Sample records for kernel oil tallow

  1. Corn kernel oil and corn fiber oil

    USDA-ARS?s Scientific Manuscript database

    Unlike most edible plant oils that are obtained directly from oil-rich seeds by either pressing or solvent extraction, corn seeds (kernels) have low levels of oil (4%) and commercial corn oil is obtained from the corn germ (embryo) which is an oil-rich portion of the kernel. Commercial corn oil cou...

  2. Oil point and mechanical behaviour of oil palm kernels in linear compression

    NASA Astrophysics Data System (ADS)

    Kabutey, Abraham; Herak, David; Choteborsky, Rostislav; Mizera, Čestmír; Sigalingging, Riswanti; Akangbe, Olaosebikan Layi

    2017-07-01

    The study described the oil point and mechanical properties of roasted and unroasted bulk oil palm kernels under compression loading. The literature information available is very limited. A universal compression testing machine and vessel diameter of 60 mm with a plunger were used by applying maximum force of 100 kN and speed ranging from 5 to 25 mm min-1. The initial pressing height of the bulk kernels was measured at 40 mm. The oil point was determined by a litmus test for each deformation level of 5, 10, 15, 20, and 25 mm at a minimum speed of 5 mmmin-1. The measured parameters were the deformation, deformation energy, oil yield, oil point strain and oil point pressure. Clearly, the roasted bulk kernels required less deformation energy compared to the unroasted kernels for recovering the kernel oil. However, both kernels were not permanently deformed. The average oil point strain was determined at 0.57. The study is an essential contribution to pursuing innovative methods for processing palm kernel oil in rural areas of developing countries.

  3. Effects of tallow, choice white grease, palm oil, corn oil, or soybean oil on apparent total tract digestibility of minerals in diets fed to growing pigs.

    PubMed

    Merriman, L A; Walk, C L; Parsons, C M; Stein, H H

    2016-10-01

    An experiment was conducted to determine the effect of supplementing diets fed to growing pigs with fat sources differing in their composition of fatty acids on the apparent total tract digestibility (ATTD) of minerals. A diet based on corn, potato protein isolate, and 7% sucrose was formulated. Five additional diets that were similar to the previous diet with the exception that sucrose was replaced by 7% tallow, choice white grease, palm oil, corn oil, or soybean oil were also formulated. Diets were formulated to contain 0.70% Ca and 0.33% standardized total tract digestible P. Growing barrows ( = 60; 15.99 ± 1.48 kg initial BW) were allotted to a randomized complete block design with 2 blocks of 30 pigs, 6 dietary treatments, and 10 replicate pigs per treatment. Experimental diets were provided for 12 d with the initial 5 d being the adaptation period. Total feces were collected for a 5-d collection period using the marker-to-marker approach, and the ATTD of minerals, ether extract, and acid hydrolyzed ether extract was calculated for all diets. Digestibility of DM was greater ( < 0.05) in the diet containing soybean oil compared with the diet containing choice white grease or the basal diet, with all other diets being intermediate. The ATTD of Ca, S, and P was greater ( < 0.05) for pigs fed diets containing soybean oil, corn oil, palm oil, or tallow than for pigs fed the basal diet or the diet containing choice white grease. The ATTD of Mg, Zn, Mn, Na, and K were not different among dietary treatments. The ATTD of ether extract was greater ( < 0.05) in diets containing palm oil, corn oil, or soybean oil compared with the diet containing choice white grease, and the ATTD of acid hydrolyzed ether extract in the diet containing soybean oil was also greater ( < 0.05) than in the diet containing choice white grease. In conclusion, supplementation of a basal diet with tallow, palm oil, corn oil, or soybean oil may increase the ATTD of some macrominerals, but that

  4. Gene expression of insulin signal-transduction pathway intermediates is lower in rats fed a beef tallow diet than in rats fed a safflower oil diet.

    PubMed

    Kim, Y B; Nakajima, R; Matsuo, T; Inoue, T; Sekine, T; Komuro, M; Tamura, T; Tokuyama, K; Suzuki, M

    1996-09-01

    To elucidate the effects of dietary fatty acid composition on the insulin signaling pathway, we measured the gene expression of the earliest steps in the insulin action pathway in skeletal muscle of rats fed a safflower oil diet or a beef tallow diet. Rats were meal-fed an isoenergetic diet based on either safflower oil or beef tallow for 8 weeks. Both diets provided 45%, 35%, and 20% of energy as fat, carbohydrate, and protein, respectively. Insulin resistance, assessed from the diurnal rhythm of plasma glucose and insulin and the oral glucose tolerance test (OGTT), developed in rats fed a beef tallow diet. Body fat content was greater in rats fed a beef tallow diet versus a safflower oil diet. The level of insulin receptor mRNA, relative expression of the insulin receptor mRNA isoforms, and receptor protein were not affected by the composition of dietary fatty acids. The abundance of insulin receptor substrate-1 (IRS-1) and phosphatidylinositol (PI) 3-kinase mRNA and protein was significantly lower in rats fed a beef tallow diet versus a safflower oil diet. We conclude that long-term feeding of a high-fat diet with saturated fatty acids induces decrease in IRS-1 and PI 3-kinase mRNA and protein levels, causing insulin resistance in skeletal muscle.

  5. Iron utilization and liver mineral concentrations in rats fed safflower oil, flaxseed oil, olive oil, or beef tallow in combination with different concentrations of dietary iron.

    PubMed

    Shotton, Andrea D; Droke, Elizabeth A

    2004-03-01

    Diets with a higher proportion of polyunsaturated fatty acids (i.e., linoleic acid) have decreased iron absorption and utilization compared with diets containing a higher proportion of the saturated fatty acid stearic acid (e.g., beef tallow). However, less is known regarding the influence of other polyunsaturated or monounsaturated fatty acids, along with higher dietary iron, on iron absorption and utilization. The present study was conducted to compare the effects of dietary fat sources known to vary in (n-3), (n-6), and (n-9) fatty acids on iron utilization and liver mineral concentrations. Male weanling rats were fed a diet containing 10, 35, or 100 microg/g iron in combination with safflower oil, flaxseed oil, olive oil, or beef tallow for 8 wk. Indicators of iron status, iron utilization, and liver iron concentrations were unaffected by an interaction between the fat source and iron concentration. Plasma copper was the only variable affected by an interaction between the fat source and dietary iron. Findings of this study demonstrate that flaxseed oil and olive oil may alter tissue minerals and affect iron utilization. Further studies should be conducted to establish the effect of varying (n-3), (n-6), and (n-9) fatty acids on trace mineral status and iron utilization.

  6. Coconut oil and beef tallow, but not tricaprylin, can replace menhaden oil in the diet of red drum (Sciaenops ocellatus) without adversely affecting growth or fatty acid composition.

    PubMed

    Craig, S R; Gatlin, D M

    1995-12-01

    The ability of juvenile red drum (Sciaenops ocellatus) to utilize medium-chain triglycerides (MCT) and other saturated dietary lipids was investigated in two 6-wk feeding experiments. Diets contained solvent-extracted menhaden fish meal to which menhaden fish oil (control), coconut oil, corn oil, beef tallow or various levels of MCT as tricaprylin (30, 46, 65 and 80% of total lipid) were added. Diets were fed to triplicate groups of juvenile red drum in aquaria containing brackish (6%) water. In the first feeding experiment, red drum fed the control diet had the greatest weight gains and feed efficiencies. Weight gain, but not feed was slightly, of fish fed corn oil and fish fed coconut oil was slightly (P < 0.05) lower. In the second feeding experiment, fish fed coconut oil and those fed beef tallow had significantly higher weight gains and feed efficiencies than did fish fed the control diet. Fish fed the diets containing tricaprylin at all inclusion levels in both feeding experiments had significantly lower weight gains and feed efficiencies and higher levels of beta-hydroxybutyric acid in plasma. Fish fed diets with high levels of MCT also had lower (n-3) and greater (n-6) fatty acid levels in the neutral lipid fraction of muscle tissue compared with fish fed the control diet. Coconut oil and beef tallow consistently resulted in greater liver lipid deposition but had variable effects on other tissue indices. Saturated dietary lipids had variable effects on fatty acid composition of muscle polar and neutral lipid fractions.(ABSTRACT TRUNCATED AT 250 WORDS)

  7. Hybrid striped bass feeds based on fish oil, beef tallow, and eicosapentaenoic acid/docosahexaenoic acid supplements: Insight regarding fish oil sparing and demand for -3 long-chain polyunsaturated fatty acids.

    PubMed

    Bowzer, J; Jackson, C; Trushenski, J

    2016-03-01

    Previous research suggests that saturated (SFA) and monounsaturated fatty acid (MUFA) rich lipids, including beef tallow, can make utilization or diet-to-tissue transfer of long-chain polyunsaturated fatty acids (LC-PUFA) more efficient. We hypothesized that using beef tallow as an alternative to fish oil may effectively reduce the LC-PUFA demand of hybrid striped bass × and allow for greater fish oil sparing. Accordingly, we evaluated growth performance and tissue fatty acid profiles of juvenile fish (23.7 ± 0.3 g) fed diets containing menhaden fish oil (considered an ideal source of LC-PUFA for this taxon), beef tallow (BEEF ONLY), or beef tallow amended with purified sources of eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA) to achieve levels corresponding to 50 or 100% of those observed in the FISH ONLY feed. Diets were randomly assigned to quadruplicate tanks of fish ( = 4; 10 fish/tank), and fish were fed assigned diets to apparent satiation once daily for 10 wk. Survival (98-100%) was equivalent among treatments, but weight gain (117-180%), specific growth rate (1.1-1.5% BW/d), feed intake (1.4-1.8% BW/d), thermal growth coefficient (0.50-0.70), and feed conversion ratio (FCR; 1.1-1.4, DM basis) varied. Except for FCR, no differences were observed between the FISH ONLY and BEEF ONLY treatments, but performance was generally numerically superior among fish fed the diets containing beef tallow supplemented with DHA at the 100% or both EPA and DHA at the 50% or 100% level. Tissue fatty acid composition was significantly distorted in favor among fish fed the beef tallow-based feeds; however, profile distortion was most overt in peripheral tissues. Results suggest that beef tallow may be used as a primary lipid source in practical diets for hybrid striped bass, but performance may be improved by supplementation with LC-PUFA, particularly DHA. Furthermore, our results suggest that -3 LC-PUFA requirements reported for hybrid striped bass may not be

  8. 21 CFR 172.861 - Cocoa butter substitute from coconut oil, palm kernel oil, or both oils.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Cocoa butter substitute from coconut oil, palm... HUMAN CONSUMPTION Multipurpose Additives § 172.861 Cocoa butter substitute from coconut oil, palm kernel oil, or both oils. The food additive, cocoa butter substitute from coconut oil, palm kernel oil, or...

  9. 21 CFR 172.861 - Cocoa butter substitute from coconut oil, palm kernel oil, or both oils.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 3 2013-04-01 2013-04-01 false Cocoa butter substitute from coconut oil, palm... substitute from coconut oil, palm kernel oil, or both oils. The food additive, cocoa butter substitute from coconut oil, palm kernel oil, or both oils, may be safely used in food in accordance with the following...

  10. 21 CFR 172.861 - Cocoa butter substitute from coconut oil, palm kernel oil, or both oils.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 3 2012-04-01 2012-04-01 false Cocoa butter substitute from coconut oil, palm... substitute from coconut oil, palm kernel oil, or both oils. The food additive, cocoa butter substitute from coconut oil, palm kernel oil, or both oils, may be safely used in food in accordance with the following...

  11. 21 CFR 172.861 - Cocoa butter substitute from coconut oil, palm kernel oil, or both oils.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Cocoa butter substitute from coconut oil, palm... substitute from coconut oil, palm kernel oil, or both oils. The food additive, cocoa butter substitute from coconut oil, palm kernel oil, or both oils, may be safely used in food in accordance with the following...

  12. Kolkhoung (Pistacia khinjuk) Hull Oil and Kernel Oil as Antioxidative Vegetable Oils with High Oxidative Stability 
and Nutritional Value.

    PubMed

    Asnaashari, Maryam; Hashemi, Seyed Mohammad Bagher; Mehr, Hamed Mahdavian; Yousefabad, Seyed Hossein Asadi

    2015-03-01

    In this study, in order to introduce natural antioxidative vegetable oil in food industry, the kolkhoung hull oil and kernel oil were extracted. To evaluate their antioxidant efficiency, gas chromatography analysis of the composition of kolkhoung hull and kernel oil fatty acids and high-performance liquid chromatography analysis of tocopherols were done. Also, the oxidative stability of the oil was considered based on the peroxide value and anisidine value during heating at 100, 110 and 120 °C. Gas chromatography analysis showed that oleic acid was the major fatty acid of both types of oil (hull and kernel) and based on a low content of saturated fatty acids, high content of monounsaturated fatty acids, and the ratio of ω-6 and ω-3 polyunsaturated fatty acids, they were nutritionally well--balanced. Moreover, both hull and kernel oil showed high oxidative stability during heating, which can be attributed to high content of tocotrienols. Based on the results, kolkhoung hull oil acted slightly better than its kernel oil. However, both of them can be added to oxidation-sensitive oils to improve their shelf life.

  13. Beef Tallow, but Not Perilla or Corn Oil, Promotion of Rat Prostate and Intestinal Carcinogenesis by 3,2‐Dimethyl‐4‐aminobiphenyl

    PubMed Central

    Mori, Toshio; Imaida, Katsumi; Tamano, Seiko; Sano, Masashi; Takahashi, Satoru; Asamoto, Makoto; Takeshita, Masazumi; Ueda, Hiroshi

    2001-01-01

    The modifying effects of three kinds of fat (corn oil, beef tallow or perilla oil, each at 20% in the diet) on F344 rat prostate carcinogenesis induced by 3,2‐dimethyl‐4‐aminobiphenyl (DMAB) were investigated. Non‐invasive carcinomas of the ventral prostate were induced by DMAB alone and invasive carcinomas of the other prostate lobes and seminal vesicles by DMAB and testosterone propionate (TP). Eight groups of F344 rats were initiated with 50 mg/kg body weight of DMAB at 2‐week intervals for the first 20 weeks, four also receiving TP, extended until week 60. The animals received basal chow powder diet or one of three high fat diets throughout the experiment (60 weeks). One further group served as a non‐carcinogen‐treated control maintained on basal chow powder diet. Beef tallow significantly increased the development of ventral prostate carcinomas with DMAB alone (from 15 to 45%, P<0.05), while perilla oil reduced the incidence of prostatic intraepithelial neoplasia (PIN) in the ventral lobe of rats given DMAB + TP (from 70 to 10%, P<0.01), but not in those given DMAB alone. No other effects of high fats were observed regarding PIN or invasive cancers of the dorsolateral and anterior prostate or seminal vesicles. A satellite experiment demonstrated that all high fat diets for 4 weeks increased the 5‐bromo‐2‐deoxyuridine (BrdU) labeling index of prostate epithelial cells, suggesting that a high fat intake, irrespective of the fatty acid composition, may accelerate cell kinetics in the prostate. Of the three high fat diets, beef tallow was also found to increase intestinal carcinogenesis. Thus, the present data revealed carcinogenesis in the prostate and intestine to be promoted by beef tallow. PMID:11676852

  14. Chemical components of cold pressed kernel oils from different Torreya grandis cultivars.

    PubMed

    He, Zhiyong; Zhu, Haidong; Li, Wangling; Zeng, Maomao; Wu, Shengfang; Chen, Shangwei; Qin, Fang; Chen, Jie

    2016-10-15

    The chemical compositions of cold pressed kernel oils of seven Torreya grandis cultivars from China were analyzed in this study. The contents of the chemical components of T. grandis kernels and kernel oils varied to different extents with the cultivar. The T. grandis kernels contained relatively high oil and protein content (45.80-53.16% and 10.34-14.29%, respectively). The kernel oils were rich in unsaturated fatty acids including linoleic (39.39-47.77%), oleic (30.47-37.54%) and eicosatrienoic acid (6.78-8.37%). The kernel oils contained some abundant bioactive substances such as tocopherols (0.64-1.77mg/g) consisting of α-, β-, γ- and δ-isomers; sterols including β-sitosterol (0.90-1.29mg/g), campesterol (0.06-0.32mg/g) and stigmasterol (0.04-0.18mg/g) in addition to polyphenols (9.22-22.16μgGAE/g). The results revealed that the T. grandis kernel oils possessed the potentially important nutrition and health benefits and could be used as oils in the human diet or functional ingredients in the food industry. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    PubMed

    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.

  16. Deep Sequencing of the Fruit Transcriptome and Lipid Accumulation in a Non-Seed Tissue of Chinese Tallow, a Potential Biofuel Crop.

    PubMed

    Divi, Uday K; Zhou, Xue-Rong; Wang, Penghao; Butlin, Jamie; Zhang, Dong-Mei; Liu, Qing; Vanhercke, Thomas; Petrie, James R; Talbot, Mark; White, Rosemary G; Taylor, Jennifer M; Larkin, Philip; Singh, Surinder P

    2016-01-01

    Chinese tallow (Triadica sebifera) is a valuable oilseed-producing tree that can grow in a variety of conditions without competing for food production, and is a promising biofuel feedstock candidate. The fruits are unique in that they contain both saturated and unsaturated fat present in the tallow and seed layer, respectively. The tallow layer is poorly studied and is considered only as an external fatty deposition secreted from the seed. In this study we show that tallow is in fact a non-seed cellular tissue capable of triglyceride synthesis. Knowledge of lipid synthesis and storage mechanisms in tissues other than seed is limited but essential to generate oil-rich biomass crops. Here, we describe the annotated transcriptome assembly generated from the fruit coat, tallow and seed tissues of Chinese tallow. The final assembly was functionally annotated, allowing for the identification of candidate genes and reconstruction of lipid pathways. A tallow tissue-specific paralog for the transcription factor gene WRINKLED1 (WRI1) and lipid droplet-associated protein genes, distinct from those expressed in seed tissue, were found to be active in tallow, underpinning the mode of oil synthesis and packaging in this tissue. Our data have established an excellent knowledge base that can provide genetic and biochemical insights for engineering non-seed tissues to accumulate large amounts of oil. In addition to the large data set of annotated transcripts, the study also provides gene-based simple sequence repeat and single nucleotide polymorphism markers. © The Author 2015. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  17. Mapping Chinese tallow with color-infrared photography

    USGS Publications Warehouse

    Ramsey, Elijah W.; Nelson, G.A.; Sapkota, S.K.; Seeger, E.B.; Martella, K.D.

    2002-01-01

    Airborne color-infrared photography (CIR) (1:12,000 scale) was used to map localized occurrences of the widespread and aggressive Chinese tallow (Sapium sebiferum), an invasive species. Photography was collected during senescence when Chinese tallow's bright red leaves presented a high spectral contrast within the native bottomland hardwood and upland forests and marsh land-cover types. Mapped occurrences were conservative because not all senescing tallow leaves are bright red simultaneously. To simulate low spectral but high spatial resolution satellite/airborne image and digital video data, the CIR photography was transformed into raster images at spatial resolutions approximating 0.5 in and 1.0 m. The image data were then spectrally classified for the occurrence of bright red leaves associated with senescing Chinese tallow. Classification accuracies were greater than 95 percent at both spatial resolutions. There was no significant difference in either forest in the detection of tallow or inclusion of non-tallow trees associated with the two spatial resolutions. In marshes, slightly more tallow occurrences were mapped with the lower spatial resolution, but there were also more misclassifications of native land covers as tallow. Combining all land covers, there was no difference at detecting tallow occurrences (equal omission errors) between the two resolutions, but the higher spatial resolution was associated with less inclusion of non-tallow land covers as tallow (lower commission error). Overall, these results confirm that high spatial (???1 m) but low spectral resolution remote sensing data can be used for mapping Chinese tallow trees in dominant environments found in coastal and adjacent upland landscapes.

