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Sample records for walnut kernels electronic

  1. Effect of different ripening stages on walnut kernel quality: antioxidant activities, lipid characterization and antibacterial properties.

    Science.gov (United States)

    Amin, Furheen; Masoodi, F A; Baba, Waqas N; Khan, Asma Ashraf; Ganie, Bashir Ahmad

    2017-11-01

    Packing tissue between and around the kernel halves just turning brown (PTB) is a phenological indicator of kernel ripening at harvest in walnuts. The effect of three ripening stages (Pre-PTB, PTB and Post-PTB) on kernel quality characteristics, mineral composition, lipid characterization, sensory analysis, antioxidant and antibacterial activity were investigated in fresh kernels of indigenous numbered walnut selection of Kashmir valley "SKAU-02". Proximate composition, physical properties and sensory analysis of walnut kernels showed better results for Pre-PTB and PTB while higher mineral content was seen for kernels at Post-PTB stage in comparison to other stages of ripening. Kernels showed significantly higher levels of Omega-3 PUFA (C18:3 n3 ) and low n6/n3 ratio when harvested at Pre-PTB and PTB stages. The highest phenolic content and antioxidant activity was observed at the first stage of ripening and a steady decrease was observed at later stages. TBARS values increased as ripening advanced but did not show any significant difference in malonaldehyde formation during early ripening stages whereas it showed marked increase in walnut kernels at post-PTB stage. Walnut extracts inhibited growth of Gram-positive bacteria ( B. cereus, B. subtilis, and S. aureus ) with respective MICs of 1, 1 and 5 mg/mL and gram negative bacteria ( E. coli, P. and K. pneumonia ) with MIC of 100 mg/mL. Zone of inhibition obtained against all the bacterial strains from walnut kernel extracts increased with increase in the stage of ripening. It is concluded that Pre-PTB harvest stage with higher antioxidant activities, better fatty acid profile and consumer acceptability could be preferred harvesting stage for obtaining functionally superior walnut kernels.

  2. RHAGOLETIS COMPLETA (DIPTERA; TEPHRITIDAE) DISTRIBUTION, FLIGHT DYNAMICS AND INFLUENCE ON WALNUT KERNEL QUALITY IN THE CONTINENTAL CROATIA

    OpenAIRE

    Božena Barić; Ivana Pajač Živković; Dinka Matošević; Milorad Šubić; Erzsébet Voigt; Miklós Tóth

    2015-01-01

    Walnut husk fly (WHF), Rhagoletis completa Cresson 1929 is an invasive species spreading quickly and damaging walnuts in Croatia and neighbouring countries. We researched distribution of this pest in the continental part of Croatia, flight dynamics in Međimurje County and its influence on quality of walnut kernels. CSALOMON®PALz traps were used for monitoring the spread and flight dynamics of R. completa. Weight and the protein content of kernels and the presence of mycotoxin contamination we...

  3. RHAGOLETIS COMPLETA (DIPTERA; TEPHRITIDAE DISTRIBUTION, FLIGHT DYNAMICS AND INFLUENCE ON WALNUT KERNEL QUALITY IN THE CONTINENTAL CROATIA

    Directory of Open Access Journals (Sweden)

    Božena Barić

    2015-06-01

    Full Text Available Walnut husk fly (WHF, Rhagoletis completa Cresson 1929 is an invasive species spreading quickly and damaging walnuts in Croatia and neighbouring countries. We researched distribution of this pest in the continental part of Croatia, flight dynamics in Međimurje County and its influence on quality of walnut kernels. CSALOMON®PALz traps were used for monitoring the spread and flight dynamics of R. completa. Weight and the protein content of kernels and the presence of mycotoxin contamination were measured. Walnut husk fly was found in six counties (Istria County: pest reconfirmation, Zagreb County, The City of Zagreb, Varaždin County, Međimurje County and Koprivnica-Križevci County. The presence of the fly was not confirmed on one site in Koprivnica-Križevci County (locality Ferdinandovac and in the eastern part of Croatia (Vukovar-Srijem County: Vinkovci locality. The flight dynamics showed rapid increase in number of adults only a year after the introduction into new area. The weight of infested kernels was 5.81% lower compared to not infested. Protein content was 14.04% in infested kernels and 17.31% in not infested kernels. There was no difference in mycotoxins levels. Additional researches on mycotoxin levels in stored nuts, ovipositional preferences of walnut husk fly and protection measures against this pest are suggested.

  4. Walnut kernel-like mesoporous silica nanoparticles as effective drug carrier for cancer therapy in vitro

    Energy Technology Data Exchange (ETDEWEB)

    Ge, Kun; Ren, Huihui; Sun, Wentong [Hebei University, Key Laboratory of Chemical Biology of Hebei Province, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of the Ministry of Education, College of Chemistry & Environmental Science (China); Zhao, Qi [Hebei University, College of Clinical Science (China); Jia, Guang [Hebei University, Key Laboratory of Chemical Biology of Hebei Province, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of the Ministry of Education, College of Chemistry & Environmental Science (China); Zang, Aimin [Affiliated Hospital of Hebei University (China); Zhang, Cuimiao, E-mail: cmzhanghbu@163.com; Zhang, Jinchao, E-mail: jczhang6970@163.com [Hebei University, Key Laboratory of Chemical Biology of Hebei Province, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of the Ministry of Education, College of Chemistry & Environmental Science (China)

    2016-03-15

    In drug delivery systems, nanocarriers could reduce the degradation and renal clearance of drugs, increase the half-life in the bloodstream and payload of drugs, control the release patterns, and improve the solubility of some insoluble drugs. In particular, mesoporous silica nanoparticles (MSNs) are considered to be attractive nanocarriers for application of delivery systems because of their large surface areas, large pore volume, tunable pore sizes, good biocompatibility, and the ease of surface functionalization. However, the large-scale synthesis of monodisperse MSNs that are smaller than 200 nm remains a challenge. In this study, monodisperse walnut kernel-like MSNs with diameters of approximately 100 nm were synthesized by a sol–gel route on a large scale. The morphology and structure of MSNs were characterized by scanning electron microscope, and transmission electron microscopy, N{sub 2} adsorption–desorption isotherms, Zeta potentials, and dynamic light scattering. Drug loading and release profile, cellular uptake, subcellular localization, and anticancer effect in vitro were further investigated. The results indicated that the loading efficiency of doxorubicinhydrochloride (DOX) into the MSNs was 57 %. The MSNs–DOX delivery system exhibited a drug-pronounced initial burst release within 12 h, followed by the slow sustained release of DOX molecules; moreover, MSNs could improve DOX release efficiency in acidic medium. Most free DOX was localized in the cytoplasm, whereas the MSNs–DOX was primarily distributed in lysosome. MSNs–DOX exhibited a potential anticancer effect against MCF-7, HeLa, and A549 cells in dose- and time-dependent manners. In summary, the as-synthesized MSNs may have well function as a promising drug carrier in drug delivery fields.Graphical Abstract.

  5. A new kernel discriminant analysis framework for electronic nose recognition

    International Nuclear Information System (INIS)

    Zhang, Lei; Tian, Feng-Chun

    2014-01-01

    Graphical abstract: - Highlights: • This paper proposes a new discriminant analysis framework for feature extraction and recognition. • The principle of the proposed NDA is derived mathematically. • The NDA framework is coupled with kernel PCA for classification. • The proposed KNDA is compared with state of the art e-Nose recognition methods. • The proposed KNDA shows the best performance in e-Nose experiments. - Abstract: Electronic nose (e-Nose) technology based on metal oxide semiconductor gas sensor array is widely studied for detection of gas components. This paper proposes a new discriminant analysis framework (NDA) for dimension reduction and e-Nose recognition. In a NDA, the between-class and the within-class Laplacian scatter matrix are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness by seeking for discriminant matrix to simultaneously maximize the between-class Laplacian scatter and minimize the within-class Laplacian scatter. In terms of the linear separability in high dimensional kernel mapping space and the dimension reduction of principal component analysis (PCA), an effective kernel PCA plus NDA method (KNDA) is proposed for rapid detection of gas mixture components by an e-Nose. The NDA framework is derived in this paper as well as the specific implementations of the proposed KNDA method in training and recognition process. The KNDA is examined on the e-Nose datasets of six kinds of gas components, and compared with state of the art e-Nose classification methods. Experimental results demonstrate that the proposed KNDA method shows the best performance with average recognition rate and total recognition rate as 94.14% and 95.06% which leads to a promising feature extraction and multi-class recognition in e-Nose

  6. Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting

    OpenAIRE

    Zivoli, Rosanna; Gambacorta, Lucia; Piemontese, Luca; Solfrizzo, Michele

    2016-01-01

    The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distributi...

  7. 7 CFR 51.2295 - Half kernel.

    Science.gov (United States)

    2010-01-01

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

  8. 7 CFR 984.56 - Disposition of reserve walnuts.

    Science.gov (United States)

    2010-01-01

    ... Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing... Board may export or authorize the disposition in export to the destinations outside the United States... marketing year a handler may deliver reserve walnuts and any substandard walnuts meeting the minimum kernel...

  9. Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting

    Directory of Open Access Journals (Sweden)

    Rosanna Zivoli

    2016-01-01

    Full Text Available The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B1 and B2 were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB1 + AFB2, whereas AFG1 and AFG2 were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%–19.9% of total peeled kernels removed 97.3%–99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%–99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB1 + AFB2 measured in rejected fractions (15%–18% of total kernels ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01–0.05 µg/kg was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB1 and from 0.06 to 1.79 μg/kg for total aflatoxins.

  10. Prediction of the antimicrobial activity of walnut (Juglans regia L.) kernel aqueous extracts using artificial neural network and multiple linear regression.

    Science.gov (United States)

    Kavuncuoglu, Hatice; Kavuncuoglu, Erhan; Karatas, Seyda Merve; Benli, Büsra; Sagdic, Osman; Yalcin, Hasan

    2018-04-09

    The mathematical model was established to determine the diameter of inhibition zone of the walnut extract on the twelve bacterial species. Type of extraction, concentration, and pathogens were taken as input variables. Two models were used with the aim of designing this system. One of them was developed with artificial neural networks (ANN), and the other was formed with multiple linear regression (MLR). Four common training algorithms were used. Levenberg-Marquardt (LM), Bayesian regulation (BR), scaled conjugate gradient (SCG) and resilient back propagation (RP) were investigated, and the algorithms were compared. Root mean squared error and correlation coefficient were evaluated as performance criteria. When these criteria were analyzed, ANN showed high prediction performance, while MLR showed low prediction performance. As a result, it is seen that when the different input values are provided to the system developed with ANN, the most accurate inhibition zone (IZ) estimates were obtained. The results of this study could offer new perspectives, particularly in the field of microbiology, because these could be applied to other type of extraction, concentrations, and pathogens, without resorting to experiments. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Investigation of tilted dose kernels for portal dose prediction in a-Si electronic portal imagers

    International Nuclear Information System (INIS)

    Chytyk, K.; McCurdy, B. M. C.

    2006-01-01

    The effect of beam divergence on dose calculation via Monte Carlo generated dose kernels was investigated in an amorphous silicon electronic portal imaging device (EPID). The flat-panel detector was simulated in EGSnrc with an additional 3.0 cm water buildup. The model included details of the detector's imaging cassette and the front cover upstream of it. To approximate the effect of the EPID's rear housing, a 2.1 cm air gap and 1.0 cm water slab were introduced into the simulation as equivalent backscatter material. Dose kernels were generated with an incident pencil beam of monoenergetic photons of energy 0.1, 2, 6, and 18 MeV. The orientation of the incident pencil beam was varied from 0 deg. to 14 deg. in 2 deg. increments. Dose was scored in the phosphor layer of the detector in both cylindrical (at 0 deg. ) and Cartesian (at 0 deg. -14 deg.) geometries. To reduce statistical fluctuations in the Cartesian geometry simulations at large radial distances from the incident pencil beam, the voxels were first averaged bilaterally about the pencil beam and then combined into concentric square rings of voxels. Profiles of the EPID dose kernels displayed increasing asymmetry with increasing angle and energy. A comparison of the superposition (tilted kernels) and convolution (parallel kernels) dose calculation methods via the χ-comparison test (a derivative of the γ-evaluation) in worst-case-scenario geometries demonstrated an agreement between the two methods within 0.0784 cm (one pixel width) distance-to-agreement and up to a 1.8% dose difference. More clinically typical field sizes and source-to-detector distances were also tested, yielding at most a 1.0% dose difference and the same distance-to-agreement. Therefore, the assumption of parallel dose kernels has less than a 1.8% dosimetric effect in extreme cases and less than a 1.0% dosimetric effect in most clinically relevant situations and should be suitable for most clinical dosimetric applications. The

  12. Linked-cluster formulation of electron-hole interaction kernel in real-space representation without using unoccupied states.

    Science.gov (United States)

    Bayne, Michael G; Scher, Jeremy A; Ellis, Benjamin H; Chakraborty, Arindam

    2018-05-21

    Electron-hole or quasiparticle representation plays a central role in describing electronic excitations in many-electron systems. For charge-neutral excitation, the electron-hole interaction kernel is the quantity of interest for calculating important excitation properties such as optical gap, optical spectra, electron-hole recombination and electron-hole binding energies. The electron-hole interaction kernel can be formally derived from the density-density correlation function using both Green's function and TDDFT formalism. The accurate determination of the electron-hole interaction kernel remains a significant challenge for precise calculations of optical properties in the GW+BSE formalism. From the TDDFT perspective, the electron-hole interaction kernel has been viewed as a path to systematic development of frequency-dependent exchange-correlation functionals. Traditional approaches, such as MBPT formalism, use unoccupied states (which are defined with respect to Fermi vacuum) to construct the electron-hole interaction kernel. However, the inclusion of unoccupied states has long been recognized as the leading computational bottleneck that limits the application of this approach for larger finite systems. In this work, an alternative derivation that avoids using unoccupied states to construct the electron-hole interaction kernel is presented. The central idea of this approach is to use explicitly correlated geminal functions for treating electron-electron correlation for both ground and excited state wave functions. Using this ansatz, it is derived using both diagrammatic and algebraic techniques that the electron-hole interaction kernel can be expressed only in terms of linked closed-loop diagrams. It is proved that the cancellation of unlinked diagrams is a consequence of linked-cluster theorem in real-space representation. The electron-hole interaction kernel derived in this work was used to calculate excitation energies in many-electron systems and results

  13. Kernel polynomial method for a nonorthogonal electronic-structure calculation of amorphous diamond

    International Nuclear Information System (INIS)

    Roeder, H.; Silver, R.N.; Drabold, D.A.; Dong, J.J.

    1997-01-01

    The Kernel polynomial method (KPM) has been successfully applied to tight-binding electronic-structure calculations as an O(N) method. Here we extend this method to nonorthogonal basis sets with a sparse overlap matrix S and a sparse Hamiltonian H. Since the KPM method utilizes matrix vector multiplications it is necessary to apply S -1 H onto a vector. The multiplication of S -1 is performed using a preconditioned conjugate-gradient method and does not involve the explicit inversion of S. Hence the method scales the same way as the original KPM method, i.e., O(N), although there is an overhead due to the additional conjugate-gradient part. We apply this method to a large scale electronic-structure calculation of amorphous diamond. copyright 1997 The American Physical Society

  14. Evaluation of some Phenological and Pomological Characteristics of Selected Walnut Genotypes from Shahroud-Iran

    Directory of Open Access Journals (Sweden)

    Sara Akhiani

    2017-05-01

    Full Text Available The first step in walnut breeding programs is to identify and evaluate superior genotypes of fruit trees. Hence, there are various walnut breeding programs in various areas of Iran. A study aimed to evaluate the morphological and chemical characteristics of selected superior genotypes of walnut was conducted in the Shahroud region in 2011-2012.  The following genotypes were selected in this study as the best walnut genotypes:  X-18 homogamous genotypes due to desirable late leafing;   genotype X-11 for its high percentage of kernel production, easily removal of shell, thin shell; genotype X-52 due to its kernel plumpness compared to other genotypes, thin shell and high percentage of kernel and genotype X-70 for its kernel brightness, easily kernel extracting and high percentage of kernels. The X-49 and X-5 genotypes had the highest amount of linoleic and linolenic fatty acids and higher nutritional quality compared to other genotypes. Three genotypes, X-3, X-11 and X-22, had the highest amount of oil. Genotypes X-9 and X-45 had the highest amount of protein. The difference between oil content and fatty acid compositions was presumably due to genetic diversity and ecological conditions of the studied genotypes cultivation.

  15. Annotated black walnut literature

    Science.gov (United States)

    J. W. Van Sambeek

    2006-01-01

    Many of our publications on the establishment, management, and utilization of black walnut, butternut, and associated high-value hardwoods are printed in conference proceedings or scientific journals that are not readily available at most public libraries or on the internet. As Chair of the Education Committee, I have tried to summarize for you the relevant findings of...

  16. Application of Electron Dose Kernels to account for heterogeneities in voxelized phantoms

    International Nuclear Information System (INIS)

    Al-Basheer, A. K.; Sjoden, G. E.; Ghita, M.; Bolch, W.

    2009-01-01

    In this paper, we present work on the application of the Electron Dose Kernel discrete ordinates method (EDK-S N ) to compute doses and account for material heterogeneities using high energy external photon beam irradiations in voxelized human phantoms. EDKs are pre-computed using photon pencil 'beamlets' that lead to dose delivery in tissue using highly converged Monte Carlo. Coupling the EDKs to accumulate dose scaled by integral photon fluences computed using S N methods in dose driving voxels (DDVs) allows for the full charged particle physics computed dose to be accumulated throughout the voxelized phantom, and is the basis of the EDK-S N method, which is fully parallelized. For material heterogeneities, a density scaling correction factor is required to yield good agreement. In a fully voxelized phantom, all doses were in agreement with those determined by independent Monte Carlo computations. We are continuing to expand upon the development of this robust approach for rapid and accurate determination of whole body and out of field organ doses due to high energy x-ray beams. (authors)

  17. Dose point kernel simulation for monoenergetic electrons and radionuclides using Monte Carlo techniques.

    Science.gov (United States)

    Wu, J; Liu, Y L; Chang, S J; Chao, M M; Tsai, S Y; Huang, D E

    2012-11-01

    Monte Carlo (MC) simulation has been commonly used in the dose evaluation of radiation accidents and for medical purposes. The accuracy of simulated results is affected by the particle-tracking algorithm, cross-sectional database, random number generator and statistical error. The differences among MC simulation software packages must be validated. This study simulated the dose point kernel (DPK) and the cellular S-values of monoenergetic electrons ranging from 0.01 to 2 MeV and the radionuclides of (90)Y, (177)Lu and (103 m)Rh, using Fluktuierende Kaskade (FLUKA) and MC N-Particle Transport Code Version 5 (MCNP5). A 6-μm-radius cell model consisting of the cell surface, cytoplasm and cell nucleus was constructed for cellular S-value calculation. The mean absolute percentage errors (MAPEs) of the scaled DPKs, simulated using FLUKA and MCNP5, were 7.92, 9.64, 4.62, 3.71 and 3.84 % for 0.01, 0.1, 0.5, 1 and 2 MeV, respectively. For the three radionuclides, the MAPEs of the scaled DPKs were within 5 %. The maximum deviations of S(N←N), S(N←Cy) and S(N←CS) for the electron energy larger than 10 keV were 6.63, 6.77 and 5.24 %, respectively. The deviations for the self-absorbed S-values and cross-dose S-values of the three radionuclides were within 4 %. On the basis of the results of this study, it was concluded that the simulation results are consistent between FLUKA and MCNP5. However, there is a minor inconsistency for low energy range. The DPK and the cellular S-value should be used as the quality assurance tools before the MC simulation results are adopted as the gold standard.

  18. Walnut mutation breeding

    International Nuclear Information System (INIS)

    Kudina, G.A.

    1989-01-01

    Full text: Walnut seeds were treated with 100-15000 R of gamma rays. Seedlings were subjected to measures of ''de-chimaerisation''. Fast-growing forms were obtained from doses below 2000 R, dwarf types at all doses but increasingly at higher doses. Among the fast growing forms, the promising ones are more precocious, flowering and fruiting at 6 years of age (one even already at 4 years). (author)

  19. Walnut (Juglans regia L.): genetic resources, chemistry, by-products.

    Science.gov (United States)

    Martínez, Marcela L; Labuckas, Diana O; Lamarque, Alicia L; Maestri, Damián M

    2010-09-01

    Walnut (Juglans regia L.) is the most widespread tree nut in the world. There is a great diversity of genotypes differing in forestry, productivity, physical and chemical nut traits. Some of them have been evaluated as promising and may serve as germplasm sources for breeding. The nutritional importance of the nut is related to the seed (kernel). It is a nutrient-dense food mainly owing to its oil content (up to 740 g kg(-1) in some commercial varieties), which can be extracted easily by screw pressing and consumed without refining. Walnut oil composition is dominated largely by unsaturated fatty acids (mainly linoleic together with lesser amounts of oleic and linolenic acids). Minor components of walnut oil include tocopherols, phospholipids, sphingolipids, sterols, hydrocarbons and volatile compounds. Phenolic compounds, present at high levels in the seed coat but poorly extracted with the oil, have been extensively characterised and found to possess strong antioxidant properties. The oil extraction residue is rich in proteins (unusually high in arginine, glutamic and aspartic acids) and has been employed in the formulation of various functional food products. This review describes current scientific knowledge concerning walnut genetic resources and composition as well as by-product obtainment and characteristics. Copyright 2010 Society of Chemical Industry.

  20. Comparison of electron dose-point kernels in water generated by the Monte Carlo codes, PENELOPE, GEANT4, MCNPX, and ETRAN.

    Science.gov (United States)

    Uusijärvi, Helena; Chouin, Nicolas; Bernhardt, Peter; Ferrer, Ludovic; Bardiès, Manuel; Forssell-Aronsson, Eva

    2009-08-01

    Point kernels describe the energy deposited at a certain distance from an isotropic point source and are useful for nuclear medicine dosimetry. They can be used for absorbed-dose calculations for sources of various shapes and are also a useful tool when comparing different Monte Carlo (MC) codes. The aim of this study was to compare point kernels calculated by using the mixed MC code, PENELOPE (v. 2006), with point kernels calculated by using the condensed-history MC codes, ETRAN, GEANT4 (v. 8.2), and MCNPX (v. 2.5.0). Point kernels for electrons with initial energies of 10, 100, 500, and 1 MeV were simulated with PENELOPE. Spherical shells were placed around an isotropic point source at distances from 0 to 1.2 times the continuous-slowing-down-approximation range (R(CSDA)). Detailed (event-by-event) simulations were performed for electrons with initial energies of less than 1 MeV. For 1-MeV electrons, multiple scattering was included for energy losses less than 10 keV. Energy losses greater than 10 keV were simulated in a detailed way. The point kernels generated were used to calculate cellular S-values for monoenergetic electron sources. The point kernels obtained by using PENELOPE and ETRAN were also used to calculate cellular S-values for the high-energy beta-emitter, 90Y, the medium-energy beta-emitter, 177Lu, and the low-energy electron emitter, 103mRh. These S-values were also compared with the Medical Internal Radiation Dose (MIRD) cellular S-values. The greatest differences between the point kernels (mean difference calculated for distances, electrons was 1.4%, 2.5%, and 6.9% for ETRAN, GEANT4, and MCNPX, respectively, compared to PENELOPE, if omitting the S-values when the activity was distributed on the cell surface for 10-keV electrons. The largest difference between the cellular S-values for the radionuclides, between PENELOPE and ETRAN, was seen for 177Lu (1.2%). There were large differences between the MIRD cellular S-values and those obtained from

  1. Low-energy electron dose-point kernel simulations using new physics models implemented in Geant4-DNA

    Energy Technology Data Exchange (ETDEWEB)

    Bordes, Julien, E-mail: julien.bordes@inserm.fr [CRCT, UMR 1037 INSERM, Université Paul Sabatier, F-31037 Toulouse (France); UMR 1037, CRCT, Université Toulouse III-Paul Sabatier, F-31037 (France); Incerti, Sébastien, E-mail: incerti@cenbg.in2p3.fr [Université de Bordeaux, CENBG, UMR 5797, F-33170 Gradignan (France); CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan (France); Lampe, Nathanael, E-mail: nathanael.lampe@gmail.com [Université de Bordeaux, CENBG, UMR 5797, F-33170 Gradignan (France); CNRS, IN2P3, CENBG, UMR 5797, F-33170 Gradignan (France); Bardiès, Manuel, E-mail: manuel.bardies@inserm.fr [CRCT, UMR 1037 INSERM, Université Paul Sabatier, F-31037 Toulouse (France); UMR 1037, CRCT, Université Toulouse III-Paul Sabatier, F-31037 (France); Bordage, Marie-Claude, E-mail: marie-claude.bordage@inserm.fr [CRCT, UMR 1037 INSERM, Université Paul Sabatier, F-31037 Toulouse (France); UMR 1037, CRCT, Université Toulouse III-Paul Sabatier, F-31037 (France)

    2017-05-01

    When low-energy electrons, such as Auger electrons, interact with liquid water, they induce highly localized ionizing energy depositions over ranges comparable to cell diameters. Monte Carlo track structure (MCTS) codes are suitable tools for performing dosimetry at this level. One of the main MCTS codes, Geant4-DNA, is equipped with only two sets of cross section models for low-energy electron interactions in liquid water (“option 2” and its improved version, “option 4”). To provide Geant4-DNA users with new alternative physics models, a set of cross sections, extracted from CPA100 MCTS code, have been added to Geant4-DNA. This new version is hereafter referred to as “Geant4-DNA-CPA100”. In this study, “Geant4-DNA-CPA100” was used to calculate low-energy electron dose-point kernels (DPKs) between 1 keV and 200 keV. Such kernels represent the radial energy deposited by an isotropic point source, a parameter that is useful for dosimetry calculations in nuclear medicine. In order to assess the influence of different physics models on DPK calculations, DPKs were calculated using the existing Geant4-DNA models (“option 2” and “option 4”), newly integrated CPA100 models, and the PENELOPE Monte Carlo code used in step-by-step mode for monoenergetic electrons. Additionally, a comparison was performed of two sets of DPKs that were simulated with “Geant4-DNA-CPA100” – the first set using Geant4′s default settings, and the second using CPA100′s original code default settings. A maximum difference of 9.4% was found between the Geant4-DNA-CPA100 and PENELOPE DPKs. Between the two Geant4-DNA existing models, slight differences, between 1 keV and 10 keV were observed. It was highlighted that the DPKs simulated with the two Geant4-DNA’s existing models were always broader than those generated with “Geant4-DNA-CPA100”. The discrepancies observed between the DPKs generated using Geant4-DNA’s existing models and “Geant4-DNA-CPA100” were

  2. Adiabatic-connection fluctuation-dissipation DFT for the structural properties of solids—The renormalized ALDA and electron gas kernels

    Energy Technology Data Exchange (ETDEWEB)

    Patrick, Christopher E., E-mail: chripa@fysik.dtu.dk; Thygesen, Kristian S., E-mail: thygesen@fysik.dtu.dk [Center for Atomic-Scale Materials Design (CAMD), Department of Physics, Technical University of Denmark, DK—2800 Kongens Lyngby (Denmark)

    2015-09-14

    We present calculations of the correlation energies of crystalline solids and isolated systems within the adiabatic-connection fluctuation-dissipation formulation of density-functional theory. We perform a quantitative comparison of a set of model exchange-correlation kernels originally derived for the homogeneous electron gas (HEG), including the recently introduced renormalized adiabatic local-density approximation (rALDA) and also kernels which (a) satisfy known exact limits of the HEG, (b) carry a frequency dependence, or (c) display a 1/k{sup 2} divergence for small wavevectors. After generalizing the kernels to inhomogeneous systems through a reciprocal-space averaging procedure, we calculate the lattice constants and bulk moduli of a test set of 10 solids consisting of tetrahedrally bonded semiconductors (C, Si, SiC), ionic compounds (MgO, LiCl, LiF), and metals (Al, Na, Cu, Pd). We also consider the atomization energy of the H{sub 2} molecule. We compare the results calculated with different kernels to those obtained from the random-phase approximation (RPA) and to experimental measurements. We demonstrate that the model kernels correct the RPA’s tendency to overestimate the magnitude of the correlation energy whilst maintaining a high-accuracy description of structural properties.

  3. Calculation of electron and isotopes dose point kernels with FLUKA Monte Carlo code for dosimetry in nuclear medicine therapy

    CERN Document Server

    Mairani, A; Valente, M; Battistoni, G; Botta, F; Pedroli, G; Ferrari, A; Cremonesi, M; Di Dia, A; Ferrari, M; Fasso, A

    2011-01-01

    Purpose: The calculation of patient-specific dose distribution can be achieved by Monte Carlo simulations or by analytical methods. In this study, FLUKA Monte Carlo code has been considered for use in nuclear medicine dosimetry. Up to now, FLUKA has mainly been dedicated to other fields, namely high energy physics, radiation protection, and hadrontherapy. When first employing a Monte Carlo code for nuclear medicine dosimetry, its results concerning electron transport at energies typical of nuclear medicine applications need to be verified. This is commonly achieved by means of calculation of a representative parameter and comparison with reference data. Dose point kernel (DPK), quantifying the energy deposition all around a point isotropic source, is often the one. Methods: FLUKA DPKS have been calculated in both water and compact bone for monoenergetic electrons (10-3 MeV) and for beta emitting isotopes commonly used for therapy ((89)Sr, (90)Y, (131)I, (153)Sm, (177)Lu, (186)Re, and (188)Re). Point isotropic...

  4. Calculation of electron and isotopes dose point kernels with FLUKA Monte Carlo code for dosimetry in nuclear medicine therapy.

    Science.gov (United States)

    Botta, F; Mairani, A; Battistoni, G; Cremonesi, M; Di Dia, A; Fassò, A; Ferrari, A; Ferrari, M; Paganelli, G; Pedroli, G; Valente, M

    2011-07-01

    The calculation of patient-specific dose distribution can be achieved by Monte Carlo simulations or by analytical methods. In this study, FLUKA Monte Carlo code has been considered for use in nuclear medicine dosimetry. Up to now, FLUKA has mainly been dedicated to other fields, namely high energy physics, radiation protection, and hadrontherapy. When first employing a Monte Carlo code for nuclear medicine dosimetry, its results concerning electron transport at energies typical of nuclear medicine applications need to be verified. This is commonly achieved by means of calculation of a representative parameter and comparison with reference data. Dose point kernel (DPK), quantifying the energy deposition all around a point isotropic source, is often the one. FLUKA DPKS have been calculated in both water and compact bone for monoenergetic electrons (10-3 MeV) and for beta emitting isotopes commonly used for therapy (89Sr, 90Y, 131I 153Sm, 177Lu, 186Re, and 188Re). Point isotropic sources have been simulated at the center of a water (bone) sphere, and deposed energy has been tallied in concentric shells. FLUKA outcomes have been compared to PENELOPE v.2008 results, calculated in this study as well. Moreover, in case of monoenergetic electrons in water, comparison with the data from the literature (ETRAN, GEANT4, MCNPX) has been done. Maximum percentage differences within 0.8.RCSDA and 0.9.RCSDA for monoenergetic electrons (RCSDA being the continuous slowing down approximation range) and within 0.8.X90 and 0.9.X90 for isotopes (X90 being the radius of the sphere in which 90% of the emitted energy is absorbed) have been computed, together with the average percentage difference within 0.9.RCSDA and 0.9.X90 for electrons and isotopes, respectively. Concerning monoenergetic electrons, within 0.8.RCSDA (where 90%-97% of the particle energy is deposed), FLUKA and PENELOPE agree mostly within 7%, except for 10 and 20 keV electrons (12% in water, 8.3% in bone). The

  5. Adiabatic-connection fluctuation-dissipation DFT for the structural properties of solids - The renormalized ALDA and electron gas kernels

    DEFF Research Database (Denmark)

    Patrick, Christopher E.; Thygesen, Kristian Sommer

    2015-01-01

    the atomization energy of the H2 molecule. We compare the results calculated with different kernels to those obtained from the random-phase approximation (RPA) and to experimental measurements. We demonstrate that the model kernels correct the RPA's tendency to overestimate the magnitude of the correlation energy...

  6. 7 CFR 984.64 - Disposition of substandard walnuts.

    Science.gov (United States)

    2010-01-01

    ....64 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE WALNUTS... merchantable walnuts and with proper safeguards to prevent such walnuts from thereafter entering channels of...

  7. Genotype and year variability of the chemical composition of walnut oil of Moroccan seedlings from the high Atlas Mountains

    Energy Technology Data Exchange (ETDEWEB)

    Kodad, O.; EstopaNan, G.; Juan, T.; Socias i Company, R.; Sindic, M.

    2016-07-01

    Protein and oil content, fatty acid composition and tocopherol concentration were determined for two years in the kernel of ten candidate walnut selections from the high Atlas Mountains in Morocco. Considerable variation between genotypes was found for all parameters. The ranges of protein content (11.58–14.5% of kernel dry weight, DW), oil content (54.4–67.48% of kernel DW), oleic (12.47–22.01% of total oil), linoleic (55.03–60.01%), linolenic (9.3–15.87%), palmitic (6.84–9.12%), and stearic (1.7–2.92%) acid percentages, ?-tocopherol (188.1–230.7 mg·kg-1 of oil), d-tocopherol (23.3–43.4 mg·kg-1), and a-tocopherol (8.9–16.57 mg·kg-1) contents agreed with previous results obtained from other commercial walnut cultivars. The effect of year was significant for all the chemical components, except for oil content and palmitic acid percentage. Some genotypes showed high oil contents and consistently high values of ?-tocopherol in both years of study. The introduction of these genotypes as new cultivars by vegetative propagation may result in a an increase in quality of the walnuts from the high Atlas Mountains of Morocco, and as a seed source for forest walnut propagation in the same region. (Author)

  8. The localization-delocalization matrix and the electron-density-weighted connectivity matrix of a finite graphene nanoribbon reconstructed from kernel fragments.

    Science.gov (United States)

    Timm, Matthew J; Matta, Chérif F; Massa, Lou; Huang, Lulu

    2014-11-26

    Bader's quantum theory of atoms in molecules (QTAIM) and chemical graph theory, merged in the localization-delocalization matrices (LDMs) and the electron-density-weighted connectivity matrices (EDWCM), are shown to benefit in computational speed from the kernel energy method (KEM). The LDM and EDWCM quantum chemical graph matrices of a 66-atom C46H20 hydrogen-terminated armchair graphene nanoribbon, in 14 (2×7) rings of C2v symmetry, are accurately reconstructed from kernel fragments. (This includes the full sets of electron densities at 84 bond critical points and 19 ring critical points, and the full sets of 66 localization and 4290 delocalization indices (LIs and DIs).) The average absolute deviations between KEM and directly calculated atomic electron populations, obtained from the sum of the LIs and half of the DIs of an atom, are 0.0012 ± 0.0018 e(-) (∼0.02 ± 0.03%) for carbon atoms and 0.0007 ± 0.0003 e(-) (∼0.01 ± 0.01%) for hydrogen atoms. The integration errors in the total electron population (296 electrons) are +0.0003 e(-) for the direct calculation (+0.0001%) and +0.0022 e(-) for KEM (+0.0007%). The accuracy of the KEM matrix elements is, thus, probably of the order of magnitude of the combined precision of the electronic structure calculation and the atomic integrations. KEM appears capable of delivering not only the total energies with chemical accuracy (which is well documented) but also local and nonlocal properties accurately, including the DIs between the fragments (crossing fragmentation lines). Matrices of the intact ribbon, the kernels, the KEM-reconstructed ribbon, and errors are available as Supporting Information .

