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.

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.

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.

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

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®.

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.

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.

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

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.

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 ...

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...

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

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

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...

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...

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.

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

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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

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.

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

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.

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

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

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...

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

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.

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...

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.

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)

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...

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.

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...

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...

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.

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...

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...

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)

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 �

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...

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

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).

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 .

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 ...

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...

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.

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.

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...

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.

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...

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...

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...

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.

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...

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...

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.

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

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.

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

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.

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.

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...

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...

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.

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...

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...

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

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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...

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.

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...

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

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.

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...

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%).

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.

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.

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.

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

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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

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

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.

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 ...

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

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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.

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.

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...

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.

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.

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

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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 CFR 984.450 - Grade and size regulations.

Science.gov (United States)

2010-01-01

... requirements for inshell walnuts for reserve disposition credit. For the purposes of §§ 984.54 and 984.56, no... credited against a handler's reserve obligation. (b) Minimum kernel content requirements for shelled walnuts for reserve disposition credit. For the purposes of §§ 984.54 and 984.56, no lot of shelled...

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...

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.

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.

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...

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.

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

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.

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.

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

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

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

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)

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 ...

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.

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...

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.

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...

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.

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...

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

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...

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...

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.

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

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)

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

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 ...

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 ...

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.

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.

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

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...

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] ...

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.

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...

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...

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 ...

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.

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...

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.

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

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)

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...

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.

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.

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...

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.

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.

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...

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

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)

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)

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

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 ...

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.

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

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.

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

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...

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.

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...

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

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

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.

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`.

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

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.

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 ...

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...

Study on application of the physical detection methods for electron beam-irradiated agricultural products

International Nuclear Information System (INIS)

Kim, Dong Yong; Park, Yong Dae; Jin, Chang Hyun; Choi, Dae Seong; Jeong, Il Yun; Yook, Hong Sun

2010-01-01

Physical detection methods, photostimulated luminescence (PSL), thermoluminescence (TL) and electron spin resonance (ESR) were applied to detect electron beam-irradiated agricultural products, such as red pepper, black pepper, raisin, walnut, beef seasoning and pistachio. The absorbed irradiation doses for representative samples were controlled at 0, 1, 3, 5 and 10 kGy. PSL values for non-irradiated samples were 1 ) except beef seasoning, whereas those of irradiated samples were more than 5,000 photon counts, upper threshold (T 2 ) in black pepper, raisin, and beef seasoning and intermediates values of T 1 -T 2 in red pepper, walnut, and pistachio. Minerals separated from the samples for TL measurement showed that non-irradiated samples except pistachio (TL ratio, 0.12) were characterized by no glow curves situated at temperature range of 50 ∼ 400 .deg. C with TL ratio (0.01 ∼ 0.08), while irradiated samples except pistachio at only 1 kGy (TL ratio, 0.08) indicated glow curve at about 150 ∼ 250 .deg. C with TL ratio (0.28 ∼ 3.10). ESR measurements of irradiated samples any specific signals to irradiation. The samples of both red pepper ad pistachio were produced specific signals derived from cellulose radicals as well as single line signals for black pepper and walnut, and multiple signals derived from crystalline sugar radicals for raisin and beef seasoning. In conclusion, The ESR methods can apply for detection of pistachio exposed to electron beam but PSL and TL are not suitable methods. Furthermore, TL and ESR suggested that both techniques were more useful detection method than PSL to confirm whether red pepper, walnut and beef seasoning samples have been exposed to electron beam

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...

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…

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.

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.

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 ...

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....

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...

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.

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.

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.

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...

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...

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.

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 ...

Study on application of the physical detection methods for electron beam-irradiated agricultural products

Energy Technology Data Exchange (ETDEWEB)

Kim, Dong Yong; Park, Yong Dae; Jin, Chang Hyun; Choi, Dae Seong; Jeong, Il Yun [Korea Atomic Energy Research Institute, Jeongeup (Korea, Republic of); Yook, Hong Sun [Chungnam National University, Daejeon (Korea, Republic of)

2010-09-15

Physical detection methods, photostimulated luminescence (PSL), thermoluminescence (TL) and electron spin resonance (ESR) were applied to detect electron beam-irradiated agricultural products, such as red pepper, black pepper, raisin, walnut, beef seasoning and pistachio. The absorbed irradiation doses for representative samples were controlled at 0, 1, 3, 5 and 10 kGy. PSL values for non-irradiated samples were <700 counts/60s (lower threshold, T{sub 1}) except beef seasoning, whereas those of irradiated samples were more than 5,000 photon counts, upper threshold (T{sub 2}) in black pepper, raisin, and beef seasoning and intermediates values of T{sub 1}-T{sub 2} in red pepper, walnut, and pistachio. Minerals separated from the samples for TL measurement showed that non-irradiated samples except pistachio (TL ratio, 0.12) were characterized by no glow curves situated at temperature range of 50 {approx} 400 .deg. C with TL ratio (0.01 {approx} 0.08), while irradiated samples except pistachio at only 1 kGy (TL ratio, 0.08) indicated glow curve at about 150 {approx} 250 .deg. C with TL ratio (0.28 {approx} 3.10). ESR measurements of irradiated samples any specific signals to irradiation. The samples of both red pepper ad pistachio were produced specific signals derived from cellulose radicals as well as single line signals for black pepper and walnut, and multiple signals derived from crystalline sugar radicals for raisin and beef seasoning. In conclusion, The ESR methods can apply for detection of pistachio exposed to electron beam but PSL and TL are not suitable methods. Furthermore, TL and ESR suggested that both techniques were more useful detection method than PSL to confirm whether red pepper, walnut and beef seasoning samples have been exposed to electron beam.

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

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

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

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...

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.

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.

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.

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

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...

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

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...

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,...

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

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...

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....

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...

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...

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 ...

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.

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.

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...

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.

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.

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

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.

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.

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

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

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...

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 ...

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.

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

Agro-Science Journal of Tropical Agriculture, Food, Environment ...

African Journals Online (AJOL)

PC USER

A study of the physical and proximate traits of seeds of African walnut (Plukenetia conophorum) from four ... statistical linkage with most of the seed physical traits; whereas kernel weight ..... antioxidant activity of Tetracarpidium ... Longevity, vol.

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

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

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

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...

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.

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 ...

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....

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.

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.

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.)

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.

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.

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...

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

Variability of some morphological traits of one-year old red oak, black walnut, birch and wild pear seedlings in the nurseries of Jastrebac region

Directory of Open Access Journals (Sweden)

Krstić Milun

2002-01-01

Full Text Available Five morphological and quantitative characteristics of one-year old seedlings of Red oak (Quercus rubra L, Black walnut (Juglans nigra L, Wild pear (Pyrus pygrowser Borkh and Birch (Betula verrucosa Ehrh were studied. The seedlings were produced and cultivated in the controlled conditions of the nursery in the region of Jastrebac, by the classical method. Aboveground seedling height, root collar diameter, root length, number of secondary roots and the leaf assimilation area were analysed. Intraspecific and interspecific variability of morphological features of the above species were assessed by the comparative analysis and statistical methods The comparative analysis shows the great individual variability of seedlings, which can indicate their genetic potential, adaptation to environment conditions, further spontaneous selection and the development in natural conditions. This justifies the need of the quality assessment and the first selection already in the nursery, in order to ensure the quality planting material and to reduce the risk of afforestation failure One-year old birch seedlings have the lowest average height (18.8 cm. Black walnut and Wild pear seedlings are approximately twice as high, and Red oak about 2.5 times higher. At the same time Red oak seedlings have for about one-fourth greater height than Black walnut, and for one-third greater height than Wild pear. Wild pear seedlings attain the averagely twice larger root collar diameter than Birch (2.8 cm, Red oak seedlings about 2.5 times larger diameter, and Black walnut 3.5 times larger diameter. Black walnut has a larger root collar diameter than Red oak for about one third, and almost twice larger than Wild pear. Birch, Red oak and Wild pear have almost twice longer root (1.8-1.9 times, Black walnut about 2.25 times longer. The total assimilation area of a Birch seedling is averagely 89.0 cm2. Compared to birch, wild pear has approximately double assimilation area per tree, Red

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.

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.

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

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...

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.

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.

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...

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...

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

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.

Changes in soil organic carbon and total nitrogen in croplands converted to walnut-based agroforestry systems and orchards in southeastern Loess Plateau of China.

Science.gov (United States)

Lu, Sen; Meng, Ping; Zhang, Jinsong; Yin, Changjun; Sun, Shiyou

2015-11-01

Limited information is available on the effects of agroforestry system practices on soil properties in the Loess Plateau of China. Over the last decade, a vegetation restoration project has been conducted in this area by converting cropland into tree-based agroforestry systems and orchards to combat soil erosion and degradation. The objective of the present study was to determine the effects of land use conversion on soil organic carbon and total nitrogen in southeastern Loess Plateau. The experiment included three treatments: walnut intercropping system (AF), walnut orchard (WO), and traditional cropland (CR). After 7 years of continual management, soil samples were collected at 0-10, 10-30, and 30-50-cm depths for three treatments, and soil organic carbon (SOC) and total nitrogen (TN) were measured. Results showed that compared with the CR and AF treatments, WO treatment decreased both SOC and TN concentrations in the 0-50-cm soil profile. However, similar patterns of SOC and TN concentrations were observed in the AF and CR treatments across the entire profile. The SOC stocks at 0-50-cm depth were 5.42, 5.52, and 4.67 kg m(-2) for CR, AF, and WO treatments, respectively. The calculated TN stocks at 0-50-cm depth were 0.63, 0.62, and 0.57 kg m(-2) for CR, AF, and WO treatments, respectively. This result demonstrated that the stocks of SOC and TN in WO were clearly lower than those of AF and CR and that the walnut-based agroforestry system was more beneficial than walnut monoculture in terms of SOC and TN sequestration. Owing to the short-term intercropping practice, the changes in SOC and TN stocks were slight in AF compared with those in CR. However, a significant decrease in SOC and TN stocks was observed during the conversion of cropland to walnut orchard after 7 years of management. We also found that land use types had no significant effect on soil C/N ratio. These findings demonstrated that intercropping between walnut rows can potentially maintain

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

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).

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.

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.

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 ...

The Design and Implementation of Persistence in the Annex System

Science.gov (United States)

2009-08-01

MONADS [Rosenberg 1990], Grasshopper [Dearle, di Bona et al. 1993], the Walnut kernel [Castro 1996], the L3 microkernel [Liedtke 1993] and its...successor L4 [Skoglund, Ceelen & Liedtke 2000], KeyKOS [Hardy 1985] and Charm [Dearle & Hulse 2000]. There is a great difference in design between these...persistence are Annex and the L4 micro-kernel [Skoglund, Ceelen & Liedtke 2000]. In either case, to implement some form of persistence a system must have a

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...

Range-separated time-dependent density-functional theory with a frequency-dependent second-order Bethe-Salpeter correlation kernel

Energy Technology Data Exchange (ETDEWEB)

Rebolini, Elisa, E-mail: elisa.rebolini@kjemi.uio.no; Toulouse, Julien, E-mail: julien.toulouse@upmc.fr [Laboratoire de Chimie Théorique, Sorbonne Universités, UPMC Univ Paris 06, CNRS, 4 place Jussieu, F-75005 Paris (France)

2016-03-07

We present a range-separated linear-response time-dependent density-functional theory (TDDFT) which combines a density-functional approximation for the short-range response kernel and a frequency-dependent second-order Bethe-Salpeter approximation for the long-range response kernel. This approach goes beyond the adiabatic approximation usually used in linear-response TDDFT and aims at improving the accuracy of calculations of electronic excitation energies of molecular systems. A detailed derivation of the frequency-dependent second-order Bethe-Salpeter correlation kernel is given using many-body Green-function theory. Preliminary tests of this range-separated TDDFT method are presented for the calculation of excitation energies of the He and Be atoms and small molecules (H{sub 2}, N{sub 2}, CO{sub 2}, H{sub 2}CO, and C{sub 2}H{sub 4}). The results suggest that the addition of the long-range second-order Bethe-Salpeter correlation kernel overall slightly improves the excitation energies.

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.

Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

Science.gov (United States)

Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

2015-05-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

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...

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 ...

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 ...

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.

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.

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

Science.gov (United States)

Tezuka, Taro

2018-06-01

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

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

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%.

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...

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.

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

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.

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.

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...

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

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....

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)

7 CFR 51.2946 - Color chart.

Science.gov (United States)

2010-01-01

... Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946... illustrates four shades of color used to describe skin color of walnut kernels. (a) Availability of color...

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...

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...

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....

Long term high resolution rainfall runoff observations for improved water balance uncertainty and database QA-QC in the Walnut Gulch Experimental Watershed.

Science.gov (United States)

Bitew, M. M.; Goodrich, D. C.; Demaria, E.; Heilman, P.; Kautz, M. A.

2017-12-01

Walnut Gulch is a semi-arid environment experimental watershed and Long Term Agro-ecosystem Research (LTAR) site managed by USDA-ARS Southwest Watershed Research Center for which high-resolution long-term hydro-climatic data are available across its 150 km2 drainage area. In this study, we present the analysis of 50 years of continuous hourly rainfall data to evaluate runoff control and generation processes for improving the QA-QC plans of Walnut Gulch to create high-quality data set that is critical for reducing water balance uncertainties. Multiple linear regression models were developed to relate rainfall properties, runoff characteristics and watershed properties. The rainfall properties were summarized to event based total depth, maximum intensity, duration, the location of the storm center with respect to the outlet, and storm size normalized to watershed area. We evaluated the interaction between the runoff and rainfall and runoff as antecedent moisture condition (AMC), antecedent runoff condition (ARC) and, runoff depth and duration for each rainfall events. We summarized each of the watershed properties such as contributing area, slope, shape, channel length, stream density, channel flow area, and percent of the area of retention stock ponds for each of the nested catchments in Walnut Gulch. The evaluation of the model using basic and categorical statistics showed good predictive skill throughout the watersheds. The model produced correlation coefficients ranging from 0.4-0.94, Nash efficiency coefficients up to 0.77, and Kling-Gupta coefficients ranging from 0.4 to 0.98. The model predicted 92% of all runoff generations and 98% of no-runoff across all sub-watersheds in Walnut Gulch. The regression model also indicated good potential to complement the QA-QC procedures in place for Walnut Gulch dataset publications developed over the years since the 1960s through identification of inconsistencies in rainfall and runoff relations.

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...

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.

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.

Features of atomic images reconstructed from photoelectron, Auger electron, and internal detector electron holography using SPEA-MEM

Energy Technology Data Exchange (ETDEWEB)

Matsushita, Tomohiro, E-mail: matusita@spring8.or.jp [Japan Synchrotron Radiation Research Institute, SPring-8, Sayo, Hyogo 679-5198 (Japan); Matsui, Fumihiko [Graduate School of Materials Science, Nara Institute of Science and Technology, Ikoma, Nara 630-0192 (Japan)

2014-08-15

Highlights: • We develop a 3D atomic image reconstruction algorithm for photoelectron, Auger electron, and internal detector holography. • We examine the shapes of the atomic images reconstructed by using a developed kernel function. • We examine refraction effect at surface, limitation effect of the hologram data, energy resolution effect, and angular resolution effect. • These discussions indicate the experimental requirements to obtain the clear 3D atomic image. - Abstract: Three-dimensional atomic images can be reconstructed from photoelectron, Auger electron, and internal detector electron holograms using a scattering pattern extraction algorithm using the maximum entropy method (SPEA-MEM) that utilizes an integral transform. An integral kernel function for the integral transform is the key to clear atomic image reconstruction. We composed the kernel function using a scattering pattern function and estimated its ability. Image distortion caused by multiple scattering was also evaluated. Four types of Auger electron wave functions were investigated, and the effect of these wave function types was estimated. In addition, we addressed refraction at the surface, the effects of data limitation, and energy and angular resolutions.

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

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...

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...

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...

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.

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.

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.

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.

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.

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

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...

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...

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

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....

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...

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...

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.

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.

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.

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...

Notes on the gamma kernel

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.

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

7 CFR 51.2948 - U.S. No. 1.

Science.gov (United States)

2010-01-01

... Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE REGULATIONS AND STANDARDS UNDER THE AGRICULTURAL MARKETING ACT OF 1946...: Provided, That at least four-sevenths of the above amount, or 40 percent of the walnuts have kernels which...

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

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...

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.

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.

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.

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.

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.

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

The heating of UO_2 kernels in argon gas medium on the physical properties of sintered UO_2 kernels

International Nuclear Information System (INIS)

Damunir; Sri Rinanti Susilowati; Ariyani Kusuma Dewi

2015-01-01

The heating of UO_2 kernels in argon gas medium on the physical properties of sinter UO_2 kernels was conducted. The heated of the UO_2 kernels was conducted in a sinter reactor of a bed type. The sample used was the UO_2 kernels resulted from the reduction results at 800 °C temperature for 3 hours that had the density of 8.13 g/cm"3; porosity of 0.26; O/U ratio of 2.05; diameter of 1146 μm and sphericity of 1.05. The sample was put into a sinter reactor, then it was vacuumed by flowing the argon gas at 180 mmHg pressure to drain the air from the reactor. After that, the cooling water and argon gas were continuously flowed with the pressure of 5 mPa with 1.5 liter/minutes velocity. The reactor temperature was increased and variated at 1200-1500 °C temperature and for 1-4 hours. The sinters UO_2 kernels resulted from the study were analyzed in term of their physical properties including the density, porosity, diameter, sphericity, and specific surface area. The density was analyzed using pycnometer with CCl_4 solution. The porosity was determined using Haynes equation. The diameters and sphericity were showed using the Dino-lite microscope. The specific surface area was determined using surface area meter Nova-1000. The obtained products showed the the heating of UO_2 kernel in argon gas medium were influenced on the physical properties of sinters UO_2 kernel. The condition of best relatively at 1400 °C temperature and 2 hours time. The product resulted from the study was relatively at its best when heating was conducted at 1400 °C temperature and 2 hours time, produced sinters UO_2 kernel with density of 10.14 gr/ml; porosity of 7 %; diameters of 893 μm; sphericity of 1.07 and specific surface area of 4.68 m"2/g with solidify shrinkage of 22 %. (author)

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.

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...

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.

Effective exchange potentials for electronically inelastic scattering

International Nuclear Information System (INIS)

Schwenke, D.W.; Staszewska, G.; Truhlar, D.G.

1983-01-01

We propose new methods for solving the electron scattering close coupling equations employing equivalent local exchange potentials in place of the continuum-multiconfiguration-Hartree--Fock-type exchange kernels. The local exchange potentials are Hermitian. They have the correct symmetry for any symmetries of excited electronic states included in the close coupling expansion, and they have the same limit at very high energy as previously employed exchange potentials. Comparison of numerical calculations employing the new exchange potentials with the results obtained with the standard nonlocal exchange kernels shows that the new exchange potentials are more accurate than the local exchange approximations previously available for electronically inelastic scattering. We anticipate that the new approximations will be most useful for intermediate-energy electronically inelastic electron--molecule scattering

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.

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%.

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

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)

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....

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.

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...

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)

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.

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...

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.

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....

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

Science.gov (United States)

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

2016-02-01

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

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

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

Science.gov (United States)

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

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 ...

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...

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...

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

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.

Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

Science.gov (United States)

Ma, Yuntao; Chen, Youjia; Zhu, Jinyu; Meng, Lei; Guo, Yan; Li, Baoguo; Hoogenboom, Gerrit

2018-02-13

Failure to account for the variation of kernel growth in a cereal crop simulation model may cause serious deviations in the estimates of crop yield. The goal of this research was to revise the GREENLAB-Maize model to incorporate source- and sink-limited allocation approaches to simulate the dry matter accumulation of individual kernels of an ear (GREENLAB-Maize-Kernel). The model used potential individual kernel growth rates to characterize the individual potential sink demand. The remobilization of non-structural carbohydrates from reserve organs to kernels was also incorporated. Two years of field experiments were conducted to determine the model parameter values and to evaluate the model using two maize hybrids with different plant densities and pollination treatments. Detailed observations were made on the dimensions and dry weights of individual kernels and other above-ground plant organs throughout the seasons. Three basic traits characterizing an individual kernel were compared on simulated and measured individual kernels: (1) final kernel size; (2) kernel growth rate; and (3) duration of kernel filling. Simulations of individual kernel growth closely corresponded to experimental data. The model was able to reproduce the observed dry weight of plant organs well. Then, the source-sink dynamics and the remobilization of carbohydrates for kernel growth were quantified to show that remobilization processes accompanied source-sink dynamics during the kernel-filling process. We conclude that the model may be used to explore options for optimizing plant kernel yield by matching maize management to the environment, taking into account responses at the level of individual kernels. © The Author(s) 2018. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

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.

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.

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.

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...

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

The validity of the density scaling method in primary electron transport for photon and electron beams

International Nuclear Information System (INIS)

Woo, M.K.; Cunningham, J.R.

1990-01-01

In the convolution/superposition method of photon beam dose calculations, inhomogeneities are usually handled by using some form of scaling involving the relative electron densities of the inhomogeneities. In this paper the accuracy of density scaling as applied to primary electrons generated in photon interactions is examined. Monte Carlo calculations are compared with density scaling calculations for air and cork slab inhomogeneities. For individual primary photon kernels as well as for photon interactions restricted to a thin layer, the results can differ significantly, by up to 50%, between the two calculations. However, for realistic photon beams where interactions occur throughout the whole irradiated volume, the discrepancies are much less severe. The discrepancies for the kernel calculation are attributed to the scattering characteristics of the electrons and the consequent oversimplified modeling used in the density scaling method. A technique called the kernel integration technique is developed to analyze the general effects of air and cork inhomogeneities. It is shown that the discrepancies become significant only under rather extreme conditions, such as immediately beyond the surface after a large air gap. In electron beams all the primary electrons originate from the surface of the phantom and the errors caused by simple density scaling can be much more significant. Various aspects relating to the accuracy of density scaling for air and cork slab inhomogeneities are discussed

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...

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...

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 .

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

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.

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)

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.

Effect of incorporation of walnut cake (Juglans regia in concentrate mixture on degradation of dry matter, organic matter and production of microbial biomass in vitro in goat

Directory of Open Access Journals (Sweden)

Mohsin Ahmad Mir

2015-10-01

Full Text Available Aim: This study was carried out to investigate the effect of incorporation of different level of walnut cake in concentrate mixture on in vitro dry matter degradation in order to determine its level of supplementation in ruminant ration. Materials and Methods: Walnut cake was used @ 0, 10, 15, 20, 25 and 30% level to formulate an iso-nitrogenous concentrate mixtures and designated as T1, T2, T3, T4, T5 and T6 respectively. The different formulae of concentrate mixtures were used for in vitro gas production studies using goat rumen liquor with wheat straw in 40:60 ratio. Proximate composition, fiber fractionation and calcium and phosphrous content of walnut cake were estimated. Result: The per cent IVDMD value of T1 and T2 diets was 68.42 ± 1.20 and 67.25 ± 1.37 respectively which was found highest (P<0.05 T3, T4, T5 and T6. Similar trend was also found for TDOM and MBP. Inclusion of walnut cake at 10% level in the concentrate mixture does not affect in vitro dry matter digestibility (IVDMD, truly degradable organic matter (TDOM, mg/200 mg DM, total gas production, microbial biomass production (MBP and efficiency of microbial biomass production (EMP. Conclusion: It is concluded that walnut cake incorporation up to 10% level in the iso -nitrogenous concentrate mixture has no any negative effect on in vitro digestibility of dry matter (DM, TDOM, MBP, EMP and total gas production in goat.

Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

International Nuclear Information System (INIS)

Carter, L.L.; Hendricks, J.S.

1983-01-01

The exponential transform is often used to improve the efficiency of deep-penetration Monte Carlo calculations. This technique is usually implemented by biasing the distance-to-collision kernel of the transport equation, but leaving the scattering kernel unchanged. Dwivedi obtained significant improvements in efficiency by biasing an isotropic scattering kernel as well as the distance-to-collision kernel. This idea is extended to anisotropic scattering, particularly the highly forward Klein-Nishina scattering of gamma rays

The integral first collision kernel method for gamma-ray skyshine analysis[Skyshine; Gamma-ray; First collision kernel; Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

Sheu, R.-D.; Chui, C.-S.; Jiang, S.-H. E-mail: shjiang@mx.nthu.edu.tw

2003-12-01

A simplified method, based on the integral of the first collision kernel, is presented for performing gamma-ray skyshine calculations for the collimated sources. The first collision kernels were calculated in air for a reference air density by use of the EGS4 Monte Carlo code. These kernels can be applied to other air densities by applying density corrections. The integral first collision kernel (IFCK) method has been used to calculate two of the ANSI/ANS skyshine benchmark problems and the results were compared with a number of other commonly used codes. Our results were generally in good agreement with others but only spend a small fraction of the computation time required by the Monte Carlo calculations. The scheme of the IFCK method for dealing with lots of source collimation geometry is also presented in this study.

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...

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.

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.

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.

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…

Point kernels and superposition methods for scatter dose calculations in brachytherapy

International Nuclear Information System (INIS)

Carlsson, A.K.

2000-01-01

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

Online learning control using adaptive critic designs with sparse kernel machines.

Science.gov (United States)

Xu, Xin; Hou, Zhongsheng; Lian, Chuanqiang; He, Haibo

2013-05-01

In the past decade, adaptive critic designs (ACDs), including heuristic dynamic programming (HDP), dual heuristic programming (DHP), and their action-dependent ones, have been widely studied to realize online learning control of dynamical systems. However, because neural networks with manually designed features are commonly used to deal with continuous state and action spaces, the generalization capability and learning efficiency of previous ACDs still need to be improved. In this paper, a novel framework of ACDs with sparse kernel machines is presented by integrating kernel methods into the critic of ACDs. To improve the generalization capability as well as the computational efficiency of kernel machines, a sparsification method based on the approximately linear dependence analysis is used. Using the sparse kernel machines, two kernel-based ACD algorithms, that is, kernel HDP (KHDP) and kernel DHP (KDHP), are proposed and their performance is analyzed both theoretically and empirically. Because of the representation learning and generalization capability of sparse kernel machines, KHDP and KDHP can obtain much better performance than previous HDP and DHP with manually designed neural networks. Simulation and experimental results of two nonlinear control problems, that is, a continuous-action inverted pendulum problem and a ball and plate control problem, demonstrate the effectiveness of the proposed kernel ACD methods.

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.

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.

Using the Intel Math Kernel Library on Peregrine | High-Performance

Science.gov (United States)

Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier

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

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.

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.

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...

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.

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.

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

Walnut supplementation reverses the scopolamine-induced memory impairment by restoration of cholinergic function via mitigating oxidative stress in rats: a potential therapeutic intervention for age related neurodegenerative disorders.

Science.gov (United States)

Haider, Saida; Batool, Zehra; Ahmad, Saara; Siddiqui, Rafat Ali; Haleem, Darakhshan Jabeen

2018-02-01

The brain is highly susceptible to the damaging effects of oxidative reactive species. The free radicals which are produced as a consequence of aerobic respiration can cause cumulative oxygen damage which may lead to age-related neurodegeneration. Scopolamine, the anti-muscarinic agent, induces amnesia and oxidative stress similar to that observed in the older age. Studies suggest that antioxidants derived from plant products may provide protection against oxidative stress. Therefore, the present study was designed to investigate the attenuation of scopolamine-induced memory impairment and oxidative stress by walnut supplementation in rats. Rats in test group were administrated with walnut suspension (400 mg/kg/day) for four weeks. Both control and walnut-treated rats were then divided into saline and scopolamine-treated groups. Rats in the scopolamine group were injected with scopolamine (0.5 mg/kg dissolved in saline) five minutes before the start of each memory test. Memory was assessed by elevated plus maze (EPM), Morris water maze (MWM), and novel object recognition task (NOR) followed by estimation of regional acetylcholine levels and acetylcholinesterase activity. In the next phase, brain oxidative status was determined by assaying lipid peroxidation, and measuring superoxide dismutase (SOD), glutathione peroxidase (GPx) and catalase (CAT) activities. Results showed that scopolamine-treatment impaired memory function, caused cholinergic dysfunction, and induced oxidative stress in rats compared to that saline-treated controls. These impairments were significantly restored by pre-administration of walnut. This study demonstrates that antioxidant properties of walnut may provide augmented effects on cholinergic function by reducing oxidative stress and thus improving memory performance.

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.

A framework for optimal kernel-based manifold embedding of medical image data.

Science.gov (United States)

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

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.

A Fourier-series-based kernel-independent fast multipole method

International Nuclear Information System (INIS)

Zhang Bo; Huang Jingfang; Pitsianis, Nikos P.; Sun Xiaobai

2011-01-01

We present in this paper a new kernel-independent fast multipole method (FMM), named as FKI-FMM, for pairwise particle interactions with translation-invariant kernel functions. FKI-FMM creates, using numerical techniques, sufficiently accurate and compressive representations of a given kernel function over multi-scale interaction regions in the form of a truncated Fourier series. It provides also economic operators for the multipole-to-multipole, multipole-to-local, and local-to-local translations that are typical and essential in the FMM algorithms. The multipole-to-local translation operator, in particular, is readily diagonal and does not dominate in arithmetic operations. FKI-FMM provides an alternative and competitive option, among other kernel-independent FMM algorithms, for an efficient application of the FMM, especially for applications where the kernel function consists of multi-physics and multi-scale components as those arising in recent studies of biological systems. We present the complexity analysis and demonstrate with experimental results the FKI-FMM performance in accuracy and efficiency.

The dipole form of the gluon part of the BFKL kernel

International Nuclear Information System (INIS)

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

2007-01-01

The dipole form of the gluon part of the color singlet BFKL kernel in the next-to-leading order (NLO) is obtained in the coordinate representation by direct transfer from the momentum representation, where the kernel was calculated before. With this paper the transformation of the NLO BFKL kernel to the dipole form, started a few months ago with the quark part of the kernel, is completed

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

Science.gov (United States)

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Does the phenotypic selection affect the genetic structure and diversity? A study case on Walnut in eastern central Italy (the region of Marche

Directory of Open Access Journals (Sweden)

Fulvio Ducci

2009-12-01

Full Text Available The Persian walnut (Juglans regia L. is widely planted in western Europe, either for fruit either for high quality timber production. This tree is generally considered non authoctonous, probably introduced from East some 7000 years ago and spread by several ancient civilisations. The possible artificial origin seems confirmed by the low intra-specific variation and the higher individual variability recorded by several Authors as well as by the lack of natural populations. Indeed, only wider fruit cultivation areas or small groups, lines or isolated walnut trees can be recorded in Italy. The occurrence of walnuts in forest, escaped from cultivation areas, is very rare. Due to the increased interest of planters, walnut plantations have been extended several ten thousands hectares throughout all western Europe. As a consequence of that it was evident the necessity of selected suitable basic populations in order to supply high quality reproductive materials. The conventional method based on the organisation of a wide and exhaustive seed procurement from the native range to establish provenance tests is at the present impossible. Thus it is necessary to study methods of selection which consider basic materials growing within the western European range. This study is aimed to test the efficiency of the multi-trait Selection Index method, in preserving levels of genetic diversity and structures compatible with the standards observed within a reference system of extended Italian populations. As a consequence of the relatively recent introduction, the genetic structure of the species shows individual variation higher than inter-population diversity. Those genetic structure characteristics were revealed also during a survey of walnut resources in the region of Marche, central Italy. The survey was the starting point for selecting and preserving basic materials for high quality woody production, possibly interesting for forest nurseries in the region. The

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.

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

Directory of Open Access Journals (Sweden)

Zhengbin Liu

2016-08-01

Full Text Available Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis. In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.

SU-E-T-154: Calculation of Tissue Dose Point Kernels Using GATE Monte Carlo Simulation Toolkit to Compare with Water Dose Point Kernel

Energy Technology Data Exchange (ETDEWEB)

Khazaee, M [shahid beheshti university, Tehran, Tehran (Iran, Islamic Republic of); Asl, A Kamali [Shahid Beheshti University, Tehran, Iran., Tehran, Tehran (Iran, Islamic Republic of); Geramifar, P [Shariati Hospital, Tehran, Iran., Tehran, Tehran (Iran, Islamic Republic of)

2015-06-15

Purpose: the objective of this study was to assess utilizing water dose point kernel (DPK)instead of tissue dose point kernels in convolution algorithms.to the best of our knowledge, in providing 3D distribution of absorbed dose from a 3D distribution of the activity, the human body is considered equivalent to water. as a Result tissue variations are not considered in patient specific dosimetry. Methods: In this study Gate v7.0 was used to calculate tissue dose point kernel. the beta emitter radionuclides which have taken into consideration in this simulation include Y-90, Lu-177 and P-32 which are commonly used in nuclear medicine. the comparison has been performed for dose point kernels of adipose, bone, breast, heart, intestine, kidney, liver, lung and spleen versus water dose point kernel. Results: In order to validate the simulation the Result of 90Y DPK in water were compared with published results of Papadimitroulas et al (Med. Phys., 2012). The results represented that the mean differences between water DPK and other soft tissues DPKs range between 0.6 % and 1.96% for 90Y, except for lung and bone, where the observed discrepancies are 6.3% and 12.19% respectively. The range of DPK difference for 32P is between 1.74% for breast and 18.85% for bone. For 177Lu, the highest difference belongs to bone which is equal to 16.91%. For other soft tissues the least discrepancy is observed in kidney with 1.68%. Conclusion: In all tissues except for lung and bone, the results of GATE for dose point kernel were comparable to water dose point kernel which demonstrates the appropriateness of applying water dose point kernel instead of soft tissues in the field of nuclear medicine.

SU-E-T-154: Calculation of Tissue Dose Point Kernels Using GATE Monte Carlo Simulation Toolkit to Compare with Water Dose Point Kernel

International Nuclear Information System (INIS)

Khazaee, M; Asl, A Kamali; Geramifar, P

2015-01-01

Purpose: the objective of this study was to assess utilizing water dose point kernel (DPK)instead of tissue dose point kernels in convolution algorithms.to the best of our knowledge, in providing 3D distribution of absorbed dose from a 3D distribution of the activity, the human body is considered equivalent to water. as a Result tissue variations are not considered in patient specific dosimetry. Methods: In this study Gate v7.0 was used to calculate tissue dose point kernel. the beta emitter radionuclides which have taken into consideration in this simulation include Y-90, Lu-177 and P-32 which are commonly used in nuclear medicine. the comparison has been performed for dose point kernels of adipose, bone, breast, heart, intestine, kidney, liver, lung and spleen versus water dose point kernel. Results: In order to validate the simulation the Result of 90Y DPK in water were compared with published results of Papadimitroulas et al (Med. Phys., 2012). The results represented that the mean differences between water DPK and other soft tissues DPKs range between 0.6 % and 1.96% for 90Y, except for lung and bone, where the observed discrepancies are 6.3% and 12.19% respectively. The range of DPK difference for 32P is between 1.74% for breast and 18.85% for bone. For 177Lu, the highest difference belongs to bone which is equal to 16.91%. For other soft tissues the least discrepancy is observed in kidney with 1.68%. Conclusion: In all tissues except for lung and bone, the results of GATE for dose point kernel were comparable to water dose point kernel which demonstrates the appropriateness of applying water dose point kernel instead of soft tissues in the field of nuclear medicine

Quantitative estimates of uptake and internal cycling of {sup 15}N-depleted fertilizer in mature walnut trees

Energy Technology Data Exchange (ETDEWEB)

Weinbaum, S; Kessel, C van [University of California at Davis, Davis, CA (United States)

1998-11-01

In mature fruit trees, internal recycling is an important source of N for the growth of new wood, leaves and fruits. Using {sup 15}N-depleted fertilizer, i.e. {sup 14}N-enriched, N-uptake efficiency and the magnitude of internal N cycling were studied in mature walnut trees. Two kg of {sup 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) 31 refs, 2 figs, 4 tabs

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...

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/

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.

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.

Improved age-diffusion model for low-energy electron transport in solids. I. Theory

International Nuclear Information System (INIS)

Devooght, J.; Dubus, A.; Dehaes, J.C.

1987-01-01

We have developed in this paper a semianalytical electron transport model designed for parametric studies of secondary-electron emission induced by low-energy electrons (keV range) and by fast light ions (100 keV range). The primary-particle transport is assumed to be known and to give rise to an internal electron source. The importance of the nearly isotropic elastic scattering in the secondary-electron energy range (50 eV) and the slowing-down process strongly reduce the influence of the anisotropy of the internal electron source, and the internal electron flux is nearly isotropic as is evidenced by the experimental results. The differential energy behavior of the inelastic scattering kernel is very complicated and the real kernel is replaced by a synthetic scattering kernel of which parameters are obtained by energy and angle moments conservation. Through a P 1 approximation and the use of the synthetic scattering kernel, the Boltzmann equation is approximated by a diffusion--slowing-down equation for the isotropic part of the internal electron flux. The energy-dependent partial reflection boundary condition reduces to a Neumann-Dirichlet boundary condition. An analytical expression for the Green's function of the diffusion--slowing-down equation with the surface boundary condition is obtained by means of approximations close to the age-diffusion theory and the model allows for transient conditions. Independently from the ''improved age-diffusion'' model, a correction formula is developed in order to take into account the backscattering of primary electrons for an incident-electron problem

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...

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

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

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...

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...

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.

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...

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.

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.

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

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.

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

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....

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.

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)

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

Effect of Walnut Consumption on Serum Lipid Profiles, High-Sensitivity C-Reactive Protein and Nitric Oxide in Patients With Coronary Artery Disease

Directory of Open Access Journals (Sweden)

Kalantarian

2015-02-01

Full Text Available Background Coronary artery disease (CAD is one of the major causes of death worldwide. There is a direct relationship between increased levels of blood cholesterol, triglycerides (TG, low density lipoproteins (LDL, high density lipoproteins (HDL, nitric oxide (NO, and high sensitivity C-reactive protein (hs-CRP and the CAD. Walnut may reduce these factors and consequently decrease the risk of CAD. Objectives The aim of this study was to evaluate the effect of walnut consumption on TG, LDL, cholesterol, HDL, NO, and hs-CRP in patients with CAD and healthy people. Patients and Methods In this randomized crossover clinical trial, 70 patients with CAD were divided into two groups: case and control groups. The patients were given 40 g walnuts daily for 4 weeks. After 4 weeks, the TG, LDL, cholesterol, HDL, NO and hs-CRP levels were measured. The experiment was also carried out on healthy people (3 groups with normal range of lipid. The LDL, HDL, cholesterol, and hs-CRP levels were measured using commercially available kits. The nitric oxide level was measured using the Griess reaction method. Results The cholesterol and LDL levels decreased significantly from 202.43 to 187.46 and 123.80 to 108.63 mmol/L (7.9% and 13.9 %, respectively in healthy subjects after the treatment (P < 0.01. In the experimental group, there was no significant difference in cholesterol (P = 0.110 and LDL levels (P = 0.176 before and after the treatment. Moreover, no significant difference was observed in other parameters between the two groups. Conclusions The walnut consumption did not affect cholesterol levels in patients with CAD; however, it might be administered as an agent for reducing the cholesterol, which is one of the risk factors associated with CAD.

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

Optimal kernel shape and bandwidth for atomistic support of continuum stress

International Nuclear Information System (INIS)

Ulz, Manfred H; Moran, Sean J

2013-01-01

The treatment of atomistic scale interactions via molecular dynamics simulations has recently found favour for multiscale modelling within engineering. The estimation of stress at a continuum point on the atomistic scale requires a pre-defined kernel function. This kernel function derives the stress at a continuum point by averaging the contribution from atoms within a region surrounding the continuum point. This averaging volume, and therefore the associated stress at a continuum point, is highly dependent on the bandwidth and shape of the kernel. In this paper we propose an effective and entirely data-driven strategy for simultaneously computing the optimal shape and bandwidth for the kernel. We thoroughly evaluate our proposed approach on copper using three classical elasticity problems. Our evaluation yields three key findings: firstly, our technique can provide a physically meaningful estimation of kernel bandwidth; secondly, we show that a uniform kernel is preferred, thereby justifying the default selection of this kernel shape in future work; and thirdly, we can reliably estimate both of these attributes in a data-driven manner, obtaining values that lead to an accurate estimation of the stress at a continuum point. (paper)

Multivariable Christoffel-Darboux Kernels and Characteristic Polynomials of Random Hermitian Matrices

Directory of Open Access Journals (Sweden)

Hjalmar Rosengren

2006-12-01

Full Text Available We study multivariable Christoffel-Darboux kernels, which may be viewed as reproducing kernels for antisymmetric orthogonal polynomials, and also as correlation functions for products of characteristic polynomials of random Hermitian matrices. Using their interpretation as reproducing kernels, we obtain simple proofs of Pfaffian and determinant formulas, as well as Schur polynomial expansions, for such kernels. In subsequent work, these results are applied in combinatorics (enumeration of marked shifted tableaux and number theory (representation of integers as sums of squares.

A multi-resolution approach to heat kernels on discrete surfaces

KAUST Repository

Vaxman, Amir

2010-07-26

Studying the behavior of the heat diffusion process on a manifold is emerging as an important tool for analyzing the geometry of the manifold. Unfortunately, the high complexity of the computation of the heat kernel - the key to the diffusion process - limits this type of analysis to 3D models of modest resolution. We show how to use the unique properties of the heat kernel of a discrete two dimensional manifold to overcome these limitations. Combining a multi-resolution approach with a novel approximation method for the heat kernel at short times results in an efficient and robust algorithm for computing the heat kernels of detailed models. We show experimentally that our method can achieve good approximations in a fraction of the time required by traditional algorithms. Finally, we demonstrate how these heat kernels can be used to improve a diffusion-based feature extraction algorithm. © 2010 ACM.

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.

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

Science.gov (United States)

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

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)

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

DEFF Research Database (Denmark)

Li, Gang; Guan, Wei; Sierszecki, Krzysztof

2012-01-01

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

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 ...

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.)

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.

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.

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 ...

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.

In silico Coding Sequence Analysis of Walnut GAI and PIP2 Genes and Comparison with Different Plant Species

Directory of Open Access Journals (Sweden)

Mahdi Mohseniazar

2017-02-01

Full Text Available Introduction: Dwarfism is one of the important traits in breeding of crops and horticulture plants. A dwarfing rootstock will produce trees with 15-50% of standard trees size. In modern intensive fruit tree orchards, dwarfing rootstocks are commonly used to reduce trees size, enabling high-density planting and easy management, thus achieving higher yield. Trees on dwarfing rootstocks can also exhibit other economically important traits, such as precocious flowering, increased yield and increased disease resistance. Dwarf rootstocks have been extensively studied and released in stone and pome fruits, because of presence of genetic materials and the simplicity of budding methods. Control of tree size using genetically dwarf rootstocks for achievement to higher density and mechanized orchard systems is now very important for walnut production in the world especially in Iran. Many different genes can be involved in appear of this. Mutations in GAI and PIP2 genes cause dwarf trait by two different mechanisms in some plant species. In this case, we study in silico analysis of GAI and PIP2 genes consist of conserved sequences and domains, exon and intron number, function of their proteins, targeting, secondary and tertiary structure, and post translational modification. Materials and methods: The GAI and PIP2 mRNA and protein sequences (FASTA format belonging to 17 monocotyledon and dicotyledon were downloaded from NCBI (http://www.ncbi.nlm.nih.gov accessed, on September 2014. Several online web services and software were used for analysis of GAI and PIP2 mRNA and Proteins in plants. Comparative and bioinformatics analyses of PIP2 and GAI proteins were performed online at two websites NCBI (http://www.ncbi.nih.gov and EXPASY (http://expasy.org/tools. Molecular Evolutionary Genetics Analysis (MEGA; version 4 program and CLUSTAL-W with default parameters were used for multiple alignments of sequences. The phylogenetic analysis of GAI and PIP2 protein was

In silico Coding Sequence Analysis of Walnut GAI and PIP2 Genes and Comparison with Different Plant Species

Directory of Open Access Journals (Sweden)

Mahdi Mohseniazar

2017-09-01

Full Text Available Introduction: Dwarfism is one of the important traits in breeding of crops and horticulture plants. A dwarfing rootstock will produce trees with 15-50% of standard trees size. In modern intensive fruit tree orchards, dwarfing rootstocks are commonly used to reduce trees size, enabling high-density planting and easy management, thus achieving higher yield. Trees on dwarfing rootstocks can also exhibit other economically important traits, such as precocious flowering, increased yield and increased disease resistance. Dwarf rootstocks have been extensively studied and released in stone and pome fruits, because of presence of genetic materials and the simplicity of budding methods. Control of tree size using genetically dwarf rootstocks for achievement to higher density and mechanized orchard systems is now very important for walnut production in the world especially in Iran. Many different genes can be involved in appear of this. Mutations in GAI and PIP2 genes cause dwarf trait by two different mechanisms in some plant species. In this case, we study in silico analysis of GAI and PIP2 genes consist of conserved sequences and domains, exon and intron number, function of their proteins, targeting, secondary and tertiary structure, and post translational modification. Materials and methods: The GAI and PIP2 mRNA and protein sequences (FASTA format belonging to 17 monocotyledon and dicotyledon were downloaded from NCBI (http://www.ncbi.nlm.nih.gov accessed, on September 2014. Several online web services and software were used for analysis of GAI and PIP2 mRNA and Proteins in plants. Comparative and bioinformatics analyses of PIP2 and GAI proteins were performed online at two websites NCBI (http://www.ncbi.nih.gov and EXPASY (http://expasy.org/tools. Molecular Evolutionary Genetics Analysis (MEGA; version 4 program and CLUSTAL-W with default parameters were used for multiple alignments of sequences. The phylogenetic analysis of GAI and PIP2 protein was

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

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.

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.

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.

A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

Charara, Ali

2017-06-06

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

A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

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

2017-01-01

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

PERI - auto-tuning memory-intensive kernels for multicore

International Nuclear Information System (INIS)

Williams, S; Carter, J; Oliker, L; Shalf, J; Yelick, K; Bailey, D; Datta, K

2008-01-01

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to sparse matrix vector multiplication (SpMV), the explicit heat equation PDE on a regular grid (Stencil), and a lattice Boltzmann application (LBMHD). We explore one of the broadest sets of multicore architectures in the high-performance computing literature, including the Intel Xeon Clovertown, AMD Opteron Barcelona, Sun Victoria Falls, and the Sony-Toshiba-IBM (STI) Cell. Rather than hand-tuning each kernel for each system, we develop a code generator for each kernel that allows us identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned kernel applications often achieve a better than 4x improvement compared with the original code. Additionally, we analyze a Roofline performance model for each platform to reveal hardware bottlenecks and software challenges for future multicore systems and applications

PERI - Auto-tuning Memory Intensive Kernels for Multicore

Energy Technology Data Exchange (ETDEWEB)

Bailey, David H; Williams, Samuel; Datta, Kaushik; Carter, Jonathan; Oliker, Leonid; Shalf, John; Yelick, Katherine; Bailey, David H

2008-06-24

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to Sparse Matrix Vector Multiplication (SpMV), the explicit heat equation PDE on a regular grid (Stencil), and a lattice Boltzmann application (LBMHD). We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon Clovertown, AMD Opteron Barcelona, Sun Victoria Falls, and the Sony-Toshiba-IBM (STI) Cell. Rather than hand-tuning each kernel for each system, we develop a code generator for each kernel that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned kernel applications often achieve a better than 4X improvement compared with the original code. Additionally, we analyze a Roofline performance model for each platform to reveal hardware bottlenecks and software challenges for future multicore systems and applications.

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.

Low-Resolution Tactile Image Recognition for Automated Robotic Assembly Using Kernel PCA-Based Feature Fusion and Multiple Kernel Learning-Based Support Vector Machine

Directory of Open Access Journals (Sweden)

Yi-Hung Liu

2014-01-01

Full Text Available In this paper, we propose a robust tactile sensing image recognition scheme for automatic robotic assembly. First, an image reprocessing procedure is designed to enhance the contrast of the tactile image. In the second layer, geometric features and Fourier descriptors are extracted from the image. Then, kernel principal component analysis (kernel PCA is applied to transform the features into ones with better discriminating ability, which is the kernel PCA-based feature fusion. The transformed features are fed into the third layer for classification. In this paper, we design a classifier by combining the multiple kernel learning (MKL algorithm and support vector machine (SVM. We also design and implement a tactile sensing array consisting of 10-by-10 sensing elements. Experimental results, carried out on real tactile images acquired by the designed tactile sensing array, show that the kernel PCA-based feature fusion can significantly improve the discriminating performance of the geometric features and Fourier descriptors. Also, the designed MKL-SVM outperforms the regular SVM in terms of recognition accuracy. The proposed recognition scheme is able to achieve a high recognition rate of over 85% for the classification of 12 commonly used metal parts in industrial applications.

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 ...

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...

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.

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

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.

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.

A survey of kernel-type estimators for copula and their applications

Science.gov (United States)

Sumarjaya, I. W.

2017-10-01

Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.

Irradiation performance of coated fuel particles with fission product retaining kernel additives

International Nuclear Information System (INIS)

Foerthmann, R.

1979-10-01

The four irradiation experiments FRJ2-P17, FRJ2-P18, FRJ2-P19, and FRJ2-P20 for testing the efficiency of fission product-retaining kernel additives in coated fuel particles are described. The evaluation of the obtained experimental data led to the following results: - zirconia and alumina kernel additives are not suitable for an effective fission product retention in oxide fuel kernels, - alumina-silica kernel additives reduce the in-pile release of Sr 90 and Ba 140 from BISO-coated particles at temperatures of about 1200 0 C by two orders of magnitude, and the Cs release from kernels by one order of magnitude, - effective transport coefficients including all parameters which contribute to kernel release are given for (Th,U)O 2 mixed oxide kernels and low enriched UO 2 kernels containing 5 wt.% alumina-silica additives: 10g sub(K)/cm 2 s -1 = - 36 028/T + 6,261 (Sr 90), 10g Dsub(K)/cm 2 c -2 = - 29 646/T + 5,826 (Cs 134/137), alumina-silica kernel additives are ineffective for retaining Ag 110 m in coated particles. However, also an intact SiC-interlayer was found not to be effective at temperatures above 1200 0 C, - the penetration of the buffer layer by fission product containing eutectic additive melt during irradiation can be avoided by using additives which consist of alumina and mullite without an excess of silica, - annealing of LASER-failed irradiated particles and the irradiation test FRJ12-P20 indicate that the efficiency of alumina-silica kernel additives is not altered if the coating becomes defect. (orig.) [de

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies

Science.gov (United States)

Manitz, Juliane; Burger, Patricia; Amos, Christopher I.; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility. PMID:28785300

Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.

Science.gov (United States)

Friedrichs, Stefanie; Manitz, Juliane; Burger, Patricia; Amos, Christopher I; Risch, Angela; Chang-Claude, Jenny; Wichmann, Heinz-Erich; Kneib, Thomas; Bickeböller, Heike; Hofner, Benjamin

2017-01-01

The analysis of genome-wide association studies (GWAS) benefits from the investigation of biologically meaningful gene sets, such as gene-interaction networks (pathways). We propose an extension to a successful kernel-based pathway analysis approach by integrating kernel functions into a powerful algorithmic framework for variable selection, to enable investigation of multiple pathways simultaneously. We employ genetic similarity kernels from the logistic kernel machine test (LKMT) as base-learners in a boosting algorithm. A model to explain case-control status is created iteratively by selecting pathways that improve its prediction ability. We evaluated our method in simulation studies adopting 50 pathways for different sample sizes and genetic effect strengths. Additionally, we included an exemplary application of kernel boosting to a rheumatoid arthritis and a lung cancer dataset. Simulations indicate that kernel boosting outperforms the LKMT in certain genetic scenarios. Applications to GWAS data on rheumatoid arthritis and lung cancer resulted in sparse models which were based on pathways interpretable in a clinical sense. Kernel boosting is highly flexible in terms of considered variables and overcomes the problem of multiple testing. Additionally, it enables the prediction of clinical outcomes. Thus, kernel boosting constitutes a new, powerful tool in the analysis of GWAS data and towards the understanding of biological processes involved in disease susceptibility.

Deep RNA-Seq profile reveals biodiversity, plant-microbe interactions and a large family of NBS-LRR resistance genes in walnut (Juglans regia) tissues.

Science.gov (United States)

Chakraborty, Sandeep; Britton, Monica; Martínez-García, P J; Dandekar, Abhaya M

2016-03-01

Deep RNA-Seq profiling, a revolutionary method used for quantifying transcriptional levels, often includes non-specific transcripts from other co-existing organisms in spite of stringent protocols. Using the recently published walnut genome sequence as a filter, we present a broad analysis of the RNA-Seq derived transcriptome profiles obtained from twenty different tissues to extract the biodiversity and possible plant-microbe interactions in the walnut ecosystem in California. Since the residual nature of the transcripts being analyzed does not provide sufficient information to identify the exact strain, inferences made are constrained to the genus level. The presence of the pathogenic oomycete Phytophthora was detected in the root through the presence of a glyceraldehyde-3-phosphate dehydrogenase. Cryptococcus, the causal agent of cryptococcosis, was found in the catkins and vegetative buds, corroborating previous work indicating that the plant surface supported the sexual cycle of this human pathogen. The RNA-Seq profile revealed several species of the endophytic nitrogen fixing Actinobacteria. Another bacterial species implicated in aerobic biodegradation of methyl tert-butyl ether (Methylibium petroleiphilum) is also found in the root. RNA encoding proteins from the pea aphid were found in the leaves and vegetative buds, while a serine protease from mosquito with significant homology to a female reproductive tract protease from Drosophila mojavensis in the vegetative bud suggests egg-laying activities. The comprehensive analysis of RNA-seq data present also unraveled detailed, tissue-specific information of ~400 transcripts encoded by the largest family of resistance (R) genes (NBS-LRR), which possibly rationalizes the resistance of the specific walnut plant to the pathogens detected. Thus, we elucidate the biodiversity and possible plant-microbe interactions in several walnut (Juglans regia) tissues in California using deep RNA-Seq profiling.

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

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…

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.

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.

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

Comparative microstructure study of oil palm fruit bunch fibre, mesocarp and kernels after microwave pre-treatment

Science.gov (United States)

Chang, Jessie S. L.; Chan, Y. S.; Law, M. C.; Leo, C. P.

2017-07-01

The implementation of microwave technology in palm oil processing offers numerous advantages; besides elimination of polluted palm oil mill effluent, it also reduces energy consumption, processing time and space. However, microwave exposure could damage a material’s microstructure which affected the quality of fruit that can be related to its physical structure including the texture and appearance. In this work, empty fruit bunches, mesocarp and kernel was microwave dried and their respective microstructures were examined. The microwave pretreatments were conducted at 100W and 200W and the microstructure investigation of both treated and untreated samples were evaluated using scanning electron microscope. The micrographs demonstrated that microwave does not significantly influence kernel and mesocarp but noticeable change was found on the empty fruit bunches where the sizes of the granular starch were reduced and a small portion of the silica bodies were disrupted. From the experimental data, the microwave irradiation was shown to be efficiently applied on empty fruit bunches followed by mesocarp and kernel as significant weight loss and size reduction was observed after the microwave treatments. The current work showed that microwave treatment did not change the physical surfaces of samples but sample shrinkage is observed.

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.

Perspectives for practical application of the combined fuel kernels in VVER-type reactors

International Nuclear Information System (INIS)

Baranov, V.; Ternovykh, M.; Tikhomirov, G.; Khlunov, A.; Tenishev, A.; Kurina, I.

2011-01-01

The paper considers the main physical processes that take place in fuel kernels under real operation conditions of VVER-type reactors. Main attention is given to the effects induced by combinations of layers with different physical properties inside of fuel kernels on these physical processes. Basic neutron-physical characteristics were calculated for some combined fuel kernels in fuel rods of VVER-type reactors. There are many goals in development of the combined fuel kernels, and these goals define selecting the combinations and compositions of radial layers inside of the kernels. For example, the slower formation of the rim-layer on outer surface of the kernels made of enriched uranium dioxide can be achieved by introduction of inner layer made of natural or depleted uranium dioxide. Other potential goals (lower temperature in the kernel center, better conditions for burn-up of neutron poisons, better retention of toxic materials) could be reached by other combinations of fuel compositions in central and peripheral zones of the fuel kernels. Also, the paper presents the results obtained in experimental manufacturing of the combined fuel pellets. (authors)

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

Science.gov (United States)

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

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...

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...

Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.)

NARCIS (Netherlands)

Bocanski, J.; Sreckov, Z.; Nastasic, A.; Ivanovic, M.; Djalovic, I.; Vukosavljev, M.

2010-01-01

Bocanski J., Z. Sreckov, A. Nastasic, M. Ivanovic, I.Djalovic and M. Vukosavljev (2010): Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.) - Genetika, Vol 42, No. 1, 169- 176. Utilization of heterosis requires the study of

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.

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

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

Science.gov (United States)

Ma, Wenxiu; Yang, Lin; Rohs, Remo; Noble, William Stafford

2017-10-01

Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affinity. However, a limitation of these methods is that they typically require a training set of aligned TF binding sites. We describe a sequence + shape kernel that leverages DNA sequence and shape information to better understand protein-DNA binding preference and affinity. This kernel extends an existing class of k-mer based sequence kernels, based on the recently described di-mismatch kernel. Using three in vitro benchmark datasets, derived from universal protein binding microarrays (uPBMs), genomic context PBMs (gcPBMs) and SELEX-seq data, we demonstrate that incorporating DNA shape information improves our ability to predict protein-DNA binding affinity. In particular, we observe that (i) the k-spectrum + shape model performs better than the classical k-spectrum kernel, particularly for small k values; (ii) the di-mismatch kernel performs better than the k-mer kernel, for larger k; and (iii) the di-mismatch + shape kernel performs better than the di-mismatch kernel for intermediate k values. The software is available at https://bitbucket.org/wenxiu/sequence-shape.git. rohs@usc.edu or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

Science.gov (United States)

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

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.

Feature Selection and Kernel Learning for Local Learning-Based Clustering.

Science.gov (United States)

Zeng, Hong; Cheung, Yiu-ming

2011-08-01

The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

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.

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.

Fuzzy-based multi-kernel spherical support vector machine for ...

Indian Academy of Sciences (India)

In the proposed classifier, we design a new multi-kernel function based on the fuzzy triangular membership function. Finally, a newly developed multi-kernel function is incorporated into the spherical support vector machine to enhance the performance significantly. The experimental results are evaluated and performance is ...

Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

Science.gov (United States)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

Modelling microwave heating of discrete samples of oil palm kernels

International Nuclear Information System (INIS)

Law, M.C.; Liew, E.L.; Chang, S.L.; Chan, Y.S.; Leo, C.P.

2016-01-01

Highlights: • Microwave (MW) drying of oil palm kernels is experimentally determined and modelled. • MW heating of discrete samples of oil palm kernels (OPKs) is simulated. • OPK heating is due to contact effect, MW interference and heat transfer mechanisms. • Electric field vectors circulate within OPKs sample. • Loosely-packed arrangement improves temperature uniformity of OPKs. - Abstract: Recently, microwave (MW) pre-treatment of fresh palm fruits has showed to be environmentally friendly compared to the existing oil palm milling process as it eliminates the condensate production of palm oil mill effluent (POME) in the sterilization process. Moreover, MW-treated oil palm fruits (OPF) also possess better oil quality. In this work, the MW drying kinetic of the oil palm kernels (OPK) was determined experimentally. Microwave heating/drying of oil palm kernels was modelled and validated. The simulation results show that temperature of an OPK is not the same over the entire surface due to constructive and destructive interferences of MW irradiance. The volume-averaged temperature of an OPK is higher than its surface temperature by 3–7 °C, depending on the MW input power. This implies that point measurement of temperature reading is inadequate to determine the temperature history of the OPK during the microwave heating process. The simulation results also show that arrangement of OPKs in a MW cavity affects the kernel temperature profile. The heating of OPKs were identified to be affected by factors such as local electric field intensity due to MW absorption, refraction, interference, the contact effect between kernels and also heat transfer mechanisms. The thermal gradient patterns of OPKs change as the heating continues. The cracking of OPKs is expected to occur first in the core of the kernel and then it propagates to the kernel surface. The model indicates that drying of OPKs is a much slower process compared to its MW heating. The model is useful