  18. Improvement of efficiency of oil extraction from wild apricot kernels by using enzymes.

    PubMed

    Bisht, Tejpal Singh; Sharma, Satish Kumar; Sati, Ramesh Chandra; Rao, Virendra Kumar; Yadav, Vijay Kumar; Dixit, Anil Kumar; Sharma, Ashok Kumar; Chopra, Chandra Shekhar

    2015-03-01

    An experiment was conducted to evaluate and standardize the protocol for enhancing recovery of oil and quality from cold pressed wild apricot kernels by using various enzymes. Wild apricot kernels were ground into powder in a grinder. Different lots of 3 kg powdered kernel were prepared and treated with different concentrations of enzyme solutions viz. Pectazyme (Pectinase), Mashzyme (Cellulase) and Pectazyme + Mashzyme. Kernel powder mixed with enzyme solutions were kept for 2 h at 50(±2) °C temperature for enzymatic treatment before its use for oil extraction through oil expeller. Results indicate that use of enzymes resulted in enhancement of oil recovery by 9.00-14.22 %. Maximum oil recovery was observed at 0.3-0.4 % enzyme concentration for both the enzymes individually, as well as in combination. All the three enzymatic treatments resulted in increasing oil yield. However, with 0.3 % (Pectazyme + Mashzyme) combination, maximum oil recovery of 47.33 % could be observed against were 33.11 % in control. The oil content left (wasted) in the cake and residue were reduced from 11.67 and 11.60 % to 7.31 and 2.72 % respectively, thus showing a high increase in efficiency of oil recovery from wild apricot kernels. Quality characteristics indicate that the oil quality was not adversely affected by enzymatic treatment. It was concluded treatment of powdered wild apricot kernels with 0.3 % (Pectazyme + Mashzyme) combination was highly effective in increasing oil recovery by 14.22 % without adversely affecting the quality and thus may be commercially used by the industry for reducing wastage of highly precious oil in the cake.

  19. Influence of high dose of phytase and an emulsifier on performance, apparent metabolisable energy and nitrogen retention in broilers fed on diets containing soy oil or tallow.

    PubMed

    Zaefarian, F; Romero, L F; Ravindran, V

    2015-01-01

    The effects of high dose of microbial phytase and an emulsifier on the performance, apparent metabolisable energy (AME) and nitrogen (N) retention in broilers fed on diets containing different fat sources were examined in a 5-week trial. Two fat sources (soy oil and tallow), two inclusion levels of E. coli phytase (500 or 1000 phytase units (FTU)/kg diet) and two inclusion levels of lysolecithin emulsifier (0 or 3.5 g/kg of diet) were evaluated in a 2 × 2 × 2 factorial arrangement of treatments. Throughout the 5-week trial, soy oil supplementation improved weight gain and feed per gain compared with tallow, but had no effect on feed intake. The high dose of phytase increased the weight gain and feed intake and lowered the feed per gain during d 1-21, but had no effect on performance parameters over the whole trial period. An effect of emulsifier was observed for feed intake during d 1-21 and over the whole trial period. Addition of emulsifier increased feed intake compared with diets without emulsifier. During weeks 1, 2, 3 and 5, birds fed on soy oil-based diets had higher nitrogen-corrected AME (AMEN) compared with those fed on tallow-based diets. During weeks 2, 3 and 5, the effect of phytase was significant for AMEN, with the high dose increasing the AMEN. During week 2, AMEN was increased with emulsifier addition. During weeks 1, 2, 3 and 5, birds fed on soy oil-based diets had higher fat retention compared with those fed on tallow-based diets. The high dose of phytase improved the retention of fat during week 5 and the addition of emulsifier resulted in higher fat retention during week 1. During weeks 2, 3 and 5, an interaction between fat source × phytase × emulsifier was observed for N retention. In soy oil-based diets, emulsifier plus 1000 FTU/kg phytase increased N retention compared with other groups, while in tallow-based diets, emulsifier addition increased N retention in diets with 500 FTU/kg, but not in 1000 FTU/kg diet. Overall, the

  20. 21 CFR 172.861 - Cocoa butter substitute from coconut oil, palm kernel oil, or both oils.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... fatty acids (complying with § 172.860) derived from edible coconut oil, edible palm kernel oil, or both oils. (b) The ingredient meets the following specifications: Acid number: Not to exceed 0.5..., citric acid, succinic acid, and spices; and (2) In compound coatings, cocoa creams, cocoa-based sweets...

  1. Effect of Acrocomia aculeata Kernel Oil on Adiposity in Type 2 Diabetic Rats.

    PubMed

    Nunes, Ângela A; Buccini, Danieli F; Jaques, Jeandre A S; Portugal, Luciane C; Guimarães, Rita C A; Favaro, Simone P; Caldas, Ruy A; Carvalho, Cristiano M E

    2018-03-01

    The macauba palm (Acrocomia aculeata) is native of tropical America and is found mostly in the Cerrados and Pantanal biomes. The fruits provide an oily pulp, rich in long chain fatty acids, and a kernel that encompass more than 50% of lipids rich in medium chain fatty acids (MCFA). Based on biochemical and nutritional evidences MCFA is readily catabolized and can reduce body fat accumulation. In this study, an animal model was employed to evaluate the effect of Acrocomia aculeata kernel oil (AKO) on the blood glucose level and the fatty acid deposit in the epididymal adipose tissue. The A. aculeata kernel oil obtained by cold pressing presented suitable quality as edible oil. Its fatty acid profile indicates high concentration of MCFA, mainly lauric, capric and caprilic. Type 2 diabetic rats fed with that kernel oil showed reduction of blood glucose level in comparison with the diabetic control group. Acrocomia aculeata kernel oil showed hypoglycemic effect. A small fraction of total dietary medium chain fatty acid was accumulated in the epididymal adipose tissue of rats fed with AKO at both low and high doses and caprilic acid did not deposit at all.

  2. Expression of Fungal diacylglycerol acyltransferase2 Genes to Increase Kernel Oil in Maize[OA

    PubMed Central

    Oakes, Janette; Brackenridge, Doug; Colletti, Ron; Daley, Maureen; Hawkins, Deborah J.; Xiong, Hui; Mai, Jennifer; Screen, Steve E.; Val, Dale; Lardizabal, Kathryn; Gruys, Ken; Deikman, Jill

    2011-01-01

    Maize (Zea mays) oil has high value but is only about 4% of the grain by weight. To increase kernel oil content, fungal diacylglycerol acyltransferase2 (DGAT2) genes from Umbelopsis (formerly Mortierella) ramanniana and Neurospora crassa were introduced into maize using an embryo-enhanced promoter. The protein encoded by the N. crassa gene was longer than that of U. ramanniana. It included 353 amino acids that aligned to the U. ramanniana DGAT2A protein and a 243-amino acid sequence at the amino terminus that was unique to the N. crassa DGAT2 protein. Two forms of N. crassa DGAT2 were tested: the predicted full-length protein (L-NcDGAT2) and a shorter form (S-NcDGAT2) that encoded just the sequences that share homology with the U. ramanniana protein. Expression of all three transgenes in maize resulted in small but statistically significant increases in kernel oil. S-NcDGAT2 had the biggest impact on kernel oil, with a 26% (relative) increase in oil in kernels of the best events (inbred). Increases in kernel oil were also obtained in both conventional and high-oil hybrids, and grain yield was not affected by expression of these fungal DGAT2 transgenes. PMID:21245192

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

    PubMed

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

    2015-02-01

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

  4. Study on Energy Productivity Ratio (EPR) at palm kernel oil processing factory: case study on PT-X at Sumatera Utara Plantation

    NASA Astrophysics Data System (ADS)

    Haryanto, B.; Bukit, R. Br; Situmeang, E. M.; Christina, E. P.; Pandiangan, F.

    2018-02-01

    The purpose of this study was to determine the performance, productivity and feasibility of the operation of palm kernel processing plant based on Energy Productivity Ratio (EPR). EPR is expressed as the ratio of output to input energy and by-product. Palm Kernel plan is process in palm kernel to become palm kernel oil. The procedure started from collecting data needed as energy input such as: palm kernel prices, energy demand and depreciation of the factory. The energy output and its by-product comprise the whole production price such as: palm kernel oil price and the remaining products such as shells and pulp price. Calculation the equality of energy of palm kernel oil is to analyze the value of Energy Productivity Ratio (EPR) bases on processing capacity per year. The investigation has been done in Kernel Oil Processing Plant PT-X at Sumatera Utara plantation. The value of EPR was 1.54 (EPR > 1), which indicated that the processing of palm kernel into palm kernel oil is feasible to be operated based on the energy productivity.

  5. Extraction and characterization of seed oil from naturally-grown Chinese tallow trees

    Treesearch

    Xiao-Qin Yang; Hui Pan; Tao Zeng; Todd F. Shupe; Chung-Yun Hse

    2013-01-01

    Seeds were collected from locally and naturally grown Chinese tallow trees (CTT) and characterized for general physical and chemical properties and fatty acid composition of the lipids. The effects of four different solvents (petroleum ether, hexane, diethyl ether, and 95 % ethanol) and two extraction methods (supercritical carbon dioxide (SC-CO2) and conventional...

  6. Chemical properties and oxidative stability of Arjan (Amygdalus reuteri) kernel oil as emerging edible oil.

    PubMed

    Tavakoli, Javad; Emadi, Teymour; Hashemi, Seyed Mohammad Bagher; Mousavi Khaneghah, Amin; Munekata, Paulo Eduardo Sichetti; Lorenzo, Jose Manuel; Brnčić, Mladen; Barba, Francisco J

    2018-05-01

    The oxidative stability, as well as the chemical composition of Amygdalus reuteri kernel oil (ARKO), were evaluated and compared to those of Amygdalus scoparia kernel oil (ASKO) and extra virgin olive oil (EVOO) during and after holding in the oven (170 °C for 8 h). The oxidative stability analysis was carried out by measuring the changes in conjugated dienes, carbonyl and acid values as well as oil/oxidative stability index and their correlation with the antioxidant compounds (tocopherol, polyphenols, and sterol compounds). The oleic acid was determined as the predominant fatty acid of ARKO (65.5%). Calculated oxidizability value and an iodine value of ARKO, ASKO and EVOO were reported as 3.29 and 3.24, 2.00 and 100.0, 101.4 and 81.9, respectively. Due to the high wax content (4.5% and 3.3%, respectively), the saponification number of ARKO and ASKO (96.4 and 99.8, respectively) was lower than that of EVOO (169.7). ARKO had the highest oxidative stability, followed by ASKO and EVOO. Therefore, ARKO can be introduced as a new source of edible oil with high oxidative stability. Copyright © 2018. Published by Elsevier Ltd.

  7. Chinese tallow: Invading the southeastern Coastal Plain

    USGS Publications Warehouse

    ,

    2000-01-01

    Chinese tallow is an ornamental tree with colorful autumn foliage that can survive full sunlight and shade, flooding, drought, and in some cases fire. To horticulturists this kind of tree sounds like a dream, but to ecologists, land managers, and land owners this kind of tree can be a nightmare, especially when it invades an area and takes over native vegetation. Chinese tallow (Triadica sebifera), a nonnative tree from China, is currently transforming the southeastern Coastal Plain.Over the last 30 years, Chinese tallow has become a common tree in old fields and bottomland swamps of coastal Louisiana. Several studies at the U.S. Geological Survey’s National Wetlands Research Center (NWRC), Lafayette, Louisiana, are aimed at understanding the factors that contribute to Chinese tallow growth, spread, and management.When tallow invades, it eventually monopolizes an area, creating a forest without native animal or plant species. This tree exhibits classic traits of most nonnative invaders: it is attractive so people want to distribute it, it has incredible resiliency, it grows quickly and in a variety of soils, and it is resistant to pests.In the coastal prairie of Louisiana and Texas, Chinese tallow can grow up to 30 feet and shade out native sun-loving prairie species. The disappearing of prairie species is troublesome because less than 1% of original coastal prairie remains, and in Louisiana, less than 500 of the original 2.2 million acres still exist.Tallow reproduces and grows quickly and can cause large-scale ecosystem modification (fig. 1). For example, when it completely replaces native vegetation, it has a negative effect on birds by degrading the habitat. Besides shading out grasses that cattle like to eat, it can also be potentially harmful to humans and animals because of its berries (fig. 2) and plant sap that contain toxins. There is some concern its leaves may shed toxins that change the soil chemistry and make it difficult for other plants to grow.

  8. Fatty acid, triacylglycerol, phytosterol, and tocopherol variations in kernel oil of Malatya apricots from Turkey.

    PubMed

    Turan, Semra; Topcu, Ali; Karabulut, Ihsan; Vural, Halil; Hayaloglu, Ali Adnan

    2007-12-26

    The fatty acid, sn-2 fatty acid, triacyglycerol (TAG), tocopherol, and phytosterol compositions of kernel oils obtained from nine apricot varieties grown in the Malatya region of Turkey were determined ( P<0.05). The names of the apricot varieties were Alyanak (ALY), Cataloglu (CAT), Cöloglu (COL), Hacihaliloglu (HAC), Hacikiz (HKI), Hasanbey (HSB), Kabaasi (KAB), Soganci (SOG), and Tokaloglu (TOK). The total oil contents of apricot kernels ranged from 40.23 to 53.19%. Oleic acid contributed 70.83% to the total fatty acids, followed by linoleic (21.96%), palmitic (4.92%), and stearic (1.21%) acids. The s n-2 position is mainly occupied with oleic acid (63.54%), linoleic acid (35.0%), and palmitic acid (0.96%). Eight TAG species were identified: LLL, OLL, PLL, OOL+POL, OOO+POO, and SOO (where P, palmitoyl; S, stearoyl; O, oleoyl; and L, linoleoyl), among which mainly OOO+POO contributed to 48.64% of the total, followed by OOL+POL at 32.63% and OLL at 14.33%. Four tocopherol and six phytosterol isomers were identified and quantified; among these, gamma-tocopherol (475.11 mg/kg of oil) and beta-sitosterol (273.67 mg/100 g of oil) were predominant. Principal component analysis (PCA) was applied to the data from lipid components of apricot kernel oil in order to explore the distribution of the apricot variety according to their kernel's lipid components. PCA separated some varieties including ALY, COL, KAB, CAT, SOG, and HSB in one group and varieties TOK, HAC, and HKI in another group based on their lipid components of apricot kernel oil. So, in the present study, PCA was found to be a powerful tool for classification of the samples.

  9. Santalbic acid from quandong kernels and oil fed to rats affects kidney and liver P450.

    PubMed

    Jones, G P; Watson, T G; Sinclair, A J; Birkett, A; Dunt, N; Nair, S S; Tonkin, S Y

    1999-09-01

    Kernels of the plant Santalum acuminatum (quandong) are eaten as Australian 'bush foods'. They are rich in oil and contain relatively large amounts of the acetylenic fatty acid, santalbic acid (trans-11-octadecen-9-ynoic acid), whose chemical structure is unlike that of normal dietary fatty acids. When rats were fed high fat diets in which oil from quandong kernels supplied 50% of dietary energy, the proportion of santalbic acid absorbed was more than 90%. Feeding quandong oil elevated not only total hepatic cytochrome P450 but also the cytochrome P450 4A subgroup of enzymes as shown by a specific immunoblotting technique. A purified methyl santalbate preparation isolated from quandong oil was fed to rats at 9% of dietary energy for 4 days and this also elevated cytochrome P450 4A in both kidney and liver microsomes in comparison with methyl esters from canola oil. Santalbic acid appears to be metabolized differently from the usual dietary fatty acids and the consumption of oil from quandong kernels may cause perturbations in normal fatty acid biochemistry.

  10. Novel near-infrared sampling apparatus for single kernel analysis of oil content in maize.

    PubMed

    Janni, James; Weinstock, B André; Hagen, Lisa; Wright, Steve

    2008-04-01

    A method of rapid, nondestructive chemical and physical analysis of individual maize (Zea mays L.) kernels is needed for the development of high value food, feed, and fuel traits. Near-infrared (NIR) spectroscopy offers a robust nondestructive method of trait determination. However, traditional NIR bulk sampling techniques cannot be applied successfully to individual kernels. Obtaining optimized single kernel NIR spectra for applied chemometric predictive analysis requires a novel sampling technique that can account for the heterogeneous forms, morphologies, and opacities exhibited in individual maize kernels. In this study such a novel technique is described and compared to less effective means of single kernel NIR analysis. Results of the application of a partial least squares (PLS) derived model for predictive determination of percent oil content per individual kernel are shown.

  11. Mapping the invasive species, Chinese tallow, with EO1 satellite Hyperion hyperspectral image data and relating tallow occurrences to a classified Landsat Thematic Mapper land cover map

    USGS Publications Warehouse

    Ramsey, Elijah W.; Rangoonwala, A.; Nelson, G.; Ehrlich, R.

    2005-01-01

    Our objective was to provide a realistic and accurate representation of the spatial distribution of Chinese tallow (Triadica sebifera) in the Earth Observing 1 (EO1) Hyperion hyperspectral image coverage by using methods designed and tested in previous studies. We transformed, corrected, and normalized Hyperion reflectance image data into composition images with a subpixel extraction model. Composition images were related to green vegetation, senescent foliage and senescing cypress-tupelo forest, senescing Chinese tallow with red leaves ('red tallow'), and a composition image that only corresponded slightly to yellowing vegetation. These statistical and visual comparisons confirmed a successful portrayal of landscape features at the time of the Hyperion image collection. These landscape features were amalgamated in the Landsat Thematic Mapper (TM) pixel, thereby preventing the detection of Chinese tallow occurrences in the Landsat TM classification. With the occurrence in percentage of red tallow (as a surrogate for Chinese tallow) per pixel mapped, we were able to link dominant land covers generated with Landsat TM image data to Chinese tallow occurrences as a first step toward determining the sensitivity and susceptibility of various land covers to tallow establishment. Results suggested that the highest occurrences and widest distribution of red tallow were (1) apparent in disturbed or more open canopy woody wetland deciduous forests (including cypress-tupelo forests), upland woody land evergreen forests (dominantly pines and seedling plantations), and upland woody land deciduous and mixed forests; (2) scattered throughout the fallow fields or located along fence rows separating active and non-active cultivated and grazing fields, (3) found along levees lining the ubiquitous canals within the marsh and on the cheniers near the coastline; and (4) present within the coastal marsh located on the numerous topographic highs. ?? 2005 US Government.

  12. Sterols and squalene in apricot (Prunus armeniaca L.) kernel oils: the variety as a key factor.

    PubMed

    Rudzińska, Magdalena; Górnaś, Paweł; Raczyk, Marianna; Soliven, Arianne

    2017-01-01

    The profile of sterols and squalene content in oils recovered from the kernels of 15 apricot (Prunus armeniaca L.) varieties were investigated. Nine sterols (campesterol, β-sitosterol, Δ5-avenasterol, 24-methylene-cycloartanol, cholesterol, gramisterol, Δ7-stigmasterol, Δ7-avenasterol and citrostadienol) were identified in apricot kernel oils. The β-sitosterol was the predominant sterol in each cultivar and consisted of 76-86% of the total detected sterols. The content of total sterols and squalene were significantly affected by the variety and ranged between 215.7-973.6 and 12.6-43.9 mg/100 g of oil, respectively.

  13. Composition and Free Radical Scavenging Activity of Kernel Oil from Torreya grandis, Carya Cathayensis, and Myrica Rubra

    PubMed Central

    Ni, Liang; Shi, Wei-Yong

    2014-01-01

    In this study, we measured the composition and free radical scavenging activity of several species of nuts, namely, Torreya grandis, Carya cathayensis, and Myrica rubra. The nut kernels of the aforementioned species are rich in fatty acids, particularly in unsaturated fatty acids, and have 51% oil content. T. grandis and C. cathayensis are mostly produced in ZheJiang province. The trace elements in the kernels of T. grandis and C. cathayensis were generally higher than those in M. rubra, except for Fe with a value of 64.41 mg/Kg. T. grandis is rich in selenium (52.91−68.71 mg/Kg). All three kernel oils have a certain free radical scavenging capacity, with the highest value in M. rubra. In the DPPH assay, the IC50 of M. rubra kernel oil was 60 μg/mL, and OH was 100 μg/mL. The results of this study provide basic data for the future development of the edible nut resources in ZheJiang province. PMID:24734074

  14. Nutritional value of raw soybeans, extruded soybeans, roasted soybeans and tallow as fat sources in early lactating dairy cows.

    PubMed

    Amanlou, H; Maheri-Sis, N; Bassiri, S; Mirza-Aghazadeh, A; Salamatdust, R; Moosavi, A; Karimi, V

    2012-01-01

    Thirty multiparous Holstein cows (29.8 ± 4.01days in milk; 671.6 ± 31.47 kg of body weight) were used in a completely randomized design to compare nutritional value of four fat sources including tallow, raw soybeans, extruded soybeans and roasted soybeans for 8 weeks. Experimental diets were a control containing 27.4 % alfalfa silage, 22.5% corn silage, and 50.1% concentrate, and four diets with either tallow, raw soybean, extruded soybean, or roasted soybean added to provide 1.93% supplemental fat. Dry matter and NEL intakes were similar among treatments, while cows fed fat diets had significantly (P<0.05) high NEL intakes when compared to control with no fat. Supplemental fat, whether tallow or full fat soybeans increased milk production (1.89-2.45 kg/d; P<0.01) and FCM production (1.05-2.79; P<0.01). Milk fat yield and percentage of cows fed fat-supplemented diets were significantly (P<0.01 and P<0.05 respectively) higher than control. Between fat-supplemented diets, roasted soybean caused highest milk fat yield and extruded soybean caused lowest milk fat yield. There was no significant effect of supplemental fat on the milk protein and lactose content and yield. Feed efficiency of fat-supplemented diets was significantly (P<0.01) higher than control. Body weight, body weight change and BCS (body condition score) of cows, as well as energy balance and energy efficiency were similar between treatments. In conclusion, while there was no significant effect of fat sources on production response of cows, fat originating from heat-treated soybean help to minimize imported RUP (rumen undegradable protein) sources level as fish meal in comparison with tallow and raw soybean oil. In the Current study, there was no statistical significance among nutritional values of oil from extruded soybeans and roasted soybeans.

  15. Modulation of antioxidant potential in liver of mice by kernel oil of cashew nut (Anacardium occidentale) and its lack of tumour promoting ability in DMBA induced skin papillomagenesis.

    PubMed

    Singh, Bimala; Kale, R K; Rao, A R

    2004-04-01

    Cashew nut shell oil has been reported to possess tumour promoting property. Therefore an attempt has been made to study the modulatory effect of cashew nut (Anlacardium occidentale) kernel oil on antioxidant potential in liver of Swiss albino mice and also to see whether it has tumour promoting ability like the shell oil. The animals were treated orally with two doses (50 and 100 microl/animal/day) of kernel oil of cashew nut for 10 days. The kernel oil was found to enhance the specific activities of SOD, catalase, GST, methylglyoxalase I and levels of GSH. These results suggested that cashew nut kernel oil had an ability to increase the antioxidant status of animals. The decreased level of lipid peroxidation supported this possibility. The tumour promoting property of the kernel oil was also examined and found that cashew nut kernel oil did not exhibit any solitary carcinogenic activity.

  16. Oil extraction from sheanut (Vitellaria paradoxa Gaertn C.F.) kernels assisted by microwaves.

    PubMed

    Nde, Divine B; Boldor, Dorin; Astete, Carlos; Muley, Pranjali; Xu, Zhimin

    2016-03-01

    Shea butter, is highly solicited in cosmetics, pharmaceuticals, chocolates and biodiesel formulations. Microwave assisted extraction (MAE) of butter from sheanut kernels was carried using the Doehlert's experimental design. Factors studied were microwave heating time, temperature and solvent/solute ratio while the responses were the quantity of oil extracted and the acid number. Second order models were established to describe the influence of experimental parameters on the responses studied. Under optimum MAE conditions of heating time 23 min, temperature 75 °C and solvent/solute ratio 4:1 more than 88 % of the oil with a free fatty acid (FFA) value less than 2, was extracted compared to the 10 h and solvent/solute ratio of 10:1 required for soxhlet extraction. Scanning electron microscopy was used to elucidate the effect of microwave heating on the kernels' microstructure. Substantial reduction in extraction time and volumes of solvent used and oil of suitable quality are the main benefits derived from the MAE process.

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

    PubMed

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

    2017-12-01

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

  18. Inclusion of tallow and soybean oil to calf starters fed to dairy calves from birth to four months of age on calf performance and digestion.

    PubMed

    Hill, T M; Bateman, H G; Aldrich, J M; Quigley, J D; Schlotterbeck, R L

    2015-07-01

    Energy demands for calves can increase during periods of heat and cold stress. One way to potentially increase energy intake is to increase the energy density of the feed with fat. Trial 1a compared a control starter with no added fat or oil (CON) to starters with 2% tallow (TAL) and 2% soybean oil (SBO). Starters were 20% crude protein (CP) and 45 to 47% starch. Male Holstein calves that were initially 3 to 5d of age were fed a 27% CP, 17% fat milk replacer at 0.66kg of dry matter daily and fully weaned by 42d of a 56-d trial. Trial 1b estimated the digestion of the diets (employed chromic oxide as an indigestible digesta flow marker) using a subset of 5 weaned calves per treatment between d 52 and 56. Trial 2 used Holstein calves initially 59 to 61d of age fed starters CON and SBO blended with 5% chopped grass hay over a 56-d trial. Trial 3 used Holstein calves initially 59 to 61d of age fed starters CON and TAL blended with 5% chopped grass hay over a 56-d trial. Treatments were compared using repeated measures (where appropriate) in a completely randomized design. In trials 1a and 1b, preplanned contrasts compared CON versus TAL and CON versus SBO. Compared with CON, calves fed SBO had reduced starter intake, average daily gain, and digestion of dry matter, organic matter, and CP before 8wk of age. Compared with CON, calves fed SBO had reduced average daily gain and change in hip width from 2 to 4 mo of age. Compared with CON, calves fed TAL had reduced average daily gain and tended to have reduced change in hip width from 2 to 4 mo of age. Calculated metabolizable energy intake was not increased in any trial by added fat or oil. Tallow and soybean oil inclusion at 2% of the starter feed was not advantageous for calf growth before 4 mo of age. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  19. Blending of palm oil, palm stearin and palm kernel oil in the preparation of table and pastry margarine.

    PubMed

    Norlida, H M; Md Ali, A R; Muhadhir, I

    1996-01-01

    Palm oil (PO ; iodin value = 52), palm stearin (POs1; i.v. = 32 and POs2; i.v. = 40) and palm kernel oil (PKO; i.v. = 17) were blended in ternary systems. The blends were then studied for their physical properties such as melting point (m.p.), solid fat content (SFC), and cooling curve. Results showed that palm stearin increased the blends melting point while palm kernel oil reduced it. To produce table margarine with melting point (m.p.) below 40 degrees C, the POs1 should be added at level of < or = 16%, while POs2 at level of < or = 20%. At 10 degrees C, eutectic interaction occur between PO and PKO which reach their maximum at about 60:40 blending ratio. Within the eutectic region, to maintain the SFC at 10 degrees C to be < or = 50%, POs1 may be added at level of < or = 7%, while POs2 at level of < or = 12%. The addition of palm stearin increased the blends solidification Tmin and Tmax values, while PKO reduced them. Blends which contained high amount of palm stearin showed melting point and cooling curves quite similar to that of pastry margarine.

  20. The effect of microwave roasting on bioactive compounds, antioxidant activity and fatty acid composition of apricot kernel and oils.

    PubMed

    Al Juhaimi, Fahad; Musa Özcan, Mehmet; Ghafoor, Kashif; Babiker, Elfadıl E

    2018-03-15

    In this study, the effect of microwave (360W, 540W and 720W) oven roasting on oil yields, phenolic compounds, antioxidant activity, and fatty acid composition of some apricot kernel and oils was investigated. While total phenol contents of control group of apricot kernels change between 54.41mgGAE/100g (Soğancıoğlu) and 59.61mgGAE/100g (Hasanbey), total phenol contents of kernel samples roasted in 720W were determined between 27.41mgGAE/100g (Çataloğlu) and 34.52mgGAE/100g (Soğancıoğlu). Roasting process in microwave at 720W caused the reduction of some phenolic compounds of apricot kernels. The gallic acid contents of control apricot kernels ranged between 7.23mg/100g (Kabaaşı) and 11.23mg/100g (Çataloğlu) whereas the gallic acid contents of kernels roasted in 540W changed between 15.35mg/100g (Soğancıoğlu) and 21.17mg/100g (Çataloğlu). In addition, oleic acid contents of control group oils vary between 65.98% (Soğancıoğlu) and 71.86% (Hasanbey), the same fatty acid ranged from 63.48% (Soğancıoğlu) to 70.36% (Hasanbey). Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Defect Analysis Of Quality Palm Kernel Meal Using Statistical Quality Control In Kernels Factory

    NASA Astrophysics Data System (ADS)

    Sembiring, M. T.; Marbun, N. J.

    2018-04-01

    The production quality has an important impact retain the totality of characteristics of a product or service to pay attention to its capabilities to meet the needs that have been established. Quality criteria Palm Kernel Meal (PKM) set Factory kernel is as follows: oil content: max 8.50%, water content: max 12,00% and impurity content: max 4.00% While the average quality of the oil content of 8.94%, the water content of 5.51%, and 8.45% impurity content. To identify the defective product quality PKM produced, then used a method of analysis using Statistical Quality Control (SQC). PKM Plant Quality Kernel shows the oil content was 0.44% excess of a predetermined maximum value, and 4.50% impurity content. With excessive PKM content of oil and dirt cause disability content of production for oil, amounted to 854.6078 kg PKM and 8643.193 kg impurity content of PKM. Analysis of the results of cause and effect diagram and SQC, the factors that lead to poor quality of PKM is Ampere second press oil expeller and hours second press oil expeller.

  2. Tadpoles of Early Breeding Amphibians are Negatively Affected by Leaf Litter From Invasive Chinese Tallow Trees

    NASA Astrophysics Data System (ADS)

    Leonard, N. E.

    2005-05-01

    As wetlands are invaded by Chinese tallow trees (Triadica sebifera), native trees are displaced and detrital inputs to amphibian breeding ponds are altered. I used a mesocosm experiment to examine the effect of Chinese tallow leaf litter on the survival to, size at, and time to metamorphosis of amphibian larvae. Fifty 1000-L cattle watering tanks were treated with 1500 g dry weight of one of five leaf litter treatments: Chinese tallow, laurel oak (Quercus laurifolia), water tupelo (Nyssa aquatica), slash pine (Pinus elliottii), or a 3:1:1:1 mixture. Each tank received 45 tadpoles of Pseudacris feriarum, Bufo terrestris, and Hyla cinerea in sequence according to their natural breeding phonologies. Every Pseudacris feriarum and Bufo terrestris tadpole exposed to Chinese tallow died prior to metamorphosis. Hyla cinerea survival in tanks with tallow-only was significantly lower than that observed for all other leaf treatments. Hyla cinerea tadpoles from tallow-only and mixed-leaf treatments were larger at metamorphosis and transformed faster than those in tanks with native leaves only. These results suggest that Chinese tallow leaf litter may negatively affect tadpoles of early breeding frogs and that Chinese tallow invasion may change the structure of amphibian communities in temporary ponds.

  3. Compressive strength, flexural strength and water absorption of concrete containing palm oil kernel shell

    NASA Astrophysics Data System (ADS)

    Noor, Nurazuwa Md; Xiang-ONG, Jun; Noh, Hamidun Mohd; Hamid, Noor Azlina Abdul; Kuzaiman, Salsabila; Ali, Adiwijaya

    2017-11-01

    Effect of inclusion of palm oil kernel shell (PKS) and palm oil fibre (POF) in concrete was investigated on the compressive strength and flexural strength. In addition, investigation of palm oil kernel shell on concrete water absorption was also conducted. Total of 48 concrete cubes and 24 concrete prisms with the size of 100mm × 100mm × 100mm and 100mm × 100mm × 500mm were prepared, respectively. Four (4) series of concrete mix consists of coarse aggregate was replaced by 0%, 25%, 50% and 75% palm kernel shell and each series were divided into two (2) main group. The first group is without POF, while the second group was mixed with the 5cm length of 0.25% of the POF volume fraction. All specimen were tested after 7 and 28 days of water curing for a compression test, and flexural test at 28 days of curing period. Water absorption test was conducted on concrete cube age 28 days. The results showed that the replacement of PKS achieves lower compressive and flexural strength in comparison with conventional concrete. However, the 25% replacement of PKS concrete showed acceptable compressive strength which within the range of requirement for structural concrete. Meanwhile, the POF which should act as matrix reinforcement showed no enhancement in flexural strength due to the balling effect in concrete. As expected, water absorption was increasing with the increasing of PKS in the concrete cause by the porous characteristics of PKS

  4. Fully-Automated High-Throughput NMR System for Screening of Haploid Kernels of Maize (Corn) by Measurement of Oil Content

    PubMed Central

    Xu, Xiaoping; Huang, Qingming; Chen, Shanshan; Yang, Peiqiang; Chen, Shaojiang; Song, Yiqiao

    2016-01-01

    One of the modern crop breeding techniques uses doubled haploid plants that contain an identical pair of chromosomes in order to accelerate the breeding process. Rapid haploid identification method is critical for large-scale selections of double haploids. The conventional methods based on the color of the endosperm and embryo seeds are slow, manual and prone to error. On the other hand, there exists a significant difference between diploid and haploid seeds generated by high oil inducer, which makes it possible to use oil content to identify the haploid. This paper describes a fully-automated high-throughput NMR screening system for maize haploid kernel identification. The system is comprised of a sampler unit to select a single kernel to feed for measurement of NMR and weight, and a kernel sorter to distribute the kernel according to the measurement result. Tests of the system show a consistent accuracy of 94% with an average screening time of 4 seconds per kernel. Field test result is described and the directions for future improvement are discussed. PMID:27454427

  5. 40 CFR 721.6183 - Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... - maleic anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine... Substances § 721.6183 Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow... anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine (PMN P-00...

  6. 40 CFR 721.6183 - Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... - maleic anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine... Substances § 721.6183 Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow... anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine (PMN P-00...

  7. Allometric biomass models and applications for branches of Chinese tallow in a Mississippi Bottomland Forest

    Treesearch

    Allison M. Stoklosa; Nana Tian; Zhaofei Fan

    2015-01-01

    Chinese tallow [Triadica sebifera (L.) Small, formerly Sapium sebiferum (L.) Roxb.] is a non-native invader moving through the southeastern United States. Tallow can invade a multitude of habitats, from coastal prairies to closed-canopy forests, forming monospecific stands and driving out native flora and fauna (Bruce and others 1997). Tallow has large impacts, both...

  8. Effect of solid fat content on structure in ice creams containing palm kernel oil and high-oleic sunflower oil.

    PubMed

    Sung, Kristine K; Goff, H Douglas

    2010-04-01

    The development of a structural fat network in ice cream as influenced by the solid:liquid fat ratio at the time of freezing/whipping was investigated. The solid fat content was varied with blends of a hard fraction of palm kernel oil (PKO) and high-oleic sunflower oil ranging from 40% to 100% PKO. Fat globule size and adsorbed protein levels in mix and overrun, fat destabilization, meltdown resistance, and air bubble size in ice cream were measured. It was found that blends comprising 60% to 80% solid fat produced the highest rates of fat destabilization that could be described as partial coalescence (as opposed to coalescence), lowest rates of meltdown, and smallest air bubble sizes. Lower levels of solid fat produced fat destabilization that was better characterized as coalescence, leading to loss of structural integrity, whereas higher levels of solid fat led to lower levels of fat network formation and thus also to reduced structural integrity. Blends of highly saturated palm kernel oil and monounsaturated high-oleic sunflower oil were used to modify the solid:liquid ratio of fat blends used for ice cream manufacture. Blends that contained 60% to 80% solid fat at freezing/whipping temperatures produced optimal structures leading to low rates of meltdown. This provides a useful reference for manufacturers to help in the selection of appropriate fat blends for nondairy-fat ice cream.

  9. Optimization of soxhlet extraction and physicochemical analysis of crop oil from seed kernel of Feun Kase (Thevetia peruviana)

    NASA Astrophysics Data System (ADS)

    Suwari, Kotta, Herry Z.; Buang, Yohanes

    2017-12-01

    Optimizing the soxhlet extraction of oil from seed kernel of Feun Kase (Thevetia peruviana) for biodiesel production was carried out in this study. The solvent used was petroleum ether and methanol, as well as their combinations. The effect of three factors namely different solvent combinations (polarity), extraction time and extraction temperature were investigated for achieving maximum oil yield. Each experiment was conducted in 250 mL soxhlet apparatus. The physicochemical properties of the oil yield (density, kinematic viscosity, acid value, iodine value, saponification value, and water content) were also analyzed. The optimum conditions were found after 4.5 h with extraction time, extraction temperature at 65 oC and petroleum ether to methanol ratio of 90 : 10 (polarity index 0.6). The oil extract was found to be 51.88 ± 3.18%. These results revealed that the crop oil from seed kernel of Feun Kase (Thevetia peruviana) is a potential feedstock for biodiesel production.

  10. Selected mechanical and physical properties of Chinese tallow tree juvenile wood

    Treesearch

    Todd F. Shupe; LEslie H. Groom; Thomas L. Eberhardt; Thomas C. Pesacreta; Timothy G. Rials

    2008-01-01

    Chinese tallow tree is a noxious, invasive plant in the Southeastern United States. It is generally considered a nuisance and has no current commercial use. The objective of this research was to determine the moduli of rupture (MOR) and elasticity (MOE) of the stem wood of this species at different vertical sampling locations. Three Chinese tallow trees were felled and...

  11. Remote sensing survey of Chinese tallow tree in the Toledo Bend Reservoir area, Louisiana and Texas

    USGS Publications Warehouse

    Ramsey, Elijah W.; Rangoonwala, Amina; Bannister, Terri; Suzuoki, Yukihiro

    2013-01-01

    We applied Hyperion sensor satellite data acquired by the National Aeronautics and Space Administration’s Earth Observing-1 (EO-1) satellite in conjunction with reconnaissance surveys to map the occurrences of the invasive Chinese tallow tree (Triadica sebifera) in the Toledo Bend Reservoir study area of northwestern Louisiana and northeastern Texas. The rationale for application of high spectral resolution EO-1 Hyperion data was based on the successful use of Hyperion data in the mapping of Chinese tallow tree in southwestern Louisiana in 2005. In contrast to the single Hyperion image used in the 2005 project, more than 20 EO-1 Hyperion and Advanced Land Imager (ALI) images of the study area were collected in 2009 and 2010 during the fall senescence when Chinese tallow tree leaves turn red. Atmospherically corrected reflectance spectra of Hyperion imagery collected at ground and aerial observation locations provided the input datasets used in the program for spectral discrimination analysis. Discrimination analysis was used to identify spectral indicator sets to best explain variance contained in the input databases. The expectation was that at least one set of Hyperion-based indicator spectra would uniquely identify occurrences of red-leaf Chinese tallow tree; however, no combination of Hyperion-based reflectance datasets produced a unique identifier. The inability to discover a unique spectral indicator resulted primarily from relatively sparse coverage by red-leaf Chinese tallow tree within the study area (percentage of coverage was less than 5 percent per 30- by 30-meter Hyperion pixel). To enhance the performance of the spectral discrimination analysis, leaf and canopy spectra of Chinese tallow tree were added to the input datasets to guide the indicator selection. In addition, input databases were segregated by land class obtained from an ALI-based landcover classification in order to reduce the input variance and to promote spectral discrimination of red

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

    NASA Astrophysics Data System (ADS)

    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.

  13. Mechanical and physical properties of composite panels manufactured from Chinese tallow tree furnish

    Treesearch

    Todd F. Shupe; Leslie H. Groom; Thomas L. Eberhardt; Timothy G. Rials; Chung Y. Hse; Thomas Pesacreta

    2006-01-01

    Chinese tallow tree is a noxious, invasive plant in the southeastern United States. It is generally considered a nuisance and has no current commercial use. The objective of this research was to determine the technical feasibility of using the stem wood of this species for particleboard, fiberboard, and structural flakeboard. Due to its rapid growth, Chinese tallow...

  14. Repeatedly heated palm kernel oil induces hyperlipidemia, atherogenic indices and hepatorenal toxicity in rats: Beneficial role of virgin coconut oil supplementation.

    PubMed

    Famurewa, Ademola C; Nwankwo, Onyebuchi E; Folawiyo, Abiola M; Igwe, Emeka C; Epete, Michael A; Ufebe, Odomero G

    2017-01-01

    The literature reports that the health benefits of vegetable oil can be deteriorated by repeated heating, which leads to lipid oxidation and the formation of free radicals. Virgin coconut oil (VCO) is emerging as a functional food oil and its health benefits are attributed to its potent polyphenolic compounds. We investigated the beneficial effect of VCO supplementation on lipid profile, liver and kidney markers in rats fed repeatedly heated palm kernel oil (HPO). Rats were divided into four groups (n = 5). The control group rats were fed with   a normal diet; group 2 rats were fed a 10% VCO supplemented diet; group 3 administered 10 ml HPO/kg b.w. orally; group 4 were fed 10% VCO + 10 ml HPO/kg for 28 days. Subsequently, serum markers of liver damage (ALT, AST, ALP and albumin), kidney damage (urea, creatinine and uric acid), lipid profile and lipid ratios as cardiovascular risk indices were evaluated. HPO induced a significant increase in serum markers of liver and kidney damage as well as con- comitant lipid abnormalities and a marked reduction in serum HDL-C. The lipid ratios evaluated for atherogenic and coronary risk indices in rats administered HPO only were remarkably higher than control. It was observed that VCO supplementation attenuated the biochemical alterations, including the indices of cardiovascular risks. VCO supplementation demonstrates beneficial health effects against HPO-induced biochemical alterations in rats. VCO may serve to modulate the adverse effects associated with consumption of repeatedly heated palm kernel oil.

  15. Pollen source effects on growth of kernel structures and embryo chemical compounds in maize.

    PubMed

    Tanaka, W; Mantese, A I; Maddonni, G A

    2009-08-01

    Previous studies have reported effects of pollen source on the oil concentration of maize (Zea mays) kernels through modifications to both the embryo/kernel ratio and embryo oil concentration. The present study expands upon previous analyses by addressing pollen source effects on the growth of kernel structures (i.e. pericarp, endosperm and embryo), allocation of embryo chemical constituents (i.e. oil, protein, starch and soluble sugars), and the anatomy and histology of the embryos. Maize kernels with different oil concentration were obtained from pollinations with two parental genotypes of contrasting oil concentration. The dynamics of the growth of kernel structures and allocation of embryo chemical constituents were analysed during the post-flowering period. Mature kernels were dissected to study the anatomy (embryonic axis and scutellum) and histology [cell number and cell size of the scutellums, presence of sub-cellular structures in scutellum tissue (starch granules, oil and protein bodies)] of the embryos. Plants of all crosses exhibited a similar kernel number and kernel weight. Pollen source modified neither the growth period of kernel structures, nor pericarp growth rate. By contrast, pollen source determined a trade-off between embryo and endosperm growth rates, which impacted on the embryo/kernel ratio of mature kernels. Modifications to the embryo size were mediated by scutellum cell number. Pollen source also affected (P < 0.01) allocation of embryo chemical compounds. Negative correlations among embryo oil concentration and those of starch (r = 0.98, P < 0.01) and soluble sugars (r = 0.95, P < 0.05) were found. Coincidently, embryos with low oil concentration had an increased (P < 0.05-0.10) scutellum cell area occupied by starch granules and fewer oil bodies. The effects of pollen source on both embryo/kernel ratio and allocation of embryo chemicals seems to be related to the early established sink strength (i.e. sink size and sink activity) of the

  16. Invasion of tallow tree into southern US forests: influencing factors and implications for mitigation

    Treesearch

    Jianbang Gan; James H. Miller; Hsiaohsuan Wang; John W. Jr. Taylor

    2009-01-01

    We identify species-environment relationships to predict the occurrence of Chinese tallow (Triadica sebifera (L.) Small) on forestlands in the southern US, where it has emerged as the most pervading, stand-replacing, alien tree species. Tallow invasions are most likely to be observed on low and flat lands, areas adjacent to water and roadways, sites recently...

  17. 40 CFR 721.6183 - Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 31 2014-07-01 2014-07-01 false Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine... Substances § 721.6183 Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow...

  18. 40 CFR 721.6183 - Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 32 2012-07-01 2012-07-01 false Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine... Substances § 721.6183 Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow...

  19. 40 CFR 721.6183 - Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 32 2013-07-01 2013-07-01 false Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow alkyl amines, sodium salts, compds. with ethanolamine... Substances § 721.6183 Amides, from ammonium hydroxide - maleic anhydride polymer and hydrogenated tallow...

  20. Biology and host range of Heterapoderopsis bicallosicollis; a potential biological control agent for Chinese tallow Triadica sebifera

    USDA-ARS?s Scientific Manuscript database

    Chinese tallow, Triadica sebifera, is an invasive weed that infests natural and agricultural areas of the southeastern USA. A candidate for biological control of Chinese tallow has been studied under quarantine conditions. The biology and host range of a primitive leaf feeding beetle, Heterapoderops...

  1. Impact of ecological and socioeconomic determinants on the spread of tallow tree in southern forest lands

    Treesearch

    Yuan Tan; Joseph Z. Fan; Christopher M. Oswalt

    2010-01-01

    Based on USDA Forest Service Forest Inventory and Analysis (FIA) database, relationships between the presence of tallow tree and related driving variables including forest landscape metrics, stand and site conditions, as well as natural and anthropogenic disturbances were analyzed for the southern states infested by tallow trees. Of the 9,966 re-measured FIA plots in...

  2. Optimization of parameters for enhanced oil recovery from enzyme treated wild apricot kernels.

    PubMed

    Rajaram, Mahatre R; Kumbhar, Baburao K; Singh, Anupama; Lohani, Umesh Chandra; Shahi, Navin C

    2012-08-01

    Present investigation was undertaken with the overall objective of optimizing the enzymatic parameters i.e. moisture content during hydrolysis, enzyme concentration, enzyme ratio and incubation period on wild apricot kernel processing for better oil extractability and increased oil recovery. Response surface methodology was adopted in the experimental design. A central composite rotatable design of four variables at five levels was chosen. The parameters and their range for the experiments were moisture content during hydrolysis (20-32%, w.b.), enzyme concentration (12-16% v/w of sample), combination of pectolytic and cellulolytic enzyme i.e. enzyme ratio (30:70-70:30) and incubation period (12-16 h). Aspergillus foetidus and Trichoderma viride was used for production of crude enzyme i.e. pectolytic and cellulolytic enzyme respectively. A complete second order model for increased oil recovery as the function of enzymatic parameters fitted the data well. The best fit model for oil recovery was also developed. The effect of various parameters on increased oil recovery was determined at linear, quadric and interaction level. The increased oil recovery ranged from 0.14 to 2.53%. The corresponding conditions for maximum oil recovery were 23% (w.b.), 15 v/w of the sample, 60:40 (pectolytic:cellulolytic), 13 h. Results of the study indicated that incubation period during enzymatic hydrolysis is the most important factor affecting oil yield followed by enzyme ratio, moisture content and enzyme concentration in the decreasing order. Enzyme ratio, incubation period and moisture content had insignificant effect on oil recovery. Second order model for increased oil recovery as a function of enzymatic hydrolysis parameters predicted the data adequately.

  3. Metabolizable energy in Chinese tallow fruit for Yellow-rumped Warblers, Northern Cardinals, and American Robins

    USGS Publications Warehouse

    Baldwin, M.J.; Barrow, W.C.; Jeske, C.; Rohwer, F.C.

    2008-01-01

    The invasive exotic Chinese tallow tree (Triadica sebifera) produces an abundant fruit crop, which is primarily bird-dispersed. The fruit pulp of tallow is lipid-rich, high in saturated fatty acids, and consumed by many bird species. Long-chained fatty acids can be difficult for many birds to digest and we investigated the ability of tallow consumers to assimilate energy in the pulp. We used the total collection method and compared apparent metabolizable energy (AME) of tallow fruit for three species of birds with differing fruit composition in their natural diets. All birds exhibited nitrogen deficits and lost body mass during the trials. Northern Cardinals (Cardinalis cardinalis) lost more mass (8.73%/day) than Yellow-rumped Warblers (Dendroica coronata) (5.29%/day) and American Robins (Turdus migratorius) (5.48%/day), and had larger nitrogen deficits (-120.1 mg N/g diet) than both species as well (-36.4 mg N/g diet and -68.9 mg N/g diet, respectively). Food intake relative to metabolic body mass was highest in Yellow-rumped Warblers (0.70 g-dry/g 0.75??day). Northern Cardinal and American Robin food intake was lower and did not differ from each other (both species: 0.13 g-dry/g 0.75??day). Nitrogen corrected values of AME were used to make species comparisons. Yellow-rumped-Warblers exhibited the highest values of AME (30.00 kJ/g), followed by American Robins (23.90 kJ/g), and Northern Cardinals (14.34 kJ/g). We suggest tallow may be an important winter food source for Yellow-rumped Warblers where their ranges overlap.

  4. Robust new NIRS coupled with multivariate methods for the detection and quantification of tallow adulteration in clarified butter samples.

    PubMed

    Mabood, Fazal; Abbas, Ghulam; Jabeen, Farah; Naureen, Zakira; Al-Harrasi, Ahmed; Hamaed, Ahmad M; Hussain, Javid; Al-Nabhani, Mahmood; Al Shukaili, Maryam S; Khan, Alamgir; Manzoor, Suryyia

    2018-03-01

    Cows' butterfat may be adulterated with animal fat materials like tallow which causes increased serum cholesterol and triglycerides levels upon consumption. There is no reliable technique to detect and quantify tallow adulteration in butter samples in a feasible way. In this study a highly sensitive near-infrared (NIR) spectroscopy combined with chemometric methods was developed to detect as well as quantify the level of tallow adulterant in clarified butter samples. For this investigation the pure clarified butter samples were intentionally adulterated with tallow at the following percentage levels: 1%, 3%, 5%, 7%, 9%, 11%, 13%, 15%, 17% and 20% (wt/wt). Altogether 99 clarified butter samples were used including nine pure samples (un-adulterated clarified butter) and 90 clarified butter samples adulterated with tallow. Each sample was analysed by using NIR spectroscopy in the reflection mode in the range 10,000-4000 cm -1 , at 2 cm -1 resolution and using the transflectance sample accessory which provided a total path length of 0.5 mm. Chemometric models including principal components analysis (PCA), partial least-squares discriminant analysis (PLSDA), and partial least-squares regressions (PLSR) were applied for statistical treatment of the obtained NIR spectral data. The PLSDA model was employed to differentiate pure butter samples from those adulterated with tallow. The employed model was then externally cross-validated by using a test set which included 30% of the total butter samples. The excellent performance of the model was proved by the low RMSEP value of 1.537% and the high correlation factor of 0.95. This newly developed method is robust, non-destructive, highly sensitive, and economical with very minor sample preparation and good ability to quantify less than 1.5% of tallow adulteration in clarified butter samples.

  5. Fish oil feeding enhances lymphocyte proliferation but impairs virus-specific T lymphocyte cytotoxicity in mice following challenge with influenza virus

    PubMed Central

    Byleveld, M; Pang, G T; Clancy, R L; Roberts, D C K

    2000-01-01

    The effect of a fish oil diet on virus-specific cytotoxicity and lymphocyte proliferation was investigated. Mice were fed fish oil (17 g fish oil and 3 g sunflower/100 g) or beef tallow (17 g tallow and 3 g sunflower/100 g) diets for 14 days before intranasal challenge with influenza virus. At day 5 after infection, lung virus-specific T lymphocyte, but not macrophage or natural killer (NK) cell, cytotoxicity was significantly lower in mice fed fish oil, while bronchial lymph node cell proliferation to virus was significantly higher. In mice fed fish oil, spleen cell proliferation to virus was also significantly higher following immunization. The results showed that, despite improved lymphocyte proliferation, fish oil impairs primary virus-specific T lymphocyte cytotoxicity. This impairment may explain the delayed virus clearance that we have previously reported in infected mice fed the fish oil diet. PMID:10632664

  6. Fish oil feeding enhances lymphocyte proliferation but impairs virus-specific T lymphocyte cytotoxicity in mice following challenge with influenza virus.

    PubMed

    Byleveld, M; Pang, G T; Clancy, R L; Roberts, D C

    2000-02-01

    The effect of a fish oil diet on virus-specific cytotoxicity and lymphocyte proliferation was investigated. Mice were fed fish oil (17 g fish oil and 3 g sunflower/100 g) or beef tallow (17 g tallow and 3 g sunflower/100 g) diets for 14 days before intranasal challenge with influenza virus. At day 5 after infection, lung virus-specific T lymphocyte, but not macrophage or natural killer (NK) cell, cytotoxicity was significantly lower in mice fed fish oil, while bronchial lymph node cell proliferation to virus was significantly higher. In mice fed fish oil, spleen cell proliferation to virus was also significantly higher following immunization. The results showed that, despite improved lymphocyte proliferation, fish oil impairs primary virus-specific T lymphocyte cytotoxicity. This impairment may explain the delayed virus clearance that we have previously reported in infected mice fed the fish oil diet.

  7. Metabolism of Some Anionic Tallow-based Detergents by Sewage Microorganisms1

    PubMed Central

    Cordon, Theone C.; Maurer, Elmer W.; Nuñez-Ponzoa, M. V.; Stirton, A. J.

    1968-01-01

    A method in which the test detergent was the sole source of carbon was used to study the metabolism of several tallow-based detergents. These were tallow alcohol sulfates, long-chain ether alcohol sulfates, and esters of α-sulfo fatty acids. Sodium p-(1-methylundecyl)benzenesulfonate (LAS) was used as a reference material. The alcohol sulfates were the most rapidly and completely metabolized (96 to 99%), and one ether alcohol sulfate was 94% degraded. The other compounds were metabolized to the extent of 61 to 87%; LAS was 80% degraded. Except for the alcohol sulfates, loss of methylene blue activity (MBAS) occurred long before the chemical oxygen demand (COD) values had reached a minimum; with the alcohol sulfates, MBAS and COD decreased simultaneously. PMID:5636472

  8. Development of Permeable Reactive Barriers (PRB) Using Edible Oils

    DTIC Science & Technology

    2008-06-01

    developed for the in-situ treatment of hazardous constituents including chlorinated solvents, perchlorate (ClO4-), chromate (CrO4-2) and oxidized... beef tallow, melted corn oil margarine, coconut oil and molasses supported the complete reductive dehalogenation of PCE to ethene in microcosms using...anaerobic bioremediation processes are being developed for the in-situ treatment of hazardous constituents including chlorinated solvents, perchlorate

  9. Kernel parameter variation-based selective ensemble support vector data description for oil spill detection on the ocean via hyperspectral imaging

    NASA Astrophysics Data System (ADS)

    Uslu, Faruk Sukru

    2017-07-01

    Oil spills on the ocean surface cause serious environmental, political, and economic problems. Therefore, these catastrophic threats to marine ecosystems require detection and monitoring. Hyperspectral sensors are powerful optical sensors used for oil spill detection with the help of detailed spectral information of materials. However, huge amounts of data in hyperspectral imaging (HSI) require fast and accurate computation methods for detection problems. Support vector data description (SVDD) is one of the most suitable methods for detection, especially for large data sets. Nevertheless, the selection of kernel parameters is one of the main problems in SVDD. This paper presents a method, inspired by ensemble learning, for improving performance of SVDD without tuning its kernel parameters. Additionally, a classifier selection technique is proposed to get more gain. The proposed approach also aims to solve the small sample size problem, which is very important for processing high-dimensional data in HSI. The algorithm is applied to two HSI data sets for detection problems. In the first HSI data set, various targets are detected; in the second HSI data set, oil spill detection in situ is realized. The experimental results demonstrate the feasibility and performance improvement of the proposed algorithm for oil spill detection problems.

  10. Generation and validation of characteristic spectra from EO1 Hyperion image data for detecting the occurrence of the invasive species, Chinese tallow

    USGS Publications Warehouse

    Ramsey, Elijah W.; Rangoonwala, A.; Nelson, G.; Ehrlich, R.; Martella, K.

    2005-01-01

    Chinese tallow (Triadica sebifera) is an invasive tree that is spreading throughout the south-eastern United States and now into the west, and in many places causing extensive change to native habitat and associated wildlife. Detecting and mapping the relative distribution of this species is important to its control and eradication. To map the relative distribution of Chinese tallow within a southwestern Louisiana coastal wetland to upland environment, Earth Observing 1 (EO1) satellite Hyperion sensor hyperspectral image data were combined with a subpixel extraction method that modelled characteristic spectra from the image data without requiring a priori characteristic spectra. Because of the low percentage occurrences of Chinese tallow and high spectral covariation in the environment, unique validation and verification methods were implemented, relying on simultaneous collection of field canopy reflectance spectra and subsequent classification of canopy compositions. The subpixel extraction method produced five characteristic spectra, which we further refined to four that adequately represented the field spectra, as well as the Hyperion imaged canopy reflectance datasets. Characteristic spectra were designated as senescing foliage, cypress-tupelo trees, and trees without leaves; shadows and green vegetation; senescing Chinese tallow with yellow leaves and yellowing foliage; and senescing Chinese tallow with red leaves ('red tallow'). About 81% (n=34) of the field and 78% (n=33) of the Hyperion imaged characteristic spectra associated with 'red tallow' were explained by the compositions generated in the field slide classifications. ?? 2005 US Government.

  11. Influence of two dietary fats on the composition of emu oil and meat.

    PubMed

    Beckerbauer, L M; Thiel-Cooper, R; Ahn, D U; Sell, J L; Parrish, F C; Beitz, D C

    2001-02-01

    Male and female emus were fed a diet rich in saturated fat (beef tallow) or a diet rich in unsaturated fat (soybean oil) until they weighed about 35 kg. Samples of subcutaneous and retroperitoneal adipose tissues and samples of six major meat cuts were taken for determination of composition. Emus fed the two different diets grew at similar rates, but the male emus had a higher percentage of carcass fat. The adipose tissue cells from males were larger than those from females. All six meat cuts averaged 2.2% fat, with the regular filet having the most and the inside and outside drums the least. Cholesterol concentration of all sizes of meat cuts averaged 32.2 mg/100 g meat. Diet did not influence cholesterol content of the rendered oil. Fan filets had the greatest concentration of cholesterol, and the inside and outside drums had the least. Source of dietary fat had no effect on fat and cholesterol content of the meats. Meat from emus fed beef tallow was more tender and juicy. Fan filets were the most tender meat, had the least intense flavor, and were the most flavorful. Untrained panelists were able to discriminate between emu meat and beef. Source of dietary fat did not influence the fatty acid compositions of the meats. As expected, the soybean oil-fed emus produced oil that was more polyunsaturated than did the tallow-fed emus.

  12. Development of integrated management practices for the control of Chinese tallow on Parris Island Marine Corps Recruit Depot

    Treesearch

    Lauren S. Pile; G. Geoff Wang; Patricia A. Layton

    2015-01-01

    Chinese tallow [Triadica sebifera (L.) Small] is an aggressive, fast-growing, highly adaptable invasive tree of the southeastern United States coastal region. Since its introduction in the early 1800s, Chinese tallow has become a serious threat to native grassland and forest communities from mid-coastal North Carolina to Northern Florida and West to Central Texas

  13. Generalized avian dispersal syndrome contributes to Chinese tallow tree (Sapium sebiferum, Euphorbiaceae) invasiveness

    USGS Publications Warehouse

    Renne, I.J.; Barrow, W.C.; Johnson, Randall L.A.; Bridges, W.C.

    2002-01-01

    Plants possessing generalized dispersal syndromes are likely to be more invasive than those relying on specialist dispersal agents. To address this issue on a local and regional scale, avian seed dispersal of the invasive alien Chinese tallow tree (Sapium sebiferum (L.) Roxb.) was assessed in forests and spoil areas of South Carolina and along forest edges in Louisiana during the 1997-99 fruiting seasons. Tallow trees in these floristically distinct habitats had a few common and many casual visitors, and considerable species overlap among habitats was found. However, bird species differed in the importance of dispersing and dropping seeds among habitats. Important dispersal agents common to forests and spoil areas of South Carolina included Northern Flicker, American Robin and Redwinged Blackbird, whereas Red-bellied Woodpecker and European Starling were important in the former and latter habitat, respectively. In Louisiana, Red-bellied Woodpecker, American Robin, Northern Cardinal and Eastern Bluebird dispersed many seeds. Nearly all species foraging on seeds were winter residents. Estimated numbers of seeds dispersed and dropped were higher in spoil areas of South Carolina than in Louisiana because of higher numbers of individuals per visit, higher seed consumption and seed dropping rates, and longer foraging durations. Within South Carolina, more seeds were dispersed and dropped in spoil areas than in forests because of higher numbers of birds per visit. These findings show that among habitats, tallow tree attracts diverse but variable coteries of dispersal agents that are qualitatively similar in seed usage patterns. We suggest that its generalized dispersal syndrome contributes to effective seed dispersal by many bird species throughout its range. Effects of differential avian use among locales may include changes in local bird communities, and differing tallow tree demographics and invasion patterns.

  14. Influence of indigenous minor components on fat crystal network of fully hydrogenated palm kernel oil and fully hydrogenated coconut oil.

    PubMed

    Chai, Xiu-Hang; Meng, Zong; Cao, Pei-Rang; Liang, Xin-Yu; Piatko, Michael; Campbell, Shawn; Koon Lo, Seong; Liu, Yuan-Fa

    2018-07-30

    Purification of triglycerides from fully hydrogenated palm kernel oil (FHPKO) and fully hydrogenated coconut oil (FHCNO) was performed by a chromatographic method. Lipid composition, thermal properties, polymorphism, isothermal crystallization behaviour, nanostructure and microstructure of FHPKO, FHPKO-triacylglycerol (TAG), FHCNO and FHCNO-TAG were evaluated. Removal of minor components had no effect on triglycerides composition. However, the presence of the minor components did increase the slip melting point and promote onset of crystallization. Furthermore, the thickness of the nanoscale crystals increased, and polymorphic transformation from β' to β occurred in FHPKO after the removal of minor components, and from α to β' in FHCNO. Sharp changes in the values of the Avrami constant K and exponent n suggested that the presence of minor components changed the crystal growth mechanism. The PLM results indicated that a coarser crystal structure with lower fractal dimension appeared after the removal of minor components from both FHPKO and FHCNO. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Utilization of wild apricot kernel press cake for extraction of protein isolate.

    PubMed

    Sharma, P C; Tilakratne, B M K S; Gupta, Anil

    2010-12-01

    The kernels of apricot (Prunus armeniaca) stones are utilized for extraction of oil. The press cake left after extraction of oil was evaluated for preparation of protein isolate for its use in food supplementation. The apricot kernels contained 45-50% oil, 23.6-26.2% protein, 4.2% ash, 5.42% crude fibre, 8.2% carbohydrates and 90 mg HCN/100 g kernels, while press cake obtained after oil extraction contained 34.5% crude protein, which can be utilized for preparation of protein isolates. The method standardized for extraction of protein isolate broadly consisted of boiling the press cake with water in 1:20 (w/v) ratio for 1 h, raising pH to 8 and stirring for a few min followed by filtration, coagulation at pH 4 prior to sieving and pressing of coagulant for overnight and drying followed by grinding which resulted in extraction of about 71.3% of the protein contained in the press cake. The protein isolate contained 68.8% protein, 6.4% crude fat, 0.8% ash, 2.2% crude fibre and 12.7% carbohydrates. Thus the apricot kernel press cake can be utilized for preparation of protein isolate to improve the nutritional status of many food formulations.

  16. 40 CFR 721.630 - Salt of a modified tallow alkylenediamine (generic).

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 30 2010-07-01 2010-07-01 false Salt of a modified tallow alkylenediamine (generic). 721.630 Section 721.630 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) TOXIC SUBSTANCES CONTROL ACT SIGNIFICANT NEW USES OF CHEMICAL SUBSTANCES Significant New Uses for Specific Chemical Substances § 721.630 Sal...

  17. Study on preparation method of Zanthoxylum bungeanum seeds kernel oil with zero trans-fatty acids.

    PubMed

    Liu, Tong; Yao, Shi-Yong; Yin, Zhong-Yi; Zheng, Xu-Xu; Shen, Yu

    2016-04-01

    The seed of Zanthoxylum bungeanum (Z. bungeanum) is a by-product of pepper production and rich in unsaturated fatty acid, cellulose, and protein. The seed oil obtained from traditional producing process by squeezing or extracting would be bad quality and could not be used as edible oil. In this paper, a new preparation method of Z. bungeanum seed kernel oil (ZSKO) was developed by comparing the advantages and disadvantages of alkali saponification-cold squeezing, alkali saponification-solvent extraction, and alkali saponification-supercritical fluid extraction with carbon dioxide (SFE-CO2). The results showed that the alkali saponification-cold squeezing could be the optimal preparation method of ZSKO, which contained the following steps: Z. bungeanum seed was pretreated by alkali saponification under the conditions of adding 10 %NaOH (w/w), solution temperature was 80 °C, and saponification reaction time was 45 min, and pretreated seed was separated by filtering, water washing, and overnight drying at 50 °C, then repeated squeezing was taken until no oil generated at 60 °C with 15 % moisture content, and ZSKO was attained finally using centrifuge. The produced ZSKO contained more than 90 % unsaturated fatty acids and no trans-fatty acids and be testified as a good edible oil with low-value level of acid and peroxide. It was demonstrated that the alkali saponification-cold squeezing process could be scaled up and applied to industrialized production of ZSKO.

  18. Straight-chain halocarbon forming fluids for TRISO fuel kernel production - Tests with yttria-stabilized zirconia microspheres

    NASA Astrophysics Data System (ADS)

    Baker, M. P.; King, J. C.; Gorman, B. P.; Braley, J. C.

    2015-03-01

    Current methods of TRISO fuel kernel production in the United States use a sol-gel process with trichloroethylene (TCE) as the forming fluid. After contact with radioactive materials, the spent TCE becomes a mixed hazardous waste, and high costs are associated with its recycling or disposal. Reducing or eliminating this mixed waste stream would not only benefit the environment, but would also enhance the economics of kernel production. Previous research yielded three candidates for testing as alternatives to TCE: 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane. This study considers the production of yttria-stabilized zirconia (YSZ) kernels in silicone oil and the three chosen alternative formation fluids, with subsequent characterization of the produced kernels and used forming fluid. Kernels formed in silicone oil and bromotetradecane were comparable to those produced by previous kernel production efforts, while those produced in chlorooctadecane and iodododecane experienced gelation issues leading to poor kernel formation and geometry.

  19. Growth pf Chinese tallow in a bottomland forest in Southern Mississippi

    Treesearch

    Nana Tian; Zhaofei Fan

    2015-01-01

    Chinese tallow tree [Triadica sebifera (L.) Small, formerly Sapium sebiferum (L.) Roxb.] is a monoecious and deciduous tree, native to central and southern China. As a nonnative invasive tree species, it has aggressively invaded forestlands in southeastern United States, particularly the low- and bottom-land forests along the coastal region of the Gulf of Mexico. This...

  20. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lynch, G.L.; Berger, L.L.; Fahey, G.C. Jr.

    Ruminant nitrogen utilization of soybean meal treated with (1) 70% ethanol at 23 or 78/sup 0/C, (2) 10% coconut oil or tallow, or (3) a combination of 70% ethanol at 78/sup 0/C and coconut oil or tallow was evaluated. Nitrogen solubility was lowest for soybean meal treated with ethanol at 78/sup 0/C, ethanol plus coconut oil and ethanol plus tallow. In situ nitrogen disappearance was lowest for soybean meal treated with ethanol at 78/sup 0/C, ethanol plus coconut oil, and ethanol plus tallow. Rates of nitrogen disappearance between 3 and 12 h were lowest for soybean meal treated with ethanolmore » at 78/sup 0/C, ethanol plus coconut oil, and ethanol plus tallow. Nitrogen retained by lambs was greater for lambs fed soybean meal treated with ethanol at 78/sup 0/C than for those fed untreated soybean meal. Ruminal ammonia 4 h post feeding was lowest for lambs fed soybean meal treated with ethanol at 78/sup 0/C, ethanol plus coconut oil, and coconut oil. These data indicate that the 78/sup 0/C ethanol treatment improved nitrogen utilization.« less

  1. Chinese tallow tree (Sapium sebiferum) utilization: characterization of extractives and cell-wall chemistry

    Treesearch

    Thomasl L. Eberhardt; Xiaobo Li; Todd F. Shupe; Chung Y. Hse

    2007-01-01

    Wood, bark, and the wax-coated seeds from Chinese tallow tree (Sapium sebiferum (L.) Roxb. syn. Triadica sebifera (L.) Small), an invasive tree species in the southeastern United States, were subjected to extractions and degradative chemical analyses in an effort to better understand the mechanism(s) by which this tree species...

  2. Predicted range expansion of Chinese tallow tree (Triadica sebifera) in forestlands of the southern United States

    Treesearch

    Hsiao-Hsuan Wang; William Grant; Todd Swannack; Jianbang Gan; William Rogers; Tomasz Koralewski; James Miller; John W. Taylor Jr.

    2011-01-01

    We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework.

  3. Production of bio-based phenolic resin and activated carbon from bio-oil and biochar derived from fast pyrolysis of palm kernel shells.

    PubMed

    Choi, Gyung-Goo; Oh, Seung-Jin; Lee, Soon-Jang; Kim, Joo-Sik

    2015-02-01

    A fraction of palm kernel shells (PKS) was pyrolyzed in a fluidized bed reactor. The experiments were performed in a temperature range of 479-555 °C to produce bio-oil, biochar, and gas. All the bio-oils were analyzed quantitatively and qualitatively by GC-FID and GC-MS. The maximum content of phenolic compounds in the bio-oil was 24.8 wt.% at ∼500 °C. The maximum phenol content in the bio-oil, as determined by the external standard method, was 8.1 wt.%. A bio-oil derived from the pyrolysis of PKS was used in the synthesis of phenolic resin, showing that the bio-oil could substitute for fossil phenol up to 25 wt.%. The biochar was activated using CO2 at a final activation temperature of 900 °C with different activation time (1-3 h) to produce activated carbon. Activated carbons produced were microporous, and the maximum surface area of the activated carbons produced was 807 m(2)/g. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. 77 FR 66832 - Notice of Receipt of Pesticide Products; Registration Applications To Register New Uses

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-07

    ..., tallow wood, tea oil plant, and vernonia). Contact: Bethany Benbow, (703) 347-8072, email address: benbow... seed, rose hip, sesame, Stokes aster, sweet rocket, tallow wood, tea oil plant, and vernonia). Contact...

  5. Risk assessment: progress of quarantine biocontrol research on Chinese Tallow, Melaleuca, and Downy Rose Myrtle

    USDA-ARS?s Scientific Manuscript database

    Risk assessments of two biocontrol candidates for Chinese tallow, Triadica sebifera (Euphoriales: Euphorbiaceae), and one for Melaleuca, Melaleuca quinquenervia (Myrtales: Myrtaceae), were conducted during 2009 and continuing into 2010 by USDA scientists located at the Florida Department of Agricul...

  6. Enzyme-catalyzed synthesis and kinetics of ultrasonic-assisted biodiesel production from waste tallow.

    PubMed

    Adewale, Peter; Dumont, Marie-Josée; Ngadi, Michael

    2015-11-01

    The use of ultrasonic processing was evaluated for its ability to achieve adequate mixing while providing sufficient activation energy for the enzymatic transesterification of waste tallow. The effects of ultrasonic parameters (amplitude, cycle and pulse) and major reaction factors (molar ratio and enzyme concentration) on the reaction kinetics of biodiesel generation from waste tallow bio-catalyzed by immobilized lipase [Candida antarctica lipase B (CALB)] were investigated. Three sets of experiments namely A, B, and C were conducted. In experiment set A, two factors (ultrasonic amplitude and cycle) were investigated at three levels; in experiment set B, two factors (molar ratio and enzyme concentration) were examined at three levels; and in experiment set C, two factors (ultrasonic amplitude and reaction time) were investigated at five levels. A Ping Pong Bi Bi kinetic model approach was employed to study the effect of ultrasonic amplitude on the enzymatic transesterification. Kinetic constants of transesterification reaction were determined at different ultrasonic amplitudes (30%, 35%, 40%, 45%, and 50%) and enzyme concentrations (4, 6, and 8 wt.% of fat) at constant molar ratio (fat:methanol); 1:6, and ultrasonic cycle; 5 Hz. Optimal conditions for ultrasound-assisted biodiesel production from waste tallow were fat:methanol molar ratio, 1:4; catalyst level 6% (w/w of fat); reaction time, 20 min (30 times less than conventional batch processes); ultrasonic amplitude 40% at 5 Hz. The kinetic model results revealed interesting features of ultrasound assisted enzyme-catalyzed transesterification (as compared to conventional system): at ultrasonic amplitude 40%, the reaction activities within the system seemed to be steady after 20 min which means the reaction could proceed with or without ultrasonic mixing. Reversed phase high performance liquid chromatography indicated the biodiesel yield to be 85.6±0.08%. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Effect of oil content and kernel processing of corn silage on digestibility and milk production by dairy cows.

    PubMed

    Weiss, W P; Wyatt, D J

    2000-02-01

    Corn silages were produced from a high oil corn hybrid and from its conventional hybrid counterpart and were harvested with a standard silage chopper or a chopper equipped with a kernel processing unit. High oil silages had higher concentrations of fatty acids (5.5 vs. 3.4% of dry matter) and crude protein (8.4 vs. 7.5% of dry matter) than the conventional hybrid. Processed silage had larger particle size than unprocessed silage, but more starch was found in small particles for processed silage. Dry matter intake was not influenced by treatment (18.4 kg/d), but yield of fat-corrected milk (23.9 vs. 22.6 kg/d) was increased by feeding high oil silage. Overall, processing corn silage did not affect milk production, but cows fed processed conventional silage tended to produce more milk than did cows fed unprocessed conventional silage. Milk protein percent, but not yield, was reduced with high oil silage. Milk fat percent, but not yield, was higher with processed silage. Overall, processed silage had higher starch digestibility, but the response was much greater for the conventional silage hybrid. The concentration of total digestible nutrients (TDN) tended to be higher for diets with high oil silage (71.6 vs. 69.9%) and tended to be higher for processed silage than unprocessed silage (71.7 vs. 69.8%), but an interaction between variety and processing was observed. Processing conventional corn silage increased TDN to values similar to high oil corn silage but processing high oil corn silage did not influence TDN.

  8. Invasibility of major forest types by non-native Chinese tallow in East Texas

    Treesearch

    Zhaofei Fan

    2015-01-01

    Non-native invasive Chinese tallow trees [Triadica sebifera (L.) Small,formerly Sapium sebiferum (L.) Roxb.] are rapidly spreading into natural ecosystems such as forests in the southeastern United States. Using the 2001-2010 USDA Forest Service’s Forest Inventory and Analysis (FIA) data and forest land cover data, we estimated the regional invasibility of major forest...

  9. In-situ transesterification of seeds of invasive Chinese tallow trees (Triadica sebifera L.) in a microwave batch system (GREEN(3)) using hexane as co-solvent: Biodiesel production and process optimization.

    PubMed

    Barekati-Goudarzi, Mohamad; Boldor, Dorin; Nde, Divine B

    2016-02-01

    In-situ transesterification (simultaneous extraction and transesterification) of Chinese tallow tree seeds into methyl esters using a batch microwave system was investigated in this study. A high degree of oil extraction and efficient conversion of oil to biodiesel were found in the proposed range. The process was further optimized in terms of product yields and conversion rates using Doehlert optimization methodology. Based on the experimental results and statistical analysis, the optimal production yield conditions for this process were determined as: catalyst concentration of 1.74wt.%, solvent ratio about 3 (v/w), reaction time of 20min and temperature of 58.1°C. H(+)NMR was used to calculate reaction conversion. All methyl esters produced using this method met ASTM biodiesel quality specifications. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Analysis Monthly Import of Palm Oil Products Using Box-Jenkins Model

    NASA Astrophysics Data System (ADS)

    Ahmad, Nurul F. Y.; Khalid, Kamil; Saifullah Rusiman, Mohd; Ghazali Kamardan, M.; Roslan, Rozaini; Che-Him, Norziha

    2018-04-01

    The palm oil industry has been an important component of the national economy especially the agriculture sector. The aim of this study is to identify the pattern of import of palm oil products, to model the time series using Box-Jenkins model and to forecast the monthly import of palm oil products. The method approach is included in the statistical test for verifying the equivalence model and statistical measurement of three models, namely Autoregressive (AR) model, Moving Average (MA) model and Autoregressive Moving Average (ARMA) model. The model identification of all product import palm oil is different in which the AR(1) was found to be the best model for product import palm oil while MA(3) was found to be the best model for products import palm kernel oil. For the palm kernel, MA(4) was found to be the best model. The results forecast for the next four months for products import palm oil, palm kernel oil and palm kernel showed the most significant decrease compared to the actual data.

  11. Moisture Sorption Isotherms and Properties of Sorbed Water of Neem ( Azadirichta indica A. Juss) Kernels

    NASA Astrophysics Data System (ADS)

    Ngono Mbarga, M. C.; Bup Nde, D.; Mohagir, A.; Kapseu, C.; Elambo Nkeng, G.

    2017-01-01

    A neem tree growing abundantly in India as well as in some regions of Asia and Africa gives fruits whose kernels have about 40-50% oil. This oil has high therapeutic and cosmetic qualities and is recently projected to be an important raw material for the production of biodiesel. Its seed is harvested at high moisture contents, which leads tohigh post-harvest losses. In the paper, the sorption isotherms are determined by the static gravimetric method at 40, 50, and 60°C to establish a database useful in defining drying and storage conditions of neem kernels. Five different equations are validated for modeling the sorption isotherms of neem kernels. The properties of sorbed water, such as the monolayer moisture content, surface area of adsorbent, number of adsorbed monolayers, and the percent of bound water are also defined. The critical moisture content necessary for the safe storage of dried neem kernels is shown to range from 5 to 10% dry basis, which can be obtained at a relative humidity less than 65%. The isosteric heats of sorption at 5% moisture content are 7.40 and 22.5 kJ/kg for the adsorption and desorption processes, respectively. This work is the first, to the best of our knowledge, to give the important parameters necessary for drying and storage of neem kernels, a potential raw material for the production of oil to be used in pharmaceutics, cosmetics, and biodiesel manufacturing.

  12. Antidiarrhoeal efficacy of Mangifera indica seed kernel on Swiss albino mice.

    PubMed

    Rajan, S; Suganya, H; Thirunalasundari, T; Jeeva, S

    2012-08-01

    To examine the antidiarrhoeal activity of alcoholic and aqueous seed kernel extract of Mangifera indica (M. indica) on castor oil-induced diarrhoeal activity in Swiss albino mice. Mango seed kernels were processed and extracted using alcohol and water. Antidiarrhoeal activity of the extracts were assessed using intestinal motility and faecal score methods. Aqueous and alcoholic extracts of M. indica significantly reduced intestinal motility and faecal score in Swiss albino mice. The present study shows the traditional claim on the use of M. indica seed kernel for treating diarrhoea in Southern parts of India. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

  13. Effects of Chinese tallow leaf litter on water chemistry and surfacing behaviour of anuran larvae

    Treesearch

    Daniel Saenz; Cory K. Adams

    2017-01-01

    The establishment of exotic invasive species, including plants, has been linked to the decline of some amphibian populations. Of particular concern with invasive plants, from an amphibian conservation perspective, is that they are disproportionately wetland or riparian species. Recent evidence suggests that Chinese tallow (Triadica sebifera), an...

  14. Effect of dietary fat source on lipoprotein composition and plasma lipid concentrations in pigs.

    PubMed

    Faidley, T D; Luhman, C M; Galloway, S T; Foley, M K; Beitz, D C

    1990-10-01

    Most studies of the effects of dietary fat sources on plasma lipid components have used diets with extreme fat compositions; the current study was designed to more nearly mimic human dietary fat intake. Young growing pigs were fed diets containing either 20 or 40% of energy as soy oil, beef tallow or a 50/50 blend of soy oil and tallow. Different dietary fats did not affect concentrations of cholesterol, triacylglycerol or protein in plasma or major lipoprotein fractions. The concentration of phospholipid was less in plasma and in very low density lipoproteins with soy oil feeding than with tallow feeding. The weight percentage of cholesteryl ester in the low density lipoprotein fraction tended to be greater with 40% than with 20% tallow and tended to be less with 40% than with 20% soy oil. Phospholipid as a weight percentage of low density lipoprotein was least in pigs fed soy oil. Tallow feeding increased the percentage of myristic, palmitic, palmitoleic and oleic acids in plasma, relative to both other groups. Soy oil feeding increased the percentage of linoleic and linolenic acids. These moderate diets were not hypercholesterolemic, but they did alter plasma fatty acid composition and phospholipid concentrations in plasma and very low density lipoprotein.

  15. Fast pyrolysis of palm kernel shells: influence of operation parameters on the bio-oil yield and the yield of phenol and phenolic compounds.

    PubMed

    Kim, Seon-Jin; Jung, Su-Hwa; Kim, Joo-Sik

    2010-12-01

    Palm kernel shells were pyrolyzed in a pyrolysis plant equipped with a fluidized-bed reactor and a char-separation system. The influence of reaction temperature, feed size and feed rate on the product spectrum was also investigated. In addition, the effect of reaction temperature on the yields of phenol and phenolic compounds in the bio-oil was examined. The maximum bio-oil yield was 48.7 wt.% of the product at 490 degrees C. The maximum yield of phenol plus phenolic compounds amounted to about 70 area percentage at 475 degrees C. The yield of pyrolytic lignin after its isolation from the bio-oil was approximately 46 wt.% based on the water and ash free oil. The pyrolytic lignin was mainly composed of phenol, phenolic compounds and oligomers of coniferyl, sinapyl and p-coumaryl alcohols. From the result of a GPC analysis, the number average molecular weight and the weight average molecular weight were 325 and 463 g/mol, respectively. 2010 Elsevier Ltd. All rights reserved.

  16. Porcine peroxisome proliferator-activated receptor delta mediates the lipolytic effects of dietary fish oil to reduce body fat deposition.

    PubMed

    Yu, Y H; Wang, P H; Cheng, W T K; Mersmann, H J; Wu, S C; Ding, S T

    2010-06-01

    Peroxisome proliferator-activated receptor delta promotes fatty acid catabolism and energy expenditure in skeletal muscle and adipose tissues. A ligand for PPARdelta is required to activate PPARdelta function. Polyunsaturated fatty acids are potential ligands for PPARdelta activation. The current experiment was designed to determine the potential for PUFA, particularly from dietary fish oil, to activate porcine PPARdelta in vivo. Transgenic mice were generated to overexpress porcine PPARdelta in the adipose tissue. Mice were fed a high-saturated fat (13% beef tallow), or high-unsaturated fat (13% fish oil) diet, or a diet containing 4 mg/kg of a PPARdelta ligand (L165041) for 4 mo. Compared with beef tallow feeding, fish oil feeding reduced fat mass and decreased (P < 0.05) plasma triacylglycerol and FFA concentrations in the transgenic mice. Adipose tissue expression of genes involved in adipogenesis (i.e., lipoprotein lipase and adipocyte fatty acid-binding protein) was decreased in transgenic mice fed fish oil or the PPARdelta ligand. In the same mice, expression of the lipolytic gene, hormone-sensitive lipase was increased (P < 0.05). Fish oil feeding also stimulated expression of genes participating in fatty acid oxidation in the liver of transgenic mice compared with wild-type mice. Overall, these results indicate that PUFA may serve as natural and effective regulators of lipid catabolism in vivo and many of these effects may be generated from activation of PPARdelta.

  17. Chinese Tallow (Triadica sebifera (L.) Small) Population expansion in Louisiana, East Texas, and Mississippi

    Treesearch

    Sonja N. Oswalt

    2010-01-01

    Chinese tallow (Triadica sebifera) is a nonnative invasive species with high fecundity rates that has naturalized from the coastal prairies of east Texas along the Gulf and Atlantic coasts as far north as North Carolina. Population differences were computed for two forest inventory periods (mid-1990s and late 2000s) in Louisiana, east Texas, and Mississippi using data...

  18. Biosynthesis and characterization of polyhydroxyalkanoate containing high 3-hydroxyhexanoate monomer fraction from crude palm kernel oil by recombinant Cupriavidus necator.

    PubMed

    Wong, Yoke-Ming; Brigham, Christopher J; Rha, ChoKyun; Sinskey, Anthony J; Sudesh, Kumar

    2012-10-01

    The potential of plant oils as sole carbon sources for production of P(3HB-co-3HHx) copolymer containing a high 3HHx monomer fraction using the recombinant Cupriavidus necator strain Re2160/pCB113 has been investigated. Various types and concentrations of plant oils were evaluated for efficient conversion of P(3HB-co-3HHx) copolymer. Crude palm kernel oil (CPKO) at a concentration of 2.5 g/L was found to be most suitable for production of copolymer with a 3HHx content of approximately 70 mol%. The time profile of these cells was also examined in order to study the trend of 3HHx monomer incorporation, PHA production and PHA synthase activity. (1)H NMR and (13)C NMR analyses confirmed the presence of P(3HB-co-3HHx) copolymer containing a high 3HHx monomer fraction, in which monomers were not randomly distributed. The results of various characterization analyses revealed that the copolymers containing a high 3HHx monomer fraction demonstrated soft and flexible mechanical properties. Copyright © 2012 Elsevier Ltd. All rights reserved.

  19. Applications of supercritical fluid extraction (SFE) of palm oil and oil from natural sources.

    PubMed

    Akanda, Mohammed Jahurul Haque; Sarker, Mohammed Zaidul Islam; Ferdosh, Sahena; Manap, Mohd Yazid Abdul; Ab Rahman, Nik Norulaini Nik; Ab Kadir, Mohd Omar

    2012-02-10

    Supercritical fluid extraction (SFE), which has received much interest in its use and further development for industrial applications, is a method that offers some advantages over conventional methods, especially for the palm oil industry. SC-CO₂ refers to supercritical fluid extraction (SFE) that uses carbon dioxide (CO₂) as a solvent which is a nontoxic, inexpensive, nonflammable, and nonpolluting supercritical fluid solvent for the extraction of natural products. Almost 100% oil can be extracted and it is regarded as safe, with organic solvent-free extracts having superior organoleptic profiles. The palm oil industry is one of the major industries in Malaysia that provides a major contribution to the national income. Malaysia is the second largest palm oil and palm kernel oil producer in the World. This paper reviews advances in applications of supercritical carbon dioxide (SC-CO₂) extraction of oils from natural sources, in particular palm oil, minor constituents in palm oil, producing fractionated, refined, bleached, and deodorized palm oil, palm kernel oil and purified fatty acid fractions commendable for downstream uses as in toiletries and confectionaries.

  20. Thermophysical characterization of the seeds of invasive Chinese tallow tree: importance for biofuel production.

    PubMed

    Picou, Laura; Boldor, Doran

    2012-10-16

    The limited supply of traditional fossil based fuels, and increased concern about their environmental impact has driven the interest in the utilization of biomass based energy sources, including those that are underutilized or otherwise nuisance species such as Chinese tallow trees (Triadica sebifera [L.]). This species is a prolific seeds producer, and this paper shows that they contain more than 50% lipids by mass that are suitable for conversion into biodiesel. We present here, for the first time, the seeds' thermophysical properties important for biofuel production. The seeds were characterized using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and ultimate analysis; their thermal conductivity, thermal diffusivity, and specific heat were determined. The characterization results were correlated to fatty acid composition and lipid content for whole seeds and individual layers, as well as to the protein, hemicellulose, cellulose, and lignin content. The TGA analysis indicated the presence, in addition to lipids, of hemicellulose, cellulose, lignin, and proteins, depending on the layer analyzed. Thermal conductivity and specific heat were, respectively 0.14 ± 0.007 W/mK and 3843.5 ± 171.16 J/kgK for wax, 0.20 ± 0.002 W/mK and 2018.7 ± 5.18 J/kgK for shells, 0.13 ± 0.0 W/mK and 1237 ± 3.15 J/kgK for internal kernel, and 0.13 ± 0.000 W/mK and 2833.9 ± 104.11 J/kgK for whole seeds. These properties and characterization method can be further used in engineering analysis used to determine the most optimum processing method for production of biofuels from this feedstock.

  1. Managing an established tree invader: developing control methods for Chinese tallow (Triadica sebifera) in maritime forests

    Treesearch

    Lauren S. Pile; G. Geoff Wang; Thomas A. Waldrop; Joan L. Walker; William C. Bridges; Patricia A. Layton

    2017-01-01

    Biological invasions by woody species in forested ecosystems can have significant impacts on forest management and conservation. We designed and tested several management options based on the physiology of Chinese tallow (Triadica sebifera [L.] Small). Specifically, we tested four treatments, including mastication, foliar herbicide, and fire (MH...

  2. Synergistic effects of the invasive Chinese tallow (Triadica sebifera) and climate change on aquatic amphibian survival

    PubMed Central

    Saenz, Daniel; Fucik, Erin M; Kwiatkowski, Matthew A

    2013-01-01

    Changes in climate and the introduction of invasive species are two major stressors to amphibians, although little is known about the interaction between these two factors with regard to impacts on amphibians. We focused our study on an invasive tree species, the Chinese tallow (Triadica sebifera), that annually sheds its leaves and produces leaf litter that is known to negatively impact aquatic amphibian survival. The purpose of our research was to determine whether the timing of leaf fall from Chinese tallow and the timing of amphibian breeding (determined by weather) influence survival of amphibian larvae. We simulated a range of winter weather scenarios, ranging from cold to warm, by altering the relative timing of when leaf litter and amphibian larvae were introduced into aquatic mesocosms. Our results indicate that amphibian larvae survival was greatly affected by the length of time Chinese tallow leaf litter decomposes in water prior to the introduction of the larvae. Larvae in treatments simulating warm winters (early amphibian breeding) were introduced to the mesocosms early in the aquatic decomposition process of the leaf litter and had significantly lower survival compared with cold winters (late amphibian breeding), likely due to significantly lower dissolved oxygen levels. Shifts to earlier breeding phenology, linked to warming climate, have already been observed in many amphibian taxa, and with most climate models predicting a significant warming trend over the next century, the trend toward earlier breeding should continue if not increase. Our results strongly suggest that a warming climate can interact with the effects of invasive plant species, in ways we have not previously considered, to reduce the survival of an already declining group of organisms. PMID:24363907

  3. Synergistic effects of the invasive Chinese tallow (Triadica sebifera) and climate change on aquatic amphibian survival.

    PubMed

    Saenz, Daniel; Fucik, Erin M; Kwiatkowski, Matthew A

    2013-11-01

    Changes in climate and the introduction of invasive species are two major stressors to amphibians, although little is known about the interaction between these two factors with regard to impacts on amphibians. We focused our study on an invasive tree species, the Chinese tallow (Triadica sebifera), that annually sheds its leaves and produces leaf litter that is known to negatively impact aquatic amphibian survival. The purpose of our research was to determine whether the timing of leaf fall from Chinese tallow and the timing of amphibian breeding (determined by weather) influence survival of amphibian larvae. We simulated a range of winter weather scenarios, ranging from cold to warm, by altering the relative timing of when leaf litter and amphibian larvae were introduced into aquatic mesocosms. Our results indicate that amphibian larvae survival was greatly affected by the length of time Chinese tallow leaf litter decomposes in water prior to the introduction of the larvae. Larvae in treatments simulating warm winters (early amphibian breeding) were introduced to the mesocosms early in the aquatic decomposition process of the leaf litter and had significantly lower survival compared with cold winters (late amphibian breeding), likely due to significantly lower dissolved oxygen levels. Shifts to earlier breeding phenology, linked to warming climate, have already been observed in many amphibian taxa, and with most climate models predicting a significant warming trend over the next century, the trend toward earlier breeding should continue if not increase. Our results strongly suggest that a warming climate can interact with the effects of invasive plant species, in ways we have not previously considered, to reduce the survival of an already declining group of organisms.

  4. Fouling mechanism in ultrafiltration of vegetable oil

    NASA Astrophysics Data System (ADS)

    Ariono, D.; Wardani, A. K.; Widodo, S.; Aryanti, Putu T. P.; Wenten, I. G.

    2018-03-01

    Energy efficient and cost-effective separation of impurities from vegetable oil is a great challenge for vegetable oil processing. Several technologies have been developed, including pressurized membrane, chemical treatment, and chemical free separation methods. Among those technologies, ultrafiltration membrane is one of the most attractive processes with low operating pressure and temperature. In this work, hydrophobic polypropylene ultrafiltration membrane was used to remove impurities such as non-dissolved solids from palm kernel oil. Unfortunately, the hydrophobicity of polypropylene membrane leads to significant impact on the reduction of permeate flux due to membrane fouling. This fouling is associated with the accumulation of substances on the membrane surface or within the membrane pores. For better understanding, fouling mechanism that occurred during palm kernel oil ultrafiltration using hydrophobic polypropylene membrane was investigated. The effect of trans-membrane pressure and feed temperature on fouling mechanism was also studied. The result showed that cake formation became the dominant fouling mechanism up to 50 min operation of palm kernel oil ultrafiltration. Furthermore, the fouling mechanism was not affected by the increase of trans-membrane pressure and feed temperature.

  5. 9 CFR 315.1 - Carcasses and parts passed for cooking; rendering into lard or tallow.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 9 Animals and Animal Products 2 2010-01-01 2010-01-01 false Carcasses and parts passed for cooking... PARTS PASSED FOR COOKING § 315.1 Carcasses and parts passed for cooking; rendering into lard or tallow. Carcasses and parts passed for cooking may be rendered into lard in accordance with § 319.702 of this...

  6. Genetic, Genomic, and Breeding Approaches to Further Explore Kernel Composition Traits and Grain Yield in Maize

    ERIC Educational Resources Information Center

    Da Silva, Helena Sofia Pereira

    2009-01-01

    Maize ("Zea mays L.") is a model species well suited for the dissection of complex traits which are often of commercial value. The purpose of this research was to gain a deeper understanding of the genetic control of maize kernel composition traits starch, protein, and oil concentration, and also kernel weight and grain yield. Germplasm with…

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

    PubMed Central

    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

  8. Effects of an invasive plant, Chinese tallow (Triadica sebifera), on development and survival of anuran larvae

    Treesearch

    Taylor B. Cotten; Matthew A. Kwiatkowski; Daniel Saenz; Michael Collyer

    2012-01-01

    Amphibians are considered one of the most threatened vertebrate groups. Although numerous studies have addressed the many causes of amphibian population decline, little is known about effects of invasive plants. Chinese tallow (Triadica sebifera) is an exotic deciduous tree that has invaded the southeastern United States. Amphibian larvae in environments invaded by T....

  9. Characteristics and composition of watermelon, pumpkin, and paprika seed oils and flours.

    PubMed

    El-Adawy, T A; Taha, K M

    2001-03-01

    The nutritional quality and functional properties of paprika seed flour and seed kernel flours of pumpkin and watermelon were studied, as were the characteristics and structure of their seed oils. Paprika seed and seed kernels of pumpkin and watermelon were rich in oil and protein. All flour samples contained considerable amounts of P, K, Mg, Mn, and Ca. Paprika seed flour was superior to watermelon and pumpkin seed kernel flours in content of lysine and total essential amino acids. Oil samples had high amounts of unsaturated fatty acids with linoleic and oleic acids as the major acids. All oil samples fractionated into seven classes including triglycerides as a major lipid class. Data obtained for the oils' characteristics compare well with those of other edible oils. Antinutritional compounds such as stachyose, raffinose, verbascose, trypsin inhibitor, phytic acid, and tannins were detected in all flours. Pumpkin seed kernel flour had higher values of chemical score, essential amino acid index, and in vitro protein digestibility than the other flours examined. The first limiting amino acid was lysine for both watermelon and pumpkin seed kernel flours, but it was leucine in paprika seed flour. Protein solubility index, water and fat absorption capacities, emulsification properties, and foam stability were excellent in watermelon and pumpkin seed kernel flours and fairly good in paprika seed flour. Flour samples could be potentially added to food systems such as bakery products and ground meat formulations not only as a nutrient supplement but also as a functional agent in these formulations.

  10. Fish oil feeding delays influenza virus clearance and impairs production of interferon-gamma and virus-specific immunoglobulin A in the lungs of mice.

    PubMed

    Byleveld, P M; Pang, G T; Clancy, R L; Roberts, D C

    1999-02-01

    Ingestion of fish oil can suppress the inflammatory response to injury and may impair host resistance to infection. To investigate the effect of a diet containing fish oil on immunity to viral infection, 148 BALB/c mice were fed diets containing 3 g/100 g of sunflower oil with either 17 g/100 g of fish oil or beef tallow for 14 d before intranasal challenge with live influenza virus. At d 1 and d 5 after infection, the mice fed fish oil had higher lung viral load and lower body weight (P < 0.05). In addition to the greater viral load and weight loss at d 5 after infection, the fish oil group consumed less food (P < 0.05) while the beef tallow group was clearing the virus, had regained their preinfection weights and was returning to their preinfection food consumption. The fish oil group had impaired production of lung interferon-gamma (IFN-gamma), serum immunoglobulin (Ig) G and lung IgA-specific antibodies (all P < 0. 05) although lung IFN-alpha/beta and the relative proportions of bronchial lymph node CD4+ and CD8+ T lymphocytes did not differ between groups after infection. The present study demonstrates a delay in virus clearance in mice fed fish oil associated with reduced IFN-gamma and antibody production and a greater weight loss and suppression of appetite following influenza virus infection. However, differences observed during the course of infection did not affect the ultimate outcome as both groups cleared the virus and returned to preinfection food consumption and body weight by d 7.

  11. Synergistic effects of the invasive Chinese tallow (Triadica sebifera) and climate change on aquatic amphibian survival

    Treesearch

    Daniel Saenz; Erin M. Fucik; Matthew A. Kwiatkowski

    2013-01-01

    Changes in climate and the introduction of invasive species are two major stressors to amphibians, although little is known about the interaction between these two factors with regard to impacts on amphibians. We focused our study on an invasive tree species, the Chinese tallow (Triadica sebifera), that annually sheds its leaves and produces leaf...

  12. Carbon partitioning between oil and carbohydrates in developing oat (Avena sativa L.) seeds.

    PubMed

    Ekman, Asa; Hayden, Daniel M; Dehesh, Katayoon; Bülow, Leif; Stymne, Sten

    2008-01-01

    Cereals accumulate starch in the endosperm as their major energy reserve in the grain. In most cereals the embryo, scutellum, and aleurone layer are high in oil, but these tissues constitute a very small part of the total seed weight. However, in oat (Avena sativa L.) most of the oil in kernels is deposited in the same endosperm cells that accumulate starch. Thus oat endosperm is a desirable model system to study the metabolic switches responsible for carbon partitioning between oil and starch synthesis. A prerequisite for such investigations is the development of an experimental system for oat that allows for metabolic flux analysis using stable and radioactive isotope labelling. An in vitro liquid culture system, developed for detached oat panicles and optimized to mimic kernel composition during different developmental stages in planta, is presented here. This system was subsequently used in analyses of carbon partitioning between lipids and carbohydrates by the administration of 14C-labelled sucrose to two cultivars having different amounts of kernel oil. The data presented in this study clearly show that a higher amount of oil in the high-oil cultivar compared with the medium-oil cultivar was due to a higher proportion of carbon partitioning into oil during seed filling, predominantly at the earlier stages of kernel development.

  13. Chinese tallow (Triadica sebifera) invasion in maritime forests: the role of anthropogenic disturbance and its management implication

    Treesearch

    Lauren S. Pile; G. Geoff Wang; Benjamin O. Knapp; Joan L. Walker; Michael C. Stambaugh

    2017-01-01

    Land-use and forest management practices may facilitate the invasion success of non-native plants in forests. In this study, we tested if agricultural land abandonment and subsequent forest management contributed to the invasion success of Chinese tallow (Triadica sebifera (L.) Small) in the maritime forest of Parris Island, SC. We compared the...

  14. The Genetic Architecture of Response to Long-Term Artificial Selection for Oil Concentration in the Maize Kernel

    PubMed Central

    Laurie, Cathy C.; Chasalow, Scott D.; LeDeaux, John R.; McCarroll, Robert; Bush, David; Hauge, Brian; Lai, Chaoqiang; Clark, Darryl; Rocheford, Torbert R.; Dudley, John W.

    2004-01-01

    In one of the longest-running experiments in biology, researchers at the University of Illinois have selected for altered composition of the maize kernel since 1896. Here we use an association study to infer the genetic basis of dramatic changes that occurred in response to selection for changes in oil concentration. The study population was produced by a cross between the high- and low-selection lines at generation 70, followed by 10 generations of random mating and the derivation of 500 lines by selfing. These lines were genotyped for 488 genetic markers and the oil concentration was evaluated in replicated field trials. Three methods of analysis were tested in simulations for ability to detect quantitative trait loci (QTL). The most effective method was model selection in multiple regression. This method detected ∼50 QTL accounting for ∼50% of the genetic variance, suggesting that >50 QTL are involved. The QTL effect estimates are small and largely additive. About 20% of the QTL have negative effects (i.e., not predicted by the parental difference), which is consistent with hitchhiking and small population size during selection. The large number of QTL detected accounts for the smooth and sustained response to selection throughout the twentieth century. PMID:15611182

  15. Visualization of Oil Body Distribution in Jatropha curcas L. by Four-Wave Mixing Microscopy

    NASA Astrophysics Data System (ADS)

    Ishii, Makiko; Uchiyama, Susumu; Ozeki, Yasuyuki; Kajiyama, Sin'ichiro; Itoh, Kazuyoshi; Fukui, Kiichi

    2013-06-01

    Jatropha curcas L. (jatropha) is a superior oil crop for biofuel production. To improve the oil yield of jatropha by breeding, the development of effective and reliable tools to evaluate the oil production efficiency is essential. The characteristics of the jatropha kernel, which contains a large amount of oil, are not fully understood yet. Here, we demonstrate the application of four-wave mixing (FWM) microscopy to visualize the distribution of oil bodies in a jatropha kernel without staining. FWM microscopy enables us to visualize the size and morphology of oil bodies and to determine the oil content in the kernel to be 33.2%. The signal obtained from FWM microscopy comprises both of stimulated parametric emission (SPE) and coherent anti-Stokes Raman scattering (CARS) signals. In the present situation, where a very short pump pulse is employed, the SPE signal is believed to dominate the FWM signal.

  16. Integrating spread dynamics and economics of timber production to manage Chinese Tallow invasions in southern U.S

    Treesearch

    Hsiao-Hsuan Wang; William E. Grant; Jianbang Gan; William E. Rogers; Todd M. Swannack; Tomasz E. Koralewski; James H. Miller; John W. Taylor

    2012-01-01

    Economic costs associated with the invasion of nonnative species are of global concern. We estimated expected costs of Chinese tallow (Triadica sebifera (L.) Small) invasions related to timber production in southern U.S. forestlands under different management strategies. Expected costs were confined to the value of timber production losses plus costs for search and...

  17. Life Cycle Assessment for the Production of Oil Palm Seeds.

    PubMed

    Muhamad, Halimah; Ai, Tan Yew; Khairuddin, Nik Sasha Khatrina; Amiruddin, Mohd Din; May, Choo Yuen

    2014-12-01

    The oil palm seed production unit that generates germinated oil palm seeds is the first link in the palm oil supply chain, followed by the nursery to produce seedling, the plantation to produce fresh fruit bunches (FFB), the mill to produce crude palm oil (CPO) and palm kernel, the kernel crushers to produce crude palm kernel oil (CPKO), the refinery to produce refined palm oil (RPO) and finally the palm biodiesel plant to produce palm biodiesel. This assessment aims to investigate the life cycle assessment (LCA) of germinated oil palm seeds and the use of LCA to identify the stage/s in the production of germinated oil palm seeds that could contribute to the environmental load. The method for the life cycle impact assessment (LCIA) is modelled using SimaPro version 7, (System for Integrated environMental Assessment of PROducts), an internationally established tool used by LCA practitioners. This software contains European and US databases on a number of materials in addition to a variety of European- and US-developed impact assessment methodologies. LCA was successfully conducted for five seed production units and it was found that the environmental impact for the production of germinated oil palm was not significant. The characterised results of the LCIA for the production of 1000 germinated oil palm seeds showed that fossil fuel was the major impact category followed by respiratory inorganics and climate change.

  18. Kernel Abortion in Maize 1

    PubMed Central

    Hanft, Jonathan M.; Jones, Robert J.

    1986-01-01

    Kernels cultured in vitro were induced to abort by high temperature (35°C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35°C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth. PMID:16664846

  19. Approximate kernel competitive learning.

    PubMed

    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.

  20. Effect of the inclusion time of dietary saturated and unsaturated fats before slaughter on the accumulation and composition of abdominal fat in female broiler chickens.

    PubMed

    Sanz, M; Lopez-Bote, C J; Flores, A; Carmona, J M

    2000-09-01

    The aim of this experiment was to assess the effects of four different feeding programs designed to include tallow, a saturated fat at 0, 8, 12, and 28 d prior to slaughter on female broiler performance and the deposition, fatty acid profile, and melting point of abdominal fat. The following treatment groups were established according to dietary inclusion--from 21 to 49 d of age--of: sunflower oil (SUN), sunflower oil followed by tallow during the last 8 d (SUN + 8TALL), sunflower oil followed by tallow during the last 12 d (SUN + 12TALL), and tallow (TALL). The diets were designed to be isoenergetic and isonitrogenous. Abdominal fat deposition increased linearly with increasing number of days in which birds were fed the tallow-enriched diet. However, linear and quadratic response patterns were found between days before slaughter in which the birds were fed the tallow-enriched diet and abdominal fat melting points. This result suggested an exponential response in which 85% of the maximum level was already attained when the dietary fat type changed from an unsaturated to a saturated condition during the last 8 d of the feeding period. The use of an unsaturated fat source during the first stages of growth, and the substitution of a saturated fat for a few days before slaughter, may offer the advantage of lower abdominal fat deposition and an acceptable fat fluidity compared with the use of a saturated fat source during the whole growing and finishing period.

  1. Pre-release assessment of Gadirtha inexacta a proposed biological control agent of Chinese tallow (Triadica sebifera) in the United States

    USDA-ARS?s Scientific Manuscript database

    Native to China, Chinese tallow, Triadica sebifera (Euphorbiaceae) is an aggressive woody invader in the southeastern United States. The noctuid, Gadirtha inexacta, is a multivoltine herbivore attacking this plant in China. To evaluate its potential as a biological control agent in the United States...

  2. Classification With Truncated Distance Kernel.

    PubMed

    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.

  3. Life Cycle Assessment for the Production of Oil Palm Seeds

    PubMed Central

    Muhamad, Halimah; Ai, Tan Yew; Khairuddin, Nik Sasha Khatrina; Amiruddin, Mohd Din; May, Choo Yuen

    2014-01-01

    The oil palm seed production unit that generates germinated oil palm seeds is the first link in the palm oil supply chain, followed by the nursery to produce seedling, the plantation to produce fresh fruit bunches (FFB), the mill to produce crude palm oil (CPO) and palm kernel, the kernel crushers to produce crude palm kernel oil (CPKO), the refinery to produce refined palm oil (RPO) and finally the palm biodiesel plant to produce palm biodiesel. This assessment aims to investigate the life cycle assessment (LCA) of germinated oil palm seeds and the use of LCA to identify the stage/s in the production of germinated oil palm seeds that could contribute to the environmental load. The method for the life cycle impact assessment (LCIA) is modelled using SimaPro version 7, (System for Integrated environMental Assessment of PROducts), an internationally established tool used by LCA practitioners. This software contains European and US databases on a number of materials in addition to a variety of European- and US-developed impact assessment methodologies. LCA was successfully conducted for five seed production units and it was found that the environmental impact for the production of germinated oil palm was not significant. The characterised results of the LCIA for the production of 1000 germinated oil palm seeds showed that fossil fuel was the major impact category followed by respiratory inorganics and climate change. PMID:27073598

  4. Physico-chemical properties of Moringa oleifera seed oil enzymatically interesterified with palm stearin and palm kernel oil and its potential application in food.

    PubMed

    Dollah, Sarafhana; Abdulkarim, Sabo Mohammed; Ahmad, Siti Hajar; Khoramnia, Anahita; Mohd Ghazali, Hasanah

    2016-08-01

    High oleic acid Moringa oleifera seed oil (MoO) has been rarely applied in food products due to the low melting point and lack of plasticity. Enzymatic interesterification (EIE) of MoO with palm stearin (PS) and palm kernel oil (PKO) could yield harder fat stocks that may impart desirable nutritional and physical properties. Blends of MoO and PS or PKO were examined for triacylglycerol (TAG) composition, thermal properties and solid fat content (SFC). EIE caused rearrangement of TAGs, reduction of U3 and increase of U2 S in MoO/PS blends while reduction of U3 and S3 following increase of S2 U and U2 S in MoO/PKO blends (U, unsaturated and S, saturated fatty acids). SFC measurements revealed a wide range of plasticity, enhancements of spreadability, mouthfeel and cooling effect for interesterified MoO/PS, indicating the possible application of these blends in margarines. However, interesterified MoO/PKO was not suitable in margarine application, while ice-cream may be formulated from these blends. A soft margarine formulated from MoO/PS 70:30 revealed high oxidative stability during 8 weeks storage with no significant changes in peroxide and p-anisidine values. EIE of fats with MoO allowed nutritional and oxidative stable plastic fats to be obtained, suitable for possible use in industrial food applications. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  5. Fatty acids and bioactive compounds of the pulps and kernels of Brazilian palm species, guariroba (Syagrus oleraces), jerivá (Syagrus romanzoffiana) and macaúba (Acrocomia aculeata).

    PubMed

    Coimbra, Michelle C; Jorge, Neuza

    2012-02-01

    Bioactive compounds are capable of providing health benefits, reducing disease incidence or favoring body functioning. There is a growing search for vegetable oils containing such compounds. This study aimed to characterize the pulp and kernel oils of the Brazilian palm species guariroba (Syagrus oleracea), jerivá (Syagrus romanzoffiana) and macaúba (Acrocomia aculeata), aiming at possible uses in several industries. Fatty acid composition, phenolic and carotenoid contents, tocopherol composition were evaluated. The majority of the fatty acids in pulps were oleic and linoleic; macaúba pulp contained 526 g kg⁻¹ of oleic acid. Lauric acid was detected in the kernels of all three species as the major saturated fatty acid, in amounts ranging from 325.8 to 424.3 g kg⁻¹. The jerivá pulp contained carotenoids and tocopherols on average of 1219 µg g⁻¹ and 323.50 mg kg⁻¹, respectively. The pulps contained more unsaturated fatty acids than the kernels, mainly oleic and linoleic. Moreover, the pulps showed higher carotenoid and tocopherol contents. The kernels showed a predominance of saturated fatty acids, especially lauric acid. The fatty acid profiles of the kernels suggest that these oils may be better suited for the cosmetic and pharmaceutical industries than for use in foods. Copyright © 2011 Society of Chemical Industry.

  6. 19 CFR 10.56 - Vegetable oils, denaturing; release.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 19 Customs Duties 1 2014-04-01 2014-04-01 false Vegetable oils, denaturing; release. 10.56 Section... Vegetable Oils § 10.56 Vegetable oils, denaturing; release. (a) Olive, palm-kernel, rapeseed, sunflower, and sesame oil shall be classifiable under subheadings 1509.10.20, 1509.10.40, 1509.90.20, 1509.90.40, 1510...

  7. 19 CFR 10.56 - Vegetable oils, denaturing; release.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 19 Customs Duties 1 2012-04-01 2012-04-01 false Vegetable oils, denaturing; release. 10.56 Section... Vegetable Oils § 10.56 Vegetable oils, denaturing; release. (a) Olive, palm-kernel, rapeseed, sunflower, and sesame oil shall be classifiable under subheadings 1509.10.20, 1509.10.40, 1509.90.20, 1509.90.40, 1510...

  8. 19 CFR 10.56 - Vegetable oils, denaturing; release.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 19 Customs Duties 1 2013-04-01 2013-04-01 false Vegetable oils, denaturing; release. 10.56 Section... Vegetable Oils § 10.56 Vegetable oils, denaturing; release. (a) Olive, palm-kernel, rapeseed, sunflower, and sesame oil shall be classifiable under subheadings 1509.10.20, 1509.10.40, 1509.90.20, 1509.90.40, 1510...

  9. 19 CFR 10.56 - Vegetable oils, denaturing; release.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 19 Customs Duties 1 2010-04-01 2010-04-01 false Vegetable oils, denaturing; release. 10.56 Section... Vegetable Oils § 10.56 Vegetable oils, denaturing; release. (a) Olive, palm-kernel, rapeseed, sunflower, and sesame oil shall be classifiable under subheadings 1509.10.20, 1509.10.40, 1509.90.20, 1509.90.40, 1510...

  10. 19 CFR 10.56 - Vegetable oils, denaturing; release.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 19 Customs Duties 1 2011-04-01 2011-04-01 false Vegetable oils, denaturing; release. 10.56 Section... Vegetable Oils § 10.56 Vegetable oils, denaturing; release. (a) Olive, palm-kernel, rapeseed, sunflower, and sesame oil shall be classifiable under subheadings 1509.10.20, 1509.10.40, 1509.90.20, 1509.90.40, 1510...

  11. The Potential of Palm Oil Waste Biomass in Indonesia in 2020 and 2030

    NASA Astrophysics Data System (ADS)

    Hambali, E.; Rivai, M.

    2017-05-01

    During replanting activity in oil palm plantation, biomass including palm frond and trunk are produced. In palm oil mills, during the conversion process of fresh fruit bunches (FFB) into crude palm oil (CPO), several kinds of waste including empty fruit bunch (EFB), mesocarp fiber (MF), palm kernel shell (PKS), palm kernel meal (PKM), and palm oil mills effluent (POME) are produced. The production of these wastes is abundant as oil palm plantation area, FFB production, and palm oil mills spread all over 22 provinces in Indonesia. These wastes are still economical as they can be utilized as sources of alternative fuel, fertilizer, chemical compounds, and biomaterials. Therefore, breakthrough studies need to be done in order to improve the added value of oil palm, minimize the waste, and make oil palm industry more sustainable.

  12. Bio-Based Nano Composites from Plant Oil and Nano Clay

    NASA Astrophysics Data System (ADS)

    Lu, Jue; Hong, Chang K.; Wool, Richard P.

    2003-03-01

    We explored the combination of nanoclay with new chemically functionalized, amphiphilic, plant oil resins to form bio-based nanocomposites with improved physical and mechanical properties. These can be used in many new applications, including the development of self-healing nanocomposites through controlled reversible exfoliation/intercalation, and self-assembled nano-structures. Several chemically modified triglyceride monomers of varying polarity, combined with styrene (ca 30include acrylated epoxidized soybean oil (AESO), maleated acrylated epoxidized soybean oil (MAESO) and soybean oil pentaerythritol glyceride maleates (SOPERMA), containing either hydroxyl group or acid functionality or both. The clay used is a natural montmorillonite modified with methyl tallow bis-2-hydroxyethyl quaternary ammonium chloride, which has hydroxyl groups. Both XRD and TEM showed a completely exfoliated structure at 3 wtwhen the clay content is above 5 wtconsidered a mix of intercalated and partially exfoliated structure. The controlled polarity of the monomer has a major effect on the reversible dispersion of clay in the polymer matrix. The bio-based nanocomposites showed a significant increase in flexural modulus and strength. Supported by EPA and DoE

  13. Dynamics of Polymorphic Transformations in Palm Oil, Palm Stearin and Palm Kernel Oil Characterized by Coupled Powder XRD-DSC.

    PubMed

    Zaliha, Omar; Elina, Hishamuddin; Sivaruby, Kanagaratnam; Norizzah, Abd Rashid; Marangoni, Alejandro G

    2018-06-01

    The in situ polymorphic forms and thermal transitions of refined, bleached and deodorized palm oil (RBDPO), palm stearin (RBDPS) and palm kernel oil (RBDPKO) were investigated using coupled X-ray diffraction (XRD) and differential scanning calorimetry (DSC). Results indicated that the DSC onset crystallisation temperature of RBDPO was at 22.6°C, with a single reflection at 4.2Å started to appear from 23.4 to 17.1°C, and were followed by two prominent exothermic peaks at 20.1°C and 8.5°C respectively. Further cooling to -40°C leads to the further formation of a β'polymorph. Upon heating, a of β'→βtransformation was observed between 32.1 to 40.8°C, before the sample was completely melted at 43.0°C. The crystallization onset temperature of RBDPS was 44.1°C, with the appearance of the α polymorph at the same temperature as the appearance of the first sharp DSC exothermic peak. This quickly changed from α→β´ in the range 25 to 21.7°C, along with the formation of a small β peak at -40°C. Upon heating, a small XRD peak for the β polymorph was observed between 32.2 to 36.0°C, becoming a mixture of (β´+ β) between 44.0 to 52.5°C. Only the β polymorph survived further heating to 59.8°C. For RBDPKO, the crystallization onset temperature was 11.6°C, with the formation of a single sharp exothermic peak at 6.5°C corresponding to the β' polymorphic form until the temperature reached -40°C. No transformation of the polymorphic form was observed during the melting process of RBDPKO, before being completely melted at 33.2°C. This work has demonstrated the detailed dynamics of polymorphic transformations of PKO and PS, two commercially important hardstocks used widely by industry and will contribute to a greater understanding of their crystallization and melting dynamics.

  14. Transcriptomic analysis revealed the mechanism of oil dynamic accumulation during developing Siberian apricot (Prunus sibirica L.) seed kernels for the development of woody biodiesel.

    PubMed

    Niu, Jun; An, Jiyong; Wang, Libing; Fang, Chengliang; Ha, Denglong; Fu, Chengyu; Qiu, Lin; Yu, Haiyan; Zhao, Haiyan; Hou, Xinyu; Xiang, Zheng; Zhou, Sufan; Zhang, Zhixiang; Feng, Xinyi; Lin, Shanzhi

    2015-01-01

    Siberian apricot (Prunus sibirica L.) has emerged as a novel potential source of biodiesel in China, but the molecular regulatory mechanism of oil accumulation in Siberian apricot seed kernels (SASK) is still unknown at present. To better develop SASK oil as woody biodiesel, it is essential to profile transcriptome and to identify the full repertoire of potential unigenes involved in the formation and accumulation of oil SASK during the different developing stages. We firstly detected the temporal patterns for oil content and fatty acid (FA) compositions of SASK in 7 different developing stages. The best time for obtaining the high quality and quantity of SASK oil was characterized at 60 days after flowering (DAF), and the representative periods (10, 30, 50, 60, and 70 DAF) were selected for transcriptomic analysis. By Illumina/Solexa sequencings, approximately 65 million short reads (average length = 96 bp) were obtained, and then assembled into 124,070 unigenes by Trinity strategy (mean size = 829.62 bp). A total of 3,000, 2,781, 2,620, and 2,675 differentially expressed unigenes were identified at 30, 50, 60, and 70 DAF (10 DAF as the control) by DESeq method, respectively. The relationship between the unigene transcriptional profiles and the oil dynamic patterns in developing SASK was comparatively analyzed, and the specific unigenes encoding some known enzymes and transcription factors involved in acetyl-coenzyme A (acetyl-CoA) formation and oil accumulation were determined. Additionally, 5 key metabolic genes implicated in SASK oil accumulation were experimentally validated by quantitative real-time PCR (qRT-PCR). Our findings could help to construction of oil accumulated pathway and to elucidate the molecular regulatory mechanism of increased oil production in developing SASK. This is the first study of oil temporal patterns, transcriptome sequencings, and differential profiles in developing SASK. All our results will serve as the important

  15. Effects of abomasal infusion of tallow or camelina oil on responses to glucose and insulin in dairy cows during late pregnancy.

    PubMed

    Salin, S; Taponen, J; Elo, K; Simpura, I; Vanhatalo, A; Boston, R; Kokkonen, T

    2012-07-01

    Late pregnancy is associated with moderate insulin resistance in ruminants. Reduced suppression of lipolysis by insulin facilitates mobilization of nonesterified fatty acids (NEFA) from adipose tissue, resulting in elevated plasma NEFA concentrations. Decrease in dry matter intake (DMI) before parturition leads to accelerated lipomobilization and increases plasma NEFA, which may further impair insulin sensitivity. The aim of the study was to evaluate the effects of elevation of plasma NEFA concentration by abomasal infusions tallow (TAL) or camelina oil (CAM) on whole-body responses to exogenous glucose and insulin. We further assessed whether CAM, rich in C18:3n-3, enhances whole-body insulin sensitivity compared with TAL. Six late-pregnant, second-parity, rumen-cannulated dry Ayrshire dairy cows fed grass silage to meet 95% of metabolizable energy requirements were used in a replicated 3 × 3 Latin square with 5-d periods and 5 recovery days between each period. Treatments consisted of abomasal infusion of 500 mL/d (430 g of lipids/d) of water (control), TAL, or CAM administered in 10 equal doses daily. Intravenous glucose tolerance test (IVGTT) and i.v. insulin challenge (IC) were performed on d 5 after 98 and 108 h of treatment infusions, respectively. Infusion of lipids increased basal plasma NEFA concentrations on d 5 (CAM: 0.25; TAL: 0.28; control: 0.17 mmol/L). Following glucose injection, the rate of glucose clearance (CR) was lower in lipid-treated cows (CAM: 1.34; TAL: 1.48; control: 1.74%/min) and time to reach half-maximal glucose concentration (T(1/2)) was longer (CAM: 54; TAL: 47; control: 42 min). Similar responses were observed after insulin injection. Increased plasma NEFA concentration tended to decrease insulin secretion in IVGTT. Infusion of CAM increased plasma C18:3n-3 content (CAM: 26.4; TAL: 16.1; control: 20.9 g/100g of fatty acids). Data suggest that CAM had an insulin-sensitizing effect, because the disposition index and insulin

  16. Polyunsaturated fatty acids reduce insulin and very low density lipoprotein levels in broiler chickens.

    PubMed

    Crespo, N; Esteve-Garcia, E

    2003-07-01

    An experiment was conducted to study the effect of different dietary fatty acid profiles on plasma levels of insulin, very low density lipoproteins (VLDL), cholesterol, and glucose. Diets with four types of fat (tallow, olive, sunflower, and linseed oils) at an inclusion level of 10% and a basal diet without additional fat were administered to female broiler chickens. Serum insulin, cholesterol, and plasma VLDL were affected by the different treatments; however, glucose concentrations were similar among treatments. In the fasted state, broilers fed diets with sunflower or linseed oil presented lower levels of insulin and cholesterol with respect to those fed tallow or olive oil (P < 0.05). VLDL in the fasted state was reduced in broilers fed sunflower and linseed oils (P < 0.05) with respect to those fed tallow, olive oil, or the basal diet. Plasma levels of VLDL were only significantly correlated with abdominal fat in birds fed the basal diet, in the fed and in the fasted state, and in those fed linseed oil in the fed state (P < 0.05). Results of this experiment suggest that higher insulin levels in broilers fed diets rich in saturated fatty acids could be related to higher fat deposition. Fat deposition in birds fed high fat diets was not correlated with circulating VLDL, which suggested direct dietary fat deposition, except for birds fed linseed oil diets. Although birds fed linseed oil diets presented lower levels of VLDL than those fed tallow, olive oil, or the basal diet, the higher correlation with abdominal fat suggests that in these birds, fat deposition is more dependent on hepatic VLDL secretion, despite the high dietary fat level.

  17. Optimized Kernel Entropy Components.

    PubMed

    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.

  18. Detection of virgin coconut oil adulteration with animal fats using quantitative cholesterol by GC × GC-TOF/MS analysis.

    PubMed

    Xu, Baocheng; Li, Peiwu; Ma, Fei; Wang, Xiuping; Matthäus, Bertrand; Chen, Ran; Yang, Qingqing; Zhang, Wen; Zhang, Qi

    2015-07-01

    A new method based on the cholesterol level was developed to detect the presence of animal fats in virgin coconut oil (VCO). In this study, the sterols in VCO and animal fats was separated using conventional one-dimensional gas chromatography (1D GC) and comprehensive two-dimensional gas chromatography (GC×GC). Compared with 1D GC, the GC×GC system could obtain a complete baseline separation of the sterol trimethylsilyl ethers derived from cholesterol and cholestanol, so that the cholesterol content in pure VCO and false VCO adulterated with animal fats could be accurately determined. Cholesterol, a main sterol found in animal fats, represented less than 5mg/kg of VCO. The study demonstrated that the determination of the cholesterol level in VCO could be used for reliable detection of the presence of lard, chicken fat, mutton tallow, beef tallow, or their mixture in VCO at a level as little as 0.25%. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Chemical and functional properties of fibre concentrates obtained from by-products of coconut kernel.

    PubMed

    Yalegama, L L W C; Nedra Karunaratne, D; Sivakanesan, Ramiah; Jayasekara, Chitrangani

    2013-11-01

    The coconut kernel residues obtained after extraction of coconut milk (MR) and virgin coconut oil (VOR) were analysed for their potential as dietary fibres. VOR was defatted and treated chemically using three solvent systems to isolate coconut cell wall polysaccharides (CCWP). Nutritional composition of VOR, MR and CCWPs indicated that crude fibre, neutral detergent fibre, acid detergent fibre and hemicelluloses contents were higher in CCWPs than in VOR and MR. MR contained a notably higher content of fat than VOR and CCWPs. The oil holding capacity, water holding capacity and swelling capacity were also higher in CCWPs than in VOR and MR. All the isolates and MR and VOR had high metal binding capacities. The CCWPs when compared with commercially available fibre isolates, indicated improved dietary fibre properties. These results show that chemical treatment of coconut kernel by-products can enhance the performance of dietary fibre to yield a better product. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. 40 CFR 112.10 - Spill Prevention, Control, and Countermeasure Plan requirements for onshore oil drilling and...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... Requirements for Petroleum Oils and Non-Petroleum Oils, Except Animal Fats and Oils and Greases, and Fish and Marine Mammal Oils; and Vegetable Oils (Including Oils from Seeds, Nuts, Fruits, and Kernels) § 112.10...

  1. 40 CFR 112.10 - Spill Prevention, Control, and Countermeasure Plan requirements for onshore oil drilling and...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... Requirements for Petroleum Oils and Non-Petroleum Oils, Except Animal Fats and Oils and Greases, and Fish and Marine Mammal Oils; and Vegetable Oils (Including Oils from Seeds, Nuts, Fruits, and Kernels) § 112.10...

  2. 40 CFR 112.10 - Spill Prevention, Control, and Countermeasure Plan requirements for onshore oil drilling and...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... Requirements for Petroleum Oils and Non-Petroleum Oils, Except Animal Fats and Oils and Greases, and Fish and Marine Mammal Oils; and Vegetable Oils (Including Oils from Seeds, Nuts, Fruits, and Kernels) § 112.10...

  3. Effect of pH on ionic liquid mediated synthesis of gold nanoparticle using elaiseguineensis (palm oil) kernel extract

    NASA Astrophysics Data System (ADS)

    Irfan, Muhammad; Ahmad, Tausif; Moniruzzaman, Muhammad; Abdullah, Bawadi

    2017-05-01

    This study was conducted for microwave assisted synthesis of stable gold nanoparticles (AuNPs) by reduction of chloroauric acid with Elaeis Guineensis (palm oil) kernel (POK) extract which was prepared in aqueous solution of ionic liquid, [EMIM][OAc], 1-Ethyl-3-methylimidazolium acetate. Effect of initial pH of reaction mixture (3.5 - 8.5) was observed on SPR absorbance, maximum wavelength (λmax ) and size distribution of AuNPs. Change of pH of reaction mixture from acidic to basic region resulted in appearance of strong SPR absorption peaks and blue shifting of λmax from 533 nm to 522 nm. TEM analysis revealed the formation of predominantly spherical AuNPs with mean diameter of 8.51 nm. Presence of reducing moieties such as flavonoids, phenolic and carboxylic groups in POK extract was confirmed by FTIR analysis. Colloidal solution of AuNPs was remained stable at room temperature and insignificant difference in zeta value was recorded within experimental tenure of 4 months.

  4. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  5. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  6. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  7. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... kernel is modified to mean a kernel, piece, or particle of almond kernel with any defect scored as... purposes of determining inedible kernels, pieces, or particles of almond kernels. [59 FR 39419, Aug. 3...

  8. UNICOS Kernel Internals Application Development

    NASA Technical Reports Server (NTRS)

    Caredo, Nicholas; Craw, James M. (Technical Monitor)

    1995-01-01

    Having an understanding of UNICOS Kernel Internals is valuable information. However, having the knowledge is only half the value. The second half comes with knowing how to use this information and apply it to the development of tools. The kernel contains vast amounts of useful information that can be utilized. This paper discusses the intricacies of developing utilities that utilize kernel information. In addition, algorithms, logic, and code will be discussed for accessing kernel information. Code segments will be provided that demonstrate how to locate and read kernel structures. Types of applications that can utilize kernel information will also be discussed.

  9. Using internet images to gather distributional data for a newly discovered Caloptilia species (Lepidoptera: Gracillariidae) specializing on Chinese tallow in North America

    USDA-ARS?s Scientific Manuscript database

    Chinese tallow tree (Triadica sebifera (L.), Euphorbiaceae) is a noxious and highly invasive species that was deliberately introduced to GA in 1772. In early 2009, an unfamiliar caterpillar was independently discovered feeding on T. sebifera trees in Gainesville, FL and Slidell, LA. Adult moths were...

  10. Safety evaluation of wild apricot oil.

    PubMed

    Gandhi, V M; Mulky, M J; Mukerji, B; Iyer, V J; Cherian, K M

    1997-06-01

    Wild apricot, a variety of Prunus armeniaca, grows in the hilly regions of India. The seeds yield 27% of kernels. The potential availability of the kernels is 40,000 tons/year and these yield 47% of oil. The oil has 94% unsaturated fatty acids, rich in oleic and linoleic acids. Systemic effects and nutritional quality of wild apricot oil (WAO) were assessed in a 13-wk feeding study in weanling albino rats using a diet containing 10% WAO as the sole source of dietary fat. A similar diet containing groundnut oil (GNO) was used as the control. WAO did not manifest any toxic potential. The food consumption, growth rate and food efficiency ratio of rats fed WAO were similar to those fed GNO. The digestibility of this oil was found to be comparable to that of GNO. There were no macroscopic or microscopic lesions in any of the organs that could be ascribed to WAO incorporation in the diet. The results of this study indicate that WAO could be used for edible purposes without any overt toxic signs or symptoms. However a long-term study may be needed to confirm its innocuousness further.

  11. Applications of single kernel conventional and hyperspectral imaging near infrared spectroscopy in cereals.

    PubMed

    Fox, Glen; Manley, Marena

    2014-01-30

    Single kernel (SK) near infrared (NIR) reflectance and transmittance technologies have been developed during the last two decades for a range of cereal grain physical quality and chemical traits as well as detecting and predicting levels of toxins produced by fungi. Challenges during the development of single kernel near infrared (SK-NIR) spectroscopy applications are modifications of existing NIR technology to present single kernels for scanning as well as modifying reference methods for the trait of interest. Numerous applications have been developed, and cover almost all cereals although most have been for key traits including moisture, protein, starch and oil in the globally important food grains, i.e. maize, wheat, rice and barley. An additional benefit in developing SK-NIR applications has been to demonstrate the value in sorting grain infected with a fungus or mycotoxins such as deoxynivalenol, fumonisins and aflatoxins. However, there is still a need to develop cost-effective technologies for high-speed sorting which can be used for small grain samples such as those from breeding programmes or commercial sorting; capable of sorting tonnes per hour. Development of SK-NIR technologies also includes standardisation of SK reference methods to analyse single kernels. For protein content, the use of the Dumas method would require minimal standardisation; for starch or oil content, considerable development would be required. SK-NIR, including the use of hyperspectral imaging, will improve our understanding of grain quality and the inherent variation in the range of a trait. In the area of food safety, this technology will benefit farmers, industry and consumers if it enables contaminated grain to be removed from the human food chain. © 2013 Society of Chemical Industry.

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

    PubMed

    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.

  13. BRIEF-REPORT New set of microsatellites for Chinese tallow tree, Triadica sebifera.

    PubMed

    Zhuang, Y F; Wang, Z F; Wu, L F

    2017-04-05

    Chinese tallow (Triadica sebifera) is an important crop and ornamental tree. After it was introduced into the USA, it gradually became a noxious invasive tree in south-eastern America since the middle of the 1900s. Because only six microsatellites were reported previously in T. sebifera, to better understand the genetic diversity and population dynamics of such species, we reported here 28 new microsatellite markers. For these 28 microsatellites, the number of alleles per locus ranged from 2-16. The expected heterozygosity and the expected heterozygosity corrected for sample size varied from 0.0796 to 0.9081 and from 0.0805 to 0.9176, respectively. These microsatellites will provide additional choice to investigate the genetic diversity and structure in T. sebifera.

  14. 7 CFR 981.7 - Edible kernel.

    Code of Federal Regulations, 2010 CFR

    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] ...

  15. Unconventional protein sources: apricot seed kernels.

    PubMed

    Gabrial, G N; El-Nahry, F I; Awadalla, M Z; Girgis, S M

    1981-09-01

    Hamawy apricot seed kernels (sweet), Amar apricot seed kernels (bitter) and treated Amar apricot kernels (bitterness removed) were evaluated biochemically. All kernels were found to be high in fat (42.2--50.91%), protein (23.74--25.70%) and fiber (15.08--18.02%). Phosphorus, calcium, and iron were determined in all experimental samples. The three different apricot seed kernels were used for extensive study including the qualitative determination of the amino acid constituents by acid hydrolysis, quantitative determination of some amino acids, and biological evaluation of the kernel proteins in order to use them as new protein sources. Weanling albino rats failed to grow on diets containing the Amar apricot seed kernels due to low food consumption because of its bitterness. There was no loss in weight in that case. The Protein Efficiency Ratio data and blood analysis results showed the Hamawy apricot seed kernels to be higher in biological value than treated apricot seed kernels. The Net Protein Ratio data which accounts for both weight, maintenance and growth showed the treated apricot seed kernels to be higher in biological value than both Hamawy and Amar kernels. The Net Protein Ratio for the last two kernels were nearly equal.

  16. Mineral contents and proximate composition of Pistacia vera kernels.

    PubMed

    Harmankaya, Mustafa; Ozcan, Mehmet Musa; Al Juhaimi, Fahad

    2014-07-01

    The mineral contents of Pistacia vera kernels were determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The minimum and maximum values of K, P, Ca, Mg, and S elements ranged from 6,333 to 8,064 mg/kg, 3,630 to 5,228 mg/kg, 1,614 to 3,226 mg/kg, 1,716 to 2,402 mg/kg, and 1,417 to 1,825 mg/kg, respectively. In addition, the mean values of Fe, Zn, Cu, Mn, B, Mo, Cr and Ni elements were determined as 42.48, 20.52, 12.81, 7.48, 11.31, 0.106, 0.511 and 1.67 mg/kg, respectively. Ash levels of kernels were found between 2.28 % (Urfa) and 2.79 % (Halebi). In addition, crude oil and protein contents were determined between 48.8 % (Halebi) to 55.3 % (Siirt) and 23.33 % (Uzun) to 27.16 % (Halebi), respectively.

  17. Influence of enzymatic and chemical interesterification on crystallisation properties of refined, bleached and deodourised (RBD) palm oil and RBD palm kernel oil blends.

    PubMed

    Norizzah, Abd Rashid; Nur Azimah, Kamarulzaman; Zaliha, Omar

    2018-04-01

    Interesterification reaction involves rearrangement of the fatty acid radicals on the glycerol backbone, either randomly (chemical interesterification) or regioselectivity (enzymatic interesterification). Refined, bleached and deodourised palm oil (RBDPO) and palm kernel oil (RBDPKO) were blended in ratios from 25:75 to 75:25 (wt/wt). All blends were subjected to enzymatic (EI) and chemical interesterification (CI) using Lipozyme TL IM (4% w/w) and sodium methoxide (0.2% m/m) as the catalysts, respectively. The effect of EI and CI on the triacylglycerol (TAG) composition, thermal behaviour, polymorphism, crystal morphology and crystallisation kinetics were studied. The aim of this research is to characterise the nature of crystals in food product for certain desired structure. The crystallisation behaviour discussed in this study involves microstructure (PLM), polymorphism (XRD), thermal properties and crystallisation kinetics by DSC. The alteration in TAG composition was greater after CI as compared to EI with the reduction of LaLaLa (from 11.00% to 5.15%) and POO (from 14.28% to 4.87%). The DSC complete melting and crystallisation temperature of blend with 75% PO increased after CI, from 39.58 °C to 41.67 °C and from -30.84 °C to -28.33 °C, respectively. EI contributed to finer crystals than CI. However, the β' and β polymorph mixture and crystallisation kinetics (n = 2) of PO-PKO blends did not change after CI and EI. The knowledge on controlling crystallisation of RBDPO and RBDPKO blends is vital for proper processing condition like margarine production. Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Gamma irradiation of peanut kernel to control mold growth and to diminish aflatoxin contamination

    NASA Astrophysics Data System (ADS)

    Y.-Y. Chiou, R.

    1996-09-01

    Peanut kernel inoculated with Aspergillus parasiticus conidia were gamma irradiated with 0, 2.5, 5.0 and 10 kGy using Co60. Levels higher than 2.5 kGy were effective in retarding the outgrowth of A. parasiticus and reducing the population of natural mold contaminants. However, complete elimination of these molds was not achieved even at the dose of 10 kGy. After 4 wk incubation of the inoculated kernels in a humidified condition, aflatoxins produced by the surviving A. parasiticus were 69.12, 2.42, 57.36 and 22.28 μ/g, corresponding to the original irradiation levels. Peroxide content of peanut oils prepared from the irradiated peanuts increased with increased irradiation dosage. After storage, at each irradiation level, peroxide content in peanuts stored at -14°C was lower than that in peanuts stored at an ambient temperature. TBA values and CDHP contents of the oil increased with increased irradiation dosage and changed slightly after storage. However, fatty acid contents of the peanut oil varied in a limited range as affected by the irradiation dosage and storage temperature. The SDS-PAGE protein pattern of peanuts revealed no noticeable variation of protein subunits resulting from irradiation and storage.

  19. 7 CFR 981.8 - Inedible kernel.

    Code of Federal Regulations, 2010 CFR

    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...

  20. 7 CFR 51.1415 - Inedible kernels.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Inedible kernels. 51.1415 Section 51.1415 Agriculture... Standards for Grades of Pecans in the Shell 1 Definitions § 51.1415 Inedible kernels. Inedible kernels means that the kernel or pieces of kernels are rancid, moldy, decayed, injured by insects or otherwise...

  1. 7 CFR 981.408 - Inedible kernel.

    Code of Federal Regulations, 2010 CFR

    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...

  2. SOME ENGINEERING PROPERTIES OF SHELLED AND KERNEL TEA (Camellia sinensis) SEEDS.

    PubMed

    Altuntas, Ebubekir; Yildiz, Merve

    2017-01-01

    Camellia sinensis is the source of tea leaves and it is an economic crop now grown around the World. Tea seed oil has been used for cooking in China and other Asian countries for more than a thousand years. Tea is the most widely consumed beverages after water in the world. It is mainly produced in Asia, central Africa, and exported throughout the World. Some engineering properties (size dimensions, sphericity, volume, bulk and true densities, friction coefficient, colour characteristics and mechanical behaviour as rupture force of shelled and kernel tea ( Camellia sinensis ) seeds were determined in this study. This research was carried out for shelled and kernel tea seeds. The shelled tea seeds used in this study were obtained from East-Black Sea Tea Cooperative Institution in Rize city of Turkey. Shelled and kernel tea seeds were characterized as large and small sizes. The average geometric mean diameter and seed mass of the shelled tea seeds were 15.8 mm, 10.7 mm (large size); 1.47 g, 0.49 g (small size); while the average geometric mean diameter and seed mass of the kernel tea seeds were 11.8 mm, 8 mm for large size; 0.97 g, 0.31 g for small size, respectively. The sphericity, surface area and volume values were found to be higher in a larger size than small size for the shelled and kernel tea samples. The shelled tea seed's colour intensity (Chroma) were found between 59.31 and 64.22 for large size, while the kernel tea seed's chroma values were found between 56.04 68.34 for large size, respectively. The rupture force values of kernel tea seeds were higher than shelled tea seeds for the large size along X axis; whereas, the rupture force values of along X axis were higher than Y axis for large size of shelled tea seeds. The static coefficients of friction of shelled and kernel tea seeds for the large and small sizes higher values for rubber than the other friction surfaces. Some engineering properties, such as geometric mean diameter, sphericity, volume, bulk

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

    PubMed

    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.

  4. Biosynthesis and characterization of poly(3-hydroxybutyrate-co-3- hydroxyhexanoate) from palm oil products in a Wautersia eutropha mutant.

    PubMed

    Loo, Ching-Yee; Lee, Wing-Hin; Tsuge, Takeharu; Doi, Yoshiharu; Sudesh, Kumar

    2005-09-01

    Palm kernel oil, palm olein, crude palm oil and palm acid oil were used for the synthesis of poly (3-hydroxybutyrate-co-3-hydroxyhexanoate) [P(3HB-co-3HHx)] by a mutant strain of Wautersia eutropha (formerly Ralstonia eutropha) harboring the Aeromonas caviae polyhydroxyalkanoate (PHA) synthase gene. Palm kernel oil was an excellent carbon source for the production of cell biomass and P(3HB-co-3HHx). About 87% (w/w) of the cell dry weight as P(3HB-co-3HHx) was obtained using 5 g palm kernel oil/l. Gravimetric and microscopic analyses further confirmed the high PHA content in the recombinant cells. The molar fraction of 3HHx remained constant at 5 mol % regardless of the type and concentration of palm oil products used. The small amount of 3HHx units was confirmed by 13C NMR analysis. The number average molecular weight (M(n)) of the PHA copolymer produced from the various palm oil products ranged from 27 0000 to 46 0000 Da. The polydispersity was in the range of 2.6-3.9.

  5. Fault detection and diagnosis for gas turbines based on a kernelized information entropy model.

    PubMed

    Wang, Weiying; Xu, Zhiqiang; Tang, Rui; Li, Shuying; Wu, Wei

    2014-01-01

    Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms.

  6. Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model

    PubMed Central

    Wang, Weiying; Xu, Zhiqiang; Tang, Rui; Li, Shuying; Wu, Wei

    2014-01-01

    Gas turbines are considered as one kind of the most important devices in power engineering and have been widely used in power generation, airplanes, and naval ships and also in oil drilling platforms. However, they are monitored without man on duty in the most cases. It is highly desirable to develop techniques and systems to remotely monitor their conditions and analyze their faults. In this work, we introduce a remote system for online condition monitoring and fault diagnosis of gas turbine on offshore oil well drilling platforms based on a kernelized information entropy model. Shannon information entropy is generalized for measuring the uniformity of exhaust temperatures, which reflect the overall states of the gas paths of gas turbine. In addition, we also extend the entropy to compute the information quantity of features in kernel spaces, which help to select the informative features for a certain recognition task. Finally, we introduce the information entropy based decision tree algorithm to extract rules from fault samples. The experiments on some real-world data show the effectiveness of the proposed algorithms. PMID:25258726

  7. Characterization of oils and fats by 1H NMR and GC/MS fingerprinting: classification, prediction and detection of adulteration.

    PubMed

    Fang, Guihua; Goh, Jing Yeen; Tay, Manjun; Lau, Hiu Fung; Li, