARCIS (Netherlands)

    Busink-van den Broeck, Hetty; Gilissen, L.J.W.J.; Brouns, F.

    2016-01-01

    With this White Paper, the current state of scientific knowledge on human disorders related to gluten and wheat is presented, with reference to other grains such as spelt, barley, rye, and oats. Backgrounds are described of coeliac disease (gluten intolerance), wheat allergies and any kind of wheat

  13. 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.

  14. Genome Wide Association Mapping for Arabinoxylan Content in a Collection of Tetraploid Wheats.

    Directory of Open Access Journals (Sweden)

    Ilaria Marcotuli

    Full Text Available Arabinoxylans (AXs are major components of plant cell walls in bread wheat and are important in bread-making and starch extraction. Furthermore, arabinoxylans are components of soluble dietary fibre that has potential health-promoting effects in human nutrition. Despite their high value for human health, few studies have been carried out on the genetics of AX content in durum wheat.The genetic variability of AX content was investigated in a set of 104 tetraploid wheat genotypes and regions attributable to AX content were identified through a genome wide association study (GWAS. The amount of arabinoxylan, expressed as percentage (w/w of the dry weight of the kernel, ranged from 1.8% to 5.5% with a mean value of 4.0%. The GWAS revealed a total of 37 significant marker-trait associations (MTA, identifying 19 quantitative trait loci (QTL associated with AX content. The highest number of MTAs was identified on chromosome 5A (seven, where three QTL regions were associated with AX content, while the lowest number of MTAs was detected on chromosomes 2B and 4B, where only one MTA identified a single locus. Conservation of synteny between SNP marker sequences and the annotated genes and proteins in Brachypodium distachyon, Oryza sativa and Sorghum bicolor allowed the identification of nine QTL coincident with candidate genes. These included a glycosyl hydrolase GH35, which encodes Gal7 and a glucosyltransferase GT31 on chromosome 1A; a cluster of GT1 genes on chromosome 2B that includes TaUGT1 and cisZog1; a glycosyl hydrolase that encodes a CelC gene on chromosome 3A; Ugt12887 and TaUGT1genes on chromosome 5A; a (1,3-β-D-glucan synthase (Gsl12 gene and a glucosyl hydrolase (Cel8 gene on chromosome 7A.This study identifies significant MTAs for the AX content in the grain of tetraploid wheat genotypes. We propose that these may be used for molecular breeding of durum wheat varieties with higher soluble fibre content.

  15. 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.

  16. Distance Based Multiple Kernel ELM: A Fast Multiple Kernel Learning Approach

    Directory of Open Access Journals (Sweden)

    Chengzhang Zhu

    2015-01-01

    Full Text Available We propose a distance based multiple kernel extreme learning machine (DBMK-ELM, which provides a two-stage multiple kernel learning approach with high efficiency. Specifically, DBMK-ELM first projects multiple kernels into a new space, in which new instances are reconstructed based on the distance of different sample labels. Subsequently, an l2-norm regularization least square, in which the normal vector corresponds to the kernel weights of a new kernel, is trained based on these new instances. After that, the new kernel is utilized to train and test extreme learning machine (ELM. Extensive experimental results demonstrate the superior performance of the proposed DBMK-ELM in terms of the accuracy and the computational cost.

  17. 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.

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

    International Nuclear Information System (INIS)

    Bartels, J.; Lipatov, L.N.; Vacca, G.P.

    2012-01-01

    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→3 kernel, computed in the tree approximation.

  19. 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... the provisions of this section. (a) Tamarind seed kernel powder is the ground kernel of tamarind seed...

  20. Higher-order Gaussian kernel in bootstrap boosting algorithm ...

    African Journals Online (AJOL)

    The bootstrap boosting algorithm is a bias reduction scheme. The adoption of higher-order Gaussian kernel in a bootstrap boosting algorithm in kernel density estimation was investigated. The algorithm used the higher-order. Gaussian kernel instead of the regular fixed kernels. A comparison of the scheme with existing ...

  1. 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...

  2. 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 ...

  3. 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 ...

  4. 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 ...

  5. 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.

  6. Classification of EEG Signals Using a Multiple Kernel Learning Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Xiaoou Li

    2014-07-01

    Full Text Available In this study, a multiple kernel learning support vector machine algorithm is proposed for the identification of EEG signals including mental and cognitive tasks, which is a key component in EEG-based brain computer interface (BCI systems. The presented BCI approach included three stages: (1 a pre-processing step was performed to improve the general signal quality of the EEG; (2 the features were chosen, including wavelet packet entropy and Granger causality, respectively; (3 a multiple kernel learning support vector machine (MKL-SVM based on a gradient descent optimization algorithm was investigated to classify EEG signals, in which the kernel was defined as a linear combination of polynomial kernels and radial basis function kernels. Experimental results showed that the proposed method provided better classification performance compared with the SVM based on a single kernel. For mental tasks, the average accuracies for 2-class, 3-class, 4-class, and 5-class classifications were 99.20%, 81.25%, 76.76%, and 75.25% respectively. Comparing stroke patients with healthy controls using the proposed algorithm, we achieved the average classification accuracies of 89.24% and 80.33% for 0-back and 1-back tasks respectively. Our results indicate that the proposed approach is promising for implementing human-computer interaction (HCI, especially for mental task classification and identifying suitable brain impairment candidates.

  7. 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...

  8. HAYABUSA SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Hayabusa SPICE data files (kernel files'') for the surveying and collection phases of the mission. The SPICE data files,...

  9. 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...

  10. Multiple Kernel Spectral Regression for Dimensionality Reduction

    Directory of Open Access Journals (Sweden)

    Bing Liu

    2013-01-01

    Full Text Available Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL into SR for dimensionality reduction. The proposed approach (termed MKL-SR seeks an embedding function in the Reproducing Kernel Hilbert Space (RKHS induced by the multiple base kernels. An MKL-SR algorithm is proposed to improve the performance of kernel-based SR (KSR further. Furthermore, the proposed MKL-SR algorithm can be performed in the supervised, unsupervised, and semi-supervised situation. Experimental results on supervised classification and semi-supervised classification demonstrate the effectiveness and efficiency of our algorithm.

  11. MESSENGER SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of MESSENGER SPICE data files (''kernel files''), which can be accessed using SPICE software. The SPICE data contains...

  12. CASSINI SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Cassini SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains geometric...

  13. NEAR SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of NEAR SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data contain geometric and...

  14. STARDUST SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Stardust SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data contains geometric...

  15. MSL SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the MSL SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contain geometric and other ancillary...

  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. Bandwidth Selection for Weighted Kernel Density Estimation

    OpenAIRE

    Wang, Bin; Wang, Xiaofeng

    2007-01-01

    In the this paper, the authors propose to estimate the density of a targeted population with a weighted kernel density estimator (wKDE) based on a weighted sample. Bandwidth selection for wKDE is discussed. Three mean integrated squared error based bandwidth estimators are introduced and their performance is illustrated via Monte Carlo simulation. The least-squares cross-validation method and the adaptive weight kernel density estimator are also studied. The authors also consider the boundary...

  18. Some Remarks on the Symmetry Kernel Test

    OpenAIRE

    Baszczyńska, Aleksandra

    2013-01-01

    The paper presents chosen statistical tests used to verify the hypothesis of the symmetry of random variable’s distribution. Detailed analysis of the symmetry kernel test is made. The properties of the regarded symmetry kernel test are compared with the other symmetry tests using Monte Carlo methods. The symmetry tests are used, as an example, in analysis of the distribution of the Human Development Index (HDI). W pracy przedstawiono wybrane statystyczne testy wykorzystywane w ...

  19. Preparation, properties and applications of wheat gluten edible films

    Directory of Open Access Journals (Sweden)

    P. TANADA-PALMU

    2008-12-01

    Full Text Available Edible films from wheat gluten were prepared with various amounts of glycerol as a plasticizer. Water vapor permeability, oxygen permeability, tensile strength and percentage elongation at break at different water activities ( aw were measured. Films with low amounts of glycerol had lower water vapor and oxygen permeabilities, higher tensile strength and lower elongation at break. Wheat gluten coatings reduced weight loss during two weeks of storage for cherry tomatoes and sharon fruits compared to uncoated controls. A bilayer film of wheat gluten and beeswax significantly lowered weight loss from coated cheese cubes compared to single layer coating of wheat gluten.;

  20. On the Inclusion Relation of Reproducing Kernel Hilbert Spaces

    OpenAIRE

    Zhang, Haizhang; Zhao, Liang

    2011-01-01

    To help understand various reproducing kernels used in applied sciences, we investigate the inclusion relation of two reproducing kernel Hilbert spaces. Characterizations in terms of feature maps of the corresponding reproducing kernels are established. A full table of inclusion relations among widely-used translation invariant kernels is given. Concrete examples for Hilbert-Schmidt kernels are presented as well. We also discuss the preservation of such a relation under various operations of ...

  1. 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 ...

  2. 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

  3. 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)

  4. Flexibly imposing periodicity in kernel independent FMM: A multipole-to-local operator approach

    Science.gov (United States)

    Yan, Wen; Shelley, Michael

    2018-02-01

    An important but missing component in the application of the kernel independent fast multipole method (KIFMM) is the capability for flexibly and efficiently imposing singly, doubly, and triply periodic boundary conditions. In most popular packages such periodicities are imposed with the hierarchical repetition of periodic boxes, which may give an incorrect answer due to the conditional convergence of some kernel sums. Here we present an efficient method to properly impose periodic boundary conditions using a near-far splitting scheme. The near-field contribution is directly calculated with the KIFMM method, while the far-field contribution is calculated with a multipole-to-local (M2L) operator which is independent of the source and target point distribution. The M2L operator is constructed with the far-field portion of the kernel function to generate the far-field contribution with the downward equivalent source points in KIFMM. This method guarantees the sum of the near-field & far-field converge pointwise to results satisfying periodicity and compatibility conditions. The computational cost of the far-field calculation observes the same O (N) complexity as FMM and is designed to be small by reusing the data computed by KIFMM for the near-field. The far-field calculations require no additional control parameters, and observes the same theoretical error bound as KIFMM. We present accuracy and timing test results for the Laplace kernel in singly periodic domains and the Stokes velocity kernel in doubly and triply periodic domains.

  5. 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.

  6. 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.

  7. Oecophylla longinoda (Hymenoptera: Formicidae) Lead to Increased Cashew Kernel Size and Kernel Quality.

    Science.gov (United States)

    Anato, F M; Sinzogan, A A C; Offenberg, J; Adandonon, A; Wargui, R B; Deguenon, J M; Ayelo, P M; Vayssières, J-F; Kossou, D K

    2017-06-01

    Weaver ants, Oecophylla spp., are known to positively affect cashew, Anacardium occidentale L., raw nut yield, but their effects on the kernels have not been reported. We compared nut size and the proportion of marketable kernels between raw nuts collected from trees with and without ants. Raw nuts collected from trees with weaver ants were 2.9% larger than nuts from control trees (i.e., without weaver ants), leading to 14% higher proportion of marketable kernels. On trees with ants, the kernel: raw nut ratio from nuts damaged by formic acid was 4.8% lower compared with nondamaged nuts from the same trees. Weaver ants provided three benefits to cashew production by increasing yields, yielding larger nuts, and by producing greater proportions of marketable kernel mass. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    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 MNF analyses handle 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. An example shows the successful application of (kernel PCA and) kernel MNF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, in Southern Germany. In the change detection...

  9. Pattern Classification of Signals Using Fisher Kernels

    Directory of Open Access Journals (Sweden)

    Yashodhan Athavale

    2012-01-01

    Full Text Available The intention of this study is to gauge the performance of Fisher kernels for dimension simplification and classification of time-series signals. Our research work has indicated that Fisher kernels have shown substantial improvement in signal classification by enabling clearer pattern visualization in three-dimensional space. In this paper, we will exhibit the performance of Fisher kernels for two domains: financial and biomedical. The financial domain study involves identifying the possibility of collapse or survival of a company trading in the stock market. For assessing the fate of each company, we have collected financial time-series composed of weekly closing stock prices in a common time frame, using Thomson Datastream software. The biomedical domain study involves knee signals collected using the vibration arthrometry technique. This study uses the severity of cartilage degeneration for classifying normal and abnormal knee joints. In both studies, we apply Fisher Kernels incorporated with a Gaussian mixture model (GMM for dimension transformation into feature space, which is created as a three-dimensional plot for visualization and for further classification using support vector machines. From our experiments we observe that Fisher Kernel usage fits really well for both kinds of signals, with low classification error rates.

  10. Multiple heat and drought events affect grain yield and accumulations of high molecular weight glutenin subunits and glutenin macropolymers in wheat

    DEFF Research Database (Denmark)

    Zhang, Xiaxiang; Cai, Jian; Wollenweber, Bernd

    2013-01-01

    Spring wheat plants were subjected to water deficit and/or high temperature episodes at spikelet initiation, anthesis or both stages. The stresses modified the early dough stage and maturity, shortened the kernel desiccation period and caused grain yield loss. Plants subjected to stress at the ea......Spring wheat plants were subjected to water deficit and/or high temperature episodes at spikelet initiation, anthesis or both stages. The stresses modified the early dough stage and maturity, shortened the kernel desiccation period and caused grain yield loss. Plants subjected to stress...

  11. 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

  12. 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.

  13. 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

  14. 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...

  15. Diversity of maize kernels from a breeding program for protein quality III: Ionome profiling

    Science.gov (United States)

    Densities of single and multiple macro- and micronutrients have been estimated in mature kernels of 1,348 accessions in 13 maize genotypes. The germplasm belonged to stiff stalk (SS) and non-stiff stalk (NS) heterotic groups (HG) with one (S1) to four (S4) years of inbreeding (IB), or open pollinati...

  16. Two axiomatizations of the kernel of TU games: bilateral and converse reduced game properties

    NARCIS (Netherlands)

    Driessen, Theo; Hu, C.-C.

    We provide two axiomatic characterizations of the kernel of TU games by means of both bilateral consistency and converse consistency with respect to two types of two-person reduced games. According to the first type, the worth of any single player in the two-person reduced game is derived from the

  17. 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

  18. 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.

  19. Phenolic constituents of shea (Vitellaria paradoxa) kernels.

    Science.gov (United States)

    Maranz, Steven; Wiesman, Zeev; Garti, Nissim

    2003-10-08

    Analysis of the phenolic constituents of shea (Vitellaria paradoxa) kernels by LC-MS revealed eight catechin compounds-gallic acid, catechin, epicatechin, epicatechin gallate, gallocatechin, epigallocatechin, gallocatechin gallate, and epigallocatechin gallate-as well as quercetin and trans-cinnamic acid. The mean kernel content of the eight catechin compounds was 4000 ppm (0.4% of kernel dry weight), with a 2100-9500 ppm range. Comparison of the profiles of the six major catechins from 40 Vitellaria provenances from 10 African countries showed that the relative proportions of these compounds varied from region to region. Gallic acid was the major phenolic compound, comprising an average of 27% of the measured total phenols and exceeding 70% in some populations. Colorimetric analysis (101 samples) of total polyphenols extracted from shea butter into hexane gave an average of 97 ppm, with the values for different provenances varying between 62 and 135 ppm of total polyphenols.

  20. Kernel Method for Nonlinear Granger Causality

    Science.gov (United States)

    Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

    2008-04-01

    Important information on the structure of complex systems can be obtained by measuring to what extent the individual components exchange information among each other. The linear Granger approach, to detect cause-effect relationships between time series, has emerged in recent years as a leading statistical technique to accomplish this task. Here we generalize Granger causality to the nonlinear case using the theory of reproducing kernel Hilbert spaces. Our method performs linear Granger causality in the feature space of suitable kernel functions, assuming arbitrary degree of nonlinearity. We develop a new strategy to cope with the problem of overfitting, based on the geometry of reproducing kernel Hilbert spaces. Applications to coupled chaotic maps and physiological data sets are presented.

  1. The scalar field kernel in cosmological spaces

    Energy Technology Data Exchange (ETDEWEB)

    Koksma, Jurjen F; Prokopec, Tomislav [Institute for Theoretical Physics (ITP) and Spinoza Institute, Utrecht University, Postbus 80195, 3508 TD Utrecht (Netherlands); Rigopoulos, Gerasimos I [Helsinki Institute of Physics, University of Helsinki, PO Box 64, FIN-00014 (Finland)], E-mail: J.F.Koksma@phys.uu.nl, E-mail: T.Prokopec@phys.uu.nl, E-mail: gerasimos.rigopoulos@helsinki.fi

    2008-06-21

    We construct the quantum-mechanical evolution operator in the functional Schroedinger picture-the kernel-for a scalar field in spatially homogeneous FLRW spacetimes when the field is (a) free and (b) coupled to a spacetime-dependent source term. The essential element in the construction is the causal propagator, linked to the commutator of two Heisenberg picture scalar fields. We show that the kernels can be expressed solely in terms of the causal propagator and derivatives of the causal propagator. Furthermore, we show that our kernel reveals the standard light cone structure in FLRW spacetimes. We finally apply the result to Minkowski spacetime, to de Sitter spacetime and calculate the forward time evolution of the vacuum in a general FLRW spacetime.

  2. Fast Generation of Sparse Random Kernel Graphs.

    Science.gov (United States)

    Hagberg, Aric; Lemons, Nathan

    2015-01-01

    The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in time at most (n(logn)2). As a practical example we show how to generate samples of power-law degree distribution graphs with tunable assortativity.

  3. Robust C-Loss Kernel Classifiers.

    Science.gov (United States)

    Xu, Guibiao; Hu, Bao-Gang; Principe, Jose C

    2018-03-01

    The correntropy-induced loss (C-loss) function has the nice property of being robust to outliers. In this paper, we study the C-loss kernel classifier with the Tikhonov regularization term, which is used to avoid overfitting. After using the half-quadratic optimization algorithm, which converges much faster than the gradient optimization algorithm, we find out that the resulting C-loss kernel classifier is equivalent to an iterative weighted least square support vector machine (LS-SVM). This relationship helps explain the robustness of iterative weighted LS-SVM from the correntropy and density estimation perspectives. On the large-scale data sets which have low-rank Gram matrices, we suggest to use incomplete Cholesky decomposition to speed up the training process. Moreover, we use the representer theorem to improve the sparseness of the resulting C-loss kernel classifier. Experimental results confirm that our methods are more robust to outliers than the existing common classifiers.

  4. 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

  5. Ensemble-based forecasting at Horns Rev: Ensemble conversion and kernel dressing

    DEFF Research Database (Denmark)

    Pinson, Pierre; Madsen, Henrik

    For management and trading purposes, information on short-term wind generation (from few hours to few days ahead) is even more crucial at large offshore wind farms, since they concentrate a large capacity at a single location. The most complete information that can be provided today consists....... The obtained ensemble forecasts of wind power are then converted into predictive distributions with an original adaptive kernel dressing method. The shape of the kernels is driven by a mean-variance model, the parameters of which are recursively estimated in order to maximize the overall skill of obtained...

  6. 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.

  7. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

    Principal component analysis (PCA) is often used to detect change over time in remotely sensed images. A commonly used technique consists of finding the projections along the two eigenvectors for data consisting of two variables which represent the same spectral band covering the same geographical...... 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...

  8. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...... 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...... found the estimates of the fully nonparametric panel data model to be more reliable....

  9. 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

  10. 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

  11. 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

  12. 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

  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. 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

  15. 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...

  16. 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

  17. Technological effects of the wheat cleaning equipment of an industrial mill

    Directory of Open Access Journals (Sweden)

    Georgeta STOENESCU

    2010-12-01

    Full Text Available Romanian wheat, Dropia variety, was cleaned and tempered in an industrial roller mill. Technological effects of the wheat cleaning equipment were investigated as function of the total impurities removed from the cereals. The impurities separated through combi-cleaner and indented separators were 83.42 and 82.83%, respectively. Through scouring, the reduction of the ash content was 0.0225%, while the grains broken were 0.223%. Correlations between the physical parameters and the impurities content were also established. The results indicated negative correlations between thousand kernel weight and impurities content.

  18. 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.

  19. 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

  20. 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.

  1. 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.)

  2. 42 Variability Bugs in the Linux Kernel

    DEFF Research Database (Denmark)

    Abal, Iago; Brabrand, Claus; Wasowski, Andrzej

    2014-01-01

    , serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 42 variability bugs collected from bug-fixing commits to the Linux kernel repository. We analyze each of the bugs, and record the results in a database. In addition, we...

  3. 40 Variability Bugs in the Linux Kernel

    DEFF Research Database (Denmark)

    Abal Rivas, Iago; Brabrand, Claus; Wasowski, Andrzej

    2014-01-01

    is a requirement for goal-oriented research, serving to evaluate tool implementations of feature-sensitive analyses by testing them on real bugs. We present a qualitative study of 40 variability bugs collected from bug-fixing commits to the Linux kernel repository. We investigate each of the 40 bugs, recording...

  4. 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

  5. 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

  6. 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

  7. Graph Bundling by Kernel Density Estimation

    NARCIS (Netherlands)

    Hurter, C.; Ersoy, O.; Telea, A.

    We present a fast and simple method to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply an image sharpening technique which progressively merges local height maxima by moving the convolved

  8. Evaluation of different combinations of palm kernel cake - and cotton ...

    African Journals Online (AJOL)

    ... sole palm kernel cake based diets than those fed combinations of palm kernel cake and cottonseed cake. It is concluded that palm kernel cake alone (without any combination with cottonseed cake) is adequate as protein source in compounding protein supplements for West African Dwarf goats for profitable performance.

  9. determination of bio-energy potential of palm kernel shell

    African Journals Online (AJOL)

    88888888

    2012-11-03

    Nov 3, 2012 ... Palm Kernel Shell (PKS) is an economically and environmentally sustainable raw material for ... oil and palm kernel oil production, palm oil fibre, effluent, kernel shell and empty fruit bunch are re- garded as wastes. According to Luangkiattikhun et ... use as concrete reinforcement in construction indus-.

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

    African Journals Online (AJOL)

    ADOWIE PERE

    ABSTRACT: A machine processing method for the separation of cracked palm kernel from the shells using ... Cracked palm kernel is a mixture of kernels, broken shells, dusts and other impurities. In order to produce ... Received 31 September 2017, received in revised form 18 October 2017, accepted 29 November 2017.

  11. An Investigation of Kernel Data Attacks and Countermeasures

    Science.gov (United States)

    2017-02-14

    demonstrate that attackers can stealthily subvert various kernel security mechanism s and develop a new keylogger , which is more stealthy than existing... keyloggers .. By classifying kernel data into different categories and handling them separately, we propose a defense mechanism and evaluate its...a computer system. 15. SUBJECT TERMS Kernel Data, Rootkit, Keylogger , Countermeasure 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF a. REPORT b

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

    Science.gov (United States)

    Giguère, Sébastien; Marchand, Mario; Laviolette, François; Drouin, Alexandre; Corbeil, Jacques

    2013-03-05

    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. 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. On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting peptide-protein binding

  13. 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.

  14. 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

  15. 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

  16. 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

  17. Online Regularized and Kernelized Extreme Learning Machines with Forgetting Mechanism

    Directory of Open Access Journals (Sweden)

    Xinran Zhou

    2014-01-01

    Full Text Available To apply the single hidden-layer feedforward neural networks (SLFN to identify time-varying system, online regularized extreme learning machine (ELM with forgetting mechanism (FORELM and online kernelized ELM with forgetting mechanism (FOKELM are presented in this paper. The FORELM updates the output weights of SLFN recursively by using Sherman-Morrison formula, and it combines advantages of online sequential ELM with forgetting mechanism (FOS-ELM and regularized online sequential ELM (ReOS-ELM; that is, it can capture the latest properties of identified system by studying a certain number of the newest samples and also can avoid issue of ill-conditioned matrix inversion by regularization. The FOKELM tackles the problem of matrix expansion of kernel based incremental ELM (KB-IELM by deleting the oldest sample according to the block matrix inverse formula when samples occur continually. The experimental results show that the proposed FORELM and FOKELM have better stability than FOS-ELM and have higher accuracy than ReOS-ELM in nonstationary environments; moreover, FORELM and FOKELM have time efficiencies superiority over dynamic regression extreme learning machine (DR-ELM under certain conditions.

  18. Binary mixtures of waxy wheat and conventional wheat as measured by NIR reflectance.

    Science.gov (United States)

    Delwiche, Stephen R; Graybosch, Robert A

    2016-01-01

    Waxy wheat contains very low concentration (generally industries seek to have a rapid technique to ensure the purity of identity preserved waxy wheat lots. Near infrared (NIR) reflectance spectroscopy, a technique widely used in the cereals industry for proximate analysis, is a logical candidate for measuring contamination level and thus is the subject of this study. Two sets of wheat samples, harvested, prepared and scanned one year apart, were used to evaluate the NIR concept. One year consisted of nine pairs of conventional:waxy preparations, with each preparation consisting of 29 binary mixtures ranging in conventional wheat fraction (by weight) of 0-100% (261 spectral samples). The second year was prepared in the same fashion, with 12 preparations, thus producing 348 spectral samples. One year's samples were controlled for protein content and moisture level between pair components in order to avoid the basis for the conventional wheat fraction models being caused by something other than spectral differences attributed to waxy and nonwaxy endosperm. Likewise the second year was controlled by selection of conventional wheat for mixture preparation based on either protein content or cluster analysis of principal components of candidate spectra. Partial least squares regression, one and two-term linear regression, and support vector machine regression models were examined. Validation statistics arising from sets within the same year or across years were remarkably similar, as were those among the three regression types. A single wavelength on second derivative transformed spectra, namely 2290 nm, was effective at estimating the mixture level by weight, with standard errors of performance in the 6-9% range. Thus, NIR spectroscopy may be used for measuring conventional hard wheat 'contamination' in waxy wheat at mixture levels above 10% w/w. Published by Elsevier B.V.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Utilizing Temporal Information in fMRI Decoding: Classifier Using Kernel Regression Methods

    Science.gov (United States)

    Chu, Carlton; Mourão-Miranda, Janaina; Chiu, Yu-Chin; Kriegeskorte, Nikolaus; Tan, Geoffrey; Ashburner, John

    2011-01-01

    This paper describes a general kernel regression approach to predict experimental conditions from activity patterns acquired with functional magnetic resonance image (fMRI). The standard approach is to use classifiers that predict conditions from activity patterns. Our approach involves training different regression machines for each experimental condition, so that a predicted temporal profile is computed for each condition. A decision function is then used to classify the responses from the testing volumes into the corresponding category, by comparing the predicted temporal profile elicited by each event, against a canonical haemodynamic response function. This approach utilizes the temporal information in the fMRI signal and maintains more training samples in order to improve the classification accuracy over an existing strategy. This paper also introduces efficient techniques of temporal compaction, which operate directly on kernel matrices for kernel classification algorithms such as the support vector machine (SVM). Temporal compacting can convert the kernel computed from each fMRI volume directly into the kernel computed from beta-maps, average of volumes or spatial-temporal kernel. The proposed method was applied to three different datasets. The first one is a block-design experiment with three conditions of image stimuli. The method outperformed the SVM classifiers of three different types of temporal compaction in single-subject leave-one-block-out cross-validation. Our method achieved 100% classification accuracy for six of the subjects and an average of 94% accuracy across all 16 subjects, exceeding the best SVM classification result, which was 83% accuracy (p=0.008). The second dataset is also a block-design experiment with two conditions of visual attention (left or right). Our method yielded 96% accuracy and SVM yielded 92% (p=0.005). The third dataset is from a fast event-related experiment with two categories of visual objects. Our method achieved

  4. 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...... models to kernel learning, and means for restoring the generalizability in both kernel Principal Component Analysis and the Support Vector Machine are proposed. Viability is proved on a wide range of benchmark machine learning data sets....... as innerproducts in the model formulation. This dissertation presents research on improving the performance of standard kernel methods like kernel Principal Component Analysis and the Support Vector Machine. Moreover, the goal of the thesis has been two-fold. The first part focuses on the use of kernel Principal...

  5. Wheat Stripe Rust

    OpenAIRE

    Pace, Mike; Israelsen, Clark; Evans, Kent; Barnhill, James

    2008-01-01

    Stripe rust, or yellow rust, is primarily a foliar fungal disease of wheat, although it can infect spike and stem tissues. If the pathogen infects the spike (head) it causes extensive quality and grain yield loss. The disease is caused by the fungus Puccinia striiformis f. sp. tritici. The fungus can only survive and reproduce on wheat. It survives from one season to the next on volunteer plants.

  6. 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.

  7. 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 ...

  8. Assessment of mechanical damage to wheat grain as detected by means of the X-ray technique

    International Nuclear Information System (INIS)

    Niewczas, J.

    1994-01-01

    The study present a method for definite digital recording of the status of internal damage (mainly cracks of endosperm) of wheat kernel. The method consists in the identification of damage in the particular fields of a square grid covering the X-ray image of the kernel under study. A number of indices have been proposed, making use of that identification. In the study an overall index was employed, defined as the number of the rectangles of the grid in which damage was observed. The test material was constituted by samples of ordinary winter wheat (Gama, Liwilla, Jara) and spring wheat (Henika, Jara, Kadett) originating from machine threshing. The destructive factor was introduced by means of the application levels and dynamic loading of individual kernels. The quantitative assessment of the status of damage of the wheat grain samples studied showed a significant intervarietal differentiation, not only as a result of the effect of the types of loading applied, but also in the control material. The control samples of all varieties tested were characterized by indexes significantly above zero, with spring varieties showing a considerably higher level of initial damage. The grain of the winter varieties turned out to be more susceptible to damage under static loading, and that of the spring varieties - under dynamic loading. (author). 45 refs, 12 figs, 14 tabs

  9. 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

  10. 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...

  11. 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.

  12. 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...

  13. Searching and Indexing Genomic Databases via Kernelization

    Directory of Open Access Journals (Sweden)

    Travis eGagie

    2015-02-01

    Full Text Available The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper we survey the twenty-year history of this idea and discuss its relation to kernelization in parameterized complexity.

  14. 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......). The MAF projection exploits the fact that interesting phenomena in images typically exhibit spatial autocorrelation. The analysis is based on nearinfrared hyperspectral images of maize grains demonstrating the superiority of the kernelbased MAF method....

  15. Multiple Kernel Learning with Data Augmentation

    Science.gov (United States)

    2016-11-22

    et al., 2010; Sun et al., 2010). Particularly, Sun et al. (2010) developed an efficient method based on sequential minimal optimization (SMO). The...http://www.robots.ox.ac.uk/~vgg/data/ flowers /17/ 58 Multiple Kernel Learning with Data Augmentation Algorithm 2 MKL with Data Augmentation approach for...Maria-Elena Nilsback and Andrew Zisserman. A visual vocabulary for flower classification. In Com- puter Vision and Pattern Recognition, 2006 IEEE Computer

  16. Multiple Kernel Spectral Regression for Dimensionality Reduction

    OpenAIRE

    Liu, Bing; Xia, Shixiong; Zhou, Yong

    2013-01-01

    Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples. To solve the out-of-sample extension problem, spectral regression (SR) solves the problem of learning an embedding function by establishing a regression framework, which can avoid eigen-decomposition of dense matrices. Motivated by the effectiveness of SR, we incorporate multiple kernel learning (MKL) into SR for dimensionality...

  17. Searching and Indexing Genomic Databases via Kernelization.

    Science.gov (United States)

    Gagie, Travis; Puglisi, Simon J

    2015-01-01

    The rapid advance of DNA sequencing technologies has yielded databases of thousands of genomes. To search and index these databases effectively, it is important that we take advantage of the similarity between those genomes. Several authors have recently suggested searching or indexing only one reference genome and the parts of the other genomes where they differ. In this paper, we survey the 20-year history of this idea and discuss its relation to kernelization in parameterized complexity.

  18. 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.

  19. 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/

  20. 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)

  1. 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...

  2. Multiple kernel learning for dimensionality reduction.

    Science.gov (United States)

    Lin, Yen-Yu; Liu, Tyng-Luh; Fuh, Chiou-Shann

    2011-06-01

    In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting data representations are typically high-dimensional and assume diverse forms. Hence, finding a way of transforming them into a unified space of lower dimension generally facilitates the underlying tasks such as object recognition or clustering. To this end, the proposed approach (termed MKL-DR) generalizes the framework of multiple kernel learning for dimensionality reduction, and distinguishes itself with the following three main contributions: first, our method provides the convenience of using diverse image descriptors to describe useful characteristics of various aspects about the underlying data. Second, it extends a broad set of existing dimensionality reduction techniques to consider multiple kernel learning, and consequently improves their effectiveness. Third, by focusing on the techniques pertaining to dimensionality reduction, the formulation introduces a new class of applications with the multiple kernel learning framework to address not only the supervised learning problems but also the unsupervised and semi-supervised ones.

  3. Scientific opinion on a quantitative pathway analysis of the likelihood ofTilletia indica M. introduction into EU with importation of US wheat

    DEFF Research Database (Denmark)

    Baker, R.; Candresse, T.; Dormannsné Simon, E.

    2010-01-01

    wheat model for several parameters related to EU country characteristics. Further research is needed to refine parameter values, to reduce uncertainty and to determine relationship between teliospores number on soil surface and number of bunted kernels resulting from infection of a wheat plant...... the US bunted kernel standard would provide equivalent protection against introduction of Tilletia indica into EU, compared to the existing EU import requirement. The Panel on Plant Health reviewed pathway scenarios, model and parameters and found several shortcomings regarding model equations....... The Panel concluded that the US bunted kernel standard does not provide a level of protection equivalent to EU requirements and that such level of protection could only be warranted by measures which include testing at harvest and before shipment to detect T. indica teliospores....

  4. 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

  5. [Competitiveness of hard wheat (Triticum durum Desf.) varieties against ripgut brome (Bromus rigidus Roth)].

    Science.gov (United States)

    Hamal, A; Benbella, M; Rzozi, S B; Bouhache, M; Msatef, Y

    2001-01-01

    Varieties with an excellent competitiveness against ripgut brome (Bromus rigidus Roth.) would be very important to reinforce others methods to control ripgut brome weed. This study was carried out in 1999-2000 season in a greenhouse experiment to test the aggressiveness degree of six varieties of hard wheat (Oum Rabia, Isly, Marzak, Karim, Sebou, and Massa) combined with ripgut brome. Plant density was fixed at 16 plants of wheat or Bromus for pure crop and 8 plants for wheat and 8 for Bromus mixture. The results showed that the numbers of kernels/spikes were higher in the mixture for on pure composition. For the kernel weight, the result was opposite except for Isly and Marzak varieties. Karim and Isly varieties obtained the highest grain yield and were more competitive in mixture composition but Sebou and Massa varieties were less competitive against ripgut brome. Results of ripgut brome productivity and water use efficiency were similar and were used to determine the aggressiveness coefficient of hard wheat varieties against ripgut brome. The reduction of the shoot dry matter of brome was 22 to 56% at flowering. The grain yield of brome was reduced from 57 to 81%.

  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. 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.

  8. 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.

  9. 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.

  10. 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

  11. Kernel-Based Sensor Fusion With Application to Audio-Visual Voice Activity Detection

    Science.gov (United States)

    Dov, David; Talmon, Ronen; Cohen, Israel

    2016-12-01

    In this paper, we address the problem of multiple view data fusion in the presence of noise and interferences. Recent studies have approached this problem using kernel methods, by relying particularly on a product of kernels constructed separately for each view. From a graph theory point of view, we analyze this fusion approach in a discrete setting. More specifically, based on a statistical model for the connectivity between data points, we propose an algorithm for the selection of the kernel bandwidth, a parameter, which, as we show, has important implications on the robustness of this fusion approach to interferences. Then, we consider the fusion of audio-visual speech signals measured by a single microphone and by a video camera pointed to the face of the speaker. Specifically, we address the task of voice activity detection, i.e., the detection of speech and non-speech segments, in the presence of structured interferences such as keyboard taps and office noise. We propose an algorithm for voice activity detection based on the audio-visual signal. Simulation results show that the proposed algorithm outperforms competing fusion and voice activity detection approaches. In addition, we demonstrate that a proper selection of the kernel bandwidth indeed leads to improved performance.

  12. 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...... 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......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data....

  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

    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...... concentrations of glucose, insulin, glucagon, incretins, cholecystokinin, and bile acids were analyzed. RESULTS: 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......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...

  14. 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...... kernels and did not give acceptable results because of high misclassification. However by using a predefined threshold and classifying entire kernels based on the number of correctly predicted pixels, improved results were achieved (sensitivity and specificity of 0.75 and 0.97). Object-wise classification...... was performed using two methods for feature extraction — score histograms and mean spectra. The model based on score histograms performed better for hard kernel classification (sensitivity and specificity of 0.93 and 0.97), while that of mean spectra gave better results for medium kernels (sensitivity...

  15. 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...... Analysis (KPCA) that only keeps features contributing mostly to image reconstruction, KECA selects the CKD that contribute mostly to the Rényi entropy of the image. These CKD are discriminative as they relate to the density distribution of the histogram of image attributes. We report superior performance...

  16. 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.

  17. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard

    show that the performance of linear models is reduced for certain scan labelings/categorizations in this data set, while the nonlinear models provide more flexibility. We show that the sensitivity map can be used to visualize nonlinear versions of kernel logistic regression, the kernel Fisher...... discriminant, and the SVM, and conclude that the sensitivity map is a versatile and computationally efficient tool for visualization of nonlinear kernel models in neuroimaging...

  18. Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression

    OpenAIRE

    Peter Exterkate; Patrick J.F. Groenen; Christiaan Heij; Dick van Dijk

    2011-01-01

    textabstractThis 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 predictive regression model is based on a shrinkage estimator to avoid overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by ...

  19. Fusarium head blight (FHB and Fusarium populations in grain of winter wheat grown in different cultivation systems

    Directory of Open Access Journals (Sweden)

    Lenc Leszek

    2015-01-01

    Full Text Available Fusarium head blight (FHB incidence, and colonisation of grain by Fusarium species on winter wheat grown in organic, integrated, and conventional systems as well as in monoculture, were studied locally in Poland, from 2002 to 2010. Fusarium head blight incidence differed throughout the study years. It was found to occur the most where rainfall was highest and where rainfall was the most prolonged before, during, and after flowering of wheat. Fusarium head blight incidence was generally less on wheat grown organically than on wheat grown in other systems. In some years, FHB was noted more in monocultures than in other systems. Fusarium poae was the most common species of FHB populations in wheat kernels, followed by F. avenaceum and F. tricinctum. Other species which occurred more rarely or sporadically were: F. culmorum, F. equiseti, F. graminearum, F. langsethiae, F. oxysporum, and F. sporotrichioides. There were found to be significant effects of the cropping system on grain colonisation by Fusarium in some years. There was a positive correlation between FHB incidence and number of kernels colonised and damaged by Fusarium, in all four systems. Inferences were drawn concerning the effects of different procedures in different production systems and the possible value for controlling FHB

  20. 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...... for physiological traits that may confer better adaptation to changing climatic conditions. Eventually, combining all the identified “good genes” may aid in developing stress tolerant cultivars to overcome environmental constraints and thereby, meet the increasing demand of future food security....

  1. 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....

  2. 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......) dimensional feature space via the kernel function and then performing a linear analysis in that space. An example shows the successful application of kernel MAF analysis to change detection in HyMap data covering a small agricultural area near Lake Waging-Taching, Bavaria, Germany....

  3. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, P.M.; Madsen, Kristoffer H; Lund, T.E.

    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...... show that the performance of linear models is reduced for certain scan labelings/categorizations in this data set, while the nonlinear models provide more flexibility. We show that the sensitivity map can be used to visualize nonlinear versions of kernel logistic regression, the kernel Fisher...

  4. 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).

  5. 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

  6. Index-free Heat Kernel Coefficients

    OpenAIRE

    van de Ven, Anton E. M.

    1997-01-01

    Using index-free notation, we present the diagonal values of the first five heat kernel coefficients associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient appears here for the first time. For a flat space with a gauge connection, the sixth coefficient is given too. Also provided are the leading terms for any coefficient, both in ascending and descending powers of the Yang-Mills and Riemann curvatures, to the same order as require...

  7. Localized Multiple Kernel Learning A Convex Approach

    Science.gov (United States)

    2016-11-22

    1/2 . Theorem 9 (CLMKL Generalization Error Bounds) Assume that km(x, x) ≤ B, ∀m ∈ NM , x ∈ X . Suppose the loss function ℓ is L- Lipschitz and...mathematical foundation (e.g., Schölkopf and Smola, 2002). The performance of such algorithms, however, crucially depends on the involved kernel function ...approaches to localized MKL (reviewed in Section 1.1) optimize non-convex objective functions . This puts their generalization ability into doubt. Indeed

  8. 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.

  9. Kernel-based machine learning techniques for infrasound signal classification

    Science.gov (United States)

    Tuma, Matthias; Igel, Christian; Mialle, Pierrick

    2014-05-01

    Infrasound monitoring is one of four remote sensing technologies continuously employed by the CTBTO Preparatory Commission. The CTBTO's infrasound network is designed to monitor the Earth for potential evidence of atmospheric or shallow underground nuclear explosions. Upon completion, it will comprise 60 infrasound array stations distributed around the globe, of which 47 were certified in January 2014. Three stages can be identified in CTBTO infrasound data processing: automated processing at the level of single array stations, automated processing at the level of the overall global network, and interactive review by human analysts. At station level, the cross correlation-based PMCC algorithm is used for initial detection of coherent wavefronts. It produces estimates for trace velocity and azimuth of incoming wavefronts, as well as other descriptive features characterizing a signal. Detected arrivals are then categorized into potentially treaty-relevant versus noise-type signals by a rule-based expert system. This corresponds to a binary classification task at the level of station processing. In addition, incoming signals may be grouped according to their travel path in the atmosphere. The present work investigates automatic classification of infrasound arrivals by kernel-based pattern recognition methods. It aims to explore the potential of state-of-the-art machine learning methods vis-a-vis the current rule-based and task-tailored expert system. To this purpose, we first address the compilation of a representative, labeled reference benchmark dataset as a prerequisite for both classifier training and evaluation. Data representation is based on features extracted by the CTBTO's PMCC algorithm. As classifiers, we employ support vector machines (SVMs) in a supervised learning setting. Different SVM kernel functions are used and adapted through different hyperparameter optimization routines. The resulting performance is compared to several baseline classifiers. All

  10. Wheat allergy: diagnosis and management

    Directory of Open Access Journals (Sweden)

    Cianferoni A

    2016-01-01

    Full Text Available Antonella Cianferoni Department of Pediatrics, Division of Allergy and Immunology, The Children’s Hospital of Philadelphia, PA, USA Abstract: Triticum aestivum (bread wheat is the most widely grown crop worldwide. In genetically predisposed individuals, wheat can cause specific immune responses. A food allergy to wheat is characterized by T helper type 2 activation which can result in immunoglobulin E (IgE and non-IgE mediated reactions. IgE mediated reactions are immediate, are characterized by the presence of wheat-specific IgE antibodies, and can be life-threatening. Non-IgE mediated reactions are characterized by chronic eosinophilic and lymphocytic infiltration of the gastrointestinal tract. IgE mediated responses to wheat can be related to wheat ingestion (food allergy or wheat inhalation (respiratory allergy. A food allergy to wheat is more common in children and can be associated with a severe reaction such as anaphylaxis and wheat-dependent, exercise-induced anaphylaxis. An inhalation induced IgE mediated wheat allergy can cause baker’s asthma or rhinitis, which are common occupational diseases in workers who have significant repetitive exposure to wheat flour, such as bakers. Non-IgE mediated food allergy reactions to wheat are mainly eosinophilic esophagitis (EoE or eosinophilic gastritis (EG, which are both characterized by chronic eosinophilic inflammation. EG is a systemic disease, and is associated with severe inflammation that requires oral steroids to resolve. EoE is a less severe disease, which can lead to complications in feeding intolerance and fibrosis. In both EoE and EG, wheat allergy diagnosis is based on both an elimination diet preceded by a tissue biopsy obtained by esophagogastroduodenoscopy in order to show the effectiveness of the diet. Diagnosis of IgE mediated wheat allergy is based on the medical history, the detection of specific IgE to wheat, and oral food challenges. Currently, the main treatment of a

  11. Dissecting the frog inner ear with Gaussian noise .1. Application of high-order Wiener-kernel analysis

    NARCIS (Netherlands)

    vanDijk, P; Wit, HP; Segenhout, JM

    1997-01-01

    Wiener kernel analysis was used to characterize the auditory pathway from tympanic membrane to single primary auditory nerve fibers in the European edible frog, Rana esculenta. Nerve fiber signals were recorded in response to white Gaussian noise. By cross-correlating the noise stimulus and the

  12. [Effects of irrigation time on the growth and water- and fertilizer use efficiencies of winter wheat].

    Science.gov (United States)

    Dang, Jian-You; Pei, Xue-Xia; Wang, Jiao-Ai; Zhang, Jing; Cao, Yong; Zhang, Ding-Yi

    2012-10-01

    A field experiment was conducted to study the effects of irrigation time before wintering (November 10th, November 25th, and December 10th) and in spring (March 5th, re-greening stage; and April 5th, jointing stage) on the growth, dry matter translocation, water use efficiency (WUE), and fertilizer use efficiency (FUE) of winter wheat after returning corn straw into soil. The irrigation time before wintering mainly affected the wheat population size before wintering and at jointing stage, whereas the irrigation time in spring mainly affected the spike number, grain yield, dry matter translocation, WUE, and FUE. The effects of irrigation time before wintering to the yield formation of winter wheat were closely related to the irrigation time in spring. When the irrigation time in spring was at re-greening stage, the earlier the irrigation time before wintering, the larger the spike number and the higher the grain yield; when the irrigation time in spring was at jointing stage, the delay of the irrigation time before wintering made the spike number and grain yield decreased after an initial increase, the kernel number per plant increased, while the 1000-kernel mass was less affected. The WUE, nutrition uptake, and FUE all decreased with the delay of the irrigation time before wintering, but increased with the delay of the irrigation time in spring. Therefore, under the conditions of returning corn straw into soil and sowing when the soil had enough moisture, to properly advance the irrigation time before wintering could make the soil more compacted, promote the tillering and increase the population size before winter, and in combining the increased irrigation at jointing stage, could control the invalid tillering in early spring, increase the spiking rate, obtain stable kernel mass, and thus, increase the WUE and FUE, realizing water-saving and high efficiency for winter wheat cultivation.

  13. Index-free heat kernel coefficients

    Science.gov (United States)

    van de Ven, Anton E. M.

    1998-08-01

    Using index-free notation, we present the diagonal values 0264-9381/15/8/014/img1 of the first five heat kernel coefficients 0264-9381/15/8/014/img2 associated with a general Laplace-type operator on a compact Riemannian space without boundary. The fifth coefficient 0264-9381/15/8/014/img3 appears here for the first time. For the special case of a flat space, but with a gauge connection, the sixth coefficient is given too. Also provided are the leading terms for any coefficient, both in ascending and descending powers of the Yang-Mills and Riemann curvatures, to the same order as required for the fourth coefficient. These results are obtained by directly solving the relevant recursion relations, working in the Fock-Schwinger gauge and Riemann normal coordinates. Our procedure is thus non-covariant, but we show that for any coefficient the `gauged', respectively `curved', version is found from the corresponding `non-gauged', respectively `flat', coefficient by making some simple covariant substitutions. These substitutions being understood, the coefficients retain their `flat' form and size. In this sense the fifth and sixth coefficient have only 26 and 75 terms, respectively, allowing us to write them down. Using index-free notation also clarifies the general structure of the heat kernel coefficients. In particular, in flat space we find that from the fifth coefficient onward, certain scalars are absent. This may be relevant for the anomalies of quantum field theories in ten or more dimensions.

  14. 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.

  15. Kernelized rank learning for personalized drug recommendation.

    Science.gov (United States)

    He, Xiao; Folkman, Lukas; Borgwardt, Karsten

    2018-03-08

    Large-scale screenings of cancer cell lines with detailed molecular profiles against libraries of pharmacological compounds are currently being performed in order to gain a better understanding of the genetic component of drug response and to enhance our ability to recommend therapies given a patient's molecular profile. These comprehensive screens differ from the clinical setting in which (1) medical records only contain the response of a patient to very few drugs, (2) drugs are recommended by doctors based on their expert judgment, and (3) selecting the most promising therapy is often more important than accurately predicting the sensitivity to all potential drugs. Current regression models for drug sensitivity prediction fail to account for these three properties. We present a machine learning approach, named Kernelized Rank Learning (KRL), that ranks drugs based on their predicted effect per cell line (patient), circumventing the difficult problem of precisely predicting the sensitivity to the given drug. Our approach outperforms several state-of-the-art predictors in drug recommendation, particularly if the training dataset is sparse, and generalizes to patient data. Our work phrases personalized drug recommendation as a new type of machine learning problem with translational potential to the clinic. The Python implementation of KRL and scripts for running our experiments are available at https://github.com/BorgwardtLab/Kernelized-Rank-Learning. xiao.he@bsse.ethz.ch, lukas.folkman@bsse.ethz.ch. Supplementary data are available at Bioinformatics online.

  16. 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.

  17. 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.

  18. 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.

  19. 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 ...

  20. BRS 277: Wheat cultivar

    Directory of Open Access Journals (Sweden)

    Eduardo Caierão

    2009-01-01

    Full Text Available The wheat cultivar ‘BRS 277’ was developed by Embrapa (Empresa Brasileira de Pesquisa Agropecuária,resulting from a cross between OR1 and Coker 97-33. The plant height of ‘BRS 277’ is short, frost resistance in the vegetativestage is good and resistance to leaf rust moderate.

  1. 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 ...

  2. 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...

  3. 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.

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

    African Journals Online (AJOL)

    A 3-factor experimental design was used to determine the influence of moisture content, roasting duration and temperature on palm kernel and sesame oil colours. Four levels each of these parameters were used. The data obtained were used to develop prediction models for palm kernel and sesame oil colours. Coefficient ...

  5. Evaluation of enzyme supplementation of palm kernel meal-based ...

    African Journals Online (AJOL)

    Journal of Agriculture, Forestry and the Social Sciences ... The results of this study showed that broilers can tolerate 20% inclusion rate of palm kernel meal in their rations without enzyme supplementation and partially replacing maize with palm kernel meal at that level of inclusion can reduce the cost of production of ...

  6. 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...

  7. Efficient methods for robust classification under uncertainty in kernel matrices

    NARCIS (Netherlands)

    Ben-Tal, A.; Bhadra, S.; Bhattacharyya, C.; Nemirovski, A.

    2012-01-01

    In this paper we study the problem of designing SVM classifiers when the kernel matrix, K , is affected by uncertainty. Specifically K is modeled as a positive affine combination of given positive semi definite kernels, with the coefficients ranging in a norm-bounded uncertainty set. We treat the

  8. 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 ...

  9. Homotopy deform method for reproducing kernel space for ...

    Indian Academy of Sciences (India)

    In this paper, the combination of homotopy deform method (HDM) and simplified reproducing kernel method (SRKM) is introduced for solving the boundary value problems (BVPs) of nonlinear differential equations. The solution methodology is based on Adomian decomposition and reproducing kernel method (RKM).

  10. 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.

  11. 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 ...

  12. 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

  13. 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...

  14. High-power asymptotics of some weighted harmonic Bergman kernels

    Czech Academy of Sciences Publication Activity Database

    Engliš, Miroslav

    2016-01-01

    Roč. 271, č. 5 (2016), s. 1243-1261 ISSN 0022-1236 Institutional support: RVO:67985840 Keywords : Bergman kernel * harmonic Bergman kernel * asymptotic expansion Subject RIV: BA - General Mathematics Impact factor: 1.254, year: 2016 http://www.sciencedirect.com/science/article/pii/S0022123616301513

  15. Efficient Kernel-based 2DPCA for Smile Stages Recognition

    Directory of Open Access Journals (Sweden)

    Fitri Damayanti

    2012-03-01

    Full Text Available Recently, an approach called two-dimensional principal component analysis (2DPCA has been proposed for smile stages representation and recognition. The essence of 2DPCA is that it computes the eigenvectors of the so-called image covariance matrix without matrix-to-vector conversion so the size of the image covariance matrix are much smaller, easier to evaluate covariance matrix, computation cost is reduced and the performance is also improved than traditional PCA. In an effort to improve and perfect the performance of smile stages recognition, in this paper, we propose efficient Kernel based 2DPCA concepts. The Kernelization of 2DPCA can be benefit to develop the nonlinear structures in the input data. This paper discusses comparison of standard Kernel based 2DPCA and efficient Kernel based 2DPCA for smile stages recognition. The results of experiments show that Kernel based 2DPCA achieve better performance in comparison with the other approaches. While the use of efficient Kernel based 2DPCA can speed up the training procedure of standard Kernel based 2DPCA thus the algorithm can achieve much more computational efficiency and remarkably save the memory consuming compared to the standard Kernel based 2DPCA.

  16. Nutritional evaluation of palm kernel meal types: 1. Proximate ...

    African Journals Online (AJOL)

    Studies were conducted to determine the proximate composition and metabolizable energy values of palm kernel meal (PKM) types. The PKM types studied were obtained from Okomu, Presco and Envoy Oil Mills and were either mechanically or solvent extracted using different varieties of palm kernels. Samples of PKM ...

  17. 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...

  18. Screening of the kernels of Pentadesma butyracea from various ...

    African Journals Online (AJOL)

    Gwla10

    Pentadesma butyracea Sabine (Clusiaceae) is a ligneous forest species of multipurpose uses. It is widely distributed in Africa from Guinea-Bissau to the West of the Democratic Republic of Congo. This study screened the kernel of P. butyracea on the basis of their physico-chemical properties. Six types of kernels were ...

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. Nonlinear Forecasting with Many Predictors using Kernel Ridge Regression

    NARCIS (Netherlands)

    P. Exterkate (Peter); P.J.F. Groenen (Patrick); C. Heij (Christiaan); D.J.C. van Dijk (Dick)

    2011-01-01

    textabstractThis 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

  4. On sensitivity kernels for 'wave-equation' transmission tomography

    NARCIS (Netherlands)

    Hoop, Maarten V. de; Hilst, R.D. van der

    2004-01-01

    We combine seismological scattering theory with the theory of distributions to study some properties of sensitivity kernels for finite frequency seismic delay times. The theory to be used for calculating the kernels depends on the way the measurements are made. For example, the sensitivity to the

  5. 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.

  6. Fusarium graminearum Isolates from Wheat and Maize in New York Show Similar Range of Aggressiveness and Toxigenicity in Cross-Species Pathogenicity Tests.

    Science.gov (United States)

    Kuhnem, Paulo R; Del Ponte, Emerson M; Dong, Yanhong; Bergstrom, Gary C

    2015-04-01

    This study aimed to assess whether pathogenic Fusarium graminearum isolates from wheat and maize were more aggressive on their host of origin and whether aggressiveness was influenced further by B-trichothecene chemotype. Fifteen isolates were selected from a contemporary collection of isolates surveyed in New York in 2011 to 2012 to represent diversity of host of origin and chemotype. Three pathogenicity assays were used to evaluate and compare these isolates. Fusarium head blight (FHB) severity and trichothecene production in wheat, and maize seedling blight were evaluated in greenhouse inoculation experiments, and Gibberella ear rot (GER) severity and trichothecene production were evaluated in maize ears inoculated in the field. Our results showed among F. graminearum isolates a wide variation in aggressiveness and mycotoxin production toward wheat and maize and these isolates could not be structured by their host of origin or by chemotype. Moreover, aggressiveness rank order changed according to the host/organ evaluated. This indicates that relative susceptibility at the seedling stage may not predict susceptibility of ears. Significant correlations were observed of total trichothecenes (deoxynivalenol [DON] and its acetylated derivatives) produced with FHB and GER severity on wheat and maize, respectively. One isolate did not produce DON or ADON in wheat or maize kernels, yet was aggressive on both hosts. Nine of the fifteen isolates produced small amounts of zearalenone (ZON) in maize kernels, but not in wheat kernels, and ZON level was not correlated with GER severity. F. graminearum isolates from New York showed wide variation in aggressiveness and mycotoxin production toward susceptible wheat and maize. Neither host of origin nor trichothecene chemotype appeared to structure the populations we sampled.

  7. Wheat allergy: diagnosis and management

    Science.gov (United States)

    Cianferoni, Antonella

    2016-01-01

    Triticum aestivum (bread wheat) is the most widely grown crop worldwide. In genetically predisposed individuals, wheat can cause specific immune responses. A food allergy to wheat is characterized by T helper type 2 activation which can result in immunoglobulin E (IgE) and non-IgE mediated reactions. IgE mediated reactions are immediate, are characterized by the presence of wheat-specific IgE antibodies, and can be life-threatening. Non-IgE mediated reactions are characterized by chronic eosinophilic and lymphocytic infiltration of the gastrointestinal tract. IgE mediated responses to wheat can be related to wheat ingestion (food allergy) or wheat inhalation (respiratory allergy). A food allergy to wheat is more common in children and can be associated with a severe reaction such as anaphylaxis and wheat-dependent, exercise-induced anaphylaxis. An inhalation induced IgE mediated wheat allergy can cause baker’s asthma or rhinitis, which are common occupational diseases in workers who have significant repetitive exposure to wheat flour, such as bakers. Non-IgE mediated food allergy reactions to wheat are mainly eosinophilic esophagitis (EoE) or eosinophilic gastritis (EG), which are both characterized by chronic eosinophilic inflammation. EG is a systemic disease, and is associated with severe inflammation that requires oral steroids to resolve. EoE is a less severe disease, which can lead to complications in feeding intolerance and fibrosis. In both EoE and EG, wheat allergy diagnosis is based on both an elimination diet preceded by a tissue biopsy obtained by esophagogastroduodenoscopy in order to show the effectiveness of the diet. Diagnosis of IgE mediated wheat allergy is based on the medical history, the detection of specific IgE to wheat, and oral food challenges. Currently, the main treatment of a wheat allergy is based on avoidance of wheat altogether. However, in the near future immunotherapy may represent a valid way to treat IgE mediated reactions to

  8. 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.

  9. 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....

  10. 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.

  11. Triso coating development progress for uranium nitride kernels

    Energy Technology Data Exchange (ETDEWEB)

    Jolly, Brian C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lindemer, Terrence [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Terrani, Kurt A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-08-01

    In support of fully ceramic matrix (FCM) fuel development [1-2], coating development work is ongoing at the Oak Ridge National Laboratory (ORNL) to produce tri-structural isotropic (TRISO) coated fuel particles with UN kernels [3]. The nitride kernels are used to increase fissile density in these SiC-matrix fuel pellets with details described elsewhere [4]. The advanced gas reactor (AGR) program at ORNL used fluidized bed chemical vapor deposition (FBCVD) techniques for TRISO coating of UCO (two phase mixture of UO2 and UCx) kernels [5]. Similar techniques were employed for coating of the UN kernels, however significant changes in processing conditions were required to maintain acceptable coating properties due to physical property and dimensional differences between the UCO and UN kernels (Table 1).

  12. 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.

  13. A weighted string kernel for protein fold recognition.

    Science.gov (United States)

    Nojoomi, Saghi; Koehl, Patrice

    2017-08-25

    Alignment-free methods for comparing protein sequences have proved to be viable alternatives to approaches that first rely on an alignment of the sequences to be compared. Much work however need to be done before those methods provide reliable fold recognition for proteins whose sequences share little similarity. We have recently proposed an alignment-free method based on the concept of string kernels, SeqKernel (Nojoomi and Koehl, BMC Bioinformatics, 2017, 18:137). In this previous study, we have shown that while Seqkernel performs better than standard alignment-based methods, its applications are potentially limited, because of biases due mostly to sequence length effects. In this study, we propose improvements to SeqKernel that follows two directions. First, we developed a weighted version of the kernel, WSeqKernel. Second, we expand the concept of string kernels into a novel framework for deriving information on amino acids from protein sequences. Using a dataset that only contains remote homologs, we have shown that WSeqKernel performs remarkably well in fold recognition experiments. We have shown that with the appropriate weighting scheme, we can remove the length effects on the kernel values. WSeqKernel, just like any alignment-based sequence comparison method, depends on a substitution matrix. We have shown that this matrix can be optimized so that sequence similarity scores correlate well with structure similarity scores. Starting from no information on amino acid similarity, we have shown that we can derive a scoring matrix that echoes the physico-chemical properties of amino acids. We have made progress in characterizing and parametrizing string kernels as alignment-based methods for comparing protein sequences, and we have shown that they provide a framework for extracting sequence information from structure.

  14. 3-D sensitivity kernels of the Rayleigh wave ellipticity

    Science.gov (United States)

    Maupin, Valérie

    2017-10-01

    The ellipticity of the Rayleigh wave at the surface depends on the seismic structure beneath and in the vicinity of the seismological station where it is measured. We derive here the expression and compute the 3-D kernels that describe this dependence with respect to S-wave velocity, P-wave velocity and density. Near-field terms as well as coupling to Love waves are included in the expressions. We show that the ellipticity kernels are the difference between the amplitude kernels of the radial and vertical components of motion. They show maximum values close to the station, but with a complex pattern, even when smoothing in a finite-frequency range is used to remove the oscillatory pattern present in mono-frequency kernels. In order to follow the usual data processing flow, we also compute and analyse the kernels of the ellipticity averaged over incoming wave backazimuth. The kernel with respect to P-wave velocity has the simplest lateral variation and is in good agreement with commonly used 1-D kernels. The kernels with respect to S-wave velocity and density are more complex and we have not been able to find a good correlation between the 3-D and 1-D kernels. Although it is clear that the ellipticity is mostly sensitive to the structure within half-a-wavelength of the station, the complexity of the kernels within this zone prevents simple approximations like a depth dependence times a lateral variation to be useful in the inversion of the ellipticity.

  15. 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

  16. 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.

  17. 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.

  18. Heat kernel methods for Lifshitz theories

    Science.gov (United States)

    Barvinsky, Andrei O.; Blas, Diego; Herrero-Valea, Mario; Nesterov, Dmitry V.; Pérez-Nadal, Guillem; Steinwachs, Christian F.

    2017-06-01

    We study the one-loop covariant effective action of Lifshitz theories using the heat kernel technique. The characteristic feature of Lifshitz theories is an anisotropic scaling between space and time. This is enforced by the existence of a preferred foliation of space-time, which breaks Lorentz invariance. In contrast to the relativistic case, covariant Lifshitz theories are only invariant under diffeomorphisms preserving the foliation structure. We develop a systematic method to reduce the calculation of the effective action for a generic Lifshitz operator to an algorithm acting on known results for relativistic operators. In addition, we present techniques that drastically simplify the calculation for operators with special properties. We demonstrate the efficiency of these methods by explicit applications.

  19. Modified kernel-based nonlinear feature extraction.

    Energy Technology Data Exchange (ETDEWEB)

    Ma, J. (Junshui); Perkins, S. J. (Simon J.); Theiler, J. P. (James P.); Ahalt, S. (Stanley)

    2002-01-01

    Feature Extraction (FE) techniques are widely used in many applications to pre-process data in order to reduce the complexity of subsequent processes. A group of Kernel-based nonlinear FE ( H E ) algorithms has attracted much attention due to their high performance. However, a serious limitation that is inherent in these algorithms -- the maximal number of features extracted by them is limited by the number of classes involved -- dramatically degrades their flexibility. Here we propose a modified version of those KFE algorithms (MKFE), This algorithm is developed from a special form of scatter-matrix, whose rank is not determined by the number of classes involved, and thus breaks the inherent limitation in those KFE algorithms. Experimental results suggest that MKFE algorithm is .especially useful when the training set is small.

  20. Heat kernel method and its applications

    CERN Document Server

    Avramidi, Ivan G

    2015-01-01

    The heart of the book is the development of a short-time asymptotic expansion for the heat kernel. This is explained in detail and explicit examples of some advanced calculations are given. In addition some advanced methods and extensions, including path integrals, jump diffusion and others are presented. The book consists of four parts: Analysis, Geometry, Perturbations and Applications. The first part shortly reviews of some background material and gives an introduction to PDEs. The second part is devoted to a short introduction to various aspects of differential geometry that will be needed later. The third part and heart of the book presents a systematic development of effective methods for various approximation schemes for parabolic differential equations. The last part is devoted to applications in financial mathematics, in particular, stochastic differential equations. Although this book is intended for advanced undergraduate or beginning graduate students in, it should also provide a useful reference ...

  1. Celluclast 1.5L pretreatment enhanced aroma of palm kernels and oil after kernel roasting.

    Science.gov (United States)

    Zhang, Wencan; Zhao, Fangju; Yang, Tiankui; Zhao, Feifei; Liu, Shaoquan

    2017-12-01

    The aroma of palm kernel oil (PKO) affects its applications. Little information is available on how enzymatic modification of palm kernels (PK) affects PK and PKO aroma after kernel roasting. Celluclast (cellulase) pretreatment of PK resulted in a 2.4-fold increment in the concentration of soluble sugars, with glucose being increased by 6.0-fold. Higher levels of 1.7-, 1.8- and 1.9-fold of O-heterocyclic volatile compounds were found in the treated PK after roasting at 180 °C for 8, 14 and 20 min respectively relative to the corresponding control, with furfural, 5-methyl-2-furancarboxaldehyde, 2-furanmethanol and maltol in particularly higher amounts. Volatile differences between PKOs from control and treated PK were also found, though less obvious owing to the aqueous extraction process. Principal component analysis based on aroma-active compounds revealed that upon the proceeding of roasting, the differentiation between control and treated PK was enlarged while that of corresponding PKOs was less clear-cut. Celluclast pretreatment enabled the medium roasted PK to impart more nutty, roasty and caramelic odor and the corresponding PKO to impart more caramelic but less roasty and burnt notes. Celluclast pretreatment of PK followed by roasting may be a promising new way of improving PKO aroma. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  2. Reaction of durum wheat cultivars to mixed SBWMV and WSSMV infection in central Italy

    Directory of Open Access Journals (Sweden)

    V. Vallega

    2003-08-01

    Full Text Available Forty-three cultivars of durum wheat (Triticum durum Desf. were grown during the 1998–99 growing season in a field near Rome with natural inoculum sources of Soilborne wheat mosaic virus (SBWMV and Wheat spindle streak mosaic virus (WSSMV, to evaluate their resistance to the mixed infection. Leaf extracts from twelve cultivars had relatively low ELISA values for WSSMV, and thirteen had low ELISA values for SBWMV. Results confirmed the high level of resistance to SBWMV of the cultivars Colorado, Ionio and Neodur. The reactions of the cultivars to SBWMV were consistent with those recorded in previous trials near Bologna, northern Italy, indicating that the SBWMV strains at the two test sites were pathogenically similar. Disease severity was significantly correlated with grain yield, thousand-kernel weight, heading date and the SBWMV-ELISA value, but not with the WSSMVELISA value. Regression analysis showed that, as a result of the mixed infection, the four cultivars with the most severe disease symptoms headed about 5 days later than normal, and suffered grain yield and kernel weight reductions of about 56 and 10% respectively. Cultivars with milder symptoms were also severely affected.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Characterization of Aldehyde Oxidase (AO Genes Involved in the Accumulation of Carotenoid Pigments in Wheat Grain

    Directory of Open Access Journals (Sweden)

    Pasqualina Colasuonno

    2017-05-01

    Full Text Available Aldehyde Oxidase (AO enzyme (EC 1.2.3.1 catalyzes the final steps of carotenoid catabolism and it is a key enzyme in the abscisic acid (ABA biosynthesis. AO isoforms are located in the cytosolic compartment of tissues in many plants, where induce the oxidation of aldehydes into carboxylic acid, and in addition, catalyze the hydroxylation of some heterocycles. The goal of the present study was to characterize the AO genes involved in the accumulation of carotenoid pigments in wheat grain, an important quantitative trait controlled by multiple genes. The cDNAs corresponding to the four AO isoforms from Arabidopsis thaliana and five AO isoforms from Brachypodium distachyon were used as query in 454 sequence assemblies data for Triticum aestivum cv. Chinese Spring (https://urgi.versailles.inra.fr/blast/blast.php to obtain the partial or whole orthologous wheat AO sequences. Three wheat isoforms, designated AO1, AO2, and AO3 were located on the chromosome groups 2, 5, and 7, respectively, and mapped on two consensus wheat maps by SNP markers located within the AO gene sequences. To validate the possible relationships between AO3 genes and carotenoid accumulation in wheat, the expression levels of AO-A3 and AO-B3 gene were determined during the kernel maturation stage of two durum wheat cultivars, Ciccio and Svevo, characterized by a low and high carotenoid content, respectively. Different AO-A3 gene expression values were observed between the two cultivars indicating that the AO-A3 allele present in Ciccio was more active in carotenoid degradation. A gene marker was developed and can be used for marker-assisted selection in wheat breeding programs.

  10. Characterization of Aldehyde Oxidase (AO) Genes Involved in the Accumulation of Carotenoid Pigments in Wheat Grain.

    Science.gov (United States)

    Colasuonno, Pasqualina; Marcotuli, Ilaria; Lozito, Maria L; Simeone, Rosanna; Blanco, Antonio; Gadaleta, Agata

    2017-01-01

    Aldehyde Oxidase (AO) enzyme (EC 1.2.3.1) catalyzes the final steps of carotenoid catabolism and it is a key enzyme in the abscisic acid (ABA) biosynthesis. AO isoforms are located in the cytosolic compartment of tissues in many plants, where induce the oxidation of aldehydes into carboxylic acid, and in addition, catalyze the hydroxylation of some heterocycles. The goal of the present study was to characterize the AO genes involved in the accumulation of carotenoid pigments in wheat grain, an important quantitative trait controlled by multiple genes. The cDNAs corresponding to the four AO isoforms from Arabidopsis thaliana and five AO isoforms from Brachypodium distachyon were used as query in 454 sequence assemblies data for Triticum aestivum cv. Chinese Spring (https://urgi.versailles.inra.fr/blast/blast.php) to obtain the partial or whole orthologous wheat AO sequences. Three wheat isoforms, designated AO1, AO2 , and AO3 were located on the chromosome groups 2, 5, and 7, respectively, and mapped on two consensus wheat maps by SNP markers located within the AO gene sequences. To validate the possible relationships between AO3 genes and carotenoid accumulation in wheat, the expression levels of AO-A3 and AO-B3 gene were determined during the kernel maturation stage of two durum wheat cultivars, Ciccio and Svevo, characterized by a low and high carotenoid content, respectively. Different AO-A3 gene expression values were observed between the two cultivars indicating that the AO-A3 allele present in Ciccio was more active in carotenoid degradation. A gene marker was developed and can be used for marker-assisted selection in wheat breeding programs.

  11. Gilkey-de Witt heat kernel expansion and zero modes

    International Nuclear Information System (INIS)

    Alonso-Izquierdo, A.; Mateos Guilarte, J.

    2013-01-01

    In this paper we propose a generalization of the Gilkey-de Witt heat kernel expansion, designed to provide us with a precise estimation of the heat trace of non-negative Schr¨odinger type differential operators with non-trivial kernel over all the domain of its “inverse temperature” variable β. We apply this modified approach to compute effectively the one-loop kink mass shift for some models whose kink fluctuation operator spectrum is unknown and the only alternative to estimate this magnitude is the use of the heat kernel expansion techniques.

  12. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, P.M.; Madsen, Kristoffer H; Lund, T.E.

    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...

  13. A Truly Jitter-Free Real-Time Kernel

    DEFF Research Database (Denmark)

    Marian, Nicolae; Jiang, Peng

    2008-01-01

    Hardware-Software co-design is a powerful method nowadays for the embedded system development. Reducing time to the market, more accuracy and interactivity with the whole system by the co-design developments are available. The paper considers and investigates a co-design solution applied to a real-time...... kernel (RTK) named HARTEX. The objective was to even more improve the timing performances of the kernel in terms of minimized, constant overhead (jitter free), in an application transparent manner. The co-design solution partitions the kernel between a pure software part, with constant overhead...

  14. Robust Learning With Kernel Mean $p$-Power Error Loss.

    Science.gov (United States)

    Chen, Badong; Xing, Lei; Wang, Xin; Qin, Jing; Zheng, Nanning

    2017-07-25

    Correntropy is a second order statistical measure in kernel space, which has been successfully applied in robust learning and signal processing. In this paper, we define a nonsecond order statistical measure in kernel space, called the kernel mean-p power error (KMPE), including the correntropic loss (C-Loss) as a special case. Some basic properties of KMPE are presented. In particular, we apply the KMPE to extreme learning machine (ELM) and principal component analysis (PCA), and develop two robust learning algorithms, namely ELM-KMPE and PCA-KMPE. Experimental results on synthetic and benchmark data show that the developed algorithms can achieve better performance when compared with some existing methods.

  15. 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...

  16. Inhibition of protein synthesis in maize and wheat by trichothecene mycotoxins and hybridoma-based enzyme immunoassay for deoxynivalenol

    Energy Technology Data Exchange (ETDEWEB)

    Casale, W.L.

    1987-01-01

    The 12,13-epoxytrichothecene mycotoxins deoxynivalenol (DON, vomitoxin) and T-2 toxin inhibited protein synthesis in vivo and in cell-free systems from wheat and maize, host plants of trichothecene-producing Fusarium spp.Protein synthesis in tissue (leaf discs and kernel sections) was measured by incorporation of /sup 3/H-leucine into acetone:ethanol insoluble material, and in cell-free translation systems from wheat embryos and maize seedling plumules by incorporation of /sup 3/H-leucine into trichloroacetic acid-insoluble material. The toxin concentration inhibiting 50% of /sup 3/H-leucine incorporation (ID/sub 50/) by several maize varieties were 0.9 ..mu..M (T-2 toxin) and 9-22 ..mu..M (DON). ID/sub 50/ values for wheat were 0.25 ..mu..M (T-2 toxin) and 4.5 ..mu..M (DON).

  17. Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels

    Directory of Open Access Journals (Sweden)

    Taiyong Li

    2016-12-01

    Full Text Available Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with this issue, in this paper, we proposed a method integrating ensemble empirical mode decomposition (EEMD, adaptive particle swarm optimization (APSO, and relevance vector machine (RVM—namely, EEMD-APSO-RVM—to predict crude oil price based on the “decomposition and ensemble” framework. Specifically, the raw time series of crude oil price were firstly decomposed into several intrinsic mode functions (IMFs and one residue by EEMD. Then, RVM with combined kernels was applied to predict target value for the residue and each IMF individually. To improve the prediction performance of each component, an extended particle swarm optimization (PSO was utilized to simultaneously optimize the weights and parameters of single kernels for the combined kernel of RVM. Finally, simple addition was used to aggregate all the predicted results of components into an ensemble result as the final result. Extensive experiments were conducted on the crude oil spot price of the West Texas Intermediate (WTI to illustrate and evaluate the proposed method. The experimental results are superior to those by several state-of-the-art benchmark methods in terms of root mean squared error (RMSE, mean absolute percent error (MAPE, and directional statistic (Dstat, showing that the proposed EEMD-APSO-RVM is promising for forecasting crude oil price.

  18. Calculation of the Trubnikov and Nanbu Collision Kernels: Implications for Numerical Modeling of Coulomb Collisions

    Energy Technology Data Exchange (ETDEWEB)

    Dimits, A M; Wang, C; Caflisch, R; Cohen, B I; Huang, Y

    2008-08-06

    We investigate the accuracy of and assumptions underlying the numerical binary Monte-Carlo collision operator due to Nanbu [K. Nanbu, Phys. Rev. E 55 (1997)]. The numerical experiments that resulted in the parameterization of the collision kernel used in Nanbu's operator are argued to be an approximate realization of the Coulomb-Lorentz pitch-angle scattering process, for which an analytical solution for the collision kernel is available. It is demonstrated empirically that Nanbu's collision operator quite accurately recovers the effects of Coulomb-Lorentz pitch-angle collisions, or processes that approximate these (such interspecies Coulomb collisions with very small mass ratio) even for very large values of the collisional time step. An investigation of the analytical solution shows that Nanbu's parameterized kernel is highly accurate for small values of the normalized collision time step, but loses some of its accuracy for larger values of the time step. Careful numerical and analytical investigations are presented, which show that the time dependence of the relaxation of a temperature anisotropy by Coulomb-Lorentz collisions has a richer structure than previously thought, and is not accurately represented by an exponential decay with a single decay rate. Finally, a practical collision algorithm is proposed that for small-mass-ratio interspecies Coulomb collisions improves on the accuracy of Nanbu's algorithm.

  19. Free radical kinetics of irradiated durum wheat

    International Nuclear Information System (INIS)

    Korkmaz, M.; Polat, M.

    2000-01-01

    In the present work, a detailed ESR investigation of characteristic features and kinetic behaviors at three different temperatures of free radicals produced in a species of durum wheat cultivated in Turkey and irradiated at doses of up to 5 kGy by a γ source, is reported. Unirradiated wheat samples exhibit a weak, single-line ESR signal originating from a radical of unknown structure called radical III in this work. Irradiation produces two more radicals identified as hydroxyalkyl (I) and aldehydalkyl (II) radicals beside radical III. The radicals (I, II and III) follow complicated kinetics. Species I and II initially decay very fast after the irradiation followed by slower decay. Radical half-life times depend on whether they were induced in the crystalline or amorphous fractions of the wheat starch. Activation energy values of the radicals were found to follow the order E a (III)>E a (II)>E a (I). ESR parameters of the radical species were determined by simulating experimental spectra recorded following the irradiation. Room temperature dose-response curves and variations of different spectral parameters between 120 and 390 K were also studied

  20. Free radical kinetics of irradiated durum wheat

    Energy Technology Data Exchange (ETDEWEB)

    Korkmaz, M.; Polat, M

    2000-04-01

    In the present work, a detailed ESR investigation of characteristic features and kinetic behaviors at three different temperatures of free radicals produced in a species of durum wheat cultivated in Turkey and irradiated at doses of up to 5 kGy by a {gamma} source, is reported. Unirradiated wheat samples exhibit a weak, single-line ESR signal originating from a radical of unknown structure called radical III in this work. Irradiation produces two more radicals identified as hydroxyalkyl (I) and aldehydalkyl (II) radicals beside radical III. The radicals (I, II and III) follow complicated kinetics. Species I and II initially decay very fast after the irradiation followed by slower decay. Radical half-life times depend on whether they were induced in the crystalline or amorphous fractions of the wheat starch. Activation energy values of the radicals were found to follow the order E{sub a}(III)>E{sub a}(II)>E{sub a}(I). ESR parameters of the radical species were determined by simulating experimental spectra recorded following the irradiation. Room temperature dose-response curves and variations of different spectral parameters between 120 and 390 K were also studied.

  1. Chromosomal Localization of Genes Conferring Desirable Agronomic Traits from Wheat-Agropyron cristatum Disomic Addition Line 5113

    Science.gov (United States)

    Pan, Cuili; Yao, Miaomiao; Zhang, Jinpeng; Yang, Xinming; Liu, Weihua; Li, Xiuquan; Xi, Yajun; Li, Lihui

    2016-01-01

    Creation of wheat-alien disomic addition lines and localization of desirable genes on alien chromosomes are important for utilization of these genes in genetic improvement of common wheat. In this study, wheat-Agropyron cristatum derivative line 5113 was characterized by genomic in situ hybridization (GISH) and specific-locus amplified fragment sequencing (SLAF-seq), and was demonstrated to be a novel wheat-A. cristatum disomic 6P addition line. Compared with its parent Fukuhokomugi (Fukuho), 5113 displayed multiple elite agronomic traits, including higher uppermost internode/plant height ratio, larger flag leaf, longer spike length, elevated grain number per spike and spikelet number per spike, more kernel number in the middle spikelet, more fertile tiller number per plant, and enhanced resistance to powdery mildew and leaf rust. Genes conferring these elite traits were localized on the A. cristatum 6P chromosome by using SLAF-seq markers and biparental populations (F1, BC1F1 and BC1F2 populations) produced from the crosses between Fukuho and 5113. Taken together, chromosomal localization of these desirable genes will facilitate transferring of high-yield and high-resistance genes from A. cristatum into common wheat, and serve as the foundation for the utilization of 5113 in wheat breeding. PMID:27824906

  2. Comparative proteomic analysis of two transgenic low-gliadin wheat lines and non-transgenic wheat control.

    Science.gov (United States)

    García-Molina, María Dolores; Muccilli, Vera; Saletti, Rosaria; Foti, Salvatore; Masci, Stefania; Barro, Francisco

    2017-08-08

    Gluten proteins are major determinants of the bread making quality of wheat, but also of important wheat-related disorders, including coeliac disease (CD), and allergies. We carried out a proteomic study using the total grain proteins from two low-gliadin wheat lines, obtained by RNAi, and the untransformed wild type as reference. The impact of silencing on both target and on non-target proteins was evaluated. Because of the great protein complexity, we performed separate analyses of four kernel protein fractions: gliadins and glutenin subunits, and metabolic and CM-like proteins, by using a classical 2D electrophoresis gel based approach followed by RP-HPLC/nESI-MS/MS. As a result of the strong down-regulation of gliadins, the HMW-GS, metabolic and chloroform/methanol soluble proteins were over-accumulated in the transgenic lines, especially in the line D793, which showed the highest silencing of gliadins. Basing on these data, and considering that metabolic proteins and chloroform/methanol soluble proteins (CM-like), such as the α-amylase/trypsin inhibitor family, β-amylase and serpins, were related to wheat allergens, further in vivo analysis will be needed, especially those related to clinical trials in controlled patients, to determine if these lines could be used for food preparation for celiac or other gluten intolerant groups. Several enteropathies and allergies are related to wheat proteins. Biotechnological techniques such as genetic transformation and RNA interference have allowed the silencing of gliadin genes, providing lines with very low gliadin content in the grains. We report a proteomic-based approach to characterize two low-gliadin transgenic wheat lines obtained by RNAi technology. These lines harbor the same silencing fragment, but driven by two different endosperm specific promoters (γ-gliadin and D-hordein). The comprehensive proteome analysis of these transgenic lines, by combining two-dimensional electrophoresis and RP

  3. Verification of helical tomotherapy delivery using autoassociative kernel regression

    International Nuclear Information System (INIS)

    Seibert, Rebecca M.; Ramsey, Chester R.; Garvey, Dustin R.; Wesley Hines, J.; Robison, Ben H.; Outten, Samuel S.

    2007-01-01

    Quality assurance (QA) is a topic of major concern in the field of intensity modulated radiation therapy (IMRT). The standard of practice for IMRT is to perform QA testing for individual patients to verify that the dose distribution will be delivered to the patient. The purpose of this study was to develop a new technique that could eventually be used to automatically evaluate helical tomotherapy treatments during delivery using exit detector data. This technique uses an autoassociative kernel regression (AAKR) model to detect errors in tomotherapy delivery. AAKR is a novel nonparametric model that is known to predict a group of correct sensor values when supplied a group of sensor values that is usually corrupted or contains faults such as machine failure. This modeling scheme is especially suited for the problem of monitoring the fluence values found in the exit detector data because it is able to learn the complex detector data relationships. This scheme still applies when detector data are summed over many frames with a low temporal resolution and a variable beam attenuation resulting from patient movement. Delivery sequences from three archived patients (prostate, lung, and head and neck) were used in this study. Each delivery sequence was modified by reducing the opening time for random individual multileaf collimator (MLC) leaves by random amounts. The error and error-free treatments were delivered with different phantoms in the path of the beam. Multiple autoassociative kernel regression (AAKR) models were developed and tested by the investigators using combinations of the stored exit detector data sets from each delivery. The models proved robust and were able to predict the correct or error-free values for a projection, which had a single MLC leaf decrease its opening time by less than 10 msec. The model also was able to determine machine output errors. The average uncertainty value for the unfaulted projections ranged from 0.4% to 1.8% of the detector

  4. Analysis of expressed sequence tags from a single wheat cultivar facilitates interpretation of tandem mass spectrometry data and discrimination of gamma gliadin proteins that may play different functional roles in flour

    Directory of Open Access Journals (Sweden)

    Altenbach Susan B

    2010-01-01

    Full Text Available Abstract Background The gamma gliadins are a complex group of proteins that together with other gluten proteins determine the functional properties of wheat flour. The proteins have unusually high levels of glutamine and proline and contain large regions of repetitive sequences. While most gamma gliadins are monomeric proteins containing eight conserved cysteine residues, some contain an additional cysteine residue that enables them to be linked with other gluten proteins into large polymers that are critical for flour quality. The ability to differentiate among the gamma gliadins is important for studies of wheat flour quality because proteins with similar sequences can have different effects on functional properties. Results The complement of gamma gliadin genes expressed in the wheat cultivar Butte 86 was evaluated by analyzing publicly available expressed sequence tag (EST data. Eleven contigs were assembled from 153 Butte 86 ESTs. Nine of the contigs encoded full-length proteins and four of the proteins contained nine cysteine residues. Only one of the encoded proteins was a perfect match with a sequence reported in NCBI. Contigs from four different publicly available EST assemblies encoded proteins that were perfect matches with some, but not all, of the Butte 86 gamma gliadins and the complement of identical proteins was different for each assembly. A specialized database that included the sequences of Butte 86 gamma gliadins was constructed for identification of flour proteins by tandem mass spectrometry (MS/MS. In a pilot experiment, proteins corresponding to six Butte 86 gamma gliadin contigs were distinguished by MS/MS, including one containing the extra cysteine residue. Two other proteins were identified as one of two closely related Butte 86 proteins but could not be distinguished unequivocally. Unique peptide tags specific for Butte 86 gamma gliadins are reported. Conclusions Inclusion of cultivar-specific gamma gliadin sequences

  5. Systematic approach in optimizing numerical memory-bound kernels on GPU

    KAUST Repository

    Abdelfattah, Ahmad

    2013-01-01

    The use of GPUs has been very beneficial in accelerating dense linear algebra computational kernels (DLA). Many high performance numerical libraries like CUBLAS, MAGMA, and CULA provide BLAS and LAPACK implementations on GPUs as well as hybrid computations involving both, CPUs and GPUs. GPUs usually score better performance than CPUs for compute-bound operations, especially those characterized by a regular data access pattern. This paper highlights a systematic approach for efficiently implementing memory-bound DLA kernels on GPUs, by taking advantage of the underlying device\\'s architecture (e.g., high throughput). This methodology proved to outperform existing state-of-the-art GPU implementations for the symmetric matrix-vector multiplication (SYMV), characterized by an irregular data access pattern, in a recent work (Abdelfattah et. al, VECPAR 2012). We propose to extend this methodology to the general matrix-vector multiplication (GEMV) kernel. The performance results show that our GEMV implementation achieves better performance for relatively small to medium matrix sizes, making it very influential in calculating the Hessenberg and bidiagonal reductions of general matrices (radar applications), which are the first step toward computing eigenvalues and singular values, respectively. Considering small and medium size matrices (≤4500), our GEMV kernel achieves an average 60% improvement in single precision (SP) and an average 25% in double precision (DP) over existing open-source and commercial software solutions. These results improve reduction algorithms for both small and large matrices. The improved GEMV performances engender an averge 30% (SP) and 15% (DP) in Hessenberg reduction and up to 25% (SP) and 14% (DP) improvement for the bidiagonal reduction over the implementation provided by CUBLAS 5.0. © 2013 Springer-Verlag.

  6. (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-.

  7. 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)

  8. 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.

  9. NEW HORIZONS SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of New Horizons (NH) SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data contain...

  10. Kernel based collaborative recommender system for e-purchasing

    Indian Academy of Sciences (India)

    Home; Journals; Sadhana; Volume 35; Issue 5. Kernel based collaborative recommender system for -purchasing ... Recommender system a new marketing strategy plays an important role particularly in an electronic commerce environment. Among the various recommender systems, collaborative recommender system ...

  11. Homotopy deform method for reproducing kernel space for ...

    Indian Academy of Sciences (India)

    2016-09-23

    Sep 23, 2016 ... Nonlinear differential equations; the homotopy deform method; the simplified reproducing kernel ... an equivalent integro differential equation. ... an algorithm for solving nonlinear multipoint BVPs by combining homotopy perturbation and variational iteration methods. Most recently, Duan and Rach [12].

  12. Quantitative trait locus (QTL) mapping for 100-kernel weight of ...

    African Journals Online (AJOL)

    hope&shola

    2010-12-06

    Zea mays L.), related to yield. To realize its ... Key words: Maize (Zea mays L.), 100-kernel weight, quantitative trait locus (QTL), recombinant inbred line. (RIL), nitrogen ... cient approach to realize genetic basis of trait, some.

  13. Homotopy deform method for reproducing kernel space for ...

    Indian Academy of Sciences (India)

    2016-09-23

    s12043-016-1269-8. Homotopy deform method for reproducing kernel space for nonlinear boundary value problems. MIN-QIANG XU. ∗ and YING-ZHEN LIN. School of Science, Zhuhai Campus, Beijing Institute of Technology, ...

  14. MARS EXPLORATION ROVER 2 SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Mars Exploration Rover 2 SPICE data files (kernel files'), which can be accessed using SPICE software. The SPICE data...

  15. ROSETTA ORBITER/LANDER SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Rosetta mission SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains...

  16. MGS MARS SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Mars Global Surveyor SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data...

  17. MARS EXPLORATION ROVER 1 SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Mars Exploration Rover 1 SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data...

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

    The iteratively re-weighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsuper- vised change detection in multi- and hyperspectral remote sensing imagery as well as for automatic radiometric normalization of multi- or hypervariate multitemporal image sequences...... code exists which allows for fast data exploration and experimentation with smaller datasets. Computationally demanding kernelization of test data with training data and kernel image projections have been programmed to run on massively parallel CUDA-enabled graphics processors, when available, giving....... 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...

  19. DEEP SPACE 1 SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Deep Space 1 (DS1) SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains...

  20. CLEMENTINE MOON SPICE KERNELS V1.0

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set includes the complete set of Clementine SPICE data files (kernel files''), which can be accessed using SPICE software. The SPICE data contains...

  1. 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.

  2. 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.

  3. Identification and validation of genomic regions influencing kernel zinc and iron in maize.

    Science.gov (United States)

    Hindu, Vemuri; Palacios-Rojas, Natalia; Babu, Raman; Suwarno, Willy B; Rashid, Zerka; Usha, Rayalcheruvu; Saykhedkar, Gajanan R; Nair, Sudha K

    2018-03-24

    Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize. Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world's poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (P ≤ 5.03 × 10 -05 ) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (P ≤ 1 × 10 -03 ) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (P ≤ 0.01, R 2  ≥ 0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.

  4. 7 CFR 981.401 - Adjusted kernel weight.

    Science.gov (United States)

    2010-01-01

    ... weight of delivery 10,000 10,000 2. Percent of edible kernel weight 53.0 84.0 3. Less weight loss in processing 1 1.00 0 4. Less excess moisture of edible kernels (excess moisture×line 2) 1.06 1.68 5. Net... Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing...

  5. Palm kernel shell as aggregate for light weight concrete | Idah ...

    African Journals Online (AJOL)

    The palm kernel, cement, sand and gravel were mixed and cast in steel or cast iron moulds of 150mm2 cubes. The results show that the PK1 with ratio of 1 :2:3: 1· of cement, sand, gravel. and palm kernel shells respectively gave the highest compressive strength of 8.03N/mm2 after 28 days of curing. Comparing the results ...

  6. Mathematical Modelling of Thin Layer Dried Cashew Kernels | Asiru ...

    African Journals Online (AJOL)

    In this paper mathematical models describing thin layer drying of cashew kernels in a batch dryer were presented. The range of drying air temperature was 70 – 110°C. The initial moisture content of the cashew kernels was 9.29% (d.b.) and the final moisture content was in the range of 3.5 to 4.6% dry-basis. Seven different ...

  7. Assessing Gamma kernels and BSS/LSS processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole E.

    This paper reviews the roles of gamma type kernels in the theory and modelling for Brownian and Lévy semistationary processes. Applications to financial econometrics and the physics of turbulence are pointed out.......This paper reviews the roles of gamma type kernels in the theory and modelling for Brownian and Lévy semistationary processes. Applications to financial econometrics and the physics of turbulence are pointed out....

  8. MULTITASKER, Multitasking Kernel for C and FORTRAN Under UNIX

    International Nuclear Information System (INIS)

    Brooks, E.D. III

    1988-01-01

    1 - Description of program or function: MULTITASKER implements a multitasking kernel for the C and FORTRAN programming languages that runs under UNIX. The kernel provides a multitasking environment which serves two purposes. The first is to provide an efficient portable environment for the development, debugging, and execution of production multiprocessor programs. The second is to provide a means of evaluating the performance of a multitasking program on model multiprocessor hardware. The performance evaluation features require no changes in the application program source and are implemented as a set of compile- and run-time options in the kernel. 2 - Method of solution: The FORTRAN interface to the kernel is identical in function to the CRI multitasking package provided for the Cray XMP. This provides a migration path to high speed (but small N) multiprocessors once the application has been coded and debugged. With use of the UNIX m4 macro preprocessor, source compatibility can be achieved between the UNIX code development system and the target Cray multiprocessor. The kernel also provides a means of evaluating a program's performance on model multiprocessors. Execution traces may be obtained which allow the user to determine kernel overhead, memory conflicts between various tasks, and the average concurrency being exploited. The kernel may also be made to switch tasks every cpu instruction with a random execution ordering. This allows the user to look for unprotected critical regions in the program. These features, implemented as a set of compile- and run-time options, cause extra execution overhead which is not present in the standard production version of the kernel

  9. Commutators of integral operators with variable kernels on Hardy ...

    Indian Academy of Sciences (India)

    (1.2). Then T ,0 is the singular integral with variable kernel, and we simply write it as T . The. Lp-boundedness of the singular integral operator with variable kernel appears in [1] (see also [3,7]). It turns out that such kind of operators are much more closely related to the elliptic partial differential equations of second order with ...

  10. Resummed memory kernels in generalized system-bath master equations

    Science.gov (United States)

    Mavros, Michael G.; Van Voorhis, Troy

    2014-08-01

    Generalized master equations provide a concise formalism for studying reduced population dynamics. Usually, these master equations require a perturbative expansion of the memory kernels governing the dynamics; in order to prevent divergences, these expansions must be resummed. Resummation techniques of perturbation series are ubiquitous in physics, but they have not been readily studied for the time-dependent memory kernels used in generalized master equations. In this paper, we present a comparison of different resummation techniques for such memory kernels up to fourth order. We study specifically the spin-boson Hamiltonian as a model system bath Hamiltonian, treating the diabatic coupling between the two states as a perturbation. A novel derivation of the fourth-order memory kernel for the spin-boson problem is presented; then, the second- and fourth-order kernels are evaluated numerically for a variety of spin-boson parameter regimes. We find that resumming the kernels through fourth order using a Padé approximant results in divergent populations in the strong electronic coupling regime due to a singularity introduced by the nature of the resummation, and thus recommend a non-divergent exponential resummation (the "Landau-Zener resummation" of previous work). The inclusion of fourth-order effects in a Landau-Zener-resummed kernel is shown to improve both the dephasing rate and the obedience of detailed balance over simpler prescriptions like the non-interacting blip approximation, showing a relatively quick convergence on the exact answer. The results suggest that including higher-order contributions to the memory kernel of a generalized master equation and performing an appropriate resummation can provide a numerically-exact solution to system-bath dynamics for a general spectral density, opening the way to a new class of methods for treating system-bath dynamics.

  11. Local Kernel for Brains Classification in Schizophrenia

    Science.gov (United States)

    Castellani, U.; Rossato, E.; Murino, V.; Bellani, M.; Rambaldelli, G.; Tansella, M.; Brambilla, P.

    In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely Scale Invariance Feature Transform (SIFT). Then, matching is obtained by introducing the local kernel for which the samples are represented by unordered set of features. Moreover, a new weighting approach is proposed to take into account the discriminative relevance of the detected groups of features. Experiments have been performed including a set of 54 patients with schizophrenia and 54 normal controls on which region of interest (ROI) have been manually traced by experts. Preliminary results on Dorso-lateral PreFrontal Cortex (DLPFC) region are promising since up to 75% of successful classification rate has been obtained with this technique and the performance has improved up to 85% when the subjects have been stratified by sex.

  12. Kernel spectral clustering with memory effect

    Science.gov (United States)

    Langone, Rocco; Alzate, Carlos; Suykens, Johan A. K.

    2013-05-01

    Evolving graphs describe many natural phenomena changing over time, such as social relationships, trade markets, metabolic networks etc. In this framework, performing community detection and analyzing the cluster evolution represents a critical task. Here we propose a new model for this purpose, where the smoothness of the clustering results over time can be considered as a valid prior knowledge. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness. The latter allows the model to cluster the current data well and to be consistent with the recent history. We also propose new model selection criteria in order to carefully choose the hyper-parameters of our model, which is a crucial issue to achieve good performances. We successfully test the model on four toy problems and on a real world network. We also compare our model with Evolutionary Spectral Clustering, which is a state-of-the-art algorithm for community detection of evolving networks, illustrating that the kernel spectral clustering with memory effect can achieve better or equal performances.

  13. KERNEL MAD ALGORITHM FOR RELATIVE RADIOMETRIC NORMALIZATION

    Directory of Open Access Journals (Sweden)

    Y. Bai

    2016-06-01

    Full Text Available The multivariate alteration detection (MAD algorithm is commonly used in relative radiometric normalization. This algorithm is based on linear canonical correlation analysis (CCA which can analyze only linear relationships among bands. Therefore, we first introduce a new version of MAD in this study based on the established method known as kernel canonical correlation analysis (KCCA. The proposed method effectively extracts the non-linear and complex relationships among variables. We then conduct relative radiometric normalization experiments on both the linear CCA and KCCA version of the MAD algorithm with the use of Landsat-8 data of Beijing, China, and Gaofen-1(GF-1 data derived from South China. Finally, we analyze the difference between the two methods. Results show that the KCCA-based MAD can be satisfactorily applied to relative radiometric normalization, this algorithm can well describe the nonlinear relationship between multi-temporal images. This work is the first attempt to apply a KCCA-based MAD algorithm to relative radiometric normalization.

  14. Calpain cleavage prediction using multiple kernel learning.

    Directory of Open Access Journals (Sweden)

    David A DuVerle

    Full Text Available Calpain, an intracellular Ca²⁺-dependent cysteine protease, is known to play a role in a wide range of metabolic pathways through limited proteolysis of its substrates. However, only a limited number of these substrates are currently known, with the exact mechanism of substrate recognition and cleavage by calpain still largely unknown. While previous research has successfully applied standard machine-learning algorithms to accurately predict substrate cleavage by other similar types of proteases, their approach does not extend well to calpain, possibly due to its particular mode of proteolytic action and limited amount of experimental data. Through the use of Multiple Kernel Learning, a recent extension to the classic Support Vector Machine framework, we were able to train complex models based on rich, heterogeneous feature sets, leading to significantly improved prediction quality (6% over highest AUC score produced by state-of-the-art methods. In addition to producing a stronger machine-learning model for the prediction of calpain cleavage, we were able to highlight the importance and role of each feature of substrate sequences in defining specificity: primary sequence, secondary structure and solvent accessibility. Most notably, we showed there existed significant specificity differences across calpain sub-types, despite previous assumption to the contrary. Prediction accuracy was further successfully validated using, as an unbiased test set, mutated sequences of calpastatin (endogenous inhibitor of calpain modified to no longer block calpain's proteolytic action. An online implementation of our prediction tool is available at http://calpain.org.

  15. Exploration of Shorea robusta (Sal seeds, kernels and its oil

    Directory of Open Access Journals (Sweden)

    Shashi Kumar C.

    2016-12-01

    Full Text Available Physical, mechanical, and chemical properties of Shorea robusta seed with wing, seed without wing, and kernel were investigated in the present work. The physico-chemical composition of sal oil was also analyzed. The physico-mechanical properties and proximate composition of seed with wing, seed without wing, and kernel at three moisture contents of 9.50% (w.b, 9.54% (w.b, and 12.14% (w.b, respectively, were studied. The results show that the moisture content of the kernel was highest as compared to seed with wing and seed without wing. The sphericity of the kernel was closer to that of a sphere as compared to seed with wing and seed without wing. The hardness of the seed with wing (32.32, N/mm and seed without wing (42.49, N/mm was lower than the kernels (72.14, N/mm. The proximate composition such as moisture, protein, carbohydrates, oil, crude fiber, and ash content were also determined. The kernel (30.20%, w/w contains higher oil percentage as compared to seed with wing and seed without wing. The scientific data from this work are important for designing of equipment and processes for post-harvest value addition of sal seeds.

  16. Self-organization as an iterative kernel smoothing process.

    Science.gov (United States)

    Mulier, F; Cherkassky, V

    1995-11-01

    Kohonen's self-organizing map, when described in a batch processing mode, can be interpreted as a statistical kernel smoothing problem. The batch SOM algorithm consists of two steps. First, the training data are partitioned according to the Voronoi regions of the map unit locations. Second, the units are updated by taking weighted centroids of the data falling into the Voronoi regions, with the weighing function given by the neighborhood. Then, the neighborhood width is decreased and steps 1, 2 are repeated. The second step can be interpreted as a statistical kernel smoothing problem where the neighborhood function corresponds to the kernel and neighborhood width corresponds to kernel span. To determine the new unit locations, kernel smoothing is applied to the centroids of the Voronoi regions in the topological space. This interpretation leads to some new insights concerning the role of the neighborhood and dimensionality reduction. It also strengthens the algorithm's connection with the Principal Curve algorithm. A generalized self-organizing algorithm is proposed, where the kernel smoothing step is replaced with an arbitrary nonparametric regression method.

  17. Patterns of suspected wheat-related allergy

    DEFF Research Database (Denmark)

    Junker Christensen, Morten; Eller, Esben; Mortz, Charlotte G

    2014-01-01

    BACKGROUND: Allergy to wheat can present clinically 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...

  18. Path Through the Wheat

    Directory of Open Access Journals (Sweden)

    David Middleton

    2005-01-01

    Full Text Available The hillside’s tidal waves of yellow-green Break downward into full-grown stalks of wheat In which a peasant, shouldering his hoe Passes along a snaking narrow path -- A teeming place through which his hard thighs press And where his head just barely stays above The swaying grain, drunken in abundance, Farm buildings almost floating on the swells Beyond which sea gulls gliding white in air Fly down on out of sight to salty fields, Taking the channel fish off Normandy, A surfeit fit for Eden i...

  19. Identifying Chemical-Disease Relationship in Biomedical Text Using a Multiple Kernel Learning-Boosting Method.

    Science.gov (United States)

    Sun, Yueping; Zhang, Yu; Li, Jiao

    2017-01-01

    Chemical-induced disease relations (CID) are crucial in various biomedical tasks. In the CID task of Biocreative V, no classifiers with multiple kernels have been developed. In this study, a multiple kernel learning-boosting (MKLB) method is proposed. Different kernel functions according to different types of features were constucted and boosted, each of which were learned with multiple kernels. Our multiple kernel learning-boosting (MKLB) method achieved a F1 score of 0.5068 without incorporating knowledge bases.

  20. Biotechnology Assisted Wheat Breeding for Organic Agriculture

    DEFF Research Database (Denmark)

    Steffan, Philipp Matthias

    so far been mapped to chromosomes, and 9 quantitative trait loci (QTL) have been reported. Infection with common bunt occurs shortly after wheat sowing, however, symptoms can only be clearly assessed after the heading stage. Thus a long time for disease assessment is required. The use of molecular......Tseq markers. Missing markers between typed markers were imputed on a 1cM grid along the whole genome, and single marker regression tests located Bt 9 to the dorsal end of chromosome 6D. The development of molecular markers in tight linkage with Bt 9 will offer the possibility to apply marker assisted...

  1. 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.

  2. Combining ability of wheat parents in two generations

    Directory of Open Access Journals (Sweden)

    Elesandro Bornhofen

    2013-12-01

    Full Text Available The objective of this study were to estimate the general ability and specific combining ability in ten wheat genotypes in two generations (F1 and F2 to indicate parents and hybrid combinations that are promising to achieve new favorable combinations. Ten wheat genotypes were hybridized in a complete diallel, without reciprocals, totaling 45 hybrid combinations. F1 hybrids and the F2 populations and parents were evaluated in a randomized block design with three replicates in spaced plant. The effect of general combining ability (GCA was greater than specific combining ability (SCA in both generations, regardless of the characters evaluated. The best performances of the CGC to grain yield per plant (GYP, number of kernels per spike (NKS, number of spikes per plant (NSP and plant height (PH were observed for the parents Fundacep 50, Pampeano, BRS Figueira and UTF 0605, respectively. Promising hybrid combinations (high magnitude of SCA in both generations and high average for the character and at least one parent presenting desirable GCA were selected. The association of GCA with the performance of characters GYP (F1 = F2 = 0.75 and 0.81, NKS (F1 = F2 = 0.61 and 0.60 and PH (F1=0.99 and F2= 0.98 showed to be a reliable criterion for choice of parents, regardless of generation evaluated.

  3. Genomic Prediction of Genetic Values for Resistance to Wheat Rusts

    Directory of Open Access Journals (Sweden)

    Leonardo Ornella

    2012-11-01

    Full Text Available Durable resistance to the rust diseases of wheat ( L. can be achieved by developing lines that have race-nonspecific adult plant resistance conferred by multiple minor slow-rusting genes. Genomic selection (GS is a promising tool for accumulating favorable alleles of slow-rusting genes. In this study, five CIMMYT wheat populations evaluated for resistance were used to predict resistance to stem rust ( and yellow rust ( using Bayesian least absolute shrinkage and selection operator (LASSO (BL, ridge regression (RR, and support vector regression with linear or radial basis function kernel models. All parents and populations were genotyped using 1400 Diversity Arrays Technology markers and different prediction problems were assessed. Results show that prediction ability for yellow rust was lower than for stem rust, probably due to differences in the conditions of infection of both diseases. For within population and environment, the correlation between predicted and observed values (Pearson’s correlation [ρ] was greater than 0.50 in 90% of the evaluations whereas for yellow rust, ρ ranged from 0.0637 to 0.6253. The BL and RR models have similar prediction ability, with a slight superiority of the BL confirming reports about the additive nature of rust resistance. When making predictions between environments and/or between populations, including information from another environment or environments or another population or populations improved prediction.

  4. Calculation of the time resolution of the J-PET tomograph using kernel density estimation

    Science.gov (United States)

    Raczyński, L.; Wiślicki, W.; Krzemień, W.; Kowalski, P.; Alfs, D.; Bednarski, T.; Białas, P.; Curceanu, C.; Czerwiński, E.; Dulski, K.; Gajos, A.; Głowacz, B.; Gorgol, M.; Hiesmayr, B.; Jasińska, B.; Kamińska, D.; Korcyl, G.; Kozik, T.; Krawczyk, N.; Kubicz, E.; Mohammed, M.; Pawlik-Niedźwiecka, M.; Niedźwiecki, S.; Pałka, M.; Rudy, Z.; Rundel, O.; Sharma, N. G.; Silarski, M.; Smyrski, J.; Strzelecki, A.; Wieczorek, A.; Zgardzińska, B.; Zieliński, M.; Moskal, P.

    2017-06-01

    In this paper we estimate the time resolution of the J-PET scanner built from plastic scintillators. We incorporate the method of signal processing using the Tikhonov regularization framework and the kernel density estimation method. We obtain simple, closed-form analytical formulae for time resolution. The proposed method is validated using signals registered by means of the single detection unit of the J-PET tomograph built from a 30 cm long plastic scintillator strip. It is shown that the experimental and theoretical results obtained for the J-PET scanner equipped with vacuum tube photomultipliers are consistent.

  5. A Quantized Kernel Learning Algorithm Using a Minimum Kernel Risk-Sensitive Loss Criterion and Bilateral Gradient Technique

    Directory of Open Access Journals (Sweden)

    Xiong Luo

    2017-07-01

    Full Text Available Recently, inspired by correntropy, kernel risk-sensitive loss (KRSL has emerged as a novel nonlinear similarity measure defined in kernel space, which achieves a better computing performance. After applying the KRSL to adaptive filtering, the corresponding minimum kernel risk-sensitive loss (MKRSL algorithm has been developed accordingly. However, MKRSL as a traditional kernel adaptive filter (KAF method, generates a growing radial basis functional (RBF network. In response to that limitation, through the use of online vector quantization (VQ technique, this article proposes a novel KAF algorithm, named quantized MKRSL (QMKRSL to curb the growth of the RBF network structure. Compared with other quantized methods, e.g., quantized kernel least mean square (QKLMS and quantized kernel maximum correntropy (QKMC, the efficient performance surface makes QMKRSL converge faster and filter more accurately, while maintaining the robustness to outliers. Moreover, considering that QMKRSL using traditional gradient descent method may fail to make full use of the hidden information between the input and output spaces, we also propose an intensified QMKRSL using a bilateral gradient technique named QMKRSL_BG, in an effort to further improve filtering accuracy. Short-term chaotic time-series prediction experiments are conducted to demonstrate the satisfactory performance of our algorithms.

  6. 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.

  7. GABA Shunt in Durum Wheat.

    Science.gov (United States)

    Carillo, Petronia

    2018-01-01

    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.

  8. Evaluating the Application of Tissue-Specific Dose Kernels Instead of Water Dose Kernels in Internal Dosimetry : A Monte Carlo Study

    NARCIS (Netherlands)

    Moghadam, Maryam Khazaee; Asl, Alireza Kamali; Geramifar, Parham; Zaidi, Habib

    2016-01-01

    Purpose: The aim of this work is to evaluate the application of tissue-specific dose kernels instead of water dose kernels to improve the accuracy of patient-specific dosimetry by taking tissue heterogeneities into consideration. Materials and Methods: Tissue-specific dose point kernels (DPKs) and

  9. 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.

  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. Characterization of a wheat-Thinopyrum bessarabicum (T2JS-2BS.2BL) translocation line.

    Science.gov (United States)

    Qi, Zengjun; Du, Pei; Qian, Baoli; Zhuang, Lifang; Chen, Huafeng; Chen, Tingting; Shen, Jian; Guo, Jie; Feng, Yigao; Pei, Ziyou

    2010-08-01

    Thinopyrum bessarabicum (2n = 2x = 14, JJ or E(b)E(b)) is an important genetic resource for wheat improvement due to its salinity tolerance and disease resistance. Development of wheat-Th. bessarabicum translocation lines will facilitate its practical utilization in wheat improvement. In this study, a novel wheat-Th. bessarabicum translocation line T2JS-2BS.2BL, which carries a segment of Th. bessarabicum chromosome arm 2JS was identified and further characterized using sequential chromosome C-banding, genomic in situ hybridization (GISH), dual-color fluorescent in situ hybridization (FISH) and DNA markers. The translocation breakpoint was mapped within bin C-2BS1-0.53 of chromosome 2B through marker analysis. Compared to the Chinese Spring (CS) parent and to CS-type lines, the translocation line has more fertile spikes per plant, longer spikes, more grains per spike and higher yield per plant, which suggests that the alien segment carries yield-related genes. However, plants with the translocation are also taller, head later and have lower 1,000-kernel weight than CS or CS-type lines. By using markers specific to the barley photoperiod response gene Ppd-H1, it was determined that the late heading date was conferred by a recessive allele located on the 2JS segment. In addition, four markers specific for the translocated segment were identified, which can be used for marker-aided screening.

  12. Protein fold recognition using geometric kernel data fusion.

    Science.gov (United States)

    Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

    2014-07-01

    Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

  13. Local coding based matching kernel method for image classification.

    Directory of Open Access Journals (Sweden)

    Yan Song

    Full Text Available This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

  14. Collision kernels in the eikonal approximation for Lennard-Jones interaction potential

    International Nuclear Information System (INIS)

    Zielinska, S.

    1985-03-01

    The velocity changing collisions are conveniently described by collisional kernels. These kernels depend on an interaction potential and there is a necessity for evaluating them for realistic interatomic potentials. Using the collision kernels, we are able to investigate the redistribution of atomic population's caused by the laser light and velocity changing collisions. In this paper we present the method of evaluating the collision kernels in the eikonal approximation. We discuss the influence of the potential parameters Rsub(o)sup(i), epsilonsub(o)sup(i) on kernel width for a given atomic state. It turns out that unlike the collision kernel for the hard sphere model of scattering the Lennard-Jones kernel is not so sensitive to changes of Rsub(o)sup(i) as the previous one. Contrary to the general tendency of approximating collisional kernels by the Gaussian curve, kernels for the Lennard-Jones potential do not exhibit such a behaviour. (author)

  15. Exogenous Cytokinins Increase Grain Yield of Winter Wheat Cultivars by Improving Stay-Green Characteristics under Heat Stress.

    Directory of Open Access Journals (Sweden)

    Dongqing Yang

    Full Text Available Stay-green, a key trait of wheat, can not only increase the yield of wheat but also its resistance to heat stress during active photosynthesis. Cytokinins are the most potent general coordinator between the stay-green trait and senescence. The objectives of the present study were to identify and assess the effects of cytokinins on the photosynthetic organ and heat resistance in wheat. Two winter wheat cultivars, Wennong 6 (a stay-green cultivar and Jimai 20 (a control cultivar, were subjected to heat stress treatment from 1 to 5 days after anthesis (DAA. The two cultivars were sprayed daily with 10 mg L-1 of 6-benzylaminopurine (6-BA between 1 and 3 DAA under ambient and elevated temperature conditions. We found that the heat stress significantly decreased the number of kernels per spike and the grain yield (P < 0.05. Heat stress also decreased the zeatin riboside (ZR content, but increased the gibberellin (GA3, indole-3-acetic acid (IAA, and abscisic acid (ABA contents at 3 to 15 DAA. Application of 6-BA significantly (P < 0.05 increased the grain-filling rate, endosperm cell division rate, endosperm cell number, and 1,000-grain weight under heated condition. 6-BA application increased ZR and IAA contents at 3 to 28 DAA, but decreased GA3 and ABA contents. The contents of ZR, ABA, and IAA in kernels were positively and significantly correlated with the grain-filling rate (P < 0.05, whereas GA3 was counter-productive at 3 to 15 DAA. These results suggest that the decrease in grain yield under heat stress was due to a lower ZR content and a higher GA3 content compared to that at elevated temperature during the early development of the kernels, which resulted in less kernel number and lower grain-filling rate. The results also provide essential information for further utilization of the cytokinin substances in the cultivation of heat-resistant wheat.

  16. Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

    Science.gov (United States)

    Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

    2017-06-21

    In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

  17. Interest Extraction Using Relevance Feedback with Kernel Method

    Science.gov (United States)

    Hidekazu, Yanagimoto; Sigeru, Omatu

    In this paper, we propose interest extraction using the relevance feedback with the kernel method. In the field of machine learning, the kernel method has been used. Since the classifier using the kernel method creates a discriminant function in a feature space, the discriminant function is a nonlinear function in a input space. The kernel method is used for the Support Vector Machine (SVM), the Kernel PCA, and so on. The SVM set a discriminant hyperplane between positive data and negative data. Hence, a distance between the hyperplane and a training sample is not important in the SVM. It is difficult to use the SVM to score other samples. Our goal is to create a method which scores the other samples in the feature space. We propose the relevance feedback which is carried out in the feature space. Hence, this relevance feedback can deal with nonlinearity of data. We compare the proposed method with the common relevance feedback using test collection NTCIR2. Finally, we comfirm the proposed method is superior to the common method through simulations.

  18. Mixed kernel function support vector regression for global sensitivity analysis

    Science.gov (United States)

    Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

    2017-11-01

    Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

  19. CELLULOSE EXTRACTION FROM PALM KERNEL CAKE USING LIQUID PHASE OXIDATION

    Directory of Open Access Journals (Sweden)

    FARM YAN YAN

    2009-03-01

    Full Text Available Cellulose is widely used in many aspect and industries such as food industry, pharmaceutical, paint, polymers, and many more. Due to the increasing demand in the market, studies and work to produce cellulose are still rapidly developing. In this work, liquid phase oxidation was used to extract cellulose from palm kernel cake to separate hemicellulose, cellulose and lignin. The method is basically a two-step process. Palm kernel cake was pretreated in hot water at 180°C and followed by liquid oxidation process with 30% H2O2 at 60°C at atmospheric pressure. The process parameters are hot water treatment time, ratio of palm kernel cake to H2O2, liquid oxidation reaction temperature and time. Analysis of the process parameters on production cellulose from palm kernel cake was performed by using Response Surface Methodology. The recovered cellulose was further characterized by Fourier Transform Infrared (FTIR. Through the hot water treatment, hemicellulose in the palm kernel cake was successfully recovered as saccharides and thus leaving lignin and cellulose. Lignin was converted to water soluble compounds in liquid oxidation step which contains small molecular weight fatty acid as HCOOH and CH3COOH and almost pure cellulose was recovered.

  20. Semi-supervised learning for ordinal Kernel Discriminant Analysis.

    Science.gov (United States)

    Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

    2016-12-01

    Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Multiple kernel sparse representations for supervised and unsupervised learning.

    Science.gov (United States)

    Thiagarajan, Jayaraman J; Ramamurthy, Karthikeyan Natesan; Spanias, Andreas

    2014-07-01

    In complex visual recognition tasks, it is typical to adopt multiple descriptors, which describe different aspects of the images, for obtaining an improved recognition performance. Descriptors that have diverse forms can be fused into a unified feature space in a principled manner using kernel methods. Sparse models that generalize well to the test data can be learned in the unified kernel space, and appropriate constraints can be incorporated for application in supervised and unsupervised learning. In this paper, we propose to perform sparse coding and dictionary learning in the multiple kernel space, where the weights of the ensemble kernel are tuned based on graph-embedding principles such that class discrimination is maximized. In our proposed algorithm, dictionaries are inferred using multiple levels of 1D subspace clustering in the kernel space, and the sparse codes are obtained using a simple levelwise pursuit scheme. Empirical results for object recognition and image clustering show that our algorithm outperforms existing sparse coding based approaches, and compares favorably to other state-of-the-art methods.

  2. Weed Dynamics and Management in Wheat

    DEFF Research Database (Denmark)

    Jabran, Khawar; Mahmood, Khalid; Melander, Bo

    2017-01-01

    Wheat is among the most important cereal and food crops of world and is grown in almost all parts of the world. It is a staple for a large part of the world population. Any decline in wheat yield by biotic or abiotic factors may affect global food security adversely. Weeds are the most damaging...... pest of wheat causing in total 24% losses in wheat grain yield. In this chapter, we discuss the (i) weed flora in different wheat-growing regions of world; (ii) the yield losses caused by weeds in wheat; (iii) the preventive and cultural options for weed management; (iv) physical weed control; (v......) chemical weed control; and (vi) integrated weed management strategy in wheat. A critical analysis of recent literature indicated that broadleaved weeds are the most common group of weeds in wheat fields followed by grass weeds, while sedges were rarely noted in wheat fields. Across the globe, the most...

  3. Non-Celiac Wheat Sensitivity

    Science.gov (United States)

    ... Green, MD Celiac Genetic Testing with Annette K. Taylor, MS, PhD Introduction to Drug Development with Daniel ... July 2016, a team of researchers at Columbia University Medical Center, published a study confirming that wheat ...

  4. 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.......9% in the third screening with 41 selected cultivars. The Fv/Fm was influenced by heat stress and the difference between the cultivars appeared only during the heat stress. Further analysis of other chlorophyll fluorescence parameters showed similar or higher GD, but they did not reveal the genetic difference....... The correlation of the cultivar response in intact plant versus detached leaf was low. Overall, the result suggests that selection of cultivars by detached leaves may operate for different genetic factors than in intact plants. In the third study, the previously selected high and low groups of cultivars (from...

  5. Stamena winter wheat variety

    Directory of Open Access Journals (Sweden)

    Mišić Todor

    2001-01-01

    Full Text Available Stamena is a winter wheat variety developed at the Institute of Field and Vegetable Crops in Novi Sad, Yugoslavia. It was released by the Federal Commission for varietals Approval in 1999. Stamena was developed by crossing genetically divergent and highly productive parents Lasta and Rodna (Breeders: T. Mišić. N. Mladenov, Z. Jerković and R. Jevtić. Spike is white, smooth, awn less, medium compact with 18-21 spike lets. The grain is vitreous and dark red (Triticum aestivum L. ssp. vulgar e var. lutescens. Stamena is a medium early variety, 1 day earlier than Partizanka and 3 days earlier than Jugoslavija (Table 4. It has excellent resistance to winterkilling, as in very winter hardy Partizanka. The average stem height is 78 cm, with a good resistance to lodging. Stamena has field resistance to leaf rust (Pucce, recondita tritict, horizontal resistance, which is the type of resistance that modern wheat breeding is interested in. The resistance to stem rust (Pucce, graminis tritict is good and to powdery mildew (Erysiphegraminis tritici very good. The 1000 grain mass is about 32 g and volume grain mass 81.3 kg/hi. (Table 2. Stamena is classified in the subgroup A-l. It has excellent milling and baking quality and it belong to the 1st technological group (quality enhancer. The quantity of dry gluten is about 9%. The variety Stamena is a very productive, with the genetic potential for grain above 11 t/ha suitable for growing on fertile and less fertile soils. It has started to be grown commercially in 2000.

  6. An Efficient Kernel Optimization Method for Radar High-Resolution Range Profile Recognition

    Directory of Open Access Journals (Sweden)

    Chen Bo

    2007-01-01

    Full Text Available A kernel optimization method based on fusion kernel for high-resolution range profile (HRRP is proposed in this paper. Based on the fusion of -norm and -norm Gaussian kernels, our method combines the different characteristics of them so that not only is the kernel function optimized but also the speckle fluctuations of HRRP are restrained. Then the proposed method is employed to optimize the kernel of kernel principle component analysis (KPCA and the classification performance of extracted features is evaluated via support vector machines (SVMs classifier. Finally, experimental results on the benchmark and radar-measured data sets are compared and analyzed to demonstrate the efficiency of our method.

  7. Field evaluation of durum wheat landraces for prevailing abiotic and biotic stresses in highland rainfed regions of Iran

    Directory of Open Access Journals (Sweden)

    Reza Mohammadi

    2015-10-01

    Full Text Available Biotic and abiotic stresses are major limiting factors for high crop productivity worldwide. A landrace collection consisting of 380 durum wheat (Triticum turgidum L. var. durum entries originating in several countries along with four check varieties were evaluated for biotic stresses: yellow rust (Puccinia striiformis Westendorf f. sp. tritici and wheat stem sawfly (WSS Cephus cinctus Norton (Hymenoptera: Cephidae, and abiotic stresses: cold and drought. The main objectives were to (i quantify phenotypic diversity and identify variation in the durum wheat landraces for the different stresses and (ii characterize the agronomic profiles of landraces in reaction to the stresses. Significant changes in reactions of landraces to stresses were observed. Landraces resistant to each stress were identified and agronomically characterized. Percentage reduction due to the stresses varied from 11.4% (yellow rust to 21.6% (cold stress for 1000-kernel weight (TKW and from 19.9 (yellow rust to 91.9% (cold stress for grain yield. Landraces from Asia and Europe showed enhanced genetic potential for both grain yield and cold tolerance under highland rainfed conditions of Iran. The findings showed that TKW and yield productivity could be used to assess the response of durum wheat landraces to different stresses. In conclusion, landraces showed high levels of resistance to both biotic and abiotic stresses, and selected landraces can serve in durum wheat breeding for adaptation to cold and drought-prone environments.

  8. Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain.

    Science.gov (United States)

    Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo

    2016-01-01

    Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3∼3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0∼19.4%) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha(-1) year(-1), except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.

  9. The spinor heat kernel in maximally symmetric spaces

    International Nuclear Information System (INIS)

    Camporesi, R.

    1992-01-01

    The heat kernel K(x, x', t) of the iterated Dirac operator on an N-dimensional simply connected maximally symmetric Riemannian manifold is calculated. On the odd-dimensional hyperbolic spaces K is a Minakshisundaram-DeWitt expansion which terminates to the coefficient a (N-1)/2 and is exact. On the odd spheres the heat kernel may be written as an image sum of WKB kernels, each term corresponding to a classical path (geodesic). In the even dimensional case the WKB approximation is not exact, but a closed form of K is derived both in terms of (spherical) eigenfunctions and of a 'sum over classical paths'. The spinor Plancherel measure μ(λ) and ζ function in the hyperbolic case are also calculated. A simple relation between the analytic structure of μ on H N and the degeneracies of the Dirac operator on S N is found. (orig.)

  10. Purification and characterization of riproximin from Ximenia americana fruit kernels.

    Science.gov (United States)

    Bayer, Helene; Ey, Noreen; Wattenberg, Andreas; Voss, Cristina; Berger, Martin R

    2012-03-01

    Highly pure riproximin was isolated from the fruit kernels of Ximenia americana, a defined, seasonally available and potentially unlimited herbal source. The newly established purification procedure included an initial aqueous extraction, removal of lipids with chloroform and subsequent chromatographic purification steps on a strong anion exchange resin and lactosyl-Sepharose. Consistent purity and stable biological properties were shown over several purification batches. The purified, kernel-derived riproximin was characterized in comparison to the African plant material riproximin and revealed highly similar biochemical and biological properties but differences in the electrophoresis pattern and mass spectrometry peptide profile. Our results suggest that although the purified fruit kernel riproximin consists of a mixture of closely related isoforms, it provides a reliable basis for further research and development of this type II ribosome inactivating protein (RIP). Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Reconstruction of noisy and blurred images using blur kernel

    Science.gov (United States)

    Ellappan, Vijayan; Chopra, Vishal

    2017-11-01

    Blur is a common in so many digital images. Blur can be caused by motion of the camera and scene object. In this work we proposed a new method for deblurring images. This work uses sparse representation to identify the blur kernel. By analyzing the image coordinates Using coarse and fine, we fetch the kernel based image coordinates and according to that observation we get the motion angle of the shaken or blurred image. Then we calculate the length of the motion kernel using radon transformation and Fourier for the length calculation of the image and we use Lucy Richardson algorithm which is also called NON-Blind(NBID) Algorithm for more clean and less noisy image output. All these operation will be performed in MATLAB IDE.

  12. Heat Kernel Asymptotics of Zaremba Boundary Value Problem

    Energy Technology Data Exchange (ETDEWEB)

    Avramidi, Ivan G. [Department of Mathematics, New Mexico Institute of Mining and Technology (United States)], E-mail: iavramid@nmt.edu

    2004-03-15

    The Zaremba boundary-value problem is a boundary value problem for Laplace-type second-order partial differential operators acting on smooth sections of a vector bundle over a smooth compact Riemannian manifold with smooth boundary but with discontinuous boundary conditions, which include Dirichlet boundary conditions on one part of the boundary and Neumann boundary conditions on another part of the boundary. We study the heat kernel asymptotics of Zaremba boundary value problem. The construction of the asymptotic solution of the heat equation is described in detail and the heat kernel is computed explicitly in the leading approximation. Some of the first nontrivial coefficients of the heat kernel asymptotic expansion are computed explicitly.

  13. Optimized data fusion for kernel k-means clustering.

    Science.gov (United States)

    Yu, Shi; Tranchevent, Léon-Charles; Liu, Xinhai; Glänzel, Wolfgang; Suykens, Johan A K; De Moor, Bart; Moreau, Yves

    2012-05-01

    This paper presents a novel optimized kernel k-means algorithm (OKKC) to combine multiple data sources for clustering analysis. The algorithm uses an alternating minimization framework to optimize the cluster membership and kernel coefficients as a nonconvex problem. In the proposed algorithm, the problem to optimize the cluster membership and the problem to optimize the kernel coefficients are all based on the same Rayleigh quotient objective; therefore the proposed algorithm converges locally. OKKC has a simpler procedure and lower complexity than other algorithms proposed in the literature. Simulated and real-life data fusion applications are experimentally studied, and the results validate that the proposed algorithm has comparable performance, moreover, it is more efficient on large-scale data sets. (The Matlab implementation of OKKC algorithm is downloadable from http://homes.esat.kuleuven.be/~sistawww/bio/syu/okkc.html.).

  14. Rational kernels for Arabic Root Extraction and Text Classification

    Directory of Open Access Journals (Sweden)

    Attia Nehar

    2016-04-01

    Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.

  15. Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing

    Science.gov (United States)

    Li, Shuang; Liu, Bing; Zhang, Chen

    2016-01-01

    Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios. PMID:27247562

  16. Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing.

    Science.gov (United States)

    Li, Shuang; Liu, Bing; Zhang, Chen

    2016-01-01

    Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.

  17. Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing

    Directory of Open Access Journals (Sweden)

    Shuang Li

    2016-01-01

    Full Text Available Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.

  18. Capturing Option Anomalies with a Variance-Dependent Pricing Kernel

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Heston, Steven; Jacobs, Kris

    2013-01-01

    We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....

  19. 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...... on the complexification $G_{\\mathbb C}/K_{\\mathbb C}$ of $Ω$, the weight being expressed explicitly in terms of a multivariable $K$-Bessel function on $Ω$. Even in the special case of the symmetric cone $Ω=\\mathbb{R}_+$ these results seem to be new.......We investigate the heat equation corresponding to the Bessel operators on a symmetric cone $Ω=G/K$. These operators form a one-parameter family of elliptic self-adjoint second order differential operators and occur in the Lie algebra action of certain unitary highest weight representations...

  20. Linear and kernel methods for multivariate change detection

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2012-01-01

    The iteratively reweighted multivariate alteration detection (IR-MAD) algorithm may be used both for unsupervised change detection in multi- and hyperspectral remote sensing imagery and for automatic radiometric normalization of multitemporal image sequences. Principal components analysis (PCA......), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...