  9. COMPUTATIONAL EFFICIENCY OF A MODIFIED SCATTERING KERNEL FOR FULL-COUPLED PHOTON-ELECTRON TRANSPORT PARALLEL COMPUTING WITH UNSTRUCTURED TETRAHEDRAL MESHES

    Directory of Open Access Journals (Sweden)

    JONG WOON KIM

    2014-04-01

    In this paper, we introduce a modified scattering kernel approach to avoid the unnecessarily repeated calculations involved with the scattering source calculation, and used it with parallel computing to effectively reduce the computation time. Its computational efficiency was tested for three-dimensional full-coupled photon-electron transport problems using our computer program which solves the multi-group discrete ordinates transport equation by using the discontinuous finite element method with unstructured tetrahedral meshes for complicated geometrical problems. The numerical tests show that we can improve speed up to 17∼42 times for the elapsed time per iteration using the modified scattering kernel, not only in the single CPU calculation but also in the parallel computing with several CPUs.

  10. Walnut tissue culture: research and field applications

    Science.gov (United States)

    2004-01-01

    Vitrotech Biotecnologia Vegetal began researching propagating Juglans regia (English walnut) and various Juglans hybrids by tissue culture in 1993 and has operated on a commercial scale since 1996. Since this time, more than one and a half million walnuts of different species have been propagated and field planted. Tissue cultured...

  11. Genetic diversity based on morphological traits in walnut (Juglans regia L.) landraces from Karakoram region-I

    International Nuclear Information System (INIS)

    Hussain, I.; Sultan, A.; Shinwari, Z. K.

    2016-01-01

    Walnut is one of the most important nutritive nut crops and widely grown in Gilgit-Baltistan region of Pakistan. In the present study 19 local landraces were analyzed for morphological traits to investigate genetic diversity and identify promising landraces for cultivar development. Multivariate analyses showed high variation for morphological traits and nut and kernel characteristics. Cluster analyses depicted diversity among the local land races which separated them into 2 major clusters groups, showing more association to morphological differences. PCA revealed that the 1st four principal components (PCs) possessed Eigen value >1.0, where PC1 and PC2 contributed total variance of 41.65 percent and 23.42 percent respectively with total variance (65.05 percent) showing maximum factor loadings by kernel ratio, shell percent, kernel yield and nut width by the first two PCs. Pearson correlation coefficient among walnut landraces revealed positively significant correlation between shell yield and nut weight(r=0.96), kernel yield and nut width(r=0.85), whereas negative correlation were observed (r = -0.89 and r = -0.76) between kernel ratio with shell yield and nut weight respectively. A wide range of diversity was observed among the local landraces from Karakoram regions and the landrace HKK and GNAG were reported as promising one with highest kernel ratio. These landraces are potential for future breeding of nut crops with distinct morphological traits. (author)

  12. Electron-beam irradiation effects on phytochemical constituents and antioxidant capacity of pecan kernels [ Carya illinoinensis (Wangenh.) K. Koch] during storage.

    Science.gov (United States)

    Villarreal-Lozoya, Jose E; Lombardini, Leonardo; Cisneros-Zevallos, Luis

    2009-11-25

    Pecans kernels (Kanza and Desirable cultivars) were irradiated with 0, 1.5, and 3.0 kGy using electron-beam (E-beam) irradiation and stored under accelerated conditions [40 degrees C and 55-60% relative humidity (RH)] for 134 days. Antioxidant capacity (AC) using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays, phenolic (TP) and condensed tannin (CT) content, high-performance liquid chromatography (HPLC) phenolic profile, tocopherol content, peroxide value (PV), and fatty acid profiles were determined during storage. Irradiation decreased TP and CT with no major detrimental effects in AC. Phenolic profiles after hydrolysis were similar among treatments (e.g., gallic and ellagic acid, catechin, and epicatechin). Tocopherol content decreased with irradiation (>21 days), and PV increased at later stages (>55 days), with no change in fatty acid composition among treatments. Color lightness decreased, and a reddish brown hue developed during storage. A proposed mechanism of kernel oxidation is presented, describing the events taking place. In general, E-beam irradiation had slight effects on phytochemical constituents and could be considered a potential tool for pecan kernel decontamination.

  13. Sensory Quality Preservation of Coated Walnuts.

    Science.gov (United States)

    Grosso, Antonella L; Asensio, Claudia M; Grosso, Nelson R; Nepote, Valeria

    2017-01-01

    The objective of this study was to evaluate the sensory stability of coated walnuts during storage. Four walnut samples were prepared: uncoated (NC), and samples coated with carboxymethyl cellulose (NCMC), methyl cellulose (NMC), or whey protein (NPS). The samples were stored at room temperature for 210 d and were periodically removed from storage to perform a sensory descriptive analysis. A consumer acceptance test was carried out on the fresh product (storage day 0) to evaluate flavor. All samples exhibited significant differences in their sensory attributes initially and after storage. Intensity ratings for oxidized and cardboard flavors increased during storage. NC showed the highest oxidized and cardboard intensity ratings (39 and 22, respectively) and NMC exhibited the lowest intensity ratings for these negative attributes (8 and 17, respectively) after 210 d of storage. Alternatively, the intensity ratings for sweetness and walnut flavors were decreased for all samples. NMC had the lowest decrease at the end of storage for these positive attributes (75.86 in walnut flavor and 12.09 in sweetness). The results of this study suggest a protective effect of the use of an edible coating to preserve sensory attributes during storage, especially for samples coated with MC. The results of the acceptance test showed that addition of the coating negatively affected the flavor acceptance for NMC and NCMC coated walnuts. Edible coatings help to preserve sensory attributes in walnuts, improving their shelf-life, however, these coatings may affect consumer acceptance in some cases. © 2016 Institute of Food Technologists®.

  14. Study on the Ingredient Proportions and After-Treatment of Laser Sintering Walnut Shell Composites

    Directory of Open Access Journals (Sweden)

    Yueqiang Yu

    2017-12-01

    Full Text Available To alleviate resource shortage, reduce the cost of materials consumption and the pollution of agricultural and forestry waste, walnut shell composites (WSPC consisting of walnut shell as additive and copolyester hot melt adhesive (Co-PES as binder was developed as the feedstock of selective laser sintering (SLS. WSPC parts with different ingredient proportions were fabricated by SLS and processed through after-treatment technology. The density, mechanical properties and surface quality of WSPC parts before and after post processing were analyzed via formula method, mechanical test and scanning electron microscopy (SEM, respectively. Results show that, when the volume fraction of the walnut shell powder in the WSPC reaches the maximum (40%, sintered WSPC parts have the smallest warping deformation and the highest dimension precision, although the surface quality, density, and mechanical properties are low. However, performing permeating resin as the after-treatment technology could considerably increase the tensile, bending and impact strength by 496%, 464%, and 516%, respectively.

  15. An efficient method for evaluating black walnut for resistance to walnut anthracnose in filed plots and the identification of resistant genotypes

    Science.gov (United States)

    K.E. Woeste; W.F. Beineke

    2001-01-01

    Black walnut is native to the eastern USA and prized for its high-quality timber. Walnut anthracnose, the most important foliar disease of black walnut, is caused by Gnomonia leptostyla. There is no germplasm available that is resistant to the disease. Ramets of 42 black walnut clones, comprising about one-third of the Midwestern USA black walnut...

  16. Genetic evaluation of domestic walnut cultivars trading on Korean ...

    African Journals Online (AJOL)

    Walnut (Juglans regia L.) is regarded as a healthy food because of its high nutritional composition and various health benefits. Although several walnut cultivars are being actively traded for domestic plantation or ornament in Korea, no particular effort has been made to evaluate genetic quality management of walnut ...

  17. Pecan walnut (Carya illinoinensis (Wangenh.) K. Koch) oil quality and phenolic compounds as affected by microwave and conventional roasting.

    Science.gov (United States)

    Juhaimi, Fahad Al; Özcan, Mehmet Musa; Uslu, Nurhan; Doğu, Süleyman

    2017-12-01

    In this study, the effects of conventional and microwave roasting on phenolic compounds, free acidity, peroxide value, fatty acid composition and tocopherol content of pecan walnut kernel and oil was investigated. The oil content of pecan kernels was 73.78% for microwave oven roasted at 720 W and 73.56% for conventional oven roasted at 110 °C. The highest free fatty acid content (0.50%) and the lowest peroxide value (2.48 meq O 2 /kg) were observed during microwave roasting at 720 W. The fatty acid profiles and tocopherol contents of pecan kernel oils did not show significant differences compared to raw samples. Roasting process in microwave oven at 720 W caused the reduction of some phenolic compounds, while the content of gallic acid exhibited a significant increase.

  18. Diagnosis, characterization and management of food allergy : a tough (wal)nut to crack

    NARCIS (Netherlands)

    Blankestijn, M.A.

    2017-01-01

    Walnut (Juglans regia) is a known food allergen, able to elicit potentially severe allergic reactions. Threshold data from walnut challenged and allergic adults demonstrated that walnut is a potent allergen, with eliciting doses similar to hazelnut. Walnut 2S albumin Jug r 1 was the dominant walnut

  19. Absorbed dose evaluation of Auger electron-emitting radionuclides: impact of input decay spectra on dose point kernels and S-values.

    Science.gov (United States)

    Falzone, Nadia; Lee, Boon Q; Fernández-Varea, José M; Kartsonaki, Christiana; Stuchbery, Andrew E; Kibédi, Tibor; Vallis, Katherine A

    2017-03-21

    The aim of this study was to investigate the impact of decay data provided by the newly developed stochastic atomic relaxation model BrIccEmis on dose point kernels (DPKs - radial dose distribution around a unit point source) and S-values (absorbed dose per unit cumulated activity) of 14 Auger electron (AE) emitting radionuclides, namely 67 Ga, 80m Br, 89 Zr, 90 Nb, 99m Tc, 111 In, 117m Sn, 119 Sb, 123 I, 124 I, 125 I, 135 La, 195m Pt and 201 Tl. Radiation spectra were based on the nuclear decay data from the medical internal radiation dose (MIRD) RADTABS program and the BrIccEmis code, assuming both an isolated-atom and condensed-phase approach. DPKs were simulated with the PENELOPE Monte Carlo (MC) code using event-by-event electron and photon transport. S-values for concentric spherical cells of various sizes were derived from these DPKs using appropriate geometric reduction factors. The number of Auger and Coster-Kronig (CK) electrons and x-ray photons released per nuclear decay (yield) from MIRD-RADTABS were consistently higher than those calculated using BrIccEmis. DPKs for the electron spectra from BrIccEmis were considerably different from MIRD-RADTABS in the first few hundred nanometres from a point source where most of the Auger electrons are stopped. S-values were, however, not significantly impacted as the differences in DPKs in the sub-micrometre dimension were quickly diminished in larger dimensions. Overestimation in the total AE energy output by MIRD-RADTABS leads to higher predicted energy deposition by AE emitting radionuclides, especially in the immediate vicinity of the decaying radionuclides. This should be taken into account when MIRD-RADTABS data are used to simulate biological damage at nanoscale dimensions.

  20. Heartwood formation in four black walnut plantations

    Science.gov (United States)

    Keith Woeste; Brian Beheler

    2003-01-01

    The amount of heartwood in black walnut (Juglans nigra L.) logs can vary widely, even among trees of the same age growing at the same location. There is little published data on the genetics, physiology, and development of heartwood in hardwoods, even though the volume of heartwood in a log can significantly influence its value.

  1. Collaborative monitoring in Walnut Creek, California

    Science.gov (United States)

    Heidi Ballard; Ralph Kraetsch; Lynn Huntsinger

    2002-01-01

    In 1995 and 2000, a monitoring program was designed and implemented to track oak regeneration and native grass populations in target management areas in the four Open Space Preserves of the City of Walnut Creek, California. The program resulted from a collaboration of scientists at the University of California, Berkeley, a group of interested citizens known as the...

  2. Evaluation of the new electron-transport algorithm in MCNP6.1 for the simulation of dose point kernel in water

    Science.gov (United States)

    Antoni, Rodolphe; Bourgois, Laurent

    2017-12-01

    In this work, the calculation of specific dose distribution in water is evaluated in MCNP6.1 with the regular condensed history algorithm the "detailed electron energy-loss straggling logic" and the new electrons transport algorithm proposed the "single event algorithm". Dose Point Kernel (DPK) is calculated with monoenergetic electrons of 50, 100, 500, 1000 and 3000 keV for different scoring cells dimensions. A comparison between MCNP6 results and well-validated codes for electron-dosimetry, i.e., EGSnrc or Penelope, is performed. When the detailed electron energy-loss straggling logic is used with default setting (down to the cut-off energy 1 keV), we infer that the depth of the dose peak increases with decreasing thickness of the scoring cell, largely due to combined step-size and boundary crossing artifacts. This finding is less prominent for 500 keV, 1 MeV and 3 MeV dose profile. With an appropriate number of sub-steps (ESTEP value in MCNP6), the dose-peak shift is almost complete absent to 50 keV and 100 keV electrons. However, the dose-peak is more prominent compared to EGSnrc and the absorbed dose tends to be underestimated at greater depths, meaning that boundaries crossing artifact are still occurring while step-size artifacts are greatly reduced. When the single-event mode is used for the whole transport, we observe the good agreement of reference and calculated profile for 50 and 100 keV electrons. Remaining artifacts are fully vanished, showing a possible transport treatment for energies less than a hundred of keV and accordance with reference for whatever scoring cell dimension, even if the single event method initially intended to support electron transport at energies below 1 keV. Conversely, results for 500 keV, 1 MeV and 3 MeV undergo a dramatic discrepancy with reference curves. These poor results and so the current unreliability of the method is for a part due to inappropriate elastic cross section treatment from the ENDF/B-VI.8 library in those

  3. Effects of walnuts (Juglans regia) on learning and memory functions.

    Science.gov (United States)

    Haider, Saida; Batool, Zehra; Tabassum, Saiqa; Perveen, Tahira; Saleem, Sadia; Naqvi, Fizza; Javed, Huma; Haleem, Darakhshan J

    2011-11-01

    Walnut has been regarded as a health food that is delicious and nutritious. Both preventive and therapeutic effects of walnut are well documented. Walnuts are rich in omega-3 fatty acids that are reported to have beneficial effects on brain function. The present work was designed to evaluate the effects of walnuts on learning and memory in male rats. The effect of oral intake of walnut was also monitored on food intake. Walnut was given orally to rats for a period of 28 days. Memory function in rats was assessed by elevated plus maze (EPM) and radial arm maze (RAM). A significant improvement in learning and memory of walnut treated rats compared to controls was observed. Walnut treated rats also exhibited a significant decrease in food intake while the change in growth rate (in terms of percentage) remained comparable between the two groups. Analysis of brain monoamines exhibited enhanced serotonergic levels in rat brain following oral intake of walnuts. The findings suggest that walnut may exert its hypophagic and nootropic actions via an enhancement of brain 5-HT metabolism.

  4. Synthesis of Monodisperse Walnut-Like SnO2 Spheres and Their Photocatalytic Performances

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2015-01-01

    Full Text Available Novel walnut-like SnO2 spheres have been synthesized using a one-step hydrothermal reaction with SnCl2·2H2O and KOH as raw materials. The morphology, microstructure, and optical properties of the products were characterized by X-ray powder diffraction (XRD, Raman spectrum, scanning electron microscopy (SEM, transmission electron microscopy (TEM, selected area electron diffraction (SAED, and ultraviolet-visible (UV-Vis absorption spectroscopy. The detailed studies revealed that these synthesized spheres are highly monodisperse and have a uniform size of approximately 250 nm. Photocatalytic activity of the prepared SnO2 spheres was evaluated by the degradation of methylene orange. The synthesized SnO2 spheres exhibited excellent photocatalytic degradation. In addition, a possible formation mechanism of the walnut-like nanostructures was proposed based on reaction time-dependent experiments.

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

    OpenAIRE

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

    2016-01-01

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

  6. Approximate kernel competitive learning.

    Science.gov (United States)

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

    2015-03-01

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

  7. A laser optical method for detecting corn kernel defects

    Energy Technology Data Exchange (ETDEWEB)

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

    1984-01-01

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

  8. Walnut shells: replacement for natural gas

    Energy Technology Data Exchange (ETDEWEB)

    Goss, J R; Williams, R O

    1977-11-01

    A method of extracting useful energy from cracked walnut shells has been developed by the University of California in co-operation with Diamond/Sunsweet, Inc., and the California Energy Resources Conservation and Development Commission. The technique involves converting the shells to producer gas, a low-Btu gas in which the major combustible components are carbon monoxide (20 to 30%) and hydrogen (10 to 15%).

  9. Phenol metabolism and preservation of fresh in-hull walnut stored in modified atmosphere packaging.

    Science.gov (United States)

    Wang, Jin; Li, Pan; Gong, Bi; Li, Shuying; Ma, Huiling

    2017-12-01

    The effects of modified atmosphere packaging (MAP) on phenol metabolism and preservation of fresh in-hull walnuts have been investigated. Fruit was packaged under MAP1 (film thickness, 30 μm), MAP2 (45 μm) and MAP3 (50 μm) and stored at -0.5 to 1.0 °C for up to 60 days. Firmness, soluble solid concentration, total phenols, total flavonoids and total antioxidant activity of the green hull were maintained at higher levels under the MAP conditions, whereas decay incidence was lower compared to the control during storage. Green hull of fruit under MAP conditions contained lower polyphenol oxidase activity than the control and the peroxidase activity was at a similar level to the control after 18 days. Phenylalanine ammonialyase activity was enhanced by MAP conditions, with two peaks on days 18 and 36. Until day 60, the peroxide value and acid value of kernel oils under MAP conditions were lower than that of the control. The MAP3 treatment was most effective for maintaining kernel quality. The protective role of MAP conditions on phenolic contents in green hull may contribute to the mitigation of decay and the maintenance of kernel quality. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  10. Optimized Kernel Entropy Components.

    Science.gov (United States)

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

    2017-06-01

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

  11. Subsampling Realised Kernels

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  12. Assessment of the microbiological safety of edible roasted nut kernels on retail sale in England, with a focus on Salmonella.

    Science.gov (United States)

    Little, C L; Jemmott, W; Surman-Lee, S; Hucklesby, L; de Pinnal, E

    2009-04-01

    There is little published information on the prevalence of Salmonella in edible nut kernels. A study in early 2008 of edible roasted nut kernels on retail sale in England was undertaken to assess the microbiological safety of this product. A total of 727 nut kernel samples of different varieties were examined. Overall, Salmonella and Escherichia coli were detected from 0.2 and 0.4% of edible roasted nut kernels. Of the nut varieties examined, Salmonella Havana was detected from 1 (4.0%) sample of pistachio nuts, indicating a risk to health. The United Kingdom Food Standards Agency was immediately informed, and full investigations were undertaken. Further examination established the contamination to be associated with the pistachio kernels and not the partly opened shells. Salmonella was not detected in other varieties tested (almonds, Brazils, cashews, hazelnuts, macadamia, peanuts, pecans, pine nuts, and walnuts). E. coli was found at low levels (range of 3.6 to 4/g) in walnuts (1.4%), almonds (1.2%), and Brazils (0.5%). The presence of Salmonella is unacceptable in edible nut kernels. Prevention of microbial contamination in these products lies in the application of good agricultural, manufacturing, and storage practices together with a hazard analysis and critical control points system that encompass all stages of production, processing, and distribution.

  13. Genetic evaluation of domestic walnut cultivars trading on Korean ...

    African Journals Online (AJOL)

    Yomi

    2012-04-10

    Apr 10, 2012 ... Walnut (Juglans regia L.) is regarded as a healthy food because of its high nutritional composition and various health benefits. Although several walnut cultivars are being actively traded for domestic plantation or ornament in Korea, no particular effort has been made to evaluate genetic quality.

  14. Current research in Spain on walnut for wood production

    Science.gov (United States)

    Neus Alet& #224; Neus NO-VALUE

    2004-01-01

    The Department of Mediterranean Trees at the Institut de Recerca i Tecnologia Agroalimentaries (IRTA) in Spain initiated a research program in 1993 to examine the variability among walnut species for wood production and to establish orchards with improved selections. The main objective of the programme is to obtain superior Persian walnut (Juglans regia...

  15. Regeneration systems for pyramiding disease resistance into walnut rootstocks

    Science.gov (United States)

    This study was conducted to regenerate selected walnut rootstocks adventitiously. This is an essential step to be able to produce transgenic walnut rootstocks with superior traits, such as disease resistance. A series of plant tissue culture experiments were conducted on RX1 and VX211 rootstocks wit...

  16. 78 FR 57101 - Walnuts Grown in California; Increased Assessment Rate

    Science.gov (United States)

    2013-09-17

    ... rate currently in effect. The quantity of assessable walnuts for the 2013-14 marketing year is... DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 984 [Doc. No. AMS-FV-13-0056; FV13-984-1 PR] Walnuts Grown in California; Increased Assessment Rate AGENCY: Agricultural Marketing...

  17. 75 FR 55944 - Walnuts Grown in California; Decreased Assessment Rate

    Science.gov (United States)

    2010-09-15

    ... Reform. Under the marketing order now in effect, California walnut handlers are subject to assessments... assessment rate currently in effect. The quantity of assessable walnuts for the 2010-11 marketing year is... DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 984 [Doc. No. AMS-FV-10-0060...

  18. 76 FR 67320 - Walnuts Grown in California; Increased Assessment Rate

    Science.gov (United States)

    2011-11-01

    ... Justice Reform. Under the marketing order now in effect, California walnut handlers are subject to... DEPARTMENT OF AGRICULTURE Agricultural Marketing Service 7 CFR Part 984 [Doc. No. AMS-FV-11-0062; FV11-984-1 FR] Walnuts Grown in California; Increased Assessment Rate AGENCY: Agricultural Marketing...

  19. The dynamics of fat, protein and sugar metabolism during walnut ...

    African Journals Online (AJOL)

    The result shows that the developmental process of walnut fruit could be divided into four stages: Slow growth {within 30 days after florescence, (DAF)}, fast growth (30 to 60 DAF), fat accumulation (60 to 100 DAF) and fruit maturity (100 to 140 DAF). Fat content in walnut fruit increased continuously and the maximum ...

  20. Red oak and black walnut growth increased with minesoil ripping

    International Nuclear Information System (INIS)

    Ashby, W.C.

    1996-01-01

    Red oak, black walnut, and black walnut with autumn olive, a 'nitrogen-fixing' shrub, were planted on graded, compacted cast overburden (topsoil substitute) coal mining minesoil with a dense ground cover consisting chiefly of all fescue grass. Compaction was mitigated by ripping on half the plots. Year 1 establishment of all species was equal or lower on the graded versus graded/ripped plots. After 12 years red oak survival was 9% where unripped versus 61% where ripped. Black walnut survival was respectively 41% and 74%. Red oak 12-year heights were 2.2 m on the graded and 4.5 m on the graded/ripped plots. Black walnut heights averaged 2.6 m and 5.5 m respectively. Diameter breast height similarly was greater with ripping for the oak and walnut. Deer damage was substantially greater on the red oak than on the black walnut trees. Black walnut was interplanted a year later with autumn olive on unripped and ripped graded minesoils. After 12 years survival of black walnut interplanted with autumn olive was 42% where unripped and 85% in two ripped plots. Corresponding heights averaged 3.8 m where graded and 5.7 to 6.4 m where graded/ripped. 16 refs., 1 fig., 4 tabs

  1. Susceptibility of walnut and hickory species to Geosmithia morbida

    Science.gov (United States)

    Curtis Utley; Tivonne Nguyen; Tatiana Roubtsova; Mark Coggeshall; Tim M. Ford; L.J. Grauke; Andrew D. Graves; Charles A. Leslie; James McKenna; Keith Woeste; Mohammad A. Yaghmour; Steve Seybold; Richard M. Bostock; Ned. Tisserat

    2013-01-01

    Thousand cankers disease (TCD) of walnut is a result of feeding in the phloem by the walnut twig beetle (WTB), Pityophthorus juglandis, and subsequent canker formation caused by Geosmithia morbida around galleries. TCD has caused extensive morbidity and mortality to Juglans nigra in the western United States and, in 2010, was...

  2. 75 FR 34950 - Walnuts Grown in California; Changes to the Quality Regulations for Shelled Walnuts

    Science.gov (United States)

    2010-06-21

    ... customers that those products were derived from walnuts that meet quality standards under the order. The... process by eliminating the need for multiple inspections for the same product, and would improve handler... the size must be noted on the inspection certificate. The end product quality must be equal to or...

  3. Influence of foliar fertilization on walnut foliar zinc levels and nut production in black walnut

    Science.gov (United States)

    William R. Reid; Andrew L. Thomas

    2013-01-01

    The impact of foliar zinc fertilizer application on nut-bearing black walnut (Juglans nigra L.) trees was studied. Foliar sprays were applied three times per season on two cultivars during four growing seasons by wetting the foliage of the entire crown using a tank mix containing 500 ppm zinc, starting at leaf burst and continuing at 2 week intervals...

  4. Phylogeography of the walnut twig beetle, Pityophthorus juglandis, the vector of thousand cankers disease in North American walnut trees

    Science.gov (United States)

    Paul F. Rugman-Jones; Steven J. Seybold; Andrew D. Graves; Richard. Stouthamer

    2015-01-01

    Thousand cankers disease (TCD) of walnut trees (Juglans spp.) results from aggressive feeding in the phloem by the walnut twig beetle (WTB), Pityophthorus juglandis, accompanied by inoculation of its galleries with a pathogenic fungus, Geosmithia morbida. In 1960, WTB was only known from four U.S. counties...

  5. 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`.

  6. Walnut and almond oil screw-press extraction at industrial scale: Effects of process parameters on oil yield and quality

    Directory of Open Access Journals (Sweden)

    M. L. Martínez

    2018-01-01

    Full Text Available Walnut and almond kernels are highly nutritious mainly due to their high oil contents. In this study, 32 factorial experimental designs were used to optimize processes for oil extraction by screw-pressing at industrial scale. Experimental designs included seed moisture content (SMC, and restriction die (RD as the main processing parameters. Theoretical models were scanned against experimental data in order to optimize oil extraction conditions. The response variables analyzed were oil yield (OY, fine solid content (FC in oil, and oil quality parameters. Fitted models for OY indicated maximum predicted values similar to the highest experimental values. Walnut oil extractions showed a maximum OY (84.5 ± 2.3 % at 7.21% SMC, and 10 mm RD. For almond kernels, maximum OY (71.9 ± 3.5% was obtained at 9.42% SMC, and 12 mm RD. Chemical quality parameters from both oils were in the ranges stated in Codex (FAO/WHO standards for virgin (non-refined oils.

  7. Walnut and almond oil screw-press extraction at industrial scale: Effects of process parameters on oil yield and quality

    International Nuclear Information System (INIS)

    Martínez, M. L.; Bordón, M.G.; Bodoira, R. M.; Penci, M.C.; Ribotta, P.D.; Maestri, D.M.

    2017-01-01

    Walnut and almond kernels are highly nutritious mainly due to their high oil contents. In this study, 32 factorial experimental designs were used to optimize processes for oil extraction by screw-pressing at industrial scale. Experimental designs included seed moisture content (SMC), and restriction die (RD) as the main processing parameters. Theoretical models were scanned against experimental data in order to optimize oil extraction conditions. The response variables analyzed were oil yield (OY), fine solid content (FC) in oil, and oil quality parameters. Fitted models for OY indicated maximum predicted values similar to the highest experimental values. Walnut oil extractions showed a maximum OY (84.5 ± 2.3 %) at 7.21% SMC, and 10 mm RD. For almond kernels, maximum OY (71.9 ± 3.5%) was obtained at 9.42% SMC, and 12 mm RD. Chemical quality parameters from both oils were in the ranges stated in Codex (FAO/WHO) standards for virgin (non-refined) oils. [es

  8. Classification With Truncated Distance Kernel.

    Science.gov (United States)

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

    2018-05-01

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

  9. Monitoring guidelines improve control of walnut husk fly in California

    International Nuclear Information System (INIS)

    Opp, Susan B.; Reynolds, Katherine M.; Pickel, Carolyn; Olson, William

    2000-01-01

    The walnut husk fly (WHF), Rhagoletis completa Cresson, is a key pest of walnuts (Juglans spp.) in California, where over 95% of the US and approximately two-thirds of the world's commercial walnuts are produced. The primary hosts of this monophagous fruit fly are J. regia L. (commercially grown English walnut), J. californica S. Wats. var. hindsii (northern California black walnut), J. californica var. californica (southern California black walnut) and J. nigra Thunb. (eastern black walnut). Some cultivars of the English walnut are more susceptible than others; the most heavily infested varieties of English walnut include Eureka, Franquette, Hartley, Mayette and Payne. Neither English walnuts nor the walnut husk fly are native to California. So-called 'English' walnuts are sometimes more appropriately called 'Persian' walnuts, in reference to Persia, the origin of J. regia. English walnuts were first planted in southern California in the 1860s. In contrast, the native range of WHF is the mid- and south-central United States where it attacks J. nigra (Boyce 1934). The fly was likely to have been introduced into southern California in the mid-1920s by tourists travelling from Kansas, New Mexico, Texas or Oklahoma. WHF was first documented in California in 1926 in the San Bernardino County when maggots were found in the husks of English walnuts (Boyce 1929). The fly gradually spread throughout walnut growing regions of California. In 1928, only three or four orchards in the San Bernardino County were known to be infested. By 1932, the fly was also found in the Los Angeles and Orange Counties (Boyce 1933), and by 1954, it was found in Ventura, Riverside, and the San Diego Counties, in addition to the northern California county of Sonoma (Anonymous 1966). The spread of the fly in northern California was rapid. By 1958, WHF was found in San Joaquin County; in 1963, the fly was in Amador, Lake, Solano, Tulare and Yolo Counties; in 1964, it was found in Fresno, Mendocino

  10. Storage quality of walnut oil containing lycopene during accelerated oxidation.

    Science.gov (United States)

    Xie, Chaonan; Ma, Zheng Feei; Li, Fang; Zhang, Hongxia; Kong, Lingming; Yang, Zhipan; Xie, Weifeng

    2018-04-01

    The purpose of investigation was to assess the effect of lycopene on the peroxide value, acid value, fatty acids, total phenolic content and ferric-reducing antioxidant power of walnut oil. Walnut oil was extracted from Xinjiang walnut variety using cold pressing method. Our study reported that after 45 days of accelerated oxidation at 60 °C (Schaal oven test), 0.005% lycopene exhibited the greatest antioxidant effect than other addition levels of lycopene. Therefore, under ambient storage conditions, the shelf-life of walnut oil could be extended up to 16 months by 0.005% lycopene. Moreover, 0.005% lycopene added to walnut oil had a significantly higher content of saturated fatty acid, unsaturated fatty acid, total phenol, reducing ability of the polar and non-polar components than the blank sample (walnut oil without any addition of lycopene). In conclusion, lycopene improved the quality of walnut oil because of its antioxidant effect against lipid oxidation.

  11. 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

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

    OpenAIRE

    Muñoz, Alberto; González, Javier

    2008-01-01

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

  13. 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

  14. Plant-water relationships and growth of black walnut in a walnut-forage multicropping regime

    Science.gov (United States)

    Daniel C. Dey; M. R. Conway; H. E. Garrett; T. S. Hinckley; G. S. Cox

    1987-01-01

    Eastern black walnut seedlings were planted on a 1.5 ? 1.5m spacing in the spring of 1976 and irrigated throughout the growing season. During the spring of 1977, forage plots consisting of Kentucky 31 tall fescue, orchard grass, or Kobe lespedeza measuring 1 m wide and 10.2 m long and centered on a row of trees, were established with and without irrigation. Soil-water...

  15. Evaluating Non-Linear Regression Models in Analysis of Persian Walnut Fruit Growth

    Directory of Open Access Journals (Sweden)

    I. Karamatlou

    2016-02-01

    Full Text Available Introduction: Persian walnut (Juglans regia L. is a large, wind-pollinated, monoecious, dichogamous, long lived, perennial tree cultivated for its high quality wood and nuts throughout the temperate regions of the world. Growth model methodology has been widely used in the modeling of plant growth. Mathematical models are important tools to study the plant growth and agricultural systems. These models can be applied for decision-making anddesigning management procedures in horticulture. Through growth analysis, planning for planting systems, fertilization, pruning operations, harvest time as well as obtaining economical yield can be more accessible.Non-linear models are more difficult to specify and estimate than linear models. This research was aimed to studynon-linear regression models based on data obtained from fruit weight, length and width. Selecting the best models which explain that fruit inherent growth pattern of Persian walnut was a further goal of this study. Materials and Methods: The experimental material comprising 14 Persian walnut genotypes propagated by seed collected from a walnut orchard in Golestan province, Minoudasht region, Iran, at latitude 37◦04’N; longitude 55◦32’E; altitude 1060 m, in a silt loam soil type. These genotypes were selected as a representative sampling of the many walnut genotypes available throughout the Northeastern Iran. The age range of walnut trees was 30 to 50 years. The annual mean temperature at the location is16.3◦C, with annual mean rainfall of 690 mm.The data used here is the average of walnut fresh fruit and measured withgram/millimeter/day in2011.According to the data distribution pattern, several equations have been proposed to describesigmoidal growth patterns. Here, we used double-sigmoid and logistic–monomolecular models to evaluate fruit growth based on fruit weight and4different regression models in cluding Richards, Gompertz, Logistic and Exponential growth for evaluation

  16. Acute Consumption of Walnuts and Walnut Components Differentially Affect Postprandial Lipemia, Endothelial Function, Oxidative Stress, and Cholesterol Efflux in Humans with Mild Hypercholesterolemia.

    Science.gov (United States)

    Walnut consumption improves cardiovascular disease risk; however, to our knowledge, the contribution of individual walnut components has not been assessed. This study evaluated the acute consumption of whole walnuts (85 g), separated nut skins (5.6 g), de-fatted nutmeat (34 g), and nut oil (51 g) on...

  17. Decision making analysis of walnut seedling production on a small ...

    African Journals Online (AJOL)

    Yomi

    2011-12-21

    Dec 21, 2011 ... Walnut production does not constitute considerable share in this region. .... average farm's historical selling prices for the 2003-2008 period. The prices ... material costs, depreciation costs and insurance premium. Then, the ...

  18. Incidence of Escherichia coli in black walnut meats.

    Science.gov (United States)

    Meyer, M T; Vaughn, R H

    1969-11-01

    Examination of commercially shelled black walnut meats showed inconsistent numbers of total aerobic bacteria, coliforms, and Escherichia coli; variation occurred among different meat sizes and within each meat size. The incidence of E. coli on meats of commercially hulled black walnuts depended on the physical condition of the nuts. Apparently tightly sealed ones contained only a few or none, whereas those with visibly separated sutures and spoiled meats yielded the most. This contamination was in part correlated to a hulling operation. Large numbers of E. coli on the husk of the walnuts contaminated the hulling water, subsequently also contaminating the meats by way of separated sutures. Chlorination of the hulling wash water was ineffective. Attempts were made to decontaminate the walnut meats without subsequent deleterious changes in flavor or texture. A treatment in coconut oil at 100 C followed by removal of excess surface oil by centrifugation was best.

  19. Allelopathic activity and chemical constituents of walnut (Juglans regia) leaf litter in walnut-winter vegetable agroforestry system.

    Science.gov (United States)

    Wang, Qian; Xu, Zheng; Hu, Tingxing; Rehman, Hafeez Ur; Chen, Hong; Li, Zhongbin; Ding, Bo; Hu, Hongling

    2014-01-01

    Walnut agroforestry systems have many ecological and economic benefits when intercropped with cool-season species. However, decomposing leaf litter is one of the main sources of allelochemicals in such systems. In this study, lettuce (Lactuca sativa var. angustata) was grown in the soil incorporated with walnut leaf litter to assess its allelopathic activity. Lettuce growth and physiological processes were inhibited by walnut leaf litter, especially during early growth stage (1-2 euphylla period) or with large amount of litter addition. The plants treated by small amount of leaf litter recovered their growth afterwards, while the inhibition for 180 g leaf litter persisted until harvest. Twenty-eight compounds were identified in the leaf litter, and several of them were reported to be phytotoxic, which may be responsible for the stress induced by walnut leaf litter. Thus, for highest economic value of vegetables such as lettuce, excessive incorporation of leaf litter should be discouraged.

  20. Discovery of Walnut Twig Beetle, Pityophthorus juglandis, Associated with Forested Black Walnut, Juglans nigra, in the Eastern U.S.

    Directory of Open Access Journals (Sweden)

    Gregory J. Wiggins

    2014-05-01

    Full Text Available Thousand cankers disease (TCD is an insect-mediated disease of walnut trees (Juglans spp. involving walnut twig beetle (Pityophthorus juglandis and a fungal pathogen (Geosmithia morbida. Although first documented on walnut species in the western U.S., TCD is now found on black walnut (J. nigra in five states in the eastern U.S. Most collections of P. juglandis or G. morbida are from trees in agriculturally- or residentially-developed landscapes. In 2013, 16 pheromone-baited funnel traps were deployed in or near black walnuts in forested conditions to assess the risk of infestation of forested trees by P. juglandis. Four of the 16 funnel traps collected adult P. juglandis from three forested areas (one in North Carolina and two in Tennessee. These collections, while in forested settings, may still be strongly influenced by human activities. The greatest number of P. juglandis (n = 338 was collected from a forested location in an urbanized area near a known TCD-positive tree. The other two forested locations where P. juglandis (n = 3 was collected were in areas where camping is common, and infested firewood may have introduced P. juglandis unintentionally into the area. Future studies to assess P. juglandis on more isolated forested walnuts are planned.

  1. Realized kernels in practice

    DEFF Research Database (Denmark)

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

    2009-01-01

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

  2. 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...

  3. 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...

  4. Kernel methods for deep learning

    OpenAIRE

    Cho, Youngmin

    2012-01-01

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

  5. 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...

  6. 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...

  7. Kernel structures for Clouds

    Science.gov (United States)

    Spafford, Eugene H.; Mckendry, Martin S.

    1986-01-01

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

  8. Acute consumption of walnuts and walnut components differentially affect postprandial lipemia, endothelial function, oxidative stress, and cholesterol efflux in humans with mild hypercholesterolemia.

    Science.gov (United States)

    Berryman, Claire E; Grieger, Jessica A; West, Sheila G; Chen, Chung-Yen O; Blumberg, Jeffrey B; Rothblat, George H; Sankaranarayanan, Sandhya; Kris-Etherton, Penny M

    2013-06-01

    Walnut consumption improves cardiovascular disease risk; however, to our knowledge, the contribution of individual walnut components has not been assessed. This study evaluated the acute consumption of whole walnuts (85 g), separated nut skins (5.6 g), de-fatted nutmeat (34 g), and nut oil (51 g) on postprandial lipemia, endothelial function, and oxidative stress. Cholesterol efflux (ex vivo) was assessed in the whole walnut treatment only. A randomized, 4-period, crossover trial was conducted in healthy overweight and obese adults (n = 15) with moderate hypercholesterolemia. There was a treatment × time point interaction for triglycerides (P < 0.01) and increased postprandial concentrations were observed for the oil and whole walnut treatments (P < 0.01). Walnut skins decreased the reactive hyperemia index (RHI) compared with baseline (P = 0.02) such that a difference persisted between the skin and oil treatments (P = 0.01). The Framingham RHI was maintained with the oil treatment compared with the skins and whole nut (P < 0.05). There was a treatment effect for the ferric reducing antioxidant potential (FRAP) (P < 0.01), and mean FRAP was greater with the oil and skin treatments compared with the nutmeat (P < 0.01). Cholesterol efflux increased by 3.3% following whole walnut consumption in J774 cells cultured with postprandial serum compared with fasting baseline (P = 0.02). Walnut oil favorably affected endothelial function and whole walnuts increased cholesterol efflux. These 2 novel mechanisms may explain in part the cardiovascular benefits of walnuts.

  9. Viscosity kernel of molecular fluids

    DEFF Research Database (Denmark)

    Puscasu, Ruslan; Todd, Billy; Daivis, Peter

    2010-01-01

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

  10. Variable Kernel Density Estimation

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1992-01-01

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

  11. 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

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

    Science.gov (United States)

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

    2013-01-01

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

  13. What's killing my walnuts -- how to find help

    Science.gov (United States)

    Jerry Van Sambeek; Jenny. Juzwik

    2010-01-01

    For the last decade, we have watched as the granulate ambrosia beetle (GAB) formerly the Asian ambrosia beetle spread into the southern region of walnut. Now we are asked to watch for the possible invasion of the thousand canker disease (TCD) complex into the eastern United States assuming we cannot prevent its invasion from the western United States. For both pest...

  14. Decision making analysis of walnut seedling production on a small ...

    African Journals Online (AJOL)

    The decision has to be made between those three alternatives aiming at achievement of optimal/best economic result for the family farm. Summarizing results obtained from the decision tree, simulation and sensitivity analysis, the optimal solution for the family farm should be to continue production of walnut seedlings with ...

  15. Managing black walnut in natural stands: the human dimension

    Science.gov (United States)

    H.E. " Hank" Stelzer

    2004-01-01

    In managing black walnut, or any forest tree species, the human dimension is often overlooked. As a result, both the number of landowners managing their land and the number of forested acres under management has not significantly increased over the past 30 years. Elements of the human landscape are explored and a roadmap for engaging landowners is proposed.

  16. 7 CFR 984.472 - Reports of merchantable walnuts shipped.

    Science.gov (United States)

    2010-01-01

    ... MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE... shipped; whether they were shipped into domestic or export channels; and for exports, the quantity by... remainder of that marketing year. (b) Reports of walnuts purchased directly from growers by handlers who are...

  17. In vitro propagation of walnut - A review | Payghamzadeh | African ...

    African Journals Online (AJOL)

    New challenges for refinements of protocols for high rate of shoot multiplication and development of cost effective methods has gained importance in the recent past. Importance of liquid and solid static culture for callus induction, embryogenesis, shoot proliferation and root induction for walnut is also discussed in the ...

  18. 7 CFR 984.35 - California Walnut Board.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false California Walnut Board. 984.35 Section 984.35 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing... acreage within districts and within the production area during recent years; (2) The importance of new...

  19. Effect Of Walnut Leaf, Coriander And Pomegranate On Blood ...

    African Journals Online (AJOL)

    Mechanism of most of herbal used for diabetes mellitus treatment has not been well defined. This study was performed to investigate hypoglycemic effect of walnut leaf (Juglans regia L.), coriander leaf (Coriandrum sativum L.) or pomegranate seed (Punica granatum L.), and their possible role on pancreatic tissue. Diabetes ...

  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. Genotype and year variability of the chemical composition of walnut oil of Moroccan seedlings from the high Atlas Mountains

    Directory of Open Access Journals (Sweden)

    Kodad, O.

    2016-03-01

    Full Text Available Protein and oil content, fatty acid composition and tocopherol concentration were determined for two years in the kernel of ten candidate walnut selections from the high Atlas Mountains in Morocco. Considerable variation between genotypes was found for all parameters. The ranges of protein content (11.58–14.5% of kernel dry weight, DW, oil content (54.4–67.48% of kernel DW, oleic (12.47–22.01% of total oil, linoleic (55.03–60.01%, linolenic (9.3–15.87%, palmitic (6.84–9.12%, and stearic (1.7–2.92% acid percentages, γ-tocopherol (188.1–230.7 mg·kg-1 of oil, δ-tocopherol (23.3–43.4 mg·kg-1, and α-tocopherol (8.9–16.57 mg·kg-1 contents agreed with previous results obtained from other commercial walnut cultivars. The effect of year was significant for all the chemical components, except for oil content and palmitic acid percentage. Some genotypes showed high oil contents and consistently high values of γ-tocopherol in both years of study. The introduction of these genotypes as new cultivars by vegetative propagation may result in a an increase in quality of the walnuts from the high Atlas Mountains of Morocco, and as a seed source for forest walnut propagation in the same region.Se determinó durante dos años el contenido en proteína y aceite, la composición en ácidos grasos y la concentración en tocoferoles en la pepita de diez plantones de nogal seleccionados en el Alto Atlas de Marruecos, encontrándose una considerable variación entre genotipos para todos los parámetros. Los rangos del contenido en proteína (11.58–14.5 % del peso seco, PS, contenido en aceite (54.4–67.48 % PS, porcentaje de ácido oleico (12.47–22.01% del aceite total, linoleico (55.03–60.01 %, linolénico (9.3–15.87 %, palmítico (6.84–9.12 %, y esteárico (1.7–2.92 %, contenido en γ-tocoferol (188.1–230.7 mg·kg−1 de aceite, δ-tocoferol (23.3–43.4 mg·kg−1 y α-tocoferol (8.9–16.57 mg·kg−1, coincidieron con

  2. 7 CFR 981.7 - Edible kernel.

    Science.gov (United States)

    2010-01-01

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

  3. 7 CFR 981.408 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

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

  4. 7 CFR 981.8 - Inedible kernel.

    Science.gov (United States)

    2010-01-01

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

  5. Multivariate realised kernels

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  6. 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....

  7. 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.

  8. Walnut twig beetle: update on the biology and chemical ecology of a vector of an invasive fatal disease of walnut in the western U.S.

    Science.gov (United States)

    Steven J. Seybold; Andrew D. Graves; Tom W. Coleman

    2011-01-01

    The walnut twig beetle, Pityophthorus juglandis Blackman (Coleoptera: Scolytidae) (sensu Wood 2007), is a native North American bark beetle that has been recently implicated as the vector of thousand cankers disease of walnut trees in the western U.S. (Tisserat et al. 2009, Utley et al. 2009, Seybold et al. 2010).

  9. Global Polynomial Kernel Hazard Estimation

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  10. 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.

  11. Oil-walnut hull fracs score in Saskatchewan

    Energy Technology Data Exchange (ETDEWEB)

    Pamenter, C B

    1967-02-01

    The fracturing of wells using crude oil and walnut shells was recently introduced in SE. Saskatchewan with remarkable success. This workover treatment showed an ability to penetrate deeply into the low capacity Mississippian carbonates, and to raise production rates by as much as 400% without affecting the acceptable oil/ water ratios. Two case histories are included that indicate some of the conditions under which the treatment can be of value. The monthly oil and water production is tabulated for each of these cases.

  12. New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

    Science.gov (United States)

    Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

    2017-06-21

    We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

  13. 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...

  14. Cold sterilisation of walnuts as potential component of bakery products

    International Nuclear Information System (INIS)

    Koreňová, J.; Lopašovská, J.; Sádecká, J.; Kolek, E.

    2010-01-01

    Microbiological quality, sensory and chemical changes in volatile and lipid fractions of gamma-irradiated walnuts (Juglans regia L.) were evaluated using gas chromatography/mass spectrometry (GC/MS), gas chromatography with flame-ionising detector (GC/FID) and sensory evaluation. Doses of gamma-radiation were with in the range 0.5 - 5 kGy, where 10 kGy represented the highest permitted dose for food applications. Microbiological analysis showed that gamma-irradiation was an effective sterilisation tool which eliminated prevalent microorganisms including coliform bacteria from initial count of 6.0 x 102 CFU/g with 1.5 kGy dose. The dose of only 0.5 kGy was found to be sufficiently effective for killing prevalent moulds. Quoted levels of ionising radiation were adequate for elimination of microbiological load for minimum storage duration of 2 kGy dose. Higher irradiation levels negatively affected organoleptic properties of studied walnuts. Significant changes in relative contents of certain fatty acids, mainly linoleic and linolenic acid, and closely related changes in relative contents of certain volatiles were observed due to the influence of ionising radiation. Unsaturated hydrocarbons as determined by GC/MS method are believed to be suitable markers of gamma-irradiation of walnuts even at 0.5 kGy dose of application

  15. Quantifying Residues from Postharvest Propylene Oxide Fumigation of Almonds and Walnuts.

    Science.gov (United States)

    Jimenez, Leonel R; Hall, Wiley A; Rodriquez, Matthew S; Cooper, William J; Muhareb, Jeanette; Jones, Tom; Walse, Spencer S

    2015-01-01

    A novel analytical approach involving solvent extraction with methyl tert-butyl ether (MTBE) followed by GC was developed to quantify residues that result from the postharvest fumigation of almonds and walnuts with propylene oxide (PPO). Verification and quantification of PPO, propylene chlorohydrin (PCH) [1-chloropropan-2-ol (PCH-1) and 2-chloropropan-1-ol (PCH-2)], and propylene bromohydrin (PBH) [1-bromopropan-2-ol (PBH-1) and 2-bromopropan-1-ol (PBH-2)] was accomplished with a combination of electron impact ionization MS (EIMS), negative ion chemical ionization MS (NCIMS), and electron capture detection (ECD). Respective GC/EIMS LOQs for PPO, PCH-1, PCH-2, PBH-1, and PBH-2 in MTBE extracts were [ppm (μg/g nut)] 0.9, 2.1, 2.5, 30.3, and 50.0 for almonds and 0.8, 2.2, 2.02, 41.6, and 45.7 for walnuts. Relative to GC/EIMS, GC-ECD analyses resulted in no detection of PPO, similar detector responses for PCH isomers, and >100-fold more sensitive detection of PBH isomers. NCIMS did not enhance detection of PBH isomers relative to EIMS and was, respectively, approximately 20-, 5-, and 10-fold less sensitive to PPO, PCH-1, and PCH-2. MTBE extraction efficiencies were >90% for all analytes. The 10-fold concentration of MTBE extracts yielded recoveries of 85-105% for the PBH isomers and a concomitant decrease in LODs and LOQs across detector types. The recoveries of PCH isomers and PPO in the MTBE concentrate were relatively low (approximately 50 to 75%), which confound improvements in LODs and LOQs regardless of detector type.

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

    International Nuclear Information System (INIS)

    Mavros, Michael G.; Van Voorhis, Troy

    2014-01-01

    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

  17. Population structure of Geosmithia morbida, the causal agent of thousand cankers disease of walnut trees in the United States

    Science.gov (United States)

    Marcelo M. Zerillo; Jorge Ibarra Caballero; Keith Woeste; Andrew D. Graves; Colleen Hartel; Jay W. Pscheidt; Jadelys Tonos; Kirk Broders; Whitney Cranshaw; Steven J. Seybold; Ned Tisserat

    2014-01-01

    The ascomycete Geosmithia morbida and the walnut twig beetle Pityophthorus juglandis are associated with thousand cankers disease of Juglans (walnut) and Pterocarya (wingnut). The disease was first reported in the western United States (USA) on several Juglans species, but...

  18. 7 CFR 981.9 - Kernel weight.

    Science.gov (United States)

    2010-01-01

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

  19. Genetic and ecological insights into glacial refugia of walnut (Juglans regia L..

    Directory of Open Access Journals (Sweden)

    Mallikarjuna Aradhya

    Full Text Available The distribution and survival of trees during the last glacial maximum (LGM has been of interest to paleoecologists, biogeographers, and geneticists. Ecological niche models that associate species occurrence and abundance with climatic variables are widely used to gain ecological and evolutionary insights and to predict species distributions over space and time. The present study deals with the glacial history of walnut to address questions related to past distributions through genetic analysis and ecological modeling of the present, LGM and Last Interglacial (LIG periods. A maximum entropy method was used to project the current walnut distribution model on to the LGM (21-18 kyr BP and LIG (130-116 kyr BP climatic conditions. Model tuning identified the walnut data set filtered at 10 km spatial resolution as the best for modeling the current distribution and to hindcast past (LGM and LIG distributions of walnut. The current distribution model predicted southern Caucasus, parts of West and Central Asia extending into South Asia encompassing northern Afghanistan, Pakistan, northwestern Himalayan region, and southwestern Tibet, as the favorable climatic niche matching the modern distribution of walnut. The hindcast of distributions suggested the occurrence of walnut during LGM was somewhat limited to southern latitudes from southern Caucasus, Central and South Asian regions extending into southwestern Tibet, northeastern India, Himalayan region of Sikkim and Bhutan, and southeastern China. Both CCSM and MIROC projections overlapped, except that MIROC projected a significant presence of walnut in the Balkan Peninsula during the LGM. In contrast, genetic analysis of the current walnut distribution suggested a much narrower area in northern Pakistan and the surrounding areas of Afghanistan, northwestern India, and southern Tajikistan as a plausible hotspot of diversity where walnut may have survived glaciations. Overall, the findings suggest that

  20. Effect of a walnut meal on postprandial oxidative stress and antioxidants in healthy individuals.

    Science.gov (United States)

    Haddad, Ella H; Gaban-Chong, Natasha; Oda, Keiji; Sabaté, Joan

    2014-01-10

    In vitro studies rank walnuts (Juglans regia) among the plant foods high in antioxidant capacity, but whether the active constituents of walnuts are bioavailable to humans remains to be determined. The intention of this study was to examine the acute effects of consuming walnuts compared to refined fat on meal induced oxidative stress. At issue is whether the ellagitannins and tocopherols in walnuts are bioavailable and provide postprandial antioxidant protection. A randomized, crossover, and controlled-feeding study was conducted to evaluate a walnut test meal compared to one composed of refined ingredients on postprandial serum antioxidants and biomarkers of oxidative status in healthy adults (n = 16) with at least 1 week between testing sessions. Following consumption of a low phenolic diet for one day and an overnight fast, blood was sampled prior to the test meals and at intervals up to 24 hours post ingestion and analyzed for total phenols, malondiadehyde (MDA), oxidized LDL, ferric reducing antioxidant power (FRAP), hydrophilic and lipophilic oxygen radical absorbance capacity (ORAC), uric acid, catechins and urinary excretion of phenylacetate metabolites and of urolithin A. Mixed linear models demonstrated a diet effect (P < 0.001) for plasma γ-tocopherol but not for α-tocopherol with the walnut meal. Following the walnut test meal, the incremental 5 hour area under the curve (AUC(0-5h)) was reduced 7.4% for MDA, increased 7.5% for hydrophilic and 8.5% for lipophilic ORAC and comparable for total phenols, FRAP and uric acid. Oxidized LDL was reduced at 2 hours after the walnut meal. Plasma concentrations of gallocatechin gallate (GCG), epicatechin gallate (ECG) and epicallocatechin gallate (EGCG) increased significantly at 1 hour after the walnut test meal. Quantities of urolithin-A excreted in the urine were significantly higher following the walnut meal. Compared to the refined control meal, the walnut meal acutely increased postprandial

  1. A kernel version of spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

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

  2. kernel oil by lipolytic organisms

    African Journals Online (AJOL)

    USER

    2010-08-02

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

  3. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

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

  4. Notes on the gamma kernel

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole E.

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

  5. Adaptability of black walnut, black cherry, and Northern red oak to Northern California

    Science.gov (United States)

    Philip M. McDonald

    1987-01-01

    When planted in sheltered sites in northern California, only 49% of black walnut (Juglans nigra L.) and 58% of black cherry (Prunus serotina Ehrh.) survived for 15 years, and 20% of northern red oak (Quercus rubra L.) survived for 10 years. The black walnut trees averaged 0.6 inches diameter at breast...

  6. Black walnut response to subsoiling, irrigation, and vegetation management on a site with a shallow fragipan

    Science.gov (United States)

    F. D. McBride; J. W. Van Sambeek

    1995-01-01

    Vegetation management with glyphosate and simazine proved to be more effective than preplant subsoiling or irrigation for achieving acceptable walnut biomass growth on an upland old field site (SI = 70 for white oak). In 1980, we direct seeded germinating black walnut seed on an upland, slightly eroded, old field ridge with a 45 to 60 cm deep fragipan. We tested all...

  7. Rethinking the history of common walnut (Juglans regia L.) in Europe: Its origins and human interactions.

    Science.gov (United States)

    Pollegioni, Paola; Woeste, Keith; Chiocchini, Francesca; Del Lungo, Stefano; Ciolfi, Marco; Olimpieri, Irene; Tortolano, Virginia; Clark, Jo; Hemery, Gabriel E; Mapelli, Sergio; Malvolti, Maria Emilia

    2017-01-01

    Common walnut (Juglans regia L) is an economically important species cultivated worldwide for its high-quality wood and nuts. It is generally accepted that after the last glaciation J. regia survived and grew in almost completely isolated stands in Asia, and that ancient humans dispersed walnuts across Asia and into new habitats via trade and cultural expansion. The history of walnut in Europe is a matter of debate, however. In this study, we estimated the genetic diversity and structure of 91 Eurasian walnut populations using 14 neutral microsatellites. By integrating fossil pollen, cultural, and historical data with population genetics, and approximate Bayesian analysis, we reconstructed the demographic history of walnut and its routes of dispersal across Europe. The genetic data confirmed the presence of walnut in glacial refugia in the Balkans and western Europe. We conclude that human-mediated admixture between Anatolian and Balkan walnut germplasm started in the Early Bronze Age, and between western Europe and the Balkans in eastern Europe during the Roman Empire. A population size expansion and subsequent decline in northeastern and western Europe was detected in the last five centuries. The actual distribution of walnut in Europe resulted from the combined effects of expansion/contraction from multiple refugia after the Last Glacial Maximum and its human exploitation over the last 5,000 years.

  8. Genetic diversity, structure and differentiation in cultivate walnut (Juglans regia L.)

    Science.gov (United States)

    M. Aradhya; K. Woeste; D. Velasco

    2012-01-01

    An analysis of genetic structure and differentiation in cultivated walnut (Juglans regia) using 15 microsatellite loci revealed a considerable amount of genetic variation with a mild genetic structure indicating five genetic groups corresponding to the centers of diversity within the home range of walnut in Eurasia. Despite the narrow genetic...

  9. Seedling-sapling growth variation in a southern Illinios black walnut provenance/progeny test

    Science.gov (United States)

    George Rink; J. W. Van Sambeek

    1987-01-01

    Nursery root and shoot measurements and annual height, basal diameter and survival data for the 5 years after outplanting were used to describe black walnut growth variation in southern Illinois. At age 5 sapling height narrow-sense heritability was found to be 0.49 for 131 open-pollinated families from across the black walnut comercial range. Greatest height and...

  10. Effect of understory management on phenological responses of eastern black walnut on an alluvial Arkansas soil

    Science.gov (United States)

    Black walnut (Juglans nigra L.) is commonly grown in agroforestry practices for nuts and/or timber with little knowledge of how understory herbage management might affect tree phenology. We compared black walnut plant type (variety and wild-type) for phenological response in date of budburst, leaf ...

  11. Effect of moderate walnut consumption on lipid profile, arterial stiffness and platelet activation in humans.

    Science.gov (United States)

    Din, J N; Aftab, S M; Jubb, A W; Carnegy, F H; Lyall, K; Sarma, J; Newby, D E; Flapan, A D

    2011-02-01

    A large intake of walnuts may improve lipid profile and endothelial function. The effect of moderate walnut consumption is not known. We investigated whether a moderate intake of walnuts would affect lipid profile, arterial stiffness and platelet activation in healthy volunteers. A total of 30 healthy males were recruited into a single-blind randomized controlled crossover trial of 4 weeks of dietary walnut supplementation (15 g/day) and 4 weeks of control (no walnuts). Arterial stiffness was assessed using pulse waveform analysis to determine the augmentation index and augmented pressure. Platelet activation was determined using flow cytometry to measure circulating platelet-monocyte aggregates. There were no differences in lipid profile after 4 weeks of walnut supplementation compared with control. Dietary intake of α-linolenic acid was increased during the walnut diet (2.1±0.4 g/day versus 0.7±0.4 g/day, Pprofile, arterial stiffness or platelet activation in man. Our results suggest that the potentially beneficial cardiac effects of walnuts may not be apparent at lower and more practical levels of consumption.

  12. Long term human impacts on genetic structure of Italian walnut inferred by SSR markers

    Science.gov (United States)

    Paola Pollegioni; Keith Woeste; Irene Olimpieri; Danilo Marandola; Francesco Cannata; Maria E Malvolti

    2011-01-01

    Life history traits, historic factors, and human activities can all shape the genetic diversity of a species. In Italy, walnut (Juglans regia L.) has a long history of cultivation both for wood and edible nuts. To better understand the genetic variability of current Italian walnut resources, we analyzed the relationships among the genetic structure...

  13. Legume ground covers alter defoliation response of black walnut saplings to drought and anthracnose

    Science.gov (United States)

    J. W. Van Sambeek

    2003-01-01

    Growth and premature defoliation of black walnut saplings underplanted 5 or 6 years earlier with six different ground covers were quantified in response to a summer drought or anthracnose. Walnut saplings growing with ground covers of hairy vetch, crownvetch, and to a lesser extent sericea lespedeza continued to have more rapid height and diameter growth than saplings...

  14. Landscape genetics of Persian walnut (Juglans regia L.) across its Asian range

    Science.gov (United States)

    Paola Pollegioni; Keith E. Woeste; Francesca Chiocchini; Irene Olimpieri; Virginia Tortolano; Jo Clark; Gabriel E. Hemery; Sergio Mapelli; Maria Emilla. Malvolti

    2014-01-01

    Persian walnut (Juglans regia L) is an economically important species cultivated worldwide for its wood and nuts. Despite the increasing interest in the development of conservation strategies for walnut germplasm, an accurate and full-scale overview of wild genetic resources of J. regia has not been conducted because natural...

  15. Database for estimating tree responses of walnut and other hardwoods to ground cover management practices

    Science.gov (United States)

    J.W. Van Sambeek

    2010-01-01

    The ground cover in plantings of walnut and other hardwoods can substantially affect tree growth and seed production. The number of alternative ground covers that have been suggested for establishment in tree plantings far exceeds the number that have already been tested with walnut and other temperate hardwoods. Knowing how other hardwood species respond to ground...

  16. 7 CFR 984.91 - Relationship with the California Walnut Commission.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 8 2010-01-01 2010-01-01 false Relationship with the California Walnut Commission...) AGRICULTURAL MARKETING SERVICE (Marketing Agreements and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF... Relationship with the California Walnut Commission. In conducting Board activities and other objectives under...

  17. Developing new microsatellite markers in walnut (Juglans regia L.) from Juglans nigra genomic GA enriched library

    Science.gov (United States)

    Hayat Topcu; Nergiz Coban; Keith Woeste; Mehmet Sutyemez; Salih. Kafkas

    2015-01-01

    We attempted to develop new polymorphic SSR primer pairs in walnut using sequences derived from Juglans nigra L. genomic enriched library with GA repeat. The designed 94 SSR primer pairs were subjected to gradient PCR in 12 walnut cultivars to determine their optimum annealing temperatures and to determine whether they produce bands. Then, the...

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

    OpenAIRE

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

    2017-01-01

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

  19. 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...

  20. An Approximate Approach to Automatic Kernel Selection.

    Science.gov (United States)

    Ding, Lizhong; Liao, Shizhong

    2016-02-02

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

  1. Model Selection in Kernel Ridge Regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

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

  2. 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.

  3. Monitoring and research at Walnut Creek National Wildlife Refuge

    Science.gov (United States)

    Roelle, James E.; Hamilton, David B.

    1993-01-01

    Walnut Creek National Wildlife Refuge-Prairie Learning Center (Walnut Creek or the Refuge) is one of the newest additions to the National Wildlife Refuge System, which consists of over 480 units throughout the United States operated by the U.S. Department of the Interior, Fish and Wildlife Service (the Service). Located about 20 miles east of Des Moines, Iowa, the Refuge has an approved acquisition boundary containing 8,654 acres (Figure 1). Acquisition is from willing sellers only, and to date the Service has purchased approximately 5,000 acres. The acquisition boundary encompasses about 43% of the watershed of Walnut Creek, which bisects the Refuge and drains into the Des Moines River to the southeast. Approximately 25%-30% of the Walnut Creek watershed is downstream of the Refuge. As authorized by Congress in 1990, the purposes of the Refuge are to (U.S. Fish and Wildlife Service 1992): • restore native tallgrass pairie, wetland, and woodland habitats for breeding and migratory waterfowl and resident wildlife; • serve as a major environmental education center providing opportunities for study; • provide outdoor recreation benefits to the public; and • provide assistance to local landowners to improve their lands for wildlife habitat. To implement these purposes authorized by Congress, the Refuge has established the goal of recreating as nearly as possible the natural communities that existed at the time of settlement by Euro-Americans (circa 1840). Current land use is largely agricultural, including 69% cropland, 17% grazed pasture, and 7.5% grassland (dominantly brome) enrolled in the Conservation Reserve Program). About 1,395 acres of relict native communities also exist on the Refuge, including prairie (725 acres), oak savanna and woodland (450 acres), and riparian or wetland areas (220 acres). Some of these relicts are highly restorable; others contain only a few prairie plants in a matrix of brome and will be more difficult to restore. When the

  4. 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

  5. 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...

  6. 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.

  7. RTOS kernel in portable electrocardiograph

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  8. Semi-Supervised Kernel PCA

    DEFF Research Database (Denmark)

    Walder, Christian; Henao, Ricardo; Mørup, Morten

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

  9. Mycoflora and mycotoxin of hazelnut (Corylus avellana L.) and walnut (Juglans regia L.) seeds in Egypt.

    Science.gov (United States)

    Abdel-Hafez, A I; Saber, S M

    1993-03-01

    Fifty-one species and 3 varieties appertaining to 20 genera were collected from 20 samples of each of hazelnut and walnut seeds on glucose- and 40% (W/V) sucrose-Czapek's agar at 25 degrees C and 45 degrees C with the most common mesophiles were Aspergillus flavus, A. fumigatus, A. niger, Cladosporium cladosporioides, C. herbarum, Penicillium chrysogenum, P. citrinum and P. oxalicum. Fusarium (represented by F. equiseti, F. moniliforme and F. oxysporum) was recovered from walnut seeds in moderate frequency (on glucose-Czapek's agar). Eurotium (E. amstelodami, E. chevalieri, E. repens and E. rubrum) was completely absent on glucose agar, but it was isolated in high frequency from the two types of seeds on 40% sucrose-Czapek's agar. Aspergillus fumigatus and Rhizomucor pusillus were the most common thermophilic fungi in hazelnut and walnut seeds on glucose agar at 45 degrees C. Humicola grisea var. themoidae and Thermoascus aurantiacus were encountered rarely from walnuts. The nuts samples were assayed for natural occurrence of aflatoxins B1, B2, G1 and G2, citrinin, ochratoxin A, patulin, sterigmatocystin, zearalenone, T-2 toxin and diacetoxyscirpenol by thin layer chromatography analysis. Aflatoxin was detected in 90% of hazelnut samples (25-175 micrograms/kg) and 75% of walnut samples (15-25 micrograms/kg). Zearalenone was detected in one sample of walnut (125 micrograms/kg). This is the first report for the presence of zearalenone in walnut. The other mycotoxins were not detected.

  10. Distribution, relationship, and risk assessment of toxic heavy metals in walnuts and growth soil.

    Science.gov (United States)

    Han, Yongxiang; Ni, Zhanglin; Li, Shiliang; Qu, Minghua; Tang, Fubin; Mo, Runhong; Ye, Caifen; Liu, Yihua

    2018-04-14

    Walnut is one of the most popular nuts worldwide and contains various mineral nutrients. Little is known, however, about the relationship between toxic heavy metals in walnuts and growth soil. In this study, we investigated the distribution, relationship, and risk assessment of five toxic heavy metals-lead (Pb), arsenic (As), chromium (Cr), cadmium (Cd), and mercury (Hg)-in walnuts and growth soil in the main production areas of China. The results showed that the main heavy metal pollution in walnut and soil was Pb and Cd. Regionally, positive relationships existed between heavy metals and the pH and organic matter of soil. In addition, we observed a notable uptake effect between walnut and growth soil. In this study, we found a significant correlation (r = 0.786, P toxic heavy metal pollution in walnuts and growth soil could be helpful to screen suitable planting sites to prevent and control heavy metal pollution and improve the quality and safety of walnut.

  11. Effect of gamma irradiation on storability of Syrian walnut

    Energy Technology Data Exchange (ETDEWEB)

    Al-Bachir, M [Atomic Energy Commission, Damascus (Syrian Arab Republic). Dept. of Radiation Technology

    2001-12-01

    Walnut fruits of Baladi variety were irradiated with 0, 0.5, 1.0, 1.5 and 2.0 kGy of gamma irradiation. The irradiated and unirradiated fruits were stored at room temperature (15 to 18 Centigrade) and at a relative humidity of 50 to 70%. Fungal load, proximate composition, chemical changes and sensory properties of nuts were evaluated immediately after irradiation, 6 and 12 months of storage. The results indicated that gamma irradiation reduced the fungal load. Used doses did not cause any significant change in proximate composition of walnuts. Immediately after irradiation, gamma irradiation increased total acidity and decreased iodine value and the volatile basic nitrogen (VBN). whereas, after 12 months of storage, gamma irradiation decreased total acidity and peroxide value and increased iodine value and (VBN). Immediately after irradiation no significant differences were observed between irradiated and non-irradiated samples in flavor and aroma. Whereas, after 12 months of storage higher doses (1.5 and 2.0 kGy) had a negative effect on sensory characteristics. (author)

  12. Effect of gamma irradiation on storability of Syrian walnut

    International Nuclear Information System (INIS)

    Al-Bachir, M.

    2002-01-01

    Walnut fruits of Baladi variety were irradiated with 0, 0.5, 1.0, 1.5 and 2.0 kGy of gamma irradiation. The irradiated and unirradiated fruits were stored at room temperature (15 to 18 Centigrade) and at a relative humidity of 50 to 70%. Fungal load, proximate composition, chemical changes and sensory properties of nuts were evaluated immediately after irradiation, 6 and 12 months of storage. The results indicated that gamma irradiation reduced the fungal load. Used doses did not cause any significant change in proximate composition of walnuts. Immediately after irradiation, gamma irradiation increased total acidity and decreased iodine value and the volatile basic nitrogen (VBN). whereas, after 12 months of storage, gamma irradiation decreased total acidity and peroxide value and increased iodine value and (VBN). Immediately after irradiation no significant differences were observed between irradiated and non-irradiated samples in flavor and aroma. Whereas, after 12 months of storage higher doses (1.5 and 2.0 kGy) had a negative effect on sensory characteristics. (author)

  13. Model selection in kernel ridge regression

    DEFF Research Database (Denmark)

    Exterkate, Peter

    2013-01-01

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

  14. Multiple Kernel Learning with Data Augmentation

    Science.gov (United States)

    2016-11-22

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

  15. A kernel version of multivariate alteration detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2013-01-01

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

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  17. Complex use of cottonseed kernels

    Energy Technology Data Exchange (ETDEWEB)

    Glushenkova, A I

    1977-01-01

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

  18. Kernel regression with functional response

    OpenAIRE

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

    2011-01-01

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

  19. 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

  20. 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

  1. Local Observed-Score Kernel Equating

    Science.gov (United States)

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

    2014-01-01

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

  2. 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

  3. 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.

  4. 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.

  5. Wigner functions defined with Laplace transform kernels.

    Science.gov (United States)

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

    2011-10-24

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

  6. Physiology and silviculture of black walnut for combined timber and nut production

    Science.gov (United States)

    J. W. Van Sambeek; George Rink

    1981-01-01

    Research literature was reviewed for evidence supporting the management of black walnut plantations for combined timber and nut production. The silviculture of the species is discussed in relation to dual cropping. Stimulation and phenology of flowering and fruiting are reviewed.

  7. Credit scoring analysis using kernel discriminant

    Science.gov (United States)

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

    2018-05-01

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

  8. 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....

  9. Kernel parameter dependence in spatial factor analysis

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

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

  10. Laser altimeter measurements at Walnut Gulch Watershed, Arizona

    International Nuclear Information System (INIS)

    Ritchie, J.C.; Humes, K.S.; Weltz, M.A.

    1995-01-01

    Measurements of landscape surface roughness properties are necessary for understanding many watershed processes. This paper reviews the use of an airborne laser altimeter to measure topography and surface roughness properties of the landscape at Walnut Gulch Watershed in Arizona. Airborne laser data were used to measure macro and micro topography as well as canopy topography, height, cover, and distribution. Macro topography of landscape profiles for segments up to 5 km (3 mi) were measured and were in agreement with available topographic maps but provided more detail. Gullies and stream channel cross-sections and their associated floodplains were measured. Laser measurements of vegetation properties (height and cover) were highly correlated with ground measurements. Landscape segments for any length can be used to measure these landscape roughness properties. Airborne laser altimeter measurements of landscape profiles can provide detailed information on watershed surface properties for improving the management of watersheds. (author)

  11. Concentration Levels of Imidacloprid and Dinotefuran in Five Tissue Types of Black Walnut, Juglans nigra

    Directory of Open Access Journals (Sweden)

    Paul Merten

    2013-11-01

    Full Text Available Black walnut, a valuable economic and environmentally important species, is threatened by thousand cankers disease. Systemic imidacloprid and dinotefuran applications were made to mature black walnut trees to evaluate their translocation and concentration levels in various tissue types including leaf, twig, trunk core, nutmeat, and walnut husk. The metabolism of imidacloprid in plants produces a metabolite, olefin-imidacloprid, which has been documented to have insecticidal properties in other systems. Trunk CoreTect (imidacloprid soil pellets and a trunk spray of dinotefuran were applied to mature black walnuts in spring 2011. Imidacloprid concentrations were detected in both the lower and upper strata in all tissue types tested and progressively increased through month 12 post-treatment in twig and leaf tissue. Olefin-imidacloprid was detected in the nutmeat and walnut husk. Dinotefuran was only detected in the first sampling period and was found in low concentration levels in leaf and twig tissue types, and was not detected in the trunk, nutmeat or the walnut husk.

  12. Potentials of raw and cooked walnuts (Tetracapidium conophorum) as sources of valuable nutrients for good health.

    Science.gov (United States)

    Moyib, O K; Falegbe, O; Moyib, F R

    2015-12-01

    The present study estimated nutrient composition of walnuts before and after cooking with respect to its potential as valuable source of nutrients for daily intake. Walnut fruits were purchased from five different markets in Ijebu-Ode local government area and its environs. The fruits samples were divided into two portions, labelled R (for raw) and C (cooked). The C samples were cooked at 100 degrees C for 1 hr and allowed to cool to room temperature. The seeds of both C and R samples were ground and analyzed for proximate, macro and micro minerals using methods of Association of Official Chemists. The results obtained showed that both raw and cooked walnuts are rich in fat, iron (Fe), manganese (Mn), and copper (Cu) in amounts that are within daily recommended intake per 100 g of walnut seeds. They also contained appreciable levels of protein, phosphorus (P), calcium (Ca), and magnesium (Mg) but with low content of moisture (MC), carbohydrate, fiber, sodium (Na) and potassium (K). Boiling significantly affected the levels of protein, carbohydrate, ash, moisture content, fat, nitrogen, calcium, sodium, copper, zinc, phosphorus, potassium, manganese and iron The study reveals that walnut is nutritious due to its appreciable level of protein and presence of various essential and macro minerals. Its low content of sodium and potassium is beneficiary in hypertensive condition as snack. The study suggests future bio-fortification of walnut with zinc, which may bring about a co-increase in Ca and protein content.

  13. Effect of roasting conditions on the composition and antioxidant properties of defatted walnut flour.

    Science.gov (United States)

    Santos, Joana; Alvarez-Ortí, Manuel; Sena-Moreno, Estela; Rabadán, Adrián; Pardo, José E; Beatriz Pp Oliveira, M

    2018-03-01

    Walnut oil extraction by pressure systems produces a press cake as a by-product, with many of the beneficial walnut properties. The objective of this work was to evaluate the composition and antioxidant properties of walnut flours submitted to different roasting protocols (50, 100 and 150 °C during 30, 60 and 120 min). All walnut flours had about 42% protein and a significant amount of dietary fibre (17%), not being affected by the roasting process. Nonetheless, the fat content increased around 50% in walnuts flours subjected to longer and higher roasting temperatures (150 °C). The lipid fraction showed a good nutritional quality with a high vitamin E content (mainly γ-tocopherol) and fatty acid profile rich in linoleic and linolenic acids. The high phenolic content also provides great antioxidant capacity to the flours. Mild roasting of walnuts did not affect the quality of the flours that could be used as a functional ingredient in the food industry. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  14. Validation of Born Traveltime Kernels

    Science.gov (United States)

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

    2001-12-01

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

  15. 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.

  16. 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.

  17. Calculation of dose point kernels for five radionuclides used in radio-immunotherapy

    International Nuclear Information System (INIS)

    Okigaki, S.; Ito, A.; Uchida, I.; Tomaru, T.

    1994-01-01

    With the recent interest in radioimmunotherapy, attention has been given to calculation of dose distribution from beta rays and monoenergetic electrons in tissue. Dose distribution around a point source of a beta ray emitting radioisotope is referred to as a beta dose point kernel. Beta dose point kernels for five radionuclides such as 131 I, 186 Re, 32 P, 188 Re, and 90 Y appropriate for radioimmunotherapy are calculated by Monte Carlo method using the EGS4 code system. Present results were compared with the published data of experiments and other calculations. Accuracy and precisions of beta dose point kernels are discussed. (author)

  18. 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...

  19. 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.

  20. Convergence of barycentric coordinates to barycentric kernels

    KAUST Repository

    Kosinka, Jiří ; Barton, Michael

    2016-01-01

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

  1. Kernel principal component analysis for change detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Morton, J.C.

    2008-01-01

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

  2. Partial Deconvolution with Inaccurate Blur Kernel.

    Science.gov (United States)

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

    2017-10-17

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

  3. 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

  4. 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.

  5. Characterization of virgin walnut oils and their residual cakes produced from different varieties.

    Science.gov (United States)

    Ojeda-Amador, Rosa M; Salvador, María Desamparados; Gómez-Alonso, Sergio; Fregapane, Giuseppe

    2018-06-01

    This study addresses the composition and properties of different walnut varieties (Chandler, Hartley and Lara), in particular their virgin oils and residual cakes obtained by screw pressing employing different cultivars. Among nuts, walnut (Juglans regia L.) exhibits interesting nutritional value, mainly due to their high content in linoleic acid, phenolic and tocopherol compounds, which show antioxidant and other healthy properties. Valuable results related to fatty acid profile and minor components were observed. Virgin walnut oil is a rich source in linoleic acid (60-62%) and γ-tocopherol (517-554 mg/kg). Moreover, walnuts show a very high content in total phenolic compounds (10,045-12,474 mg/kg; as gallic acid), which contribute to a great antioxidant activity (105-170 mmol/kg for DPPH, and 260-393 mmol/kg for ORAC), being the hydrolysable tannins (2132-4204 mg/kg) and flavanols (796-2433 mg/kg) their main phenolic groups. Aldehydes account for the highest contribution to aromatic volatiles in virgin walnut oil (about 35% of total). As expected, polar phenolic compounds concentrate in the residual cake, after the separation of the oily phase, reaching a content of up to 19,869 mg/kg, leading to potential added value and applications as source of bioactive compounds to this by-product. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    African Journals Online (AJOL)

    ADOWIE PERE

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

  7. Mitigation of artifacts in rtm with migration kernel decomposition

    KAUST Repository

    Zhan, Ge; Schuster, Gerard T.

    2012-01-01

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

  8. Efficacy of Heat Treatment for the Thousand Cankers Disease Vector and Pathogen in Small Black Walnut Logs

    Science.gov (United States)

    A. E. Mayfield; S. W. Fraedrich; A. Taylor; P. Merten; S. W. Myers

    2014-01-01

    Thousand cankers disease, caused by the walnut twig beetle (Pityophthorus juglandis Blackman) and an associated fungal pathogen (Geosmithia morbida M. Kolarõ´k, E. Freeland, C. Utley, and N. Tisserat), threatens the health and commercial use of eastern black walnut (Juglans nigra L.), one of the most economically...

  9. 7 CFR 999.500 - Safeguard procedures for walnuts and certain dates exempt from grade, size, quality, and maturity...

    Science.gov (United States)

    2010-01-01

    ... and Orders; Fruits, Vegetables, Nuts), DEPARTMENT OF AGRICULTURE SPECIALTY CROPS; IMPORT REGULATIONS... cannot be used for drying and sale as dried walnuts); walnuts used in non-competitive outlets such as use... the Marketing Order Administration Branch, Fruit and Vegetable Division, AMS, USDA, and shall show the...

  10. Infrared pre-drying and dry-dehulling of walnuts for improved processing efficiency and product quality

    Science.gov (United States)

    The walnut industry is faced with an urgent need to improve post-harvest processing efficiency, particularly drying and dehulling operations. This research investigated the feasibility of dry-dehulling and infrared (IR) pre-drying of walnuts for improved processing efficiency and dried product quali...

  11. Dose calculation methods in photon beam therapy using energy deposition kernels

    International Nuclear Information System (INIS)

    Ahnesjoe, A.

    1991-01-01

    The problem of calculating accurate dose distributions in treatment planning of megavoltage photon radiation therapy has been studied. New dose calculation algorithms using energy deposition kernels have been developed. The kernels describe the transfer of energy by secondary particles from a primary photon interaction site to its surroundings. Monte Carlo simulations of particle transport have been used for derivation of kernels for primary photon energies form 0.1 MeV to 50 MeV. The trade off between accuracy and calculational speed has been addressed by the development of two algorithms; one point oriented with low computional overhead for interactive use and one for fast and accurate calculation of dose distributions in a 3-dimensional lattice. The latter algorithm models secondary particle transport in heterogeneous tissue by scaling energy deposition kernels with the electron density of the tissue. The accuracy of the methods has been tested using full Monte Carlo simulations for different geometries, and found to be superior to conventional algorithms based on scaling of broad beam dose distributions. Methods have also been developed for characterization of clinical photon beams in entities appropriate for kernel based calculation models. By approximating the spectrum as laterally invariant, an effective spectrum and dose distribution for contaminating charge particles are derived form depth dose distributions measured in water, using analytical constraints. The spectrum is used to calculate kernels by superposition of monoenergetic kernels. The lateral energy fluence distribution is determined by deconvolving measured lateral dose distributions by a corresponding pencil beam kernel. Dose distributions for contaminating photons are described using two different methods, one for estimation of the dose outside of the collimated beam, and the other for calibration of output factors derived from kernel based dose calculations. (au)

  12. 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.

  13. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

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

    2017-01-01

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

  14. 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

  15. 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)

  16. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

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

  17. Improving the Bandwidth Selection in Kernel Equating

    Science.gov (United States)

    Andersson, Björn; von Davier, Alina A.

    2014-01-01

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

  18. Kernel Korner : The Linux keyboard driver

    NARCIS (Netherlands)

    Brouwer, A.E.

    1995-01-01

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

  19. Analysis of Drude model using fractional derivatives without singular kernels

    Directory of Open Access Journals (Sweden)

    Jiménez Leonardo Martínez

    2017-11-01

    Full Text Available We report study exploring the fractional Drude model in the time domain, using fractional derivatives without singular kernels, Caputo-Fabrizio (CF, and fractional derivatives with a stretched Mittag-Leffler function. It is shown that the velocity and current density of electrons moving through a metal depend on both the time and the fractional order 0 < γ ≤ 1. Due to non-singular fractional kernels, it is possible to consider complete memory effects in the model, which appear neither in the ordinary model, nor in the fractional Drude model with Caputo fractional derivative. A comparison is also made between these two representations of the fractional derivatives, resulting a considered difference when γ < 0.8.

  20. Improvement in retention of solid fission products in HTGR fuel particles by ceramic kernel additives

    International Nuclear Information System (INIS)

    Foerthmann, R.; Groos, E.; Gruebmeier, H.

    1975-08-01

    Increased requirements concerning the retention of long-lived solid fission products in fuel elements for use in advanced High Temperature Gas-cooled Reactors led to the development of coated particles with improved fission product retention of the kernel, which represent an alternative to silicon carbide-coated fuel particles. Two irradiation experiments have shown that the release of strontium, barium, and caesium from pyrocarbon-coated particles can be reduced by orders of magnitude if the oxide kernel contains alumina-silica additives. It was detected by electron microprobe analysis that the improved retention of the mentioned fission products in the fuel kernel is caused by formation of the stable aluminosilicates SrAl 2 Si 2 O 8 , BaAl 2 Si 2 O 8 and CsAlSi 2 O 6 in the additional aluminasilica phase of the kernel. (orig.) [de

  1. X-ray photoelectron spectroscopic analysis of rice kernels and flours: Measurement of surface chemical composition.

    Science.gov (United States)

    Nawaz, Malik A; Gaiani, Claire; Fukai, Shu; Bhandari, Bhesh

    2016-12-01

    The objectives of this study were to evaluate the ability of X-ray photoelectron spectroscopy (XPS) to differentiate rice macromolecules and to calculate the surface composition of rice kernels and flours. The uncooked kernels and flours surface composition of the two selected rice varieties, Thadokkham-11 (TDK11) and Doongara (DG) demonstrated an over-expression of lipids and proteins and an under-expression of starch compared to the bulk composition. The results of the study showed that XPS was able to differentiate rice polysaccharides (mainly starch), proteins and lipids in uncooked rice kernels and flours. Nevertheless, it was unable to distinguish components in cooked rice samples possibly due to complex interactions between gelatinized starch, denatured proteins and lipids. High resolution imaging methods (Scanning Electron Microscopy and Confocal Laser Scanning Microscopy) were employed to obtain complementary information about the properties and location of starch, proteins and lipids in rice kernels and flours. Copyright © 2016. Published by Elsevier Ltd.

  2. Metabolic network prediction through pairwise rational kernels.

    Science.gov (United States)

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

    2014-09-26

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

  3. The effect of walnut intake on factors related to prostate and vascular health in older men

    Directory of Open Access Journals (Sweden)

    West Sheila G

    2008-05-01

    Full Text Available Abstract Background Tocopherols may protect against prostate cancer and cardiovascular disease (CVD. Methods We assessed the effect of walnuts, which are rich in tocopherols, on markers of prostate and vascular health in men at risk for prostate cancer. We conducted an 8-week walnut supplement study to examine effects of walnuts on serum tocopherols and prostate specific antigen (PSA. Subjects (n = 21 consumed (in random order their usual diet +/- a walnut supplement (75 g/d that was isocalorically incorporated in their habitual diets. Prior to the supplement study, 5 fasted subjects participated in an acute timecourse experiment and had blood taken at baseline and 1, 2, 4, and 8 h after consuming walnuts (75 g. Results During the timecourse experiment, triglycerides peaked at 4 h, and gamma-tocopherol (γ-T increased from 4 to 8 h. Triglyceride – normalized γ-T was two-fold higher (P = 0.01 after 8 versus 4 h. In the supplement study, change from baseline was +0.83 ± 0.52 μmol/L for γ-T, -2.65 ± 1.30 μmol/L for alpha-tocopherol (α-T and -3.49 ± 1.99 for the tocopherol ratio (α-T: γ-T. A linear mixed model showed that, although PSA did not change, the ratio of free PSA:total PSA increased and approached significance (P = 0.07. The α-T: γ-T ratio decreased significantly (P = 0.01, partly reflecting an increase in serum γ-T, which approached significance (P = 0.08. Conclusion The significant decrease in the α-T: γ-T ratio with an increase in serum γ-T and a trend towards an increase in the ratio of free PSA:total PSA following the 8-week supplement study suggest that walnuts may improve biomarkers of prostate and vascular status.

  4. 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.

  5. Putting Priors in Mixture Density Mercer Kernels

    Science.gov (United States)

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

    2004-01-01

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

  6. Anisotropic hydrodynamics with a scalar collisional kernel

    Science.gov (United States)

    Almaalol, Dekrayat; Strickland, Michael

    2018-04-01

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

  7. Introducing etch kernels for efficient pattern sampling and etch bias prediction

    Science.gov (United States)

    Weisbuch, François; Lutich, Andrey; Schatz, Jirka

    2018-01-01

    Successful patterning requires good control of the photolithography and etch processes. While compact litho models, mainly based on rigorous physics, can predict very well the contours printed in photoresist, pure empirical etch models are less accurate and more unstable. Compact etch models are based on geometrical kernels to compute the litho-etch biases that measure the distance between litho and etch contours. The definition of the kernels, as well as the choice of calibration patterns, is critical to get a robust etch model. This work proposes to define a set of independent and anisotropic etch kernels-"internal, external, curvature, Gaussian, z_profile"-designed to represent the finest details of the resist geometry to characterize precisely the etch bias at any point along a resist contour. By evaluating the etch kernels on various structures, it is possible to map their etch signatures in a multidimensional space and analyze them to find an optimal sampling of structures. The etch kernels evaluated on these structures were combined with experimental etch bias derived from scanning electron microscope contours to train artificial neural networks to predict etch bias. The method applied to contact and line/space layers shows an improvement in etch model prediction accuracy over standard etch model. This work emphasizes the importance of the etch kernel definition to characterize and predict complex etch effects.

  8. Walnut consumption increases satiation but has no effect on insulin resistance or the metabolic profile over a 4-day period.

    Science.gov (United States)

    Brennan, Aoife M; Sweeney, Laura L; Liu, Xiaowen; Mantzoros, Christos S

    2010-06-01

    Obesity and diabetes have been associated with increased consumption of highly processed foods, and reduced consumption of whole grains and nuts. It has been proposed, mainly on the basis of observational studies, that nuts may provide superior satiation, may lead to reduced calorie consumption, and may decrease the risk of type 2 diabetes; but evidence from randomized, interventional studies is lacking. A total of 20 men and women with the metabolic syndrome participated in a randomized, double-blind, crossover study of walnut consumption. Subjects had two 4-day admissions to the clinical research center where they were fed an isocaloric diet. In addition, they consumed shakes for breakfast containing either walnuts or placebo (shakes were standardized for calories, carbohydrate, and fat content). Appetite, insulin resistance, and metabolic parameters were measured. We found an increased level of satiety (overall P value = 0.0079) and sense of fullness (P = 0.05) in prelunch questionnaires following the walnut breakfast as compared to the placebo breakfast, with the walnut effect achieving significance on day 3 and 4 (P = 0.02 and P = 0.03). We did not find any change in resting energy expenditure, hormones known to mediate satiety, or insulin resistance when comparing the walnut vs. placebo diet. Walnut consumption over 4 days increased satiety by day 3. Long-term studies are needed to confirm the physiologic role of walnuts, the duration of time needed for these effects to occur, and to elucidate the underlying mechanisms.

  9. 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 ...

  10. 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.

  11. 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 ...

  12. 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 ...

  13. 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...

  14. 7 CFR 51.1441 - Half-kernel.

    Science.gov (United States)

    2010-01-01

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

  15. 7 CFR 51.2296 - Three-fourths half kernel.

    Science.gov (United States)

    2010-01-01

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

  16. 7 CFR 981.401 - Adjusted kernel weight.

    Science.gov (United States)

    2010-01-01

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

  17. 7 CFR 51.1403 - Kernel color classification.

    Science.gov (United States)

    2010-01-01

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

  18. The Linux kernel as flexible product-line architecture

    NARCIS (Netherlands)

    M. de Jonge (Merijn)

    2002-01-01

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

  19. The Influence of Container Type and Potting Medium on Growth of Black Walnut Seedlings

    Science.gov (United States)

    David T. Funk; Paul L Roth; C. K. Celmer

    1980-01-01

    Container size and shape, potting medium, and genotype interacted to influence the growth of black walnut (Juglans nigra L.) seedlings. Larger containers tended to produce larger trees. In tall, narrow, vent-pipe containers, different, proportions of peat and sand in potting media had no effect on total weight; a higher proportion of peat than of very fine sand in...

  20. Soil Structure and Mycorrhizae Encourage Black Walnut Growth on Old Fields

    Science.gov (United States)

    Felix Jr. Ponder

    1979-01-01

    Examination of black walnut seedlings grown in forest and field soils showed all root systems were infected with mycorrhizae; the amount of infection was influenced by treatments. Mean height and dry weight of tops and roots were greater for seedlings grown in forest than field soil. Seedling height growth was not increased by disturbing either soil; but, root dry...

  1. York University PhD Thesis about the voyage of the Walnut

    Index Scriptorium Estoniae

    2007-01-01

    York'i Ülikooli sotsiaalantropoloogia üliõpilase Lynda Männiku uurimistööst, mis käsitleb 1948. a. novembris ohtliku merereisi Briti miinilaeval "Walnut" Rootsist Kanadasse üle elanud inimeste, kelle hulgas oli ka Lynda isa, saatust

  2. Hydroxytyrosol extracts, olive oil and walnuts as functional components in chicken sausages.

    Science.gov (United States)

    Nieto, Gema; Martínez, Lorena; Castillo, Julian; Ros, Gaspar

    2017-08-01

    Olive oil, hydroxytyrosol and walnut can be considered ideal Mediterranean ingredients for their high polyphenolic content and healthy properties. Three extracts of hydroxytyrosol obtained using different extraction processes (HXT 1, 2, 3) (50 ppm) were evaluated for use as antioxidants in eight different chicken sausage formulas enriched in polyunsaturated fatty acids (2.5 g 100 g -1 walnut) or using extra virgin olive oil (20 g 100 g -1 ) as fat replacer. Lipid and protein oxidation, colour, emulsion stability, and the microstructure of the resulting chicken sausages were investigated and a sensory analysis was carried out. The sausages with HXT extracts were found to decrease lipid oxidation and to lead to the loss of thiol groups compared with control sausages. Emulsion stability (capacity to hold water and fat) was greater in the sausages containing olive oil and walnut than in control sausages. In contrast, the HXT extracts produced high emulsion instability (increasing cooking losses). Sensory analysis suggested that two of the HXT extracts studied (HXT 2 and HXT 3 ) were unacceptable, while the acceptability of the other was similar to that of the control products. Sausages incorporating HXT showed different structures than control samples or sausages with olive oil, related to the composition of the emulsion. These results suggest the possibility of replacing animal fat by olive oil and walnut in order to produce healthy meat products. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  3. Chemical Weed Control in a Two-Year-Old Walnut Planting

    Science.gov (United States)

    Gayne G. Erdmann; Leeroy Green

    1967-01-01

    Six herbicide mixtures were sprayed directly on broadleaf weeds and grasses competing with black walnut trees. Mixtures of papquat (1/2 lb/acre) with simazine (4 lb/acre) or atrazine (4 lb/acre), and amitrole (2 lb/acre) plus simazine (4 lb/acre) gave satisfactory weed control which resulted in significantly better tree height and diameter growth.

  4. Effect of weed control treatments on total leaf area of plantation black walnut (Juglans nigra)

    Science.gov (United States)

    Jason Cook; Michael R. Saunders

    2013-01-01

    Determining total tree leaf area is necessary for describing tree carbon balance, growth efficiency, and other measures used in tree-level and stand-level physiological growth models. We examined the effects of vegetation control methods on the total leaf area of sapling-size plantation black walnut trees using allometric approaches. We found significant differences in...

  5. The Effect of the Alcoholic Extract of Walnut on the Testis Tissue of Adult Male Rats

    Directory of Open Access Journals (Sweden)

    M Abedinzade

    2012-08-01

    Methods: In the present experimental study, forty adult male Wistar rats weighing 250-300 grams were divided into five groups. The control group did not receive any treatment. Normal saline was intraperitoneally injected to the control group. Experimental groups received three different doses of alcoholic extract of walnut: 10, 20 and 50 mg/ kg intraperitoneally/daily, respectively. The testes were removed from the abdomen and the tissue sections were studied. The gathered data were analyzed using One-way Analysis of variance and Tukey's range test. Results: Results indicated that walnut extract affect the development and maintenance of spermatogenesis to its final stages, and increased the number of sperms and interstitial cells in the testis. Alcoholic extract of walnut during the test instrument did not have much impact on the structure of the sperm tube tissue. Conclusion: The alcoholic extract of walnut led to the increased activity of the testis and interstitial cells, followed by an increase in sperm cells and reproductive activity of male rats.

  6. Socio-economic potentials and threats to the African walnut in ...

    African Journals Online (AJOL)

    The African walnut, Plukenetia conophora Mull-Arg (Syn. Tetracarpidium conophorum) is an important climber species that contributes immensely to food security and poverty alleviation in communities within the humid tropical forests of West and Central Africa. However, the challenges facing its year-round availability have ...

  7. Localized gene expression changes during adventitious root formation in black walnut (Juglans nigra L.)

    Science.gov (United States)

    Micah E Stevens; Keith E Woeste; Paula M Pijut

    2018-01-01

    Cutting propagation plays a large role in the forestry and horticulture industries where superior genotypes need to be clonally multiplied. Integral to this process is the ability of cuttings to form adventitious roots. Recalcitrance to adventitious root development is a serious hurdle for many woody plant propagation systems including black walnut (Juglans...

  8. Ancient humans influenced the current spatial genetic structure of common walnut populations in Asia

    Science.gov (United States)

    Paola Pollegioni; Keith E. Woeste; Francesca Chiocchini; Stefano Del Lungo; Irene Olimpieri; Virginia Tortolano; Jo Clark; Gabriel E. Hemery; Sergio Mapelli; Maria Emilia Malvolti; Gyaneshwer. Chaubey

    2015-01-01

    Common walnut (Juglans regia L) is an economically important species cultivated worldwide for its wood and nuts. It is generally accepted that J. regia survived and grew spontaneously in almost completely isolated stands in its Asian native range after the Last Glacial Maximum. Despite its natural geographic isolation, J....

  9. Composition, structure and functional properties of protein concentrates and isolates produced from walnut (Juglans regia L.).

    Science.gov (United States)

    Mao, Xiaoying; Hua, Yufei

    2012-01-01

    In this study, composition, structure and the functional properties of protein concentrate (WPC) and protein isolate (WPI) produced from defatted walnut flour (DFWF) were investigated. The results showed that the composition and structure of walnut protein concentrate (WPC) and walnut protein isolate (WPI) were significantly different. The molecular weight distribution of WPI was uniform and the protein composition of DFWF and WPC was complex with the protein aggregation. H(0) of WPC was significantly higher (p structure of WPI was similar to WPC. WPI showed big flaky plate like structures; whereas WPC appeared as a small flaky and more compact structure. The most functional properties of WPI were better than WPC. In comparing most functional properties of WPI and WPC with soybean protein concentrate and isolate, WPI and WPC showed higher fat absorption capacity (FAC). Emulsifying properties and foam properties of WPC and WPI in alkaline pH were comparable with that of soybean protein concentrate and isolate. Walnut protein concentrates and isolates can be considered as potential functional food ingredients.

  10. Quantifying residues from postharvest fumigation of almonds and walnuts with propylene oxide

    Science.gov (United States)

    A novel analytical approach, involving solvent extraction with methyl tert-butyl ether (MTBE) followed by gas chromatography (GC), was developed to quantify residues that result from the postharvest fumigation of almonds and walnuts with propylene oxide (PPO). Verification and quantification of PPO,...

  11. Planted Black Walnut Does Well on Cleared Forest Sites -- if Competition is Controlled

    Science.gov (United States)

    John E. Krajicek

    1975-01-01

    After seven growing seasons, survival of black walnut seedlings planted in cleared forest openings did not differ by competition control treatments. The trees grew somewhat larger where all competing vegetation was controlled but almost as large where only herbaceous competition was controlled. Controlling only woody vegetation was no better than no control of any...

  12. Amino acid profile of raw and boiled seeds of african walnut ...

    African Journals Online (AJOL)

    Principal Component Analysis (PCA) explained close to 50% of the total variability in amino acid composition, identifying arginine, asparagine, lysine, methionine, valine, glutamic acid, leucine, cysteine, threonine, alanine and isoleucine as the key amino acids for describing African walnut seeds in the south-eastern zone of ...

  13. Sorting in-shell walnuts using near infrared spectroscopy for improved drying efficiency and product quality

    Science.gov (United States)

    In the current walnut drying practice, dryers comingle nuts with varying moisture contents (MC) which results in over drying of nuts with low MC and thereby decrease product quality. The objectives of this research were to investigate correlations among near infrared (NIR) spectral data and MC of fr...

  14. 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...

  15. Parsimonious Wavelet Kernel Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Wang Qin

    2015-11-01

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

  16. 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...

  17. Effects of thinning and mixed plantations with Alnus cordata on growth and efficiency of common walnut (Juglans regia L.

    Directory of Open Access Journals (Sweden)

    Giannini T

    2009-01-01

    Full Text Available Results about the effects of thinning and mixed plantations with Italian alder (Alnus cordata Loisel. on growth and efficiency of common walnut (Juglans regia L. plantations for wood production are reported. The study, carried out for six years on sixteen year old plantations, compared three theses: pure common walnut plantation (pure common walnut; 50% common walnut - 50% Italian alder plantation; 25% common walnut - 75% Italian alder plantation. Beyond annual surveys of girth at breast height, total height, stem volume and biomass, several variables, useful to describe canopy and foliage characteristics such as leaf area index (LAI, leaf biomass and photosynthetic active radiation below the canopy, were recorded. Data collected allowed to compare growth at individual and whole stand level, to calculate the net assimilation rate (NAR and to compare the growth efficiency of the three theses. Mixed plantations performed results significantly higher than the pure plantation in terms of growth, LAI and leaf biomass both before and after experimental thinning. With reference only to common walnut, growth in mixed plantations was higher than the pure plantation with differences ranging from +40% to +100%. More relevant differences among pure common walnut, 50% common walnut and 25% common walnut at canopy and foliage characteristics were observed, with LAI values of 1.07, 3.96 e 4.35 m2 m-2 respectively. Results accounted for a general positive effect of Italian alder as accessory tree species on growth and efficiency of mixed plantations, mainly due to the good performances induced in common walnut trees. Such performances were enabled by the good ecological integration between the two species and by the positive effects of N-fixing activity of Italian alder. Experimental thinning applied, although heavy, did not biased the dynamics observed before thinning both in pure and mixed plantations. In addition, they had positive effects on common walnut

  18. Control Transfer in Operating System Kernels

    Science.gov (United States)

    1994-05-13

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

  19. Uranium kernel formation via internal gelation

    International Nuclear Information System (INIS)

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

    2004-01-01

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

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

    International Nuclear Information System (INIS)

    Pellonpaeae, Juha-Pekka

    2009-01-01

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

  1. The Effect of Walnut Oil Consumption on Blood Sugar in Patients With Diabetes Mellitus Type 2.

    Science.gov (United States)

    Zibaeenezhad, Mohammadjavad; Aghasadeghi, Kamran; Hakimi, Hossein; Yarmohammadi, Hassan; Nikaein, Farzad

    2016-07-01

    Prevalence of diabetes mellitus type 2 (DM) is increasing globally. Considering the potential role of poly-unsaturated fatty acids in prevention of DM type 2 and lipid profiles improvement, some studies have been carried out on walnut. However, there are no studies on control of blood sugar in DM type 2 patients using walnut. The current study aimed to evaluate the effect of walnut oil on blood sugar in DM type 2 patients. This randomized control clinical trial was performed on 100 patients with DM type 2. For the experiment group (n = 50), walnut oil (15 g/day for three months) was added to their diet, while the control group (n = 50) did not undergo any interventions. Before initiation of the experiment and after the experiment, the systolic and diastolic blood pressure (SBP and DBP) levels, fasting blood sugar (FBS) and HbA1c were measured. The two groups were not significantly different for SBP, DBP, body weight, and Body Mass Index. HbA1c level decreased significantly in the experiment group by 7.86% ± 21.97 (P = 0.005) from 7.00 ± 1.08 before the intervention to 6.37 ± 1.29 after the intervention. Also, FBS level decreased significantly by 8.24% ± 16.77 (P = 0.001); from 158.37 ± 48.16 before the intervention to 137.91 ± 23.24 after the intervention in the experimental group. These changes in the control group were not significant. Consumption of walnut oil (15 g/day for three months) was shown to improve blood glucose level but, no changes were noted for bodyweight and blood pressure in type two diabetic patients.

  2. 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 ...

  3. Revisiting the definition of local hardness and hardness kernel.

    Science.gov (United States)

    Polanco-Ramírez, Carlos A; Franco-Pérez, Marco; Carmona-Espíndola, Javier; Gázquez, José L; Ayers, Paul W

    2017-05-17

    An analysis of the hardness kernel and local hardness is performed to propose new definitions for these quantities that follow a similar pattern to the one that characterizes the quantities associated with softness, that is, we have derived new definitions for which the integral of the hardness kernel over the whole space of one of the variables leads to local hardness, and the integral of local hardness over the whole space leads to global hardness. A basic aspect of the present approach is that global hardness keeps its identity as the second derivative of energy with respect to the number of electrons. Local hardness thus obtained depends on the first and second derivatives of energy and electron density with respect to the number of electrons. When these derivatives are approximated by a smooth quadratic interpolation of energy, the expression for local hardness reduces to the one intuitively proposed by Meneses, Tiznado, Contreras and Fuentealba. However, when one combines the first directional derivatives with smooth second derivatives one finds additional terms that allow one to differentiate local hardness for electrophilic attack from the one for nucleophilic attack. Numerical results related to electrophilic attacks on substituted pyridines, substituted benzenes and substituted ethenes are presented to show the overall performance of the new definition.

  4. Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

    Energy Technology Data Exchange (ETDEWEB)

    Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha (China)

    2006-10-15

    Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method.

  5. Automatic Modulation Recognition by Support Vector Machines Using Wavelet Kernel

    International Nuclear Information System (INIS)

    Feng, X Z; Yang, J; Luo, F L; Chen, J Y; Zhong, X P

    2006-01-01

    Automatic modulation identification plays a significant role in electronic warfare, electronic surveillance systems and electronic counter measure. The task of modulation recognition of communication signals is to determine the modulation type and signal parameters. In fact, automatic modulation identification can be range to an application of pattern recognition in communication field. The support vector machines (SVM) is a new universal learning machine which is widely used in the fields of pattern recognition, regression estimation and probability density. In this paper, a new method using wavelet kernel function was proposed, which maps the input vector xi into a high dimensional feature space F. In this feature space F, we can construct the optimal hyperplane that realizes the maximal margin in this space. That is to say, we can use SVM to classify the communication signals into two groups, namely analogue modulated signals and digitally modulated signals. In addition, computer simulation results are given at last, which show good performance of the method

  6. 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.

  7. Extraction and Characterization of Natural Dye from Green Walnut Shells and Its Use in Dyeing Polyamide: Focus on Antibacterial Properties

    Directory of Open Access Journals (Sweden)

    Mohammad Mirjalili

    2013-01-01

    Full Text Available Extraction of dyes from walnut using Soxhlet apparatus has been studied. The color components extracted and isolated from walnut shells were characterized by column chromatography, thin layer chromatography (TLC, nuclear magnetic resonance (NMR, mass spectroscopy (MS, and infrared (IR techniques. Natural dye extract obtained from the walnut was used in dyeing polyamide fabrics with different mordants. The dyed fabrics were evaluated for antibacterial activity against pathogenic strains of Gram-positive (Staphylococcus aureus and Gram-negative (Escherichia coli bacteria. As such, the relationship between antibacterial activity and dye concentration is investigated. Durability of antibacterial activity to laundering is also discussed. Results indicate that the polyamide dyed with walnut displayed excellent antibacterial activity in the presence of ferric sulfate, cupric sulfate, and potassium aluminum sulfate and exhibited good and durable fastness properties.

  8. Walnut Polyphenol Extract Attenuates Immunotoxicity Induced by 4-Pentylphenol and 3-methyl-4-nitrophenol in Murine Splenic Lymphocyte

    OpenAIRE

    Lubing Yang; Sihui Ma; Yu Han; Yuhan Wang; Yan Guo; Qiang Weng; Meiyu Xu

    2016-01-01

    4-pentylphenol (PP) and 3-methyl-4-nitrophenol (PNMC), two important components of vehicle emissions, have been shown to confer toxicity in splenocytes. Certain natural products, such as those derived from walnuts, exhibit a range of antioxidative, antitumor, and anti-inflammatory properties. Here, we investigated the effects of walnut polyphenol extract (WPE) on immunotoxicity induced by PP and PNMC in murine splenic lymphocytes. Treatment with WPE was shown to significantly enhance prolifer...

  9. A cross sectional study of the association between walnut consumption and cognitive function among adult US populations represented in NHANES.

    Science.gov (United States)

    Arab, L; Ang, A

    2015-03-01

    To examine the association between walnut consumption and measures of cognitive function in the US population. Nationally representative cross sectional study using 24 hour dietary recalls of intakes to assess walnut and other nut consumption as compared to the group reporting no nut consumption. 1988-1994 and 1999-2002 rounds of the National Health and Nutrition Examination Survey (NHANES). Representative weighted sample of US adults 20 to 90 years of age. The Neurobehavioral Evaluation System 2 (NES2), consisting of simple reaction time (SRTT), symbol digit substitution (SDST), the single digit learning (SDLT), Story Recall (SRT) and digit-symbol substitution (DSST) tests. Adults 20-59 years old reporting walnut consumption of an average of 10.3 g/d required 16.4ms less time to respond on the SRTT, P=0.03, and 0.39s less for the SDST, P=0.01. SDLT scores were also significantly lower by 2.38s (P=0.05). Similar results were obtained when tertiles of walnut consumption were examined in trend analyses. Significantly better outcomes were noted in all cognitive test scores among those with higher walnut consumption (P < 0.01). Among adults 60 years and older, walnut consumers averaged 13.1 g/d, scored 7.1 percentile points higher, P=0.03 on the SRT and 7.3 percentile points higher on the DSST, P=0.05. Here also trend analyses indicate significant improvements in all cognitive test scores (P < 0.01) except for SRTT (P = 0.06) in the fully adjusted models. These significant, positive associations between walnut consumption and cognitive functions among all adults, regardless of age, gender or ethnicity suggest that daily walnut intake may be a simple beneficial dietary behavior.

  10. Aflatoxin contamination of developing corn kernels.

    Science.gov (United States)

    Amer, M A

    2005-01-01

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

  11. 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.

  12. Amino Acid Composition, Molecular Weight Distribution and Gel Electrophoresis of Walnut (Juglans regia L. Proteins and Protein Fractionations

    Directory of Open Access Journals (Sweden)

    Xiaoying Mao

    2014-01-01

    Full Text Available As a by-product of oil production, walnut proteins are considered as an additional source of plant protein for human food. To make full use of the protein resource, a comprehensive understanding of composition and characteristics of walnut proteins are required. Walnut proteins have been fractionated and characterized in this study. Amino acid composition, molecular weight distribution and gel electrophoresis of walnut proteins and protein fractionations were analyzed. The proteins were sequentially separated into four fractions according to their solubility. Glutelin was the main component of the protein extract. The content of glutelin, albumin, globulin and prolamin was about 72.06%, 7.54%, 15.67% and 4.73% respectively. Glutelin, albumin and globulin have a balanced content of essential amino acids, except for methionine, with respect to the FAO pattern recommended for adults. SDS-PAGE patterns of albumin, globulin and glutelin showed several polypeptides with molecular weights 14.4 to 66.2 kDa. The pattern of walnut proteins in two-dimension electrophoresis (2-DE showed that the isoelectric point was mainly in the range of 4.8–6.8. The results of size exclusion chromatogram indicated molecular weight of the major components of walnut proteins were between 3.54 and 81.76 kDa.

  13. Effects of gamma irradiation on the biochemical properties of walnut and pistachio nut in Syria, first phase: just after irradiation

    International Nuclear Information System (INIS)

    Karajoli, M.; Moussa, A.; Al-Kaed, A.; Othman, I.

    1997-05-01

    The report describes a preliminary study that led to explore the possibility of preserving and extending the storage life of walnut and pistachio nut by gamma radiation. Syrian walnut and pistachio nut were irradiated in a Gamma cell (dose rate 0.08 kGy/min). Radiation doses used were 0.50 and 1.00 kGy and the samples were stored at room temperature (25 to 30 Centigrade) after packaging in polyethylene pouches. Fungi infestation was determined before and after gamma radiation treatment. A radiation dose of 1.00 kGy completely inhibited fungi infestation. The present study has, therefore, been conducted to investigate the effects of gamma radiation on the Biochemical properties of walnut and pistachio nut just after irradiation (first phase). Chemical analyses have shown the phosphorus and total proteins value decrease at 0.50 and 1.00 kGy and some significant changes were observed in carbohydrates. A slight decrease in the amount of converted sugars was also observed. Fats in walnut are less vulnerable to gamma radiation than pistachio nut due certainly to the high amount in unsaturated oleic and linoleic acids. In conclusion the effect of gamma radiation on walnut and pantheistic appears nutritionally significant in pistachio nut and less in walnut. More investigations are necessary after a long time of storage to prove their intact nutritional quality and eventually their good digestibility. (author). 6 refs., 6 figs., 22 tabs

  14. effects of gamma irradiation on the biochemical properties of walnut and pistachio nut in Syria, first phase: just after irradiation

    International Nuclear Information System (INIS)

    Othman, I.; Karajoli, M.; Moussa, A.; Al-Kaed, A.

    1998-01-01

    The report describes a preliminary study that led to explore the possibility of preserving and extending the storage life of walnut and pistachio nut by gamma radiation. Syrian walnut and pistachio nut were irradiated in a Gamma cell (dose rate 0.08 kGy/min). Radiation doses used were 0.50 and 1.00 kGy and the samples were stored at room temperature (25 to 30 Centigrade) after packaging in polyethylene pouches. Fungi infestation was determined before and after gamma radiation treatment. A radiation dose of 1.00 kGy completely inhibited fungi infestation. The present study has, therefore, been conducted to investigate the effects of gamma radiation on the Biochemical properties of walnut and pistachio nut just after irradiation (first phase). Chemical analyses have shown the phosphorus and total proteins value decrease at 0.50 and 1.00 kGy and some significant changes were observed in carbohydrates. A slight decrease in the amount of converted sugars was also observed. Fats in walnut are less vulnerable to gamma radiation than pistachio nut due certainly to the high amount in unsaturated oleic and linoleic acids. In conclusion the effect of gamma radiation on walnut and pantheistic appears nutritionally significant in pistachio nut and less in walnut. More investigations are necessary after a long time of storage to prove their intact nutritional quality and eventually their good digestibility. (author). 6 refs

  15. Effects of gamma irradiation on the biochemical properties of walnut and pistachio nut in Syria, first phase: just after irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Karajoli, M; Moussa, A; Al-Kaed, A; Othman, I [Atomic Energy Commission, Radiation Technology Unit, Irradiation Plant, Damascus (Syrian Arab Republic)

    1997-05-01

    The report describes a preliminary study that led to explore the possibility of preserving and extending the storage life of walnut and pistachio nut by gamma radiation. Syrian walnut and pistachio nut were irradiated in a Gamma cell (dose rate 0.08 kGy/min). Radiation doses used were 0.50 and 1.00 kGy and the samples were stored at room temperature (25 to 30 Centigrade) after packaging in polyethylene pouches. Fungi infestation was determined before and after gamma radiation treatment. A radiation dose of 1.00 kGy completely inhibited fungi infestation. The present study has, therefore, been conducted to investigate the effects of gamma radiation on the Biochemical properties of walnut and pistachio nut just after irradiation (first phase). Chemical analyses have shown the phosphorus and total proteins value decrease at 0.50 and 1.00 kGy and some significant changes were observed in carbohydrates. A slight decrease in the amount of converted sugars was also observed. Fats in walnut are less vulnerable to gamma radiation than pistachio nut due certainly to the high amount in unsaturated oleic and linoleic acids. In conclusion the effect of gamma radiation on walnut and pantheistic appears nutritionally significant in pistachio nut and less in walnut. More investigations are necessary after a long time of storage to prove their intact nutritional quality and eventually their good digestibility. (author). 6 refs., 6 figs., 22 tabs.

  16. Effects of gamma irradiation on the biochemical properties of walnut and pistachio nut in Syria, first phase: just after irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Othman, I; Karajoli, M; Moussa, A; Al-Kaed, A [Atomic Energy commission, Radiation Technology Unit, Damascus, (Syrian Arab Republic)

    1998-03-01

    The report describes a preliminary study that led to explore the possibility of preserving and extending the storage life of walnut and pistachio nut by gamma radiation. Syrian walnut and pistachio nut were irradiated in a Gamma cell (dose rate 0.08 kGy/min). Radiation doses used were 0.50 and 1.00 kGy and the samples were stored at room temperature (25 to 30 Centigrade) after packaging in polyethylene pouches. Fungi infestation was determined before and after gamma radiation treatment. A radiation dose of 1.00 kGy completely inhibited fungi infestation. The present study has, therefore, been conducted to investigate the effects of gamma radiation on the Biochemical properties of walnut and pistachio nut just after irradiation (first phase). Chemical analyses have shown the phosphorus and total proteins value decrease at 0.50 and 1.00 kGy and some significant changes were observed in carbohydrates. A slight decrease in the amount of converted sugars was also observed. Fats in walnut are less vulnerable to gamma radiation than pistachio nut due certainly to the high amount in unsaturated oleic and linoleic acids. In conclusion the effect of gamma radiation on walnut and pantheistic appears nutritionally significant in pistachio nut and less in walnut. More investigations are necessary after a long time of storage to prove their intact nutritional quality and eventually their good digestibility. (author). 6 refs.

  17. In-situ biogas upgrading during anaerobic digestion of food waste amended with walnut shell biochar at bench scale.

    Science.gov (United States)

    Linville, Jessica L; Shen, Yanwen; Ignacio-de Leon, Patricia A; Schoene, Robin P; Urgun-Demirtas, Meltem

    2017-06-01

    A modified version of an in-situ CO 2 removal process was applied during anaerobic digestion of food waste with two types of walnut shell biochar at bench scale under batch operating mode. Compared with the coarse walnut shell biochar, the fine walnut shell biochar has a higher ash content (43 vs. 36 wt%) and higher concentrations of calcium (31 vs. 19 wt% of ash), magnesium (8.4 vs. 5.6 wt% of ash) and sodium (23.4 vs. 0.3 wt% of ash), but a lower potassium concentration (0.2 vs. 40% wt% of ash). The 0.96-3.83 g biochar (g VS added ) -1 fine walnut shell biochar amended digesters produced biogas with 77.5%-98.1% CH 4 content by removing 40%-96% of the CO 2 compared with the control digesters at mesophilic and thermophilic temperature conditions. In a direct comparison at 1.83 g biochar (g VS added ) -1 , the fine walnut shell biochar amended digesters (85.7% CH 4 content and 61% CO 2 removal) outperformed the coarse walnut shell biochar amended digesters (78.9% CH 4 content and 51% CO 2 removal). Biochar addition also increased alkalinity as CaCO 3 from 2800 mg L -1 in the control digesters to 4800-6800 mg L -1 , providing process stability for food waste anaerobic digestion.

  18. The effect of partial substitution of pork back fat with vegetable oils and walnuts on chemical composition, texture profile and sensorial properties of meatloaf

    Directory of Open Access Journals (Sweden)

    Gabriel Dănuţ MOCANU

    2015-08-01

    Full Text Available The present study investigates the effects of the partial substitution of the pork back fat with different vegetable oils (sea buckthorn, walnut and sunflower and walnuts on the chemical composition, texture profile and sensory characteristics of meatloaves. The dry matter and ash content of meatloaf with vegetable oils and walnuts were higher than the control sample (P < 0.05. The cooking loss, energy values and lipid oxidation for the samples with walnuts and vegetable oils were lower than the control sample. The meatloaf sample containing walnuts and sea buckthorn oil had the highest total antioxidant capacity. The partial substitution of pork back fat showed a positive effect on textural and sensorial characteristics. Results reveal that the incorporation of vegetable oils and walnuts has successfully reduced the animal fat content in the finite products while improving the quality characteristics.

  19. Non-separable pairing interaction kernels applied to superconducting cuprates

    International Nuclear Information System (INIS)

    Haley, Stephen B.; Fink, Herman J.

    2014-01-01

    Highlights: • Non-separable interaction kernels with weak interactions produces HTS. • A probabilistic approach is used in filling the electronic states in the unit cell. • A set of coupled equations is derived which describes the energy gap. • SC properties of separable with non-separable interactions are compared. • There is agreement with measured properties of the SC and normal states. - Abstract: A pairing Hamiltonian H(Γ) with a non-separable interaction kernel Γ produces HTS for relatively weak interactions. The doping and temperature dependence of Γ(x,T) and the chemical potential μ(x) is determined by a probabilistic filling of the electronic states in the cuprate unit cell. A diverse set of HTS and normal state properties is examined, including the SC phase transition boundary T C (x), SC gap Δ(x,T), entropy S(x,T), specific heat C(x,T), and spin susceptibility χ s (x,T). Detailed x,T agreement with cuprate experiment is obtained for all properties

  20. 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

  1. 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.

  2. 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...

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

    Science.gov (United States)

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

    2017-12-15

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

  4. 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

  5. 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

  6. Reduced multiple empirical kernel learning machine.

    Science.gov (United States)

    Wang, Zhe; Lu, MingZhe; Gao, Daqi

    2015-02-01

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

  7. Sensory evaluation of commercial fat spreads based on oilseeds and walnut

    Directory of Open Access Journals (Sweden)

    Dimić Etelka B.

    2013-01-01

    Full Text Available The main focus of this study was on the sensory evaluation of commercial oilseeds spreads, as the most significant characteristic of this type of product from the consumers’ point of view. Sensory analysis was conducted by five experts using a quantitative descriptive and sensory profile test, applying a scoring method according to the standard procedure. Five different spreads were evaluated: sunflower, pumpkin, sesame, peanut, and walnut. Oil content and amounts of separated oil on the surface were determined for each spread. The results have shown that the color of spreads was very different, depending on the oilseed: gray for sunflower, brown for walnut, yellowish-brown for peanut butter, ivory for sesame and profoundly dark green for pumpkin seeds spread. The flavor and odor of the spreads were characteristic for the raw materials used; however, the sunflower and walnut spreads had a slight rancid flavor. Generally, the spreadability of all spreads was good, but their mouth feel was not acceptable. During the consumption, all of them were sticking immensely to the roof of the mouth, which made the swallowing harder. The highest total score of 16.20 points (max. 20 was obtained for the peanut butter, while the lowest (10.38 was achieved by the sunflower butter. Oil separation (various degrees was noticed in all spreads, which negatively influenced the appearance and entire sensorial quality of the products. The quantity of separated oil depended on the age and total amount of oil in the spreads, and was between 1.13% in the peanut butter and 12.15% in the walnut spread in reference to the net weight of the product. [Projekat Ministarstva nauke Republike Srbije, br. TR 31014: Development of the new functional confectionery products based on oil crops

  8. A new naphthalenone isolated from the green walnut husks of Juglans mandshurica Maxim.

    Science.gov (United States)

    Chen, Guang; Pi, Xin-Mei; Yu, Chang-Yuan

    2015-01-01

    Phytochemical study of green walnut husks of Juglans mandshurica Maxim. led to the isolation of a new naphthalenone, (4R)-3,4-dihydro-4-butoxy-5-hydroxy-naphthalen-1(2H)-one (1), together with 16 known compounds. Compounds 4-6, 13, 14 and 17 were isolated from the genus Juglans for the first time, and their chemotaxonomic significance was also evaluated.

  9. Sensory evaluation of commercial fat spreads based on oilseeds and walnut

    OpenAIRE

    Dimić, Etelka B.; Vujasinović, Vesna B.; Radočaj, Olga F.; Borić, Bojan D.

    2013-01-01

    The main focus of this study was on the sensory evaluation of commercial oilseeds spreads, as the most significant characteristic of this type of product from the consumers’ point of view. Sensory analysis was conducted by five experts using a quantitative descriptive and sensory profile test, applying a scoring method according to the standard procedure. Five different spreads were evaluated: sunflower, pumpkin, sesame, peanut, and walnut. Oil content and ...

  10. 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...

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

    CSIR Research Space (South Africa)

    Van der Walt, Christiaan M

    2017-02-01

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

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

    African Journals Online (AJOL)

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

  13. 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

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Canty, Morton J.

    2010-01-01

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

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

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2009-01-01

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

  16. Estimation of structural attributes of walnut trees based on terrestrial laser scanning

    Directory of Open Access Journals (Sweden)

    J. Estornell

    2017-06-01

    Full Text Available Juglans regia L. (walnut is a tree of significant economic importance, usually cultivated for its seed used in the food market, and for its wood used in the furniture industry. The aim of this work was to develop regression models to predict crown parameters for walnut trees using a terrestrial laser scanner. A set of 30 trees was selected and the total height, crown height and crown diameter were measured in the field. The trees were also measured by a laser scanner and algorithms were applied to compute the crown volume, crown diameter, total and crown height. Linear regression models were calculated to estimate walnut tree parameters from TLS data. Good results were obtained with values of R2 between 0.90 and 0.98. In addition, to analyze whether coarser point cloud densities might affect the results, the point clouds for all trees were subsampled using different point densities: points every 0.005 m, 0.01 m, 0.05 m, 0.1 m, 0.25 m, 0.5 m, 1 m, and 2 m. New regression models were calculated to estimate field parameters. For total height and crown volume good estimations were obtained from TLS parameters derived for all subsampled point cloud (0.005 m – 2 m.

  17. Antioxidant hydrolysed peptides from Manchurian walnut (Juglansmandshurica Maxim.) attenuate scopolamine-induced memory impairment in mice.

    Science.gov (United States)

    Ren, Dayong; Zhao, Fanrui; Liu, Chunlei; Wang, Ji; Guo, Yong; Liu, Jingsheng; Min, Weihong

    2018-04-13

    Walnut protein, which is obtained as a by-product of oil expression, has not been used efficiently. Although walnuts are beneficial for cognitive functioning, the potential of their protein composition in strengthening learning and memory functions remains unknown. In this research, the inhibition of memory impairment by the Manchurian walnut hydrolyzed peptide (MWHP) was evaluated. Small-molecular-weight MWHP (<3 kDa) achieved the optimal antioxidative activity. Therefore, MWHP (<3 kDa) was subjected to the following mice trials to evaluate its attenuation effect on memory impairment. In the Morris water maze test, MWHP shortened the total path for searching the platform, reduced the escape latency, and increased the dwelling distance and time in the coverage zone. MWHP also prolonged the latency and diminished errors in the passive avoidance response tests. These behavioral tests demonstrated that MWHP could inhibit scopolamine-induced memory impairment. MWHP improved memory by reducing oxidative stress, inhibiting apoptosis, regulating neurotransmitter functions, maintaining hippocampal CA3 pyramidal neurons, and increasing p-CaMK II levels in brain tissues. Experimental results proved that MWHP exhibits potential in improving memory and should be used to develop novel functional food. This article is protected by copyright. All rights reserved.

  18. HPLC determination of phenolic acids, flavonoids and juglone in walnut leaves.

    Science.gov (United States)

    Nour, Violeta; Trandafir, Ion; Cosmulescu, Sina

    2013-10-01

    A high-performance liquid chromatographic method with gradient elution and diode-array detection was developed to quantify free phenolic acids (gallic, vanillic, chlorogenic, caffeic, syringic, p-coumaric, ferulic, sinapic, salycilic, elagic and trans-cinnamic), flavonoids (catechin, epicatechin, rutin, myricetin and quercetin) and juglone in walnut leaves. Chromatographic separation was performed on a Hypersil Gold C18 column (5 µm particle size, 250 × 4.6 mm) and detection was conducted at three different wavelengths (254, 278 and 300 nm) according to the absorption maxima of the analyzed compounds. Validation procedures were conducted and the method was proven to be precise, accurate and sensitive. The developed method has been applied to analyze walnut leaves samples from nine different cultivars, with the same agricultural, geographical and climatic conditions. The experimental results revealed high concentrations of myricetin, catechin hydrate and rutin, and low concentrations of quercetin and epicatechin aglycones. Ellagic acid was established as the dominating phenolic acid of walnut leaves, followed by trans-cinnamic, chlorogenic and caffeic acids. Juglone content varied between 44.55 and 205.12 mg/100 g fresh weight. Significant differences were detected among cultivars for the concentration levels of phenolics.

  19. 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.

  20. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    Science.gov (United States)

    2016-01-05

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

  1. Relationship between attenuation coefficients and dose-spread kernels

    International Nuclear Information System (INIS)

    Boyer, A.L.

    1988-01-01

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

  2. Fabrication of Uranium Oxycarbide Kernels for HTR Fuel

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  3. Consistent Estimation of Pricing Kernels from Noisy Price Data

    OpenAIRE

    Vladislav Kargin

    2003-01-01

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

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

    Science.gov (United States)

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

    2017-10-02

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

  5. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

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

    2009-01-01

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

  6. Quantum logic in dagger kernel categories

    NARCIS (Netherlands)

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

    2011-01-01

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

  7. 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.

  8. 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

  9. Reproducing kernel Hilbert spaces of Gaussian priors

    NARCIS (Netherlands)

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

    2008-01-01

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

  10. 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

  11. 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

  12. On convergence of kernel learning estimators

    NARCIS (Netherlands)

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

    2009-01-01

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

  13. 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.)

  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...

  15. Kernel Temporal Differences for Neural Decoding

    Science.gov (United States)

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

    2015-01-01

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

  16. Scattering kernels and cross sections working group

    International Nuclear Information System (INIS)

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

    1998-01-01

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

  17. 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...

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

    African Journals Online (AJOL)

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

  19. Stable Kernel Representations as Nonlinear Left Coprime Factorizations

    NARCIS (Netherlands)

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

    1994-01-01

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

  20. 7 CFR 981.60 - Determination of kernel weight.

    Science.gov (United States)

    2010-01-01

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

  1. 21 CFR 176.350 - Tamarind seed kernel powder.

    Science.gov (United States)

    2010-04-01

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

  2. End-use quality of soft kernel durum wheat

    Science.gov (United States)

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

  3. 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...

  4. A Fast and Simple Graph Kernel for RDF

    NARCIS (Netherlands)

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

    2013-01-01

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

  5. 7 CFR 981.61 - Redetermination of kernel weight.

    Science.gov (United States)

    2010-01-01

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

  6. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

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

  7. Caracterização química e perfil de ácidos graxos em cultivares de nogueira-macadâmia Chemical characterization and fatty acids profile in macadamia walnut cultivars

    Directory of Open Access Journals (Sweden)

    Luana Aparecida Castilho Maro

    2012-12-01

    kernels of all walnut macadamia cultivars showed palmitic and oleic acids.

  8. Scuba: scalable kernel-based gene prioritization.

    Science.gov (United States)

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

    2018-01-25

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

  9. Kernel based orthogonalization for change detection in hyperspectral images

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

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

  10. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

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

    2016-05-01

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

  11. 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.

  12. Difference between standard and quasi-conformal BFKL kernels

    International Nuclear Information System (INIS)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2018-03-14

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

  14. Incidence of Agrobacterium tumefaciens biovar 1 in and on ‘Paradox’ (Juglans hindsii x Juglans regia) walnut seed collected from commercial nurseries

    Science.gov (United States)

    The walnut rootstock Paradox (Juglans hindsii (Jeps) Rehder x J. regia L.) is susceptible to Agrobacterium tumefaciens (7) which often results in a high incidence of crown gall in nursery or walnut production orchards. Though A. tumefaciens is susceptible to the commonly used preplant soil fumigant...

  15. Genetic diversity and genetic structure of Persian walnut (Juglans regia) accessions from 14 European, African, and Asian countries using SSR markers

    Science.gov (United States)

    Aziz Ebrahimi; Abdolkarim Zarei; Shaneka Lawson; Keith E. Woeste; M. J. M. Smulders

    2016-01-01

    Persian walnut (Juglans regia L.) is the world's most widely grown nut crop, but large-scale assessments and comparisons of the genetic diversity of the crop are notably lacking. To guide the conservation and utilization of Persian walnut genetic resources, genotypes (n = 189) from 25 different regions in 14 countries on...

  16. Walnuts lower TRAMP prostate tumor growth by altering IGF-1, energy and cholesterol metabolism and is not due to their fatty acids

    Science.gov (United States)

    Dietary changes could potentially reduce prostate cancer morbidity and mortality. Prostate tumor size, gene expression, metabolite and plasma responses to a 100 g of fat/kg diet (whole walnuts, walnut oil and other oils; balanced for macronutrients, tocopherols (a-and ' ) for 18 weeks were assessed ...

  17. Evaluation of sintering effects on SiC-incorporated UO2 kernels under Ar and Ar–4%H2 environments

    International Nuclear Information System (INIS)

    Silva, Chinthaka M.; Lindemer, Terrence B.; Hunt, Rodney D.; Collins, Jack L.; Terrani, Kurt A.; Snead, Lance L.

    2013-01-01

    Silicon carbide (SiC) is suggested as an oxygen getter in UO 2 kernels used for tristructural isotropic (TRISO) particle fuels and to prevent kernel migration during irradiation. Scanning electron microscopy and X-ray diffractometry analyses performed on sintered kernels verified that an internal gelation process can be used to incorporate SiC in UO 2 fuel kernels. Even though the presence of UC in either argon (Ar) or Ar–4%H 2 sintered samples suggested a lowering of the SiC up to 3.5–1.4 mol%, respectively, the presence of other silicon-related chemical phases indicates the preservation of silicon in the kernels during sintering process. UC formation was presumed to occur by two reactions. The first was by the reaction of SiC with its protective SiO 2 oxide layer on SiC grains to produce volatile SiO and free carbon that subsequently reacted with UO 2 to form UC. The second process was direct UO 2 reaction with SiC grains to form SiO, CO, and UC. A slightly higher density and UC content were observed in the sample sintered in Ar–4%H 2 , but both atmospheres produced kernels with ∼95% of theoretical density. It is suggested that incorporating CO in the sintering gas could prevent UC formation and preserve the initial SiC content

  18. Analytic scattering kernels for neutron thermalization studies

    International Nuclear Information System (INIS)

    Sears, V.F.

    1990-01-01

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

  19. Quantized kernel least mean square algorithm.

    Science.gov (United States)

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

    2012-01-01

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

  20. 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...

  1. 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.

  2. 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...

  3. 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.

  4. 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/

  5. 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)

  6. 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

  7. Genetic variation of common walnut (Juglans regia in Piedmont, Northwestern Italy

    Directory of Open Access Journals (Sweden)

    Ferrazzini D

    2007-12-01

    Full Text Available The European or common walnut is a large tree prized as a multipurpose species: it provides valuable timber and produces a high-quality edible nut. The diffusion of the species in Italy has been largely influenced by the human activity, mainly through germplasm movement, selection of genotypes most suited for wood or fruit production and adaptation induced on fruit crop reproductive materials. As a consequence, genetic variability has been reduced, so that programs aimed at its preservation appear of the utmost importance. 104 walnut plants growing in Piedmont, northwestern Italy, were investigated through genetic variation scored at RAPD loci, yielded by PCR amplification of 10 decamer primers. Among the 101 studied loci, only 53 were polymorphic, showing a low level of genetic variation within the studied material. Genetic differentiation was estimated both at individual and geographical area level. Only in few cases trees growing in the same area showed to be genetically similar, while the differentiation between areas accounted for about 10% of the total variation, according to AMOVA. No significant correlation was found between genetic and geographic distances. The results of the study showed that also in Piedmont (such as it was already demonstrated in other parts of Italy the distribution of common walnut is a direct consequence of the human activity. The selection of individual trees, to be used as basic materials for seed supply, should therefore be based mainly on phenotypic traits, rather than ecological features of the location: in species characterized by artificial diffusion, the adoption of Region of Provenance has a scarce significance and prominence should be given to the phenotype selection.

  8. 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.

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

    Science.gov (United States)

    Kwak, Nojun

    2016-05-20

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

  10. Chemical and amino acid composition of cooked walnut (juglans regia) flour

    International Nuclear Information System (INIS)

    Niyi, H.; Ogungbenle, N.

    2009-01-01

    The proximate analysis of cooked walnut (Juglans regia) flour revealed the composition as protein (14.18%), moisture (11.01%), ash (3.14%), crude fibre (3.03%), crude fat (10.22%), carbohydrate (58.42%), phytate (20.18 mg/g), oxalate (1.13 mg/g) and tannin (2.33%). Glutamic and aspartic acids were the most predominant amino acids in the sample with values of 151.6 mg/g and 89.5 mg/g, respectively. (author)

  11. Impact of root growth and root hydraulic conductance on water availability of young walnut trees

    Science.gov (United States)

    Jerszurki, Daniela; Couvreur, Valentin; Hopmans, Jan W.; Silva, Lucas C. R.; Shackel, Kenneth A.; de Souza, Jorge L. M.

    2015-04-01

    Walnut (Juglans regia L.) is a tree species of high economic importance in the Central Valley of California. This crop has particularly high water requirements, which makes it highly dependent on irrigation. The context of decreasing water availability in the state calls for efficient water management practices, which requires improving our understanding of the relationship between water application and walnut water availability. In addition to the soil's hydraulic conductivity, two plant properties are thought to control the supply of water from the bulk soil to the canopy: (i) root distribution and (ii) plant hydraulic conductance. Even though these properties are clearly linked to crop water requirements, their quantitative relation remains unclear. The aim of this study is to quantitatively explain walnut water requirements under water deficit from continuous measurements of its water consumption, soil and stem water potential, root growth and root system hydraulic conductance. For that purpose, a greenhouse experiment was conducted for a two month period. Young walnut trees were planted in transparent cylindrical pots, equipped with: (i) rhizotron tubes, which allowed for non-invasive monitoring of root growth, (ii) pressure transducer tensiometers for soil water potential, (iii) psychrometers attached to non-transpiring leaves for stem water potential, and (iv) weighing scales for plant transpiration. Treatments consisted of different irrigation rates: 100%, 75% and 50% of potential crop evapotranspiration. Plant responses were compared to predictions from three simple process-based soil-plant-atmosphere models of water flow: (i) a hydraulic model of stomatal regulation based on stem water potential and vapor pressure deficit, (ii) a model of plant hydraulics predicting stem water potential from soil-root interfaces water potential, and (iii) a model of soil water depletion predicting the water potential drop between the bulk soil and soil-root interfaces

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

  13. LZW-Kernel: fast kernel utilizing variable length code blocks from LZW compressors for protein sequence classification.

    Science.gov (United States)

    Filatov, Gleb; Bauwens, Bruno; Kertész-Farkas, Attila

    2018-05-07

    Bioinformatics studies often rely on similarity measures between sequence pairs, which often pose a bottleneck in large-scale sequence analysis. Here, we present a new convolutional kernel function for protein sequences called the LZW-Kernel. It is based on code words identified with the Lempel-Ziv-Welch (LZW) universal text compressor. The LZW-Kernel is an alignment-free method, it is always symmetric, is positive, always provides 1.0 for self-similarity and it can directly be used with Support Vector Machines (SVMs) in classification problems, contrary to normalized compression distance (NCD), which often violates the distance metric properties in practice and requires further techniques to be used with SVMs. The LZW-Kernel is a one-pass algorithm, which makes it particularly plausible for big data applications. Our experimental studies on remote protein homology detection and protein classification tasks reveal that the LZW-Kernel closely approaches the performance of the Local Alignment Kernel (LAK) and the SVM-pairwise method combined with Smith-Waterman (SW) scoring at a fraction of the time. Moreover, the LZW-Kernel outperforms the SVM-pairwise method when combined with BLAST scores, which indicates that the LZW code words might be a better basis for similarity measures than local alignment approximations found with BLAST. In addition, the LZW-Kernel outperforms n-gram based mismatch kernels, hidden Markov model based SAM and Fisher kernel, and protein family based PSI-BLAST, among others. Further advantages include the LZW-Kernel's reliance on a simple idea, its ease of implementation, and its high speed, three times faster than BLAST and several magnitudes faster than SW or LAK in our tests. LZW-Kernel is implemented as a standalone C code and is a free open-source program distributed under GPLv3 license and can be downloaded from https://github.com/kfattila/LZW-Kernel. akerteszfarkas@hse.ru. Supplementary data are available at Bioinformatics Online.

  14. Kernel based eigenvalue-decomposition methods for analysing ham

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Nielsen, Allan Aasbjerg; Møller, Flemming

    2010-01-01

    methods, such as PCA, MAF or MNF. We therefore investigated the applicability of kernel based versions of these transformation. This meant implementing the kernel based methods and developing new theory, since kernel based MAF and MNF is not described in the literature yet. The traditional methods only...... have two factors that are useful for segmentation and none of them can be used to segment the two types of meat. The kernel based methods have a lot of useful factors and they are able to capture the subtle differences in the images. This is illustrated in Figure 1. You can see a comparison of the most...... useful factor of PCA and kernel based PCA respectively in Figure 2. The factor of the kernel based PCA turned out to be able to segment the two types of meat and in general that factor is much more distinct, compared to the traditional factor. After the orthogonal transformation a simple thresholding...

  15. Classification of maize kernels using NIR hyperspectral imaging

    DEFF Research Database (Denmark)

    Williams, Paul; Kucheryavskiy, Sergey V.

    2016-01-01

    NIR hyperspectral imaging was evaluated to classify maize kernels of three hardness categories: hard, medium and soft. Two approaches, pixel-wise and object-wise, were investigated to group kernels according to hardness. The pixel-wise classification assigned a class to every pixel from individual...... and specificity of 0.95 and 0.93). Both feature extraction methods can be recommended for classification of maize kernels on production scale....

  16. Ideal gas scattering kernel for energy dependent cross-sections

    International Nuclear Information System (INIS)

    Rothenstein, W.; Dagan, R.

    1998-01-01

    A third, and final, paper on the calculation of the joint kernel for neutron scattering by an ideal gas in thermal agitation is presented, when the scattering cross-section is energy dependent. The kernel is a function of the neutron energy after scattering, and of the cosine of the scattering angle, as in the case of the ideal gas kernel for a constant bound atom scattering cross-section. The final expression is suitable for numerical calculations

  17. Application of walnut shell modified with Zinc Oxide (ZnO nanoparticles in removal of natural organic matters (NOMs from aqueous solution

    Directory of Open Access Journals (Sweden)

    ali naghizadeh

    2015-10-01

    Full Text Available Background & Aims of the Study: Natural organic matters (NOMs are a mixture of chemically complex polyelectrolytes produced mainly from the decomposition of plant and animal residues that are present in all surface and groundwater resources. This paper evaluates the aqueous NOMs adsorption efficiency on walnut shell modified with Zinc Oxide (ZnO. Materials & Methods: This study examined the feasibility of removing NOMs from aqueous solutions using walnut shell modified with ZnO. The effects of NOMs concentration, modified walnut shell with ZnO dosage, and pH on adsorption of NOMs by modified walnut shell with ZnO were evaluated. Results: The adsorption capacities of modified walnut shell with ZnO in the best conditions were 37.93 mg/g. The results also demonstrated that adsorption capacity of NOMs on modified walnut shell with ZnO was higher in lower pHs due to significantly high electrostatic attraction exists between the positively charged surface of the adsorbent and negatively charged NOMs. And finally adsorption capacity decreases as adsorbent dose increase. Conclusion: Walnut shell modified with ZnO can be proposed as a natural adsorbent in the removal of NOMs from aqueous solutions

  18. A mind cleared by walnut oil: The effects of polyunsaturated and saturated fat on extinction learning.

    Science.gov (United States)

    Miller, Holly C; Struyf, Dieter; Baptist, Pascale; Dalile, Boushra; Van Oudenhove, Lukas; Van Diest, Ilse

    2018-04-07

    The treatment of anxiety-based psychopathology often hinges upon extinction learning. Research in nutritional neuroscience has observed that the regular consumption of perilla oil (50% alpha-linolenic acid (ALA)) facilitates extinction learning in rats (Yamamoto et al., 1988). However, acute facilitation of extinction learning by oils rich in ALA has not been reported for rats or humans, though the acute consumption of rapeseed oil (10% ALA) has been observed to improve cognitive processing speed in humans (Jones, Sünram-Lea, & Wesnes, 2012). For this reason, the present laboratory work examined the effects of adding walnut oil (12% ALA) to a chocolate milkshake on the acquisition, generalization, and extinction of a fear-based prediction in young adults. It compared performance between subjects. The other participants consumed a similar milkshake with either an equicaloric amount of cream (saturated fat), or with no added fat (control). Acquisition and generalization of the fear-based prediction were similar for all groups. However, those who consumed walnut oil extinguished most rapidly and profoundly. Implications for extinction learning are discussed. Copyright © 2018. Published by Elsevier Ltd.

  19. Comparison of Neuroprotective and Cognition-Enhancing Properties of Hydrolysates from Soybean, Walnut, and Peanut Protein

    Directory of Open Access Journals (Sweden)

    Wenzhi Li

    2016-01-01

    Full Text Available Hydrolysates were prepared from soybean, walnut, and peanut protein by papain, respectively. Their amino acid compositions and molecular weight distributions, the effects of various hydrolysates on H2O2-induced injury PC12 cells, and cognition of mice were investigated, respectively. Results showed that the three hydrolysates were dominated by the peptides with 1–3 KDa with large amount of neurotrophic amino acids. All the hydrolysates exhibited much stronger inhibitory activity against H2O2-induced toxicity than cerebrolysin, and soy protein hydrolysate showed the highest activity. Moreover, the hydrolysates also could reduce the rate of nonviable apoptotic cells at the concentration of 2 mg/mL. The test of animal’s cognition indicated that three hydrolysates could present partly better effect of improving recurred memory ability of normal mice and consolidated memory ability of anisodine-treated mice than piracetam. Therefore, soybean, walnut, and peanut protein hydrolysates were recommended as a potential food raw material for prevention or treatment of neurodegenerative disorders.

  20. Removal of mercury from water by carbonaceous sorbents derived from walnut shell

    International Nuclear Information System (INIS)

    Zabihi, M.; Ahmadpour, A.; Asl, A. Haghighi

    2009-01-01

    The adsorption ability of a powdered activated carbon (PAC) derived from walnut shell was investigated in an attempt to produce more economic and effective sorbent for the control of Hg(II) ion from industrial liquid streams. Carbonaceous sorbents derived from Iranian walnut shell (WS) were prepared by chemical activation method using ZnCl 2 as an activating reagent. To the best of our knowledge, this adsorbent was not used before for removing mercury from water. Adsorption of Hg(II) from aqueous solutions was carried out under different experimental conditions by varying treatment time, metal ion concentration, adsorbent amount, pH and solution temperature. It was determined that Hg(II) adsorption follows both Langmuir and Freundlich isotherms as well as pseudo-second-order kinetics. It was also shown that Hg(II) uptake decreases with increasing pH of the solution. The proper choice of preparation conditions resulted in a microporous activated carbon with 0.45 g/cm 3 density, 737 mg/g iodine number and 780 m 2 /g BET surface area. The monolayer sorption capacity of this optimum adsorbent was obtained as 151.5 mg/g.

  1. Embedded real-time operating system micro kernel design

    Science.gov (United States)

    Cheng, Xiao-hui; Li, Ming-qiang; Wang, Xin-zheng

    2005-12-01

    Embedded systems usually require a real-time character. Base on an 8051 microcontroller, an embedded real-time operating system micro kernel is proposed consisting of six parts, including a critical section process, task scheduling, interruption handle, semaphore and message mailbox communication, clock managent and memory managent. Distributed CPU and other resources are among tasks rationally according to the importance and urgency. The design proposed here provides the position, definition, function and principle of micro kernel. The kernel runs on the platform of an ATMEL AT89C51 microcontroller. Simulation results prove that the designed micro kernel is stable and reliable and has quick response while operating in an application system.

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2014-10-01

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

  4. 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

  5. Hadamard Kernel SVM with applications for breast cancer outcome predictions.

    Science.gov (United States)

    Jiang, Hao; Ching, Wai-Ki; Cheung, Wai-Shun; Hou, Wenpin; Yin, Hong

    2017-12-21

    Breast cancer is one of the leading causes of deaths for women. It is of great necessity to develop effective methods for breast cancer detection and diagnosis. Recent studies have focused on gene-based signatures for outcome predictions. Kernel SVM for its discriminative power in dealing with small sample pattern recognition problems has attracted a lot attention. But how to select or construct an appropriate kernel for a specified problem still needs further investigation. Here we propose a novel kernel (Hadamard Kernel) in conjunction with Support Vector Machines (SVMs) to address the problem of breast cancer outcome prediction using gene expression data. Hadamard Kernel outperform the classical kernels and correlation kernel in terms of Area under the ROC Curve (AUC) values where a number of real-world data sets are adopted to test the performance of different methods. Hadamard Kernel SVM is effective for breast cancer predictions, either in terms of prognosis or diagnosis. It may benefit patients by guiding therapeutic options. Apart from that, it would be a valuable addition to the current SVM kernel families. We hope it will contribute to the wider biology and related communities.

  6. 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....

  7. Analysis of Advanced Fuel Kernel Technology

    International Nuclear Information System (INIS)

    Oh, Seung Chul; Jeong, Kyung Chai; Kim, Yeon Ku; Kim, Young Min; Kim, Woong Ki; Lee, Young Woo; Cho, Moon Sung

    2010-03-01

    The reference fuel for prismatic reactor concepts is based on use of an LEU UCO TRISO fissile particle. This fuel form was selected in the early 1980s for large high-temperature gas-cooled reactor (HTGR) concepts using LEU, and the selection was reconfirmed for modular designs in the mid-1980s. Limited existing irradiation data on LEU UCO TRISO fuel indicate the need for a substantial improvement in performance with regard to in-pile gaseous fission product release. Existing accident testing data on LEU UCO TRISO fuel are extremely limited, but it is generally expected that performance would be similar to that of LEU UO 2 TRISO fuel if performance under irradiation were successfully improved. Initial HTGR fuel technology was based on carbide fuel forms. In the early 1980s, as HTGR technology was transitioning from high-enriched uranium (HEU) fuel to LEU fuel. An initial effort focused on LEU prismatic design for large HTGRs resulted in the selection of UCO kernels for the fissile particles and thorium oxide (ThO 2 ) for the fertile particles. The primary reason for selection of the UCO kernel over UO 2 was reduced CO pressure, allowing higher burnup for equivalent coating thicknesses and reduced potential for kernel migration, an important failure mechanism in earlier fuels. A subsequent assessment in the mid-1980s considering modular HTGR concepts again reached agreement on UCO for the fissile particle for a prismatic design. In the early 1990s, plant cost-reduction studies led to a decision to change the fertile material from thorium to natural uranium, primarily because of a lower long-term decay heat level for the natural uranium fissile particles. Ongoing economic optimization in combination with anticipated capabilities of the UCO particles resulted in peak fissile particle burnup projection of 26% FIMA in steam cycle and gas turbine concepts

  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. Research of Performance Linux Kernel File Systems

    Directory of Open Access Journals (Sweden)

    Andrey Vladimirovich Ostroukh

    2015-10-01

    Full Text Available The article describes the most common Linux Kernel File Systems. The research was carried out on a personal computer, the characteristics of which are written in the article. The study was performed on a typical workstation running GNU/Linux with below characteristics. On a personal computer for measuring the file performance, has been installed the necessary software. Based on the results, conclusions and proposed recommendations for use of file systems. Identified and recommended by the best ways to store data.

  10. 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

  11. Reciprocity relation for multichannel coupling kernels

    International Nuclear Information System (INIS)

    Cotanch, S.R.; Satchler, G.R.

    1981-01-01

    Assuming time-reversal invariance of the many-body Hamiltonian, it is proven that the kernels in a general coupled-channels formulation are symmetric, to within a specified spin-dependent phase, under the interchange of channel labels and coordinates. The theorem is valid for both Hermitian and suitably chosen non-Hermitian Hamiltonians which contain complex effective interactions. While of direct practical consequence for nuclear rearrangement reactions, the reciprocity relation is also appropriate for other areas of physics which involve coupled-channels analysis

  12. Evaluations and modifications of semi-selective media for improved isolation of Agrobacterium tumefaciens biovar 1 from cultivated walnut

    Science.gov (United States)

    Agrobacterium tumefaciens, the causal agent of crown gall of walnut, is an aerobic, Gram negative bacterium belonging to the family Rhizobiaceae. Like many in this group, A. tumefaciens is a common inhabitant of soil and plant host tissue. Isolation from these complex environments is difficult even ...

  13. The Influence of Atmosphere on the Oxidation of Ground Walnut During Storage at 20 °C

    Directory of Open Access Journals (Sweden)

    Rajko Vidrih

    2012-01-01

    Full Text Available The aim of this study is to determine the impact of atmosphere on the oxidation of ground walnut during storage at 20 °C. Seven varieties of walnut (Juglans regia L. were ground and stored under O2 or N2 atmospheres in hermetically sealed vials for 10 months at room temperature. Antioxidative potential, total phenolic content, fatty acid composition, and oxidative degradation products were determined after 10 months of storage. Cultivar, atmosphere and cultivar×atmosphere interactions significantly influenced the antioxidative potential. Cultivar and atmosphere significantly influenced the content of total polyphenols, with more polyphenols found in walnut stored in the N2 atmosphere. The mass fraction of unsaturated linolenic acid tended to decrease during storage under the O2 atmosphere; statistically significant differences were only found between individual varieties. The O2 atmosphere also resulted in an increase in the synthesis of oxidative degradation products. Among the degradation products, hexanal was the most abundant volatile compound, followed by 1-octen-3-ol, octanal, as well as the mixture of 2-octenal and 1-octen-3-ol. In general, higher concentrations of these degradation products were found in walnut stored under the O2 atmosphere, although these differences were statistically significant only between individual varieties for some compounds.

  14. Response of northern red oak, black walnut, and white ash seedlings to various levels of simulated summer deer browsing

    Science.gov (United States)

    Robert C. Morrissey; Douglass F. Jacobs; John R. Seifert

    2008-01-01

    Understanding the response of tree seedlings to browsing by white-tailed deer (Odocoileus virginianus Zimmerman) is critical to the management of high value hardwood plantations in the Central Hardwood Forest Region. One-year-old black walnut (Juglans nigra L.), northern red oak (Quercus rubra L.), and white ash...

  15. Seasonal changes in english walnut (Juglans regia L.) (Juglandaceae), fruit properties and host use patterns by Rhagoletis zoqui (Diptera: Tephritidae)

    Science.gov (United States)

    Rhagoletis zoqui Bush is a Neosubtropical, univoltine, frugivorous tephritid fly that exploits both native Juglans spp. and the introduced, Palearctic English walnut, Juglans regia. The seasonal development of commercial J. regia fruit and the pattern of host exploitation by R. zoqui were tracked ov...

  16. Rooting and Other Characteristics of a Transgenic Walnut Hybrid (Juglans hindsii x J. regia) Rootstock Expressing rolABC

    Science.gov (United States)

    Kourosh Vahdati; James R. McKenna; Abhaya M. Dandekar; Charles A. Leslie; Sandie L. Uratsu; Wesley P. Hackett; Paola Negri; Gale H. McGranahan

    2002-01-01

    Walnuts (Juglans spp.) are difficult-to-root woody plants. The rolABC genes (rolA + rolB + rolC), derived from the bacteria Agrobacterium rhizogenes, have been shown to increase the rooting potential of other difficult-to-root woody plants. We inserted the...

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

    Indian Academy of Sciences (India)

    2011-12-02

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

  18. Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods

    DEFF Research Database (Denmark)

    Arenas-Garcia, J.; Petersen, K.; Camps-Valls, G.

    2013-01-01

    correlation analysis (CCA), and orthonormalized PLS (OPLS), as well as their nonlinear extensions derived by means of the theory of reproducing kernel Hilbert spaces (RKHSs). We also review their connections to other methods for classification and statistical dependence estimation and introduce some recent...

  19. Kernel learning at the first level of inference.

    Science.gov (United States)

    Cawley, Gavin C; Talbot, Nicola L C

    2014-05-01

    Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Electronics

    Science.gov (United States)

    2001-01-01

    International Acer Incorporated, Hsin Chu, Taiwan Aerospace Industrial Development Corporation, Taichung, Taiwan American Institute of Taiwan, Taipei, Taiwan...Singapore and Malaysia .5 - 4 - The largest market for semiconductor products is the high technology consumer electronics industry that consumes up...Singapore, and Malaysia . A new semiconductor facility costs around $3 billion to build and takes about two years to become operational

  1. 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.

  2. Consistent Valuation across Curves Using Pricing Kernels

    Directory of Open Access Journals (Sweden)

    Andrea Macrina

    2018-03-01

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

  3. Aligning Biomolecular Networks Using Modular Graph Kernels

    Science.gov (United States)

    Towfic, Fadi; Greenlee, M. Heather West; Honavar, Vasant

    Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. We explore a class of algorithms for aligning large biomolecular networks by breaking down such networks into subgraphs and computing the alignment of the networks based on the alignment of their subgraphs. The resulting subnetworks are compared using graph kernels as scoring functions. We provide implementations of the resulting algorithms as part of BiNA, an open source biomolecular network alignment toolkit. Our experiments using Drosophila melanogaster, Saccharomyces cerevisiae, Mus musculus and Homo sapiens protein-protein interaction networks extracted from the DIP repository of protein-protein interaction data demonstrate that the performance of the proposed algorithms (as measured by % GO term enrichment of subnetworks identified by the alignment) is competitive with some of the state-of-the-art algorithms for pair-wise alignment of large protein-protein interaction networks. Our results also show that the inter-species similarity scores computed based on graph kernels can be used to cluster the species into a species tree that is consistent with the known phylogenetic relationships among the species.

  4. 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.

  5. Formal truncations of connected kernel equations

    International Nuclear Information System (INIS)

    Dixon, R.M.

    1977-01-01

    The Connected Kernel Equations (CKE) of Alt, Grassberger and Sandhas (AGS); Kouri, Levin and Tobocman (KLT); and Bencze, Redish and Sloan (BRS) are compared against reaction theory criteria after formal channel space and/or operator truncations have been introduced. The Channel Coupling Class concept is used to study the structure of these CKE's. The related wave function formalism of Sandhas, of L'Huillier, Redish and Tandy and of Kouri, Krueger and Levin are also presented. New N-body connected kernel equations which are generalizations of the Lovelace three-body equations are derived. A method for systematically constructing fewer body models from the N-body BRS and generalized Lovelace (GL) equations is developed. The formally truncated AGS, BRS, KLT and GL equations are analyzed by employing the criteria of reciprocity and two-cluster unitarity. Reciprocity considerations suggest that formal truncations of BRS, KLT and GL equations can lead to reciprocity-violating results. This study suggests that atomic problems should employ three-cluster connected truncations and that the two-cluster connected truncations should be a useful starting point for nuclear systems

  6. 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.

  7. 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.

  8. 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.

  9. 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

  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. Capturing option anomalies with a variance-dependent pricing kernel

    NARCIS (Netherlands)

    Christoffersen, P.; Heston, S.; Jacobs, K.

    2013-01-01

    We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

  13. 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...

  14. 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.

  15. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

  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. Geodesic exponential kernels: When Curvature and Linearity Conflict

    DEFF Research Database (Denmark)

    Feragen, Aase; Lauze, François; Hauberg, Søren

    2015-01-01

    manifold, the geodesic Gaussian kernel is only positive definite if the Riemannian manifold is Euclidean. This implies that any attempt to design geodesic Gaussian kernels on curved Riemannian manifolds is futile. However, we show that for spaces with conditionally negative definite distances the geodesic...

  18. 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...

  19. 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 ...

  20. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

  1. Genetic relationship between plant growth, shoot and kernel sizes in ...

    African Journals Online (AJOL)

    Maize (Zea mays L.) ear vascular tissue transports nutrients that contribute to grain yield. To assess kernel heritabilities that govern ear development and plant growth, field studies were conducted to determine the combining abilities of parents that differed for kernel-size, grain-filling rates and shoot-size. Thirty two hybrids ...

  2. 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

  3. 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

  4. Oven-drying reduces ruminal starch degradation in maize kernels

    NARCIS (Netherlands)

    Ali, M.; Cone, J.W.; Hendriks, W.H.; Struik, P.C.

    2014-01-01

    The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels

  5. 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.

  6. Resolvent kernel for the Kohn Laplacian on Heisenberg groups

    Directory of Open Access Journals (Sweden)

    Neur Eddine Askour

    2002-07-01

    Full Text Available We present a formula that relates the Kohn Laplacian on Heisenberg groups and the magnetic Laplacian. Then we obtain the resolvent kernel for the Kohn Laplacian and find its spectral density. We conclude by obtaining the Green kernel for fractional powers of the Kohn Laplacian.

  7. Reproducing Kernels and Coherent States on Julia Sets

    Energy Technology Data Exchange (ETDEWEB)

    Thirulogasanthar, K., E-mail: santhar@cs.concordia.ca; Krzyzak, A. [Concordia University, Department of Computer Science and Software Engineering (Canada)], E-mail: krzyzak@cs.concordia.ca; Honnouvo, G. [Concordia University, Department of Mathematics and Statistics (Canada)], E-mail: g_honnouvo@yahoo.fr

    2007-11-15

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems.

  8. Reproducing Kernels and Coherent States on Julia Sets

    International Nuclear Information System (INIS)

    Thirulogasanthar, K.; Krzyzak, A.; Honnouvo, G.

    2007-01-01

    We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems

  9. 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...

  10. Comparison of Kernel Equating and Item Response Theory Equating Methods

    Science.gov (United States)

    Meng, Yu

    2012-01-01

    The kernel method of test equating is a unified approach to test equating with some advantages over traditional equating methods. Therefore, it is important to evaluate in a comprehensive way the usefulness and appropriateness of the Kernel equating (KE) method, as well as its advantages and disadvantages compared with several popular item…

  11. An analysis of 1-D smoothed particle hydrodynamics kernels

    International Nuclear Information System (INIS)

    Fulk, D.A.; Quinn, D.W.

    1996-01-01

    In this paper, the smoothed particle hydrodynamics (SPH) kernel is analyzed, resulting in measures of merit for one-dimensional SPH. Various methods of obtaining an objective measure of the quality and accuracy of the SPH kernel are addressed. Since the kernel is the key element in the SPH methodology, this should be of primary concern to any user of SPH. The results of this work are two measures of merit, one for smooth data and one near shocks. The measure of merit for smooth data is shown to be quite accurate and a useful delineator of better and poorer kernels. The measure of merit for non-smooth data is not quite as accurate, but results indicate the kernel is much less important for these types of problems. In addition to the theory, 20 kernels are analyzed using the measure of merit demonstrating the general usefulness of the measure of merit and the individual kernels. In general, it was decided that bell-shaped kernels perform better than other shapes. 12 refs., 16 figs., 7 tabs

  12. Optimal Bandwidth Selection in Observed-Score Kernel Equating

    Science.gov (United States)

    Häggström, Jenny; Wiberg, Marie

    2014-01-01

    The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

  13. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, Jeroen

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  14. Computing an element in the lexicographic kernel of a game

    NARCIS (Netherlands)

    Faigle, U.; Kern, Walter; Kuipers, J.

    2002-01-01

    The lexicographic kernel of a game lexicographically maximizes the surplusses $s_{ij}$ (rather than the excesses as would the nucleolus). We show that an element in the lexicographic kernel can be computed efficiently, provided we can efficiently compute the surplusses $s_{ij}(x)$ corresponding to a

  15. Removal of Malachite Green Dye by Mangifera indica Seed Kernel Powder

    Science.gov (United States)

    Singh, Dilbagh; Sowmya, V.; Abinandan, S.; Shanthakumar, S.

    2017-11-01

    In this study, batch experiments were carried out to study the adsorption of Malachite green dye from aqueous solution by Mangifera indica (mango) seed kernel powder. The mango seed kernel powder was characterized by Fourier transform infrared spectroscopy and scanning electron microscopy. Effect of various parameters including pH, contact time, adsorbent dosage, initial dye concentration and temperature on adsorption capacity of the adsorbent was observed and the optimized condition for maximum dye removal was identified. Maximum percentage removal of 96% was achieved with an adsorption capacity of 22.8 mg/g at pH 6 with an initial concentration of 100 mg/l. The equilibrium data were examined to fit the Langmuir and Freundlich isotherm models. Thermodynamic parameters for the adsorption process were also calculated.

  16. Aida-CMK multi-algorithm optimization kernel applied to analog IC sizing

    CERN Document Server

    Lourenço, Ricardo; Horta, Nuno

    2015-01-01

    This work addresses the research and development of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this works describes the modifications inside the AIDA Framework, an electronic design automation framework fully developed by at the Integrated Circuits Group-LX of the Instituto de Telecomunicações, Lisbon. It focusses on AIDA-CMK, by enhancing AIDA-C, which is the circuit optimizer component of AIDA, with a new multi-objective multi-constraint optimization module that constructs a base for multiple algorithm implementations. The proposed solution implements three approaches to multi-objective multi-constraint optimization, namely, an evolutionary approach with NSGAII, a swarm intelligence approach with MOPSO and stochastic hill climbing approach with MOSA. Moreover, the implemented structure allows the easy hybridization between kernels transforming the previous simple NSGAII optimization module into a more evolved and versatile module supporting multiple s...

  17. 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.

  18. Anatomically-aided PET reconstruction using the kernel method.

    Science.gov (United States)

    Hutchcroft, Will; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

    2016-09-21

    This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model. In contrast to existing methods that incorporate anatomical information using a penalized likelihood framework, the proposed method incorporates this information in the simpler maximum likelihood (ML) formulation and is amenable to ordered subsets. The new method also does not require any segmentation of the anatomical image to obtain edge information. We compare the kernel method with the Bowsher method for anatomically-aided PET image reconstruction through a simulated data set. Computer simulations demonstrate that the kernel method offers advantages over the Bowsher method in region of interest quantification. Additionally the kernel method is applied to a 3D patient data set. The kernel method results in reduced noise at a matched contrast level compared with the conventional ML expectation maximization algorithm.

  19. 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....

  20. 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.

  1. Surface Water Interim Measures/Interim Remedial Action Plan/Environmental Assessment and Decision Document, South Walnut Creek Basin, Operable Unit No. 2

    International Nuclear Information System (INIS)

    1991-01-01

    Volume 2 of this IM/IRA Plan contains OU 2 surface water, sediment, ground water and soil chemistry data, as well as the South Walnut Creek Basin Surface Water IM/IRA schedule and a tabulation of ARARs. (FL)

  2. Mortality and reduced brood production in walnut twig beetles, Pityophthorus juglandis (Coleoptera: Curculionidae), following exposure to commercial strains of entomopathogenic fungi Beauveria bassiana and Metarhizium brunneum

    Science.gov (United States)

    Louela A. Castrillo; Albert E. Mayfield; Michael H. Griggs; Robert Camp; Bryan Mudder; Adam Taylor; John D. Vandenberg

    2017-01-01

    Thousand cankers disease (TCD), caused by the walnut twig beetle (WTB), Pityophthorus juglandis, and its associated fungal symbiont, Geosmithia morbida, is a disease of economic and ecological concern on eastern black...

  3. A comparative fluctuating asymmetry study between two walnut (Juglans regia L.) populations may contribute as an early signal for bio-monitoring

    NARCIS (Netherlands)

    Kourmpetis, Y.I.A.; Aravanopoulos, F.A.

    2010-01-01

    Developmental stability, the ability of an individual to eliminate environmental disturbances while expressing a heritable phenotypic trait, was compared in two walnut (Juglans regia L.) populations, a natural and an artificial. Bilateral leaf morphometrics were used to estimate fluctuating

  4. Improved modeling of clinical data with kernel methods.

    Science.gov (United States)

    Daemen, Anneleen; Timmerman, Dirk; Van den Bosch, Thierry; Bottomley, Cecilia; Kirk, Emma; Van Holsbeke, Caroline; Valentin, Lil; Bourne, Tom; De Moor, Bart

    2012-02-01

    Despite the rise of high-throughput technologies, clinical data such as age, gender and medical history guide clinical management for most diseases and examinations. To improve clinical management, available patient information should be fully exploited. This requires appropriate modeling of relevant parameters. When kernel methods are used, traditional kernel functions such as the linear kernel are often applied to the set of clinical parameters. These kernel functions, however, have their disadvantages due to the specific characteristics of clinical data, being a mix of variable types with each variable its own range. We propose a new kernel function specifically adapted to the characteristics of clinical data. The clinical kernel function provides a better representation of patients' similarity by equalizing the influence of all variables and taking into account the range r of the variables. Moreover, it is robust with respect to changes in r. Incorporated in a least squares support vector machine, the new kernel function results in significantly improved diagnosis, prognosis and prediction of therapy response. This is illustrated on four clinical data sets within gynecology, with an average increase in test area under the ROC curve (AUC) of 0.023, 0.021, 0.122 and 0.019, respectively. Moreover, when combining clinical parameters and expression data in three case studies on breast cancer, results improved overall with use of the new kernel function and when considering both data types in a weighted fashion, with a larger weight assigned to the clinical parameters. The increase in AUC with respect to a standard kernel function and/or unweighted data combination was maximum 0.127, 0.042 and 0.118 for the three case studies. For clinical data consisting of variables of different types, the proposed kernel function--which takes into account the type and range of each variable--has shown to be a better alternative for linear and non-linear classification problems

  5. Activated carbons prepared from hazelnut shells, walnut shells and peanut shells for high CO2 adsorption

    Directory of Open Access Journals (Sweden)

    Lewicka Katarzyna

    2017-06-01

    Full Text Available Research treats about producing activated carbons for CO2 capture from hazelnut shells (HN, walnut shells (WN and peanut shells (PN. Saturated solution of KOH was used as an activating agent in ratio 1:1. Samples were carbonized in the furnace in the range of temperatures 600°C–900°C. Properties of carbons were tested by N2 adsorption method, using BET equation, DFT method and volumetric CO2 adsorption method. With the increase of carbonization temperature specific surface area of studied samples increased. The largest surface area was calculated for samples carbonized at 900°C and the highest values of CO2 adsorption had samples: PN900 at 0°C (5.5 mmol/g and WN900 at 25°C (4.34 mmol/g. All of the samples had a well-developed microporous structure.

  6. Determination of fatty acid composition of γ-irradiated hazelnuts, walnuts, almonds, and pistachios

    International Nuclear Information System (INIS)

    Gecgel, Umit; Gumus, Tuncay; Tasan, Murat; Daglioglu, Orhan; Arici, Muhammet

    2011-01-01

    Hazelnut, walnut, almonds, and pistachio nuts were treated with 1, 3, 5, and 7 kGy of gamma irradiation, respectively. Oil content, free fatty acid, peroxide value, and fatty acid composition of the nuts were investigated immediately after irradiation. The data obtained from the experiments indicated that gamma irradiation did not cause any significant change in the oil content of nuts. In contrast, free fatty acid and peroxide value of the nuts increased proportionally to the dose (p<0.05). Among the fatty acids determined, the concentration of total saturated fatty acids increased while total monounsaturated and total polyunsaturated fatty acids decreased with the irradiation dose (p<0.05 and <0.01).

  7. Determination of fatty acid composition of γ-irradiated hazelnuts, walnuts, almonds, and pistachios

    Science.gov (United States)

    Gecgel, Umit; Gumus, Tuncay; Tasan, Murat; Daglioglu, Orhan; Arici, Muhammet

    2011-04-01

    Hazelnut, walnut, almonds, and pistachio nuts were treated with 1, 3, 5, and 7 kGy of gamma irradiation, respectively. Oil content, free fatty acid, peroxide value, and fatty acid composition of the nuts were investigated immediately after irradiation. The data obtained from the experiments indicated that gamma irradiation did not cause any significant change in the oil content of nuts. In contrast, free fatty acid and peroxide value of the nuts increased proportionally to the dose (p<0.05). Among the fatty acids determined, the concentration of total saturated fatty acids increased while total monounsaturated and total polyunsaturated fatty acids decreased with the irradiation dose (p<0.05 and <0.01).

  8. Determination of fatty acid composition of {gamma}-irradiated hazelnuts, walnuts, almonds, and pistachios

    Energy Technology Data Exchange (ETDEWEB)

    Gecgel, Umit [Namik Kemal University, Agricultural Faculty, Department of Food Engineering, 59030 Tekirdag (Turkey); Gumus, Tuncay; Tasan, Murat; Daglioglu, Orhan; Arici, Muhammet [Namik Kemal University, Agricultural Faculty, Department of Food Engineering, 59030 Tekirdag (Turkey)

    2011-04-15

    Hazelnut, walnut, almonds, and pistachio nuts were treated with 1, 3, 5, and 7 kGy of gamma irradiation, respectively. Oil content, free fatty acid, peroxide value, and fatty acid composition of the nuts were investigated immediately after irradiation. The data obtained from the experiments indicated that gamma irradiation did not cause any significant change in the oil content of nuts. In contrast, free fatty acid and peroxide value of the nuts increased proportionally to the dose (p<0.05). Among the fatty acids determined, the concentration of total saturated fatty acids increased while total monounsaturated and total polyunsaturated fatty acids decreased with the irradiation dose (p<0.05 and <0.01).

  9. High demand for firewood leads to overuse of walnut-fruit forests in Kyrgyzstan

    Institute of Scientific and Technical Information of China (English)

    Maik Rehnus; Annemarie Nazarek; Davlet Mamadzhanov; Bronislav Ivanovitch Venglovsky; Jean-Pierre Sorg

    2013-01-01

    After Kyrgyzstan gained independence in 1991, the importance of the primary sector for food-and energy-supply increased significantly. This has led to a discussion about the sustainability of current firewood use. We investigated firewood collection and use practices in three selected villages and analysed differences between the annual increment of woody biomass and firewood consumption for heating during winter months. The calculated individual firewood consumption is on average 3.90 kg/capita/heating day and the calculation of differences between increment and consumption shows that in minimum one village the surrounding forests are overused for firewood collection. Pressure on the forest and the overuse of preferred tree species for firewood can lead to an overuse of the resource and to a decrease in the genetic diversity of these species in the walnut-fruit forests which are considered as a biodiversity hotspot of international significance due to the diversity of woody.

  10. 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

  11. Assessment of Bacterial Blight Tolerance of Persian Walnut Based on Immature Nut Test

    Directory of Open Access Journals (Sweden)

    Attila BANDI

    2015-06-01

    Full Text Available Bacterial blight is one of the most serious diseases affecting Persian walnut (Juglans regia L.. Susceptibility to this disease was evaluated by artificial inoculation in an in vitro experiment for cultivars developed in Hungary and for selections from Transylvania. Thirty pieces of immature fruit of 11 walnut cultivars and 10 selections were inoculated by punction using a suspension containing a mixture of Xaj-isolates of controlled virulence. As control, a moderate resistant (mR ‘Pedro’ and a highly susceptible (hS ‘Milotai intenzív’ cultivars were used. After ten days the diameter of the necrotic area around the inoculation points was measured and the disease rate (DR was noted. For the calculation of indexes it was taken the structure of the lesions (diffuse or defined margin into consideration. None of the 21 cultivars/selections analysed were found to be hardly resistant, although all of them showed a higher degree of resistance than the susceptible control (‘Milotai intenzív’. The majority of the analysed cultivars fit into the moderate susceptible (mS and moderate resistant (mR group. ‘Milotai kései’ and SZEN-10, had a notable reaction as considered to be moderate resistant (mR, showed a similar degree of resistance compared to the control cultivar ‘Pedro’. It was concluded that these cultivars, based on their resistance to Xanthomonas arboricola pv. juglandis, could be proposed as resistance gene sources, as well as for production purposes in the environmental conditions of the Carpathian Basin.

  12. GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

    Science.gov (United States)

    Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

    2017-12-01

    Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of

  13. 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.

  14. Walnut consumption in a weight reduction intervention: effects on body weight, biological measures, blood pressure and satiety.

    Science.gov (United States)

    Rock, Cheryl L; Flatt, Shirley W; Barkai, Hava-Shoshana; Pakiz, Bilge; Heath, Dennis D

    2017-12-04

    Dietary strategies that help patients adhere to a weight reduction diet may increase the likelihood of weight loss maintenance and improved long-term health outcomes. Regular nut consumption has been associated with better weight management and less adiposity. The objective of this study was to compare the effects of a walnut-enriched reduced-energy diet to a standard reduced-energy-density diet on weight, cardiovascular disease risk factors, and satiety. Overweight and obese men and women (n = 100) were randomly assigned to a standard reduced-energy-density diet or a walnut-enriched (15% of energy) reduced-energy diet in the context of a behavioral weight loss intervention. Measurements were obtained at baseline and 3- and 6-month clinic visits. Participants rated hunger, fullness and anticipated prospective consumption at 3 time points during the intervention. Body measurements, blood pressure, physical activity, lipids, tocopherols and fatty acids were analyzed using repeated measures mixed models. Both study groups reduced body weight, body mass index and waist circumference (time effect p weight was -9.4 (0.9)% vs. -8.9 (0.7)% (mean [SE]), for the standard vs. walnut-enriched diet groups, respectively. Systolic blood pressure decreased in both groups at 3 months, but only the walnut-enriched diet group maintained a lower systolic blood pressure at 6 months. The walnut-enriched diet group, but not the standard reduced-energy-density diet group, reduced total cholesterol and low-density lipoprotein cholesterol (LDL-C) at 6 months, from 203 to 194 mg/dL and 121 to 112 mg/dL, respectively (p weight loss that is comparable to a standard reduced-energy-density diet in the context of a behavioral weight loss intervention. Although weight loss in response to both dietary strategies was associated with improvements in cardiovascular disease risk factors, the walnut-enriched diet promoted more favorable effects on LDL-C and systolic blood pressure. The trial

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Study of Genetic Diversity of Some Persian walnut Genotypes in Mashhad Commercial Orchards by using ISSR Marker

    Directory of Open Access Journals (Sweden)

    Shadi Attar

    2018-02-01

    Full Text Available Introduction: Persian walnut (Juglans regia L., belonging to the Juglandaceae family, has its natural origin in the mountainous regions of central Asia and especially northern forests of Iran. Most walnut genotypes are seedling and sexually reproduced. Conducting studies on the genetic structure of these genotypes to identify, select and maintain their genetic resources is important. Identifying and collecting local varieties of fruit trees is considered as the first step on the path of breeding programs and lack of information regarding plants genetic characteristics causes the breeding work to be done slowly. Various methods have been used for studying genetic diversity and determining the genetic relationship between European and Asian varieties of walnut and identifying commercial walnut varieties, among which we can mention: Morphologic indices, Alozyme, Isozym, RFLP, RAPD, AFLP and ISSR markers. ISSR molecular marker was used in order to investigate genetic diversity of some genotypes of Persian walnut (Juglans regia L. in Mashhad orchards. . Materials and methods: To begin with, about 56 walnut trees from 4 orchards in Mashhad (Esteghlal (1, Golestan (2, Alandasht (3 and Emam Reza (4 were selected and tagged from 2014 to 2016. In the spring of 2014 with the beginning of trees growth and opening of leaves, a number of leaves from each genotype were collected. After DNA extraction, the quality of samples by agarose gel (1 percentage and electrophoresis method and quantity of them via spectrophotometer device at 260 and 280 nm wavelengths were determined. First, 24 primers of ISSR marker were prepared and after initial evaluation on 5 random genotypes, 9 primers with high polymorphism and repeatability were selected for further investigation. For PCR reaction, Amplicon kit (code 180 301, made in Denmark was used. Gel electrophoresis images of primers that produced polymorphic bands with suitable resolution were analyzed manually. After

  3. Photon beam convolution using polyenergetic energy deposition kernels

    International Nuclear Information System (INIS)

    Hoban, P.W.; Murray, D.C.; Round, W.H.

    1994-01-01

    In photon beam convolution calculations where polyenergetic energy deposition kernels (EDKs) are used, the primary photon energy spectrum should be correctly accounted for in Monte Carlo generation of EDKs. This requires the probability of interaction, determined by the linear attenuation coefficient, μ, to be taken into account when primary photon interactions are forced to occur at the EDK origin. The use of primary and scattered EDKs generated with a fixed photon spectrum can give rise to an error in the dose calculation due to neglecting the effects of beam hardening with depth. The proportion of primary photon energy that is transferred to secondary electrons increases with depth of interaction, due to the increase in the ratio μ ab /μ as the beam hardens. Convolution depth-dose curves calculated using polyenergetic EDKs generated for the primary photon spectra which exist at depths of 0, 20 and 40 cm in water, show a fall-off which is too steep when compared with EGS4 Monte Carlo results. A beam hardening correction factor applied to primary and scattered 0 cm EDKs, based on the ratio of kerma to terma at each depth, gives primary, scattered and total dose in good agreement with Monte Carlo results. (Author)

  4. Improvement in retention of solid fission products in HTGR fuel particles by ceramic kernel additives

    Energy Technology Data Exchange (ETDEWEB)

    Foerthmann, R.; Groos, E.; Gruebmeier, H.

    1975-08-15

    Increased requirements concerning the retention of long-lived solid fission products in fuel elements for use in advanced High Temperature Gas-cooled Reactors led to the development of coated particles with improved fission product retention which represent an alternative to silicon carbide-coated fuel particles. Two irradiation experiments have shown that the release of strontium, barium, and caesium from pyrocarbon-coated particles can be reduced by orders of magnitude if the oxide kernel contains alumina-silica additives. It was detected by electron microprobe analysis that the improved retention of the mentioned fission products in the fuel kernel is caused by formation of the stable aluminosilicates SrAl2Si2O8, BaAl2Si2O8and CsAlSi2O6 in the additional alumina-silica phase of the kernel.

  5. Enhancement and prediction of modulus of elasticity of palm kernel shell concrete

    International Nuclear Information System (INIS)

    Alengaram, U. Johnson; Mahmud, Hilmi; Jumaat, Mohd Zamin

    2011-01-01

    Research highlights: → Micro-pores of size 16-24 μm were found on the outer surface of palm kernel shell. → Infilling of pores by mineral admixtures was evident. → Sand content influenced both modulus of elasticity and compressive strength. → Proposed equation predicts modulus of elasticity within ±1.5 kN/mm 2 of test results. -- Abstract: This paper presents results of an investigation conducted to enhance and predict the modulus of elasticity (MOE) of palm kernel shell concrete (PKSC). Scanning electron microscopic (SEM) analysis on palm kernel shell (PKS) was conducted. Further, the effect of varying sand and PKS contents and mineral admixtures (silica fume and fly ash) on compressive strength and MOE was investigated. The variables include water-to-binder (w/b) and sand-to-cement (s/c) ratios. Nine concrete mixes were prepared, and tests on static and dynamic moduli of elasticity and compressive strength were conducted. The SEM result showed presence of large number of micro-pores on PKS. The mineral admixtures uniformly filled the micro-pores on the outer surface of PKS. Further, the increase in sand content coupled with reduction in PKS content enhanced the compressive strength and static MOE: The highest MOE recorded in this investigation, 11 kN/mm 2 , was twice that previously published. Moreover, the proposed equation based on CEB/FIP code formula appears to predict the MOE close to the experimental values.

  6. Evaluating and interpreting the chemical relevance of the linear response kernel for atoms II: open shell.

    Science.gov (United States)

    Boisdenghien, Zino; Fias, Stijn; Van Alsenoy, Christian; De Proft, Frank; Geerlings, Paul

    2014-07-28

    Most of the work done on the linear response kernel χ(r,r') has focussed on its atom-atom condensed form χAB. Our previous work [Boisdenghien et al., J. Chem. Theory Comput., 2013, 9, 1007] was the first effort to truly focus on the non-condensed form of this function for closed (sub)shell atoms in a systematic fashion. In this work, we extend our method to the open shell case. To simplify the plotting of our results, we average our results to a symmetrical quantity χ(r,r'). This allows us to plot the linear response kernel for all elements up to and including argon and to investigate the periodicity throughout the first three rows in the periodic table and in the different representations of χ(r,r'). Within the context of Spin Polarized Conceptual Density Functional Theory, the first two-dimensional plots of spin polarized linear response functions are presented and commented on for some selected cases on the basis of the atomic ground state electronic configurations. Using the relation between the linear response kernel and the polarizability we compare the values of the polarizability tensor calculated using our method to high-level values.

  7. Gradient-based adaptation of general gaussian kernels.

    Science.gov (United States)

    Glasmachers, Tobias; Igel, Christian

    2005-10-01

    Gradient-based optimizing of gaussian kernel functions is considered. The gradient for the adaptation of scaling and rotation of the input space is computed to achieve invariance against linear transformations. This is done by using the exponential map as a parameterization of the kernel parameter manifold. By restricting the optimization to a constant trace subspace, the kernel size can be controlled. This is, for example, useful to prevent overfitting when minimizing radius-margin generalization performance measures. The concepts are demonstrated by training hard margin support vector machines on toy data.

  8. On weights which admit the reproducing kernel of Bergman type

    Directory of Open Access Journals (Sweden)

    Zbigniew Pasternak-Winiarski

    1992-01-01

    Full Text Available In this paper we consider (1 the weights of integration for which the reproducing kernel of the Bergman type can be defined, i.e., the admissible weights, and (2 the kernels defined by such weights. It is verified that the weighted Bergman kernel has the analogous properties as the classical one. We prove several sufficient conditions and necessary and sufficient conditions for a weight to be an admissible weight. We give also an example of a weight which is not of this class. As a positive example we consider the weight μ(z=(Imz2 defined on the unit disk in ℂ.

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

    DEFF Research Database (Denmark)

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

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus...... on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...

  10. 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.

  11. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  12. Explicit signal to noise ratio in reproducing kernel Hilbert spaces

    DEFF Research Database (Denmark)

    Gomez-Chova, Luis; Nielsen, Allan Aasbjerg; Camps-Valls, Gustavo

    2011-01-01

    This paper introduces a nonlinear feature extraction method based on kernels for remote sensing data analysis. The proposed approach is based on the minimum noise fraction (MNF) transform, which maximizes the signal variance while also minimizing the estimated noise variance. We here propose...... an alternative kernel MNF (KMNF) in which the noise is explicitly estimated in the reproducing kernel Hilbert space. This enables KMNF dealing with non-linear relations between the noise and the signal features jointly. Results show that the proposed KMNF provides the most noise-free features when confronted...

  13. Removal of Dissolved Cadmium by Adsorption onto Walnut and Almond Shell Charcoal: Comparison with Granular Activated Carbon (GAC

    Directory of Open Access Journals (Sweden)

    Mohsen Saeedi

    2009-06-01

    Full Text Available In the present study, adsorption of dissolved Cadmium (Cd onto walnut and almond shell charcoal and the standard granular activated carbon (GAC has been investigated and compared. The effect of pH value, initial concentration of dissolved Cadmium and amount of adsorbent on the adsorption of Cd by the mentioned adsorbents were investigated. Results showed that the adsorption process was highly dependent on pH. Maximum Cd removal was achieved when the final pH of the mixture fell within 6.5-7. Adsorption test results revealed that Cd adsorption on the studied adsorbents could be better described by Longmuir isotherm. Maximum Cd removal efficiencies were obtained by walnut shell charcoal (91%, almond shell charcoal (85%, and GAC (81%.

  14. Quantitative estimates of uptake and internal cycling of 15N-depleted fertilizer in mature walnut trees

    International Nuclear Information System (INIS)

    Weinbaum, S.; Kessel, C. van

    1998-01-01

    In mature fruit trees, internal recycling is an important source of N for the growth of new wood, leaves and fruits. Using 15 N-depleted fertilizer, i.e. 14 N-enriched, N-uptake efficiency and the magnitude of internal N cycling were studied in mature walnut trees. Two kg of 14 N-labelled ammonium sulfate N were applied per tree, and compartmentation of N was followed over a period of 6 years by analyzing catkins, pistillate flowers, leaves and fruits each year for total N content and isotopic composition. Subsequently, two of the six labelled trees were excavated and analyzed for labelled-N content. The data indicate that mature walnut uses most of the N accumulated from soil and fertilizer for storage purposes, to be remobilized for new growth within 2 years, and about half of the total-N pool in a mature tree is present as non-structural compounds, available for recycling. (author)

  15. Sudden increase in atmospheric concentration reveals strong coupling between shoot carbon uptake and root nutrient uptake in young walnut trees

    International Nuclear Information System (INIS)

    Delaire, M.; Sigogne, M.; Beaujard, F.; Frak, E.; Adam, B.; Le Roux, X.

    2005-01-01

    Short-term effects of a sudden increase in carbon dioxide concentration on nutrient uptake by roots during vegetative growth was studied in young walnut trees. Rates of carbon dioxide uptake and water loss by individual trees were determined by a branch bag method from three days before and six days after carbon dioxide concentration was increased. Nutrient uptake rates were measured concurrently by a hydroponic recirculating nutrient solution system. Carbon dioxide uptake rates increased greatly with increasing atmospheric carbon dioxide; nutrient uptake rates were proportional to carbon dioxide uptake rates, except for the phosphorus ion. Daily water loss rates were only slightly affected by elevated carbon dioxide. Overall, it was concluded that in the presence of non-limiting supplies of water and nutrients, root nutrient uptake and shoot carbon assimilation are strongly coupled in the short term in young walnut trees despite the important carbon and nutrient storage capacities od woody species. 45 refs., 7 figs

  16. 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

  17. Examining Potential Boundary Bias Effects in Kernel Smoothing on Equating: An Introduction for the Adaptive and Epanechnikov Kernels.

    Science.gov (United States)

    Cid, Jaime A; von Davier, Alina A

    2015-05-01

    Test equating is a method of making the test scores from different test forms of the same assessment comparable. In the equating process, an important step involves continuizing the discrete score distributions. In traditional observed-score equating, this step is achieved using linear interpolation (or an unscaled uniform kernel). In the kernel equating (KE) process, this continuization process involves Gaussian kernel smoothing. It has been suggested that the choice of bandwidth in kernel smoothing controls the trade-off between variance and bias. In the literature on estimating density functions using kernels, it has also been suggested that the weight of the kernel depends on the sample size, and therefore, the resulting continuous distribution exhibits bias at the endpoints, where the samples are usually smaller. The purpose of this article is (a) to explore the potential effects of atypical scores (spikes) at the extreme ends (high and low) on the KE method in distributions with different degrees of asymmetry using the randomly equivalent groups equating design (Study I), and (b) to introduce the Epanechnikov and adaptive kernels as potential alternative approaches to reducing boundary bias in smoothing (Study II). The beta-binomial model is used to simulate observed scores reflecting a range of different skewed shapes.

  18. Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

    Science.gov (United States)

    Urrutia, Eugene; Lee, Seunggeun; Maity, Arnab; Zhao, Ni; Shen, Judong; Li, Yun; Wu, Michael C

    Analysis of rare genetic variants has focused on region-based analysis wherein a subset of the variants within a genomic region is tested for association with a complex trait. Two important practical challenges have emerged. First, it is difficult to choose which test to use. Second, it is unclear which group of variants within a region should be tested. Both depend on the unknown true state of nature. Therefore, we develop the Multi-Kernel SKAT (MK-SKAT) which tests across a range of rare variant tests and groupings. Specifically, we demonstrate that several popular rare variant tests are special cases of the sequence kernel association test which compares pair-wise similarity in trait value to similarity in the rare variant genotypes between subjects as measured through a kernel function. Choosing a particular test is equivalent to choosing a kernel. Similarly, choosing which group of variants to test also reduces to choosing a kernel. Thus, MK-SKAT uses perturbation to test across a range of kernels. Simulations and real data analyses show that our framework controls type I error while maintaining high power across settings: MK-SKAT loses power when compared to the kernel for a particular scenario but has much greater power than poor choices.

  19. Evaluation of sintering effects on SiC-incorporated UO{sub 2} kernels under Ar and Ar–4%H{sub 2} environments

    Energy Technology Data Exchange (ETDEWEB)

    Silva, Chinthaka M., E-mail: silvagw@ornl.gov [Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee TN 37831-6223 (United States); Materials Science and Engineering, The University of Tennessee Knoxville, TN 37996-2100, United States. (United States); Lindemer, Terrence B.; Hunt, Rodney D.; Collins, Jack L.; Terrani, Kurt A.; Snead, Lance L. [Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee TN 37831-6223 (United States)

    2013-11-15

    Silicon carbide (SiC) is suggested as an oxygen getter in UO{sub 2} kernels used for tristructural isotropic (TRISO) particle fuels and to prevent kernel migration during irradiation. Scanning electron microscopy and X-ray diffractometry analyses performed on sintered kernels verified that an internal gelation process can be used to incorporate SiC in UO{sub 2} fuel kernels. Even though the presence of UC in either argon (Ar) or Ar–4%H{sub 2} sintered samples suggested a lowering of the SiC up to 3.5–1.4 mol%, respectively, the presence of other silicon-related chemical phases indicates the preservation of silicon in the kernels during sintering process. UC formation was presumed to occur by two reactions. The first was by the reaction of SiC with its protective SiO{sub 2} oxide layer on SiC grains to produce volatile SiO and free carbon that subsequently reacted with UO{sub 2} to form UC. The second process was direct UO{sub 2} reaction with SiC grains to form SiO, CO, and UC. A slightly higher density and UC content were observed in the sample sintered in Ar–4%H{sub 2}, but both atmospheres produced kernels with ∼95% of theoretical density. It is suggested that incorporating CO in the sintering gas could prevent UC formation and preserve the initial SiC content.

  20. A Walnut-Enriched Diet Reduces Lipids in Healthy Caucasian Subjects, Independent of Recommended Macronutrient Replacement and Time Point of Consumption: a Prospective, Randomized, Controlled Trial.

    Science.gov (United States)

    Bamberger, Charlotte; Rossmeier, Andreas; Lechner, Katharina; Wu, Liya; Waldmann, Elisa; Stark, Renée G; Altenhofer, Julia; Henze, Kerstin; Parhofer, Klaus G

    2017-10-06

    Studies indicate a positive association between walnut intake and improvements in plasma lipids. We evaluated the effect of an isocaloric replacement of macronutrients with walnuts and the time point of consumption on plasma lipids. We included 194 healthy subjects (134 females, age 63 ± 7 years, BMI 25.1 ± 4.0 kg/m²) in a randomized, controlled, prospective, cross-over study. Following a nut-free run-in period, subjects were randomized to two diet phases (8 weeks each). Ninety-six subjects first followed a walnut-enriched diet (43 g walnuts/day) and then switched to a nut-free diet. Ninety-eight subjects followed the diets in reverse order. Subjects were also randomized to either reduce carbohydrates ( n = 62), fat ( n = 65), or both ( n = 67) during the walnut diet, and instructed to consume walnuts either as a meal or as a snack. The walnut diet resulted in a significant reduction in fasting cholesterol (walnut vs. -8.5 ± 37.2 vs. -1.1 ± 35.4 mg/dL; p = 0.002), non-HDL cholesterol (-10.3 ± 35.5 vs. -1.4 ± 33.1 mg/dL; p ≤ 0.001), LDL-cholesterol (-7.4 ± 32.4 vs. -1.7 ± 29.7 mg/dL; p = 0.029), triglycerides (-5.0 ± 47.5 vs. 3.7 ± 48.5 mg/dL; p = 0.015) and apoB (-6.7 ± 22.4 vs. -0.5 ± 37.7; p ≤ 0.001), while HDL-cholesterol and lipoprotein (a) did not change significantly. Neither macronutrient replacement nor time point of consumption significantly affected the effect of walnuts on lipids. Thus, 43 g walnuts/d improved the lipid profile independent of the recommended macronutrient replacement and the time point of consumption.

  1. Synergistic anti-tumor effects of melatonin and PUFAs from walnuts in a murine mammary adenocarcinoma model.

    Science.gov (United States)

    Garcia, Carolina P; Lamarque, Alicia L; Comba, Andrea; Berra, María A; Silva, Renata A; Labuckas, Diana O; Das, Undurti N; Eynard, Aldo R; Pasqualini, Maria E

    2015-04-01

    The aim of this study was to determine the effects of some polyunsaturated fatty acids plus phytomelatonin from walnuts in the development of mammary gland adenocarcinoma. BALB/c mice were fed a semisynthetic diet supplemented with either 6% walnut oil and 8% walnut flour containing phytomelatonin (walnut diet: WD); or 6% corn oil plus commercial melatonin (melatonin diet: MD), or the control group (CD), which received only 6% of corn oil. Membrane fatty acids of tumor cells (TCs) were analyzed by gas liquid chromatography, cyclooxygenase (COX) and lipoxygenase (LOX) derivatives, and plasma melatonin by high-performance liquid chromatography; apoptosis and tumor-infiltrating lymphocytes by flow cytometry. TCs from the MD and WD mice showed significant decreases in linoleic acid compared with the CD group (P < 0.05). Significantly lower levels of LOX-[13(S)-HODE] were found in TCs from the MD and WD group than in CD (P < 0.0001). COX-[12(S)-HHT] was lower and 12 LOX-[12(S)-HETE] was higher in TCs from the MD group than form the WD and CD arms (P < 0.05). Plasma melatonin, apoptosis, tumor infiltration, and survival time were significantly lower in CD mice than in MD and WD mice (P < 0.05). This study shows that melatonin, along with polyunsaturated fatty acids, exerts a selective inhibition of some COX and LOX activities and has a synergistic anti-tumor effect on a mammary gland adenocarcinoma model. Published by Elsevier Inc.

  2. Production of granular activated carbon from food-processing wastes (walnut shells and jujube seeds) and its adsorptive properties.

    Science.gov (United States)

    Bae, Wookeun; Kim, Jongho; Chung, Jinwook

    2014-08-01

    Commercial activated carbon is a highly effective absorbent that can be used to remove micropollutants from water. As a result, the demand for activated carbon is increasing. In this study, we investigated the optimum manufacturing conditions for producing activated carbon from ligneous wastes generated from food processing. Jujube seeds and walnut shells were selected as raw materials. Carbonization and steam activation were performed in a fixed-bed laboratory electric furnace. To obtain the highest iodine number, the optimum conditions for producing activated carbon from jujube seeds and walnut shells were 2 hr and 1.5 hr (carbonization at 700 degrees C) followed by 1 hr and 0.5 hr (activation at 1000 degrees C), respectively. The surface area and iodine number of activated carbon made from jujube seeds and walnut shells were 1,477 and 1,184 m2/g and 1,450 and 1,200 mg/g, respectively. A pore-distribution analysis revealed that most pores had a pore diameter within or around 30-40 angstroms, and adsorption capacity for surfactants was about 2 times larger than the commercial activated carbon, indicating that waste-based activated carbon can be used as alternative. Implications: Wastes discharged from agricultural and food industries results in a serious environmental problem. A method is proposed to convert food-processing wastes such as jujube seeds and walnut shells into high-grade granular activated carbon. Especially, the performance of jujube seeds as activated carbon is worthy of close attention. There is little research about the application ofjujube seeds. Also, when compared to two commercial carbons (Samchully and Calgon samples), the results show that it is possible to produce high-quality carbon, particularly from jujube seed, using a one-stage, 1,000 degrees C, steam pyrolysis. The preparation of activated carbon from food-processing wastes could increase economic return and reduce pollution.

  3. Efficient Online Subspace Learning With an Indefinite Kernel for Visual Tracking and Recognition

    NARCIS (Netherlands)

    Liwicki, Stephan; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Pantic, Maja

    2012-01-01

    We propose an exact framework for online learning with a family of indefinite (not positive) kernels. As we study the case of nonpositive kernels, we first show how to extend kernel principal component analysis (KPCA) from a reproducing kernel Hilbert space to Krein space. We then formulate an

  4. Walnut Polyphenol Extract Attenuates Immunotoxicity Induced by 4-Pentylphenol and 3-methyl-4-nitrophenol in Murine Splenic Lymphocyte

    Directory of Open Access Journals (Sweden)

    Lubing Yang

    2016-05-01

    Full Text Available 4-pentylphenol (PP and 3-methyl-4-nitrophenol (PNMC, two important components of vehicle emissions, have been shown to confer toxicity in splenocytes. Certain natural products, such as those derived from walnuts, exhibit a range of antioxidative, antitumor, and anti-inflammatory properties. Here, we investigated the effects of walnut polyphenol extract (WPE on immunotoxicity induced by PP and PNMC in murine splenic lymphocytes. Treatment with WPE was shown to significantly enhance proliferation of splenocytes exposed to PP or PNMC, characterized by increases in the percentages of splenic T lymphocytes (CD3+ T cells and T cell subsets (CD4+ and CD8+ T cells, as well as the production of T cell-related cytokines and granzymes (interleukin-2, interleukin-4, and granzyme-B in cells exposed to PP or PNMC. These effects were associated with a decrease in oxidative stress, as evidenced by changes in OH, SOD, GSH-Px, and MDA levels. The total phenolic content of WPE was 34,800 ± 200 mg gallic acid equivalents/100 g, consisting of at least 16 unique phenols, including ellagitannins, quercetin, valoneic acid dilactone, and gallic acid. Taken together, these results suggest that walnut polyphenols significantly attenuated PP and PNMC-mediated immunotoxicity and improved immune function by inhibiting oxidative stress.

  5. Walnut Polyphenol Extract Attenuates Immunotoxicity Induced by 4-Pentylphenol and 3-methyl-4-nitrophenol in Murine Splenic Lymphocyte.

    Science.gov (United States)

    Yang, Lubing; Ma, Sihui; Han, Yu; Wang, Yuhan; Guo, Yan; Weng, Qiang; Xu, Meiyu

    2016-05-12

    4-pentylphenol (PP) and 3-methyl-4-nitrophenol (PNMC), two important components of vehicle emissions, have been shown to confer toxicity in splenocytes. Certain natural products, such as those derived from walnuts, exhibit a range of antioxidative, antitumor, and anti-inflammatory properties. Here, we investigated the effects of walnut polyphenol extract (WPE) on immunotoxicity induced by PP and PNMC in murine splenic lymphocytes. Treatment with WPE was shown to significantly enhance proliferation of splenocytes exposed to PP or PNMC, characterized by increases in the percentages of splenic T lymphocytes (CD3+ T cells) and T cell subsets (CD4+ and CD8+ T cells), as well as the production of T cell-related cytokines and granzymes (interleukin-2, interleukin-4, and granzyme-B) in cells exposed to PP or PNMC. These effects were associated with a decrease in oxidative stress, as evidenced by changes in OH, SOD, GSH-Px, and MDA levels. The total phenolic content of WPE was 34,800 ± 200 mg gallic acid equivalents/100 g, consisting of at least 16 unique phenols, including ellagitannins, quercetin, valoneic acid dilactone, and gallic acid. Taken together, these results suggest that walnut polyphenols significantly attenuated PP and PNMC-mediated immunotoxicity and improved immune function by inhibiting oxidative stress.

  6. Calculation of the thermal neutron scattering kernel using the synthetic model. Pt. 2. Zero-order energy transfer kernel

    International Nuclear Information System (INIS)

    Drozdowicz, K.

    1995-01-01

    A comprehensive unified description of the application of Granada's Synthetic Model to the slow-neutron scattering by the molecular systems is continued. Detailed formulae for the zero-order energy transfer kernel are presented basing on the general formalism of the model. An explicit analytical formula for the total scattering cross section as a function of the incident neutron energy is also obtained. Expressions of the free gas model for the zero-order scattering kernel and for total scattering kernel are considered as a sub-case of the Synthetic Model. (author). 10 refs

  7. A kernel adaptive algorithm for quaternion-valued inputs.

    Science.gov (United States)

    Paul, Thomas K; Ogunfunmi, Tokunbo

    2015-10-01

    The use of quaternion data can provide benefit in applications like robotics and image recognition, and particularly for performing transforms in 3-D space. Here, we describe a kernel adaptive algorithm for quaternions. A least mean square (LMS)-based method was used, resulting in the derivation of the quaternion kernel LMS (Quat-KLMS) algorithm. Deriving this algorithm required describing the idea of a quaternion reproducing kernel Hilbert space (RKHS), as well as kernel functions suitable with quaternions. A modified HR calculus for Hilbert spaces was used to find the gradient of cost functions defined on a quaternion RKHS. In addition, the use of widely linear (or augmented) filtering is proposed to improve performance. The benefit of the Quat-KLMS and widely linear forms in learning nonlinear transformations of quaternion data are illustrated with simulations.

  8. Bioconversion of palm kernel meal for aquaculture: Experiences ...

    African Journals Online (AJOL)

    SERVER

    2008-04-17

    Apr 17, 2008 ... es as well as food supplies have existed traditionally with coastal regions of Liberia and ..... Contamination of palm kernel meal with Aspergillus ... Sciences, Universiti Sains Malaysia, Penang 11800, Malaysia. Aquacult. Res.

  9. The effect of apricot kernel flour incorporation on the ...

    African Journals Online (AJOL)

    STORAGESEVER

    2009-01-05

    Jan 5, 2009 ... 2Department of Food Engineering, Erciyes University 38039, Kayseri, Turkey. Accepted 27 ... Key words: Noodle; apricot kernel, flour, cooking, sensory properties. ... their simple preparation requirement, desirable sensory.

  10. 3-D waveform tomography sensitivity kernels for anisotropic media

    KAUST Repository

    Djebbi, Ramzi; Alkhalifah, Tariq Ali

    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

  11. Kernel-based noise filtering of neutron detector signals

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Shin, Ho Cheol; Lee, Eun Ki

    2007-01-01

    This paper describes recently developed techniques for effective filtering of neutron detector signal noise. In this paper, three kinds of noise filters are proposed and their performance is demonstrated for the estimation of reactivity. The tested filters are based on the unilateral kernel filter, unilateral kernel filter with adaptive bandwidth and bilateral filter to show their effectiveness in edge preservation. Filtering performance is compared with conventional low-pass and wavelet filters. The bilateral filter shows a remarkable improvement compared with unilateral kernel and wavelet filters. The effectiveness and simplicity of the unilateral kernel filter with adaptive bandwidth is also demonstrated by applying it to the reactivity measurement performed during reactor start-up physics tests

  12. Linear and kernel methods for multivariate change detection

    DEFF Research Database (Denmark)

    Canty, Morton J.; Nielsen, Allan Aasbjerg

    2012-01-01

    ), 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...... that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed...

  13. On Improving Convergence Rates for Nonnegative Kernel Density Estimators

    OpenAIRE

    Terrell, George R.; Scott, David W.

    1980-01-01

    To improve the rate of decrease of integrated mean square error for nonparametric kernel density estimators beyond $0(n^{-\\frac{4}{5}}),$ we must relax the constraint that the density estimate be a bonafide density function, that is, be nonnegative and integrate to one. All current methods for kernel (and orthogonal series) estimators relax the nonnegativity constraint. In this paper we show how to achieve similar improvement by relaxing the integral constraint only. This is important in appl...

  14. Improved Variable Window Kernel Estimates of Probability Densities

    OpenAIRE

    Hall, Peter; Hu, Tien Chung; Marron, J. S.

    1995-01-01

    Variable window width kernel density estimators, with the width varying proportionally to the square root of the density, have been thought to have superior asymptotic properties. The rate of convergence has been claimed to be as good as those typical for higher-order kernels, which makes the variable width estimators more attractive because no adjustment is needed to handle the negativity usually entailed by the latter. However, in a recent paper, Terrell and Scott show that these results ca...

  15. Graphical analyses of connected-kernel scattering equations

    International Nuclear Information System (INIS)

    Picklesimer, A.

    1982-10-01

    Simple graphical techniques are employed to obtain a new (simultaneous) derivation of a large class of connected-kernel scattering equations. This class includes the Rosenberg, Bencze-Redish-Sloan, and connected-kernel multiple scattering equations as well as a host of generalizations of these and other equations. The graphical method also leads to a new, simplified form for some members of the class and elucidates the general structural features of the entire class

  16. 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

  17. The Flux OSKit: A Substrate for Kernel and Language Research

    Science.gov (United States)

    1997-10-01

    unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 tions. Our own microkernel -based OS, Fluke [17], puts almost all of the OSKit to use...kernels distance the language from the hardware; even microkernels and other extensible kernels enforce some default policy which often conflicts with a...be particu- larly useful in these research projects. 6.1.1 The Fluke OS In 1996 we developed an entirely new microkernel - based system called Fluke

  18. Salus: Kernel Support for Secure Process Compartments

    Directory of Open Access Journals (Sweden)

    Raoul Strackx

    2015-01-01

    Full Text Available Consumer devices are increasingly being used to perform security and privacy critical tasks. The software used to perform these tasks is often vulnerable to attacks, due to bugs in the application itself or in included software libraries. Recent work proposes the isolation of security-sensitive parts of applications into protected modules, each of which can be accessed only through a predefined public interface. But most parts of an application can be considered security-sensitive at some level, and an attacker who is able to gain inapplication level access may be able to abuse services from protected modules. We propose Salus, a Linux kernel modification that provides a novel approach for partitioning processes into isolated compartments sharing the same address space. Salus significantly reduces the impact of insecure interfaces and vulnerable compartments by enabling compartments (1 to restrict the system calls they are allowed to perform, (2 to authenticate their callers and callees and (3 to enforce that they can only be accessed via unforgeable references. We describe the design of Salus, report on a prototype implementation and evaluate it in terms of security and performance. We show that Salus provides a significant security improvement with a low performance overhead, without relying on any non-standard hardware support.

  19. 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.

  20. 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.

  1. An Ensemble Approach to Building Mercer Kernels with Prior Information

    Science.gov (United States)

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

    2005-01-01

    This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly dimensional feature space. we describe a new method called Mixture Density Mercer Kernels to learn kernel function directly from data, rather than using pre-defined kernels. These data adaptive kernels can encode prior knowledge in the kernel using a Bayesian formulation, thus allowing for physical information to be encoded in the model. Specifically, we demonstrate the use of the algorithm in situations with extremely small samples of data. We compare the results with existing algorithms on data from the Sloan Digital Sky Survey (SDSS) and demonstrate the method's superior performance against standard methods. The code for these experiments has been generated with the AUTOBAYES tool, which automatically generates efficient and documented C/C++ code from abstract statistical model specifications. The core of the system is a schema library which contains templates for learning and knowledge discovery algorithms like different versions of EM, or numeric optimization methods like conjugate gradient methods. The template instantiation is supported by symbolic-algebraic computations, which allows AUTOBAYES to find closed-form solutions and, where possible, to integrate them into the code.

  2. A new discrete dipole kernel for quantitative susceptibility mapping.

    Science.gov (United States)

    Milovic, Carlos; Acosta-Cabronero, Julio; Pinto, José Miguel; Mattern, Hendrik; Andia, Marcelo; Uribe, Sergio; Tejos, Cristian

    2018-09-01

    Most approaches for quantitative susceptibility mapping (QSM) are based on a forward model approximation that employs a continuous Fourier transform operator to solve a differential equation system. Such formulation, however, is prone to high-frequency aliasing. The aim of this study was to reduce such errors using an alternative dipole kernel formulation based on the discrete Fourier transform and discrete operators. The impact of such an approach on forward model calculation and susceptibility inversion was evaluated in contrast to the continuous formulation both with synthetic phantoms and in vivo MRI data. The discrete kernel demonstrated systematically better fits to analytic field solutions, and showed less over-oscillations and aliasing artifacts while preserving low- and medium-frequency responses relative to those obtained with the continuous kernel. In the context of QSM estimation, the use of the proposed discrete kernel resulted in error reduction and increased sharpness. This proof-of-concept study demonstrated that discretizing the dipole kernel is advantageous for QSM. The impact on small or narrow structures such as the venous vasculature might by particularly relevant to high-resolution QSM applications with ultra-high field MRI - a topic for future investigations. The proposed dipole kernel has a straightforward implementation to existing QSM routines. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. 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.

  4. Omnibus risk assessment via accelerated failure time kernel machine modeling.

    Science.gov (United States)

    Sinnott, Jennifer A; Cai, Tianxi

    2013-12-01

    Integrating genomic information with traditional clinical risk factors to improve the prediction of disease outcomes could profoundly change the practice of medicine. However, the large number of potential markers and possible complexity of the relationship between markers and disease make it difficult to construct accurate risk prediction models. Standard approaches for identifying important markers often rely on marginal associations or linearity assumptions and may not capture non-linear or interactive effects. In recent years, much work has been done to group genes into pathways and networks. Integrating such biological knowledge into statistical learning could potentially improve model interpretability and reliability. One effective approach is to employ a kernel machine (KM) framework, which can capture nonlinear effects if nonlinear kernels are used (Scholkopf and Smola, 2002; Liu et al., 2007, 2008). For survival outcomes, KM regression modeling and testing procedures have been derived under a proportional hazards (PH) assumption (Li and Luan, 2003; Cai, Tonini, and Lin, 2011). In this article, we derive testing and prediction methods for KM regression under the accelerated failure time (AFT) model, a useful alternative to the PH model. We approximate the null distribution of our test statistic using resampling procedures. When multiple kernels are of potential interest, it may be unclear in advance which kernel to use for testing and estimation. We propose a robust Omnibus Test that combines information across kernels, and an approach for selecting the best kernel for estimation. The methods are illustrated with an application in breast cancer. © 2013, The International Biometric Society.

  5. Ideal Gas Resonance Scattering Kernel Routine for the NJOY Code

    International Nuclear Information System (INIS)

    Rothenstein, W.

    1999-01-01

    In a recent publication an expression for the temperature-dependent double-differential ideal gas scattering kernel is derived for the case of scattering cross sections that are energy dependent. Some tabulations and graphical representations of the characteristics of these kernels are presented in Ref. 2. They demonstrate the increased probability that neutron scattering by a heavy nuclide near one of its pronounced resonances will bring the neutron energy nearer to the resonance peak. This enhances upscattering, when a neutron with energy just below that of the resonance peak collides with such a nuclide. A routine for using the new kernel has now been introduced into the NJOY code. Here, its principal features are described, followed by comparisons between scattering data obtained by the new kernel, and the standard ideal gas kernel, when such comparisons are meaningful (i.e., for constant values of the scattering cross section a 0 K). The new ideal gas kernel for variable σ s 0 (E) at 0 K leads to the correct Doppler-broadened σ s T (E) at temperature T

  6. 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.

  7. The Walnut Gulch - Santa Rita Wildland Watershed-Scale LTAR Sites

    Science.gov (United States)

    Goodrich, D. C.; Heilman, P.; Scott, R. L.; Nearing, M. A.; Moran, M. S.; Nichols, M.; Vivoni, E. R.; Archer, S. R.; Biederman, J.; Naito, A. T.

    2015-12-01

    The 150 km2 Walnut Gulch Experimental Watershed (WGEW), a Long-Term Agroecosystem Research (LTAR) site, near Tombstone, Arizona was established in 1953 by the USDA-ARS Southwest Watershed Research Center in Tucson. It is one of the most intensively instrumented semiarid experimental watersheds in the world with elevation ranging from 1220 to 1950 m with mean annual temperature and precipitation equal to 17.7°C and 312 mm. Desert shrubs dominate the lower two thirds of the watershed and grasses the upper third. Spatial variation in precipitation is measured with a network of 88 weighing-type recording rain gauges. Surface runoff is quantified over a range of scales (0.002 to 0.06 km2) to characterize interactions between rainfall intensity, soils and vegetation at nine sub-watersheds. Channel network processes and rainfall spatial variability are studied using 11 nested watersheds (2 to 150 km2). Sediment from the small sub-watersheds is sampled. Meteorological, soil moisture and temperature, and energy/water/CO2 flux measurements are made within two vegetation/soil complexes. Parallel investigations dating back to 1974 have also been conducted on eight small experimental watersheds at the Santa Rita Experimental Range (SRER) 80 km west of Walnut Gulch. In contrast to the creosote bush-grass WGEW, the mesquite-grass SRER is publicly owned, which ensures control and consistent reporting of management for research purposes. A key LTAR objective is to contrast a "business as usual" to an alternate management strategy presumed to have the potential of significantly improving forage and livestock production and diversification of ecosystem services. Consequently, a new ARS-U. of Arizona-Arizona State U. partnership will assess the watershed-scale impacts of brush management, a common land use practice typically applied in conjunction with livestock grazing, on a suite of ecosystem services at the SRER including provisioning (forage production, water yield), supporting

  8. Enzymatically interesterified fats based on mutton tallow and walnut oil suitable for cosmetic emulsions.

    Science.gov (United States)

    Kowalska, M; Mendrycka, M; Zbikowska, A; Stawarz, S

    2015-02-01

    Formation of emulsion systems based on interesterified fats was the objective of the study. Enzymatic interesterification was carried out between enzymatic mutton tallow and walnut oil in the proportions 2 : 3 (w/w) to produce fats not available in nature. At the beginning of the interesterification process, the balance between the interesterification and fat hydrolysis was intentionally disturbed by adding more water to the catalyst (Lipozyme IR MR) of the reaction to produce more of the polar fraction monoacylglycerols [MAGs] and diacylglycerols [DAGs]. To obtain a greater quantity of MAGs and DAGs in the reaction environment via hydrolysis, water was added (11, 13, 14, 16 w-%) to the enzymatic preparation. The obtained fats were used to form emulsions. The emulsions were evaluated with respect to sensory and skin moisturizing properties by 83 respondents. Determination of emulsion stability using temperature and centrifugal tests was carried out. Morphology and the type of emulsions were determined. The respondents described the skin to which the emulsions in testing were applied as smooth, pleasant to touch and adequately moisturized. The work has demonstrated that interesterification of a mutton tallow and walnut oil blend resulted in new fats with very interesting characteristics of triacylglycerols that are not present in the environment. The results of the present work indicate the possibility of application of fats with the largest quantity of MAGs and DAGs as a fat base of emulsions in the cosmetic industries. The hypothesis assumed in this work of producing additional quantities of MAGs and DAGs (in the process of enzymatic interesterification) responsible for the stability of the system was confirmed. It should be pointed out that the emulsions based on interesterified fats exhibited a greater level of moisturization of the skin than the emulsions containing non-interesterified fat. Also, in the respondents' opinion, the emulsion containing fat, which

  9. 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

  10. Scientific opinion on the acute health risks related to the presence of cyanogenic glycosides in raw apricot kernels and products derived from raw apricot kernels

    DEFF Research Database (Denmark)

    Petersen, Annette

    of kernels promoted (10 and 60 kernels/day for the general population and cancer patients, respectively), exposures exceeded the ARfD 17–413 and 3–71 times in toddlers and adults, respectively. The estimated maximum quantity of apricot kernels (or raw apricot material) that can be consumed without exceeding...

  11. Market analysis of food products for detection of allergenic walnut (Juglans regia) and pecan (Carya illinoinensis) by real-time PCR.

    Science.gov (United States)

    López-Calleja, Inés María; de la Cruz, Silvia; González, Isabel; García, Teresa; Martín, Rosario

    2015-06-15

    Two real-time polymerase chain reaction (PCR)-based assays for detection of walnut (Juglans regia) and pecan (Carya illinoinensis) traces in a wide range of processed foods are described here. The method consists on a real-time PCR assay targeting the ITS1 region, using a nuclease (TaqMan) probe labeled with FAM and BBQ. The method was positive for walnut and pecan respectively, and negative for all other heterologous plants and animals tested. Using a series of model samples with defined raw walnut in wheat flour and heat-treated walnut in wheat flour with a range of concentrations of 0.1-100,000 mg kg(-1), a practical detection limit of 0.1 mg kg(-1) of walnut content was estimated. Identical binary mixtures were done for pecan, reaching the same limit of detection of 0.1 mg kg(-1). The assay was successfully trialed on a total of 232 commercial foodstuffs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Investigating local variation in groundwater recharge along a topographic gradient, Walnut Creek, Iowa, USA

    Science.gov (United States)

    Schilling, K.E.

    2009-01-01

    Groundwater recharge is an important component to hydrologic studies but is known to vary considerably across the landscape. The purpose of this study was to examine 4 years of water-level behavior in a transect of four water-table wells installed at Walnut Creek, Iowa, USA to evaluate how groundwater recharge varied along a topographic gradient. The amount of daily water-table rise (WTR) in the wells was summed at monthly and annual scales and estimates of specific yield (Sy) were used to convert the WTR to recharge. At the floodplain site, Sy was estimated from the ratio of WTR to total rainfall and in the uplands was based on the ratio of baseflow to WTR. In the floodplain, where the water table is shallow, recharge occurred throughout the year whenever precipitation occurred. In upland areas where the water table was deeper, WTR occurred in a stepped fashion and varied by season. Results indicated that the greatest amount of water-table rise over the 4-year period was observed in the floodplain (379 mm), followed by the upland (211 mm) and sideslopes (122 mm). Incorporating spatial variability in recharge in a watershed will improve groundwater resource evaluation and flow and transport modeling. ?? Springer-Verlag 2008.

  13. Rainfall simulation experiments in the southwestern USA using the Walnut Gulch Rainfall Simulator

    Science.gov (United States)

    Polyakov, Viktor; Stone, Jeffry; Holifield Collins, Chandra; Nearing, Mark A.; Paige, Ginger; Buono, Jared; Gomez-Pond, Rae-Landa

    2018-01-01

    This dataset contains hydrological, erosion, vegetation, ground cover, and other supplementary information from 272 rainfall simulation experiments conducted on 23 semiarid rangeland locations in Arizona and Nevada between 2002 and 2013. On 30 % of the plots, simulations were conducted up to five times during the decade of study. The rainfall was generated using the Walnut Gulch Rainfall Simulator on 2 m by 6 m plots. Simulation sites included brush and grassland areas with various degrees of disturbance by grazing, wildfire, or brush removal. This dataset advances our understanding of basic hydrological and biological processes that drive soil erosion on arid rangelands. It can be used to estimate runoff, infiltration, and erosion rates at a variety of ecological sites in the Southwestern USA. The inclusion of wildfire and brush treatment locations combined with long-term observations makes it important for studying vegetation recovery, ecological transitions, and the effect of management. It is also a valuable resource for erosion model parameterization and validation. The dataset is available from the National Agricultural Library at https://data.nal.usda.gov/search/type/dataset (DOI: https://doi.org/10.15482/USDA.ADC/1358583).

  14. Use of innovative groundcovers in Mediterranean afforestations: aerial and belowground effects in hybrid walnut.

    Directory of Open Access Journals (Sweden)

    Angelo Vitone

    2016-11-01

    Full Text Available Forest restoration in the Mediterranean area is particularly limited by water scarcity in summer and by weed competition, especially during the first years after establishment. The negative impact of these factors can be mitigated through environmentally friendly and cost-effective techniques which favour root development. This study describes the results of innovative weeding techniques in a reforestation carried out in a former agricultural field in Solsona, NE Spain, under Continental Mediterranean Sub-humid climate conditions. The tested weeding techniques included both novel groundcovers (based on prototypes built on a new biodegradable biopolymer, jute treated with resin and recycled rubber and reference techniques, i.e. herbicide application and polyethylene and commercial biofilm groundcovers. We studied the response of hybrid walnut (Juglans x intermedia to the application of these techniques during the first vegetative period in terms of survival, aerial growth and aboveground and belowground biomass allocation. The innovative groundcovers resulted generally in similar outcomes as the reference techniques with regard to tree survival and growth, and to better results in the case of belowground and, to a lesser extent, total tree biomass. Although preliminary, our results suggest that the tested novel groundcovers, notably the model based on treated jute, represent a promising alternative to plastic mulching and herbicide application in afforestation of agricultural lands in Mediterranean continental conditions. Besides these promising productive results, the novel groundcovers bring together relevant technical and environmental benefits, related to their use (not requiring removal or being reusable and composition, based on biodegradable or recycled materials.

  15. 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.

  16. 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.

  17. Generalized synthetic kernel approximation for elastic moderation of fast neutrons

    International Nuclear Information System (INIS)

    Yamamoto, Koji; Sekiya, Tamotsu; Yamamura, Yasunori.

    1975-01-01

    A method of synthetic kernel approximation is examined in some detail with a view to simplifying the treatment of the elastic moderation of fast neutrons. A sequence of unified kernel (fsub(N)) is introduced, which is then divided into two subsequences (Wsub(n)) and (Gsub(n)) according to whether N is odd (Wsub(n)=fsub(2n-1), n=1,2, ...) or even (Gsub(n)=fsub(2n), n=0,1, ...). The W 1 and G 1 kernels correspond to the usual Wigner and GG kernels, respectively, and the Wsub(n) and Gsub(n) kernels for n>=2 represent generalizations thereof. It is shown that the Wsub(n) kernel solution with a relatively small n (>=2) is superior on the whole to the Gsub(n) kernel solution for the same index n, while both converge to the exact values with increasing n. To evaluate the collision density numerically and rapidly, a simple recurrence formula is derived. In the asymptotic region (except near resonances), this recurrence formula allows calculation with a relatively coarse mesh width whenever hsub(a)<=0.05 at least. For calculations in the transient lethargy region, a mesh width of order epsilon/10 is small enough to evaluate the approximate collision density psisub(N) with an accuracy comparable to that obtained analytically. It is shown that, with the present method, an order of approximation of about n=7 should yield a practically correct solution diviating not more than 1% in collision density. (auth.)

  18. 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.

  19. A Non-Local, Energy-Optimized Kernel: Recovering Second-Order Exchange and Beyond in Extended Systems

    Science.gov (United States)

    Bates, Jefferson; Laricchia, Savio; Ruzsinszky, Adrienn

    The Random Phase Approximation (RPA) is quickly becoming a standard method beyond semi-local Density Functional Theory that naturally incorporates weak interactions and eliminates self-interaction error. RPA is not perfect, however, and suffers from self-correlation error as well as an incorrect description of short-ranged correlation typically leading to underbinding. To improve upon RPA we introduce a short-ranged, exchange-like kernel that is one-electron self-correlation free for one and two electron systems in the high-density limit. By tuning the one free parameter in our model to recover an exact limit of the homogeneous electron gas correlation energy we obtain a non-local, energy-optimized kernel that reduces the errors of RPA for both homogeneous and inhomogeneous solids. To reduce the computational cost of the standard kernel-corrected RPA, we also implement RPA renormalized perturbation theory for extended systems, and demonstrate its capability to describe the dominant correlation effects with a low-order expansion in both metallic and non-metallic systems. Furthermore we stress that for norm-conserving implementations the accuracy of RPA and beyond RPA structural properties compared to experiment is inherently limited by the choice of pseudopotential. Current affiliation: King's College London.

  20. 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)

  1. Walnut and almond oil screw-press extraction at industrial scale: Effects of process parameters on oil yield and quality; Extracción de aceite de nuez y almendra a escala industrial: efecto de parámetros del proceso sobre el rendimiento y la calidad del aceite

    Energy Technology Data Exchange (ETDEWEB)

    Martínez, M. L.; Bordón, M.G.; Bodoira, R. M.; Penci, M.C.; Ribotta, P.D.; Maestri, D.M.

    2017-07-01

    Walnut and almond kernels are highly nutritious mainly due to their high oil contents. In this study, 32 factorial experimental designs were used to optimize processes for oil extraction by screw-pressing at industrial scale. Experimental designs included seed moisture content (SMC), and restriction die (RD) as the main processing parameters. Theoretical models were scanned against experimental data in order to optimize oil extraction conditions. The response variables analyzed were oil yield (OY), fine solid content (FC) in oil, and oil quality parameters. Fitted models for OY indicated maximum predicted values similar to the highest experimental values. Walnut oil extractions showed a maximum OY (84.5 ± 2.3 %) at 7.21% SMC, and 10 mm RD. For almond kernels, maximum OY (71.9 ± 3.5%) was obtained at 9.42% SMC, and 12 mm RD. Chemical quality parameters from both oils were in the ranges stated in Codex (FAO/WHO) standards for virgin (non-refined) oils. [Spanish] La nuez y almendra son frutos sumamente nutritivos debido a su alto contenido de aceite. Mediante un diseño experimental de tipo factorial 32 se optimizó el proceso de extracción de estos aceites con prensa de tornillo a escala industrial. Las variables de proceso analizadas fueron el contenido de humedad de la semilla (CHS) y el diámetro de reducción (DR). Los modelos ajustados para rendimiento de aceite (RA) indicaron valores máximos predichos similares a los valores experimentales. Las extracciones de aceite de nuez mostraron un RA máximo (84,5 ± 2,3%) a 7,21% CHS, y 10 mm DR. Para almendra, se obtuvo un máximo de RA (71,9 ± 3,5%) con 9,42% de CHS y 12 mm de DR. Los parámetros de calidad química de ambos aceites se encontraban en los rangos establecidos en las normas del Codex (FAO / OMS) para aceites vírgenes (no refinados).

  2. Bivariate discrete beta Kernel graduation of mortality data.

    Science.gov (United States)

    Mazza, Angelo; Punzo, Antonio

    2015-07-01

    Various parametric/nonparametric techniques have been proposed in literature to graduate mortality data as a function of age. Nonparametric approaches, as for example kernel smoothing regression, are often preferred because they do not assume any particular mortality law. Among the existing kernel smoothing approaches, the recently proposed (univariate) discrete beta kernel smoother has been shown to provide some benefits. Bivariate graduation, over age and calendar years or durations, is common practice in demography and actuarial sciences. In this paper, we generalize the discrete beta kernel smoother to the bivariate case, and we introduce an adaptive bandwidth variant that may provide additional benefits when data on exposures to the risk of death are available; furthermore, we outline a cross-validation procedure for bandwidths selection. Using simulations studies, we compare the bivariate approach proposed here with its corresponding univariate formulation and with two popular nonparametric bivariate graduation techniques, based on Epanechnikov kernels and on P-splines. To make simulations realistic, a bivariate dataset, based on probabilities of dying recorded for the US males, is used. Simulations have confirmed the gain in performance of the new bivariate approach with respect to both the univariate and the bivariate competitors.

  3. 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.

  4. 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.

  5. On flame kernel formation and propagation in premixed gases

    Energy Technology Data Exchange (ETDEWEB)

    Eisazadeh-Far, Kian; Metghalchi, Hameed [Northeastern University, Mechanical and Industrial Engineering Department, Boston, MA 02115 (United States); Parsinejad, Farzan [Chevron Oronite Company LLC, Richmond, CA 94801 (United States); Keck, James C. [Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)

    2010-12-15

    Flame kernel formation and propagation in premixed gases have been studied experimentally and theoretically. The experiments have been carried out at constant pressure and temperature in a constant volume vessel located in a high speed shadowgraph system. The formation and propagation of the hot plasma kernel has been simulated for inert gas mixtures using a thermodynamic model. The effects of various parameters including the discharge energy, radiation losses, initial temperature and initial volume of the plasma have been studied in detail. The experiments have been extended to flame kernel formation and propagation of methane/air mixtures. The effect of energy terms including spark energy, chemical energy and energy losses on flame kernel formation and propagation have been investigated. The inputs for this model are the initial conditions of the mixture and experimental data for flame radii. It is concluded that these are the most important parameters effecting plasma kernel growth. The results of laminar burning speeds have been compared with previously published results and are in good agreement. (author)

  6. Insights from Classifying Visual Concepts with Multiple Kernel Learning

    Science.gov (United States)

    Binder, Alexander; Nakajima, Shinichi; Kloft, Marius; Müller, Christina; Samek, Wojciech; Brefeld, Ulf; Müller, Klaus-Robert; Kawanabe, Motoaki

    2012-01-01

    Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote sparse mixtures. Unfortunately, 1-norm regularized MKL variants are often observed to be outperformed by an unweighted sum kernel. The main contributions of this paper are the following: we apply a recently developed non-sparse MKL variant to state-of-the-art concept recognition tasks from the application domain of computer vision. We provide insights on benefits and limits of non-sparse MKL and compare it against its direct competitors, the sum-kernel SVM and sparse MKL. We report empirical results for the PASCAL VOC 2009 Classification and ImageCLEF2010 Photo Annotation challenge data sets. Data sets (kernel matrices) as well as further information are available at http://doc.ml.tu-berlin.de/image_mkl/(Accessed 2012 Jun 25). PMID:22936970

  7. 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.

  8. Kernel Methods for Mining Instance Data in Ontologies

    Science.gov (United States)

    Bloehdorn, Stephan; Sure, York

    The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

  9. Comparing growth rate in a mixed plantation (walnut, poplar and nurse trees with different planting designs: results from an experimental plantation in northern Italy

    Directory of Open Access Journals (Sweden)

    Francesco Pelleri

    2013-12-01

    Full Text Available 800x600 Results of a mixed plantation with poplar, walnut and nurse trees established in winter 2003 in Northern Italy, are reported. Main tree species (poplar and walnut were planted according to a rectangular design (10 x 11m, with different spacings and alternate lines. The experimental trial was carried out to verify the following working hypotheses: (i possibility to combine main trees with different growth levels (common walnut, hybrid walnut, and different poplar clones and test two different poplar and walnut spacings (5.0 and 7.4 m in the same plantation; (ii opportunity to reduce cultivation’s workload, in comparison with poplar monoculture, using mixtures with different poplar clones and N-fixing nurse trees; (iii verifying the growth pattern of two new poplar clones in comparison with the traditional clones cultivated for different purposes in Italy.The use of different valuable crop trees’ mixtures intercropped with nurse trees and shrubs (including N-fixing trees allows to decrease the cultivation’s workload. In fact, a heavy reduction of cultural practices - fertilizers, weed control, irrigation and pesticides applications (-61% are the main concurrent, supplementary benefits. The best growth performances (DBH and tree height, associated with the higher competition towards walnuts, were recorded with the new clones Lena and Neva in comparison with the I214 and Villafranca. The closer spacing (5 m between poplar and walnut trees was found to be unsuited to get merchantable poplars sized 30 cm without developing a heavy competition towards walnut trees. The wider spacing (7.4 m resulted vice versa suitable to get poplar trees sized as requested by veneer factories and to maintain an acceptable competitive level with walnut. Within this plantation design, a shorter rotation (8 yrs is needed for Lena and Neva clones in comparison with I214 and Villafranca (10 yrs. Walnut intercropped with poplar showed cone-shaped crowns, light

  10. Gibbons (Nomascus gabriellae) provide key seed dispersal for the Pacific walnut (Dracontomelon dao), in Asia's lowland tropical forest

    Science.gov (United States)

    Hai, Bach Thanh; Chen, Jin; McConkey, Kim R.; Dayananda, Salindra K.

    2018-04-01

    Understanding the mutualisms between frugivores and plants is essential for developing successful forest management and conservation strategies, especially in tropical rainforests where the majority of plants are dispersed by animals. Gibbons are among the most effective seed dispersers in South East Asia's tropical forests, but are also one of the highly threatened arboreal mammals in the region. Here we studied the seed dispersal of the Pacific walnut (Dracontomelon dao), a canopy tree which produces fruit that are common in the diet of the endangered southern yellow-cheeked crested gibbon (Nomascus gabriellae). We found that gibbons were the most effective disperser for this species; they consumed approximately 45% of the fruit crop, which was four times more than that consumed by macaques - the only other legitimate disperser. Gibbons tracked the temporal (but not spatial) abundance of ripe fruits, indicating this fruit was a preferred species for the gibbon. Both gibbons and macaques dispersed the majority (>90%) of the seeds at least 20 m away from parent crowns, with mean dispersal distances by gibbons measuring 179.3 ± 98.0 m (range: 4-425 m). Seeds defecated by gibbons germinated quicker and at greater rates than seeds spat by macaques, or in undispersed fruits. Gibbon-dispersed seeds were also more likely to be removed by unknown seed predators or unknown secondary dispersers. Overall, gibbons play a key role in the regeneration of the Pacific walnut. Our findings have significant implications both for the management of the Pacific walnut tree dominating tropical rainforest as well as the reintroduction program of the Southern yellow-cheeked crested gibbon.

  11. Semisupervised kernel marginal Fisher analysis for face recognition.

    Science.gov (United States)

    Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

    2013-01-01

    Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

  12. 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....

  13. 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.

  14. Weighted Feature Gaussian Kernel SVM for Emotion Recognition.

    Science.gov (United States)

    Wei, Wei; Jia, Qingxuan

    2016-01-01

    Emotion recognition with weighted feature based on facial expression is a challenging research topic and has attracted great attention in the past few years. This paper presents a novel method, utilizing subregion recognition rate to weight kernel function. First, we divide the facial expression image into some uniform subregions and calculate corresponding recognition rate and weight. Then, we get a weighted feature Gaussian kernel function and construct a classifier based on Support Vector Machine (SVM). At last, the experimental results suggest that the approach based on weighted feature Gaussian kernel function has good performance on the correct rate in emotion recognition. The experiments on the extended Cohn-Kanade (CK+) dataset show that our method has achieved encouraging recognition results compared to the state-of-the-art methods.

  15. 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.

  16. Consumption of restructured meat products with added walnuts has a cholesterol-lowering effect in subjects at high cardiovascular risk: a randomised, crossover, placebo-controlled study.

    Science.gov (United States)

    Olmedilla-Alonso, B; Granado-Lorencio, F; Herrero-Barbudo, C; Blanco-Navarro, I; Blázquez-García, S; Pérez-Sacristán, B

    2008-04-01

    Diet and lifestyle are modifiable factors involved in the development and prevention of non-communicable diseases, including cardiovascular disease. Nut consumption, particularly walnut intake, has been inversely related to incident coronary heart disease (CHD) in observational studies and to improved lipid profiles in short-term feeding trials. To assess the potential functional effect associated with the regular consumption of walnut-enriched restructured meat products in subjects at risk for cardiovascular disease (CVD). A crossover single-dose bioavailability study (n = 3) using gamma-tocopherol as exposure marker and a crossover unblinded dietary intervention study (5 weeks) in subjects at risk (n = 25). Dietary intervention consisted of regular consumption of the meat product, with or without walnuts, five times per week for five weeks with a 1-month washout in between. Overnight fasting blood samples were collected on days 0, 12, 21, 28 and 35, coinciding with blood pressure and body weight recordings. Participants were asked to complete a diet record throughout the study. The functional effects were assessed using clinically relevant and related biomarkers of CHD: serum total, HDL and LDL cholesterol, triacylglycerols, homocysteine, vitamins B(6) and B(12), folic acid, alpha-tocopherol and platelet function test (obturation time). The regular consumption of walnut-enriched meat products compared with that of the restructured meat products without added walnuts provokes a decrease in total cholesterol of 6.8 mg/dl (CI(95%): -12.8, -0.85). Compared to baseline (mixed diet), meat products with walnuts decreased total cholesterol (-10.7 mg/dl, CI(95%): -17.1, -4.2), LDL cholesterol (-7.6 mg/dl, CI(95%): -2.2, -13.0) and body weight (-0.5 kg, CI(95%): -0.1, -0.9) and increased gamma-tocopherol (8.9 mg/dl, CI(95%): 1.0, 16.8). The restructured meat products with added walnuts supplied in this study can be considered functional foods for subjects at high risk for

  17. A multi-label learning based kernel automatic recommendation method for support vector machine.

    Science.gov (United States)

    Zhang, Xueying; Song, Qinbao

    2015-01-01

    Choosing an appropriate kernel is very important and critical when classifying a new problem with Support Vector Machine. So far, more attention has been paid on constructing new kernels and choosing suitable parameter values for a specific kernel function, but less on kernel selection. Furthermore, most of current kernel selection methods focus on seeking a best kernel with the highest classification accuracy via cross-validation, they are time consuming and ignore the differences among the number of support vectors and the CPU time of SVM with different kernels. Considering the tradeoff between classification success ratio and CPU time, there may be multiple kernel functions performing equally well on the same classification problem. Aiming to automatically select those appropriate kernel functions for a given data set, we propose a multi-label learning based kernel recommendation method built on the data characteristics. For each data set, the meta-knowledge data base is first created by extracting the feature vector of data characteristics and identifying the corresponding applicable kernel set. Then the kernel recommendation model is constructed on the generated meta-knowledge data base with the multi-label classification method. Finally, the appropriate kernel functions are recommended to a new data set by the recommendation model according to the characteristics of the new data set. Extensive experiments over 132 UCI benchmark data sets, with five different types of data set characteristics, eleven typical kernels (Linear, Polynomial, Radial Basis Function, Sigmoidal function, Laplace, Multiquadric, Rational Quadratic, Spherical, Spline, Wave and Circular), and five multi-label classification methods demonstrate that, compared with the existing kernel selection methods and the most widely used RBF kernel function, SVM with the kernel function recommended by our proposed method achieved the highest classification performance.

  18. Broken rice kernels and the kinetics of rice hydration and texture during cooking.

    Science.gov (United States)

    Saleh, Mohammed; Meullenet, Jean-Francois

    2013-05-01

    During rice milling and processing, broken kernels are inevitably present, although to date it has been unclear as to how the presence of broken kernels affects rice hydration and cooked rice texture. Therefore, this work intended to study the effect of broken kernels in a rice sample on rice hydration and texture during cooking. Two medium-grain and two long-grain rice cultivars were harvested, dried and milled, and the broken kernels were separated from unbroken kernels. Broken rice kernels were subsequently combined with unbroken rice kernels forming treatments of 0, 40, 150, 350 or 1000 g kg(-1) broken kernels ratio. Rice samples were then cooked and the moisture content of the cooked rice, the moisture uptake rate, and rice hardness and stickiness were measured. As the amount of broken rice kernels increased, rice sample texture became increasingly softer (P hardness was negatively correlated to the percentage of broken kernels in rice samples. Differences in the proportions of broken rice in a milled rice sample play a major role in determining the texture properties of cooked rice. Variations in the moisture migration kinetics between broken and unbroken kernels caused faster hydration of the cores of broken rice kernels, with greater starch leach-out during cooking affecting the texture of the cooked rice. The texture of cooked rice can be controlled, to some extent, by varying the proportion of broken kernels in milled rice. © 2012 Society of Chemical Industry.

  19. Measurement of Weight of Kernels in a Simulated Cylindrical Fuel Compact for HTGR

    International Nuclear Information System (INIS)

    Kim, Woong Ki; Lee, Young Woo; Kim, Young Min; Kim, Yeon Ku; Eom, Sung Ho; Jeong, Kyung Chai; Cho, Moon Sung; Cho, Hyo Jin; Kim, Joo Hee

    2011-01-01

    The TRISO-coated fuel particle for the high temperature gas-cooled reactor (HTGR) is composed of a nuclear fuel kernel and outer coating layers. The coated particles are mixed with graphite matrix to make HTGR fuel element. The weight of fuel kernels in an element is generally measured by the chemical analysis or a gamma-ray spectrometer. Although it is accurate to measure the weight of kernels by the chemical analysis, the samples used in the analysis cannot be put again in the fabrication process. Furthermore, radioactive wastes are generated during the inspection procedure. The gamma-ray spectrometer requires an elaborate reference sample to reduce measurement errors induced from the different geometric shape of test sample from that of reference sample. X-ray computed tomography (CT) is an alternative to measure the weight of kernels in a compact nondestructively. In this study, X-ray CT is applied to measure the weight of kernels in a cylindrical compact containing simulated TRISO-coated particles with ZrO 2 kernels. The volume of kernels as well as the number of kernels in the simulated compact is measured from the 3-D density information. The weight of kernels was calculated from the volume of kernels or the number of kernels. Also, the weight of kernels was measured by extracting the kernels from a compact to review the result of the X-ray CT application

  20. Carbon Abatement and Emissions Associated with the Gasification of Walnut Shells for Bioenergy and Biochar Production.

    Science.gov (United States)

    Pujol Pereira, Engil Isadora; Suddick, Emma C; Six, Johan

    2016-01-01

    By converting biomass residue to biochar, we could generate power cleanly and sequester carbon resulting in overall greenhouse gas emissions (GHG) savings when compared to typical fossil fuel usage and waste disposal. We estimated the carbon dioxide (CO2) abatements and emissions associated to the concurrent production of bioenergy and biochar through biomass gasification in an organic walnut farm and processing facility in California, USA. We accounted for (i) avoided-CO2 emissions from displaced grid electricity by bioenergy; (ii) CO2 emissions from farm machinery used for soil amendment of biochar; (iii) CO2 sequestered in the soil through stable biochar-C; and (iv) direct CO2 and nitrous oxide (N2O) emissions from soil. The objective of these assessments was to pinpoint where the largest C offsets can be expected in the bioenergy-biochar chain. We found that energy production from gasification resulted in 91.8% of total C offsets, followed by stable biochar-C (8.2% of total C sinks), offsetting a total of 107.7 kg CO2-C eq Mg-1 feedstock. At the field scale, we monitored gas fluxes from soils for 29 months (180 individual observations) following field management and precipitation events in addition to weekly measurements within three growing seasons and two tree dormancy periods. We compared four treatments: control, biochar, compost, and biochar combined with compost. Biochar alone or in combination with compost did not alter total N2O and CO2 emissions from soils, indicating that under the conditions of this study, biochar-prompted C offsets may not be expected from the mitigation of direct soil GHG emissions. However, this study revealed a case where a large environmental benefit was given by the waste-to-bioenergy treatment, addressing farm level challenges such as waste management, renewable energy generation, and C sequestration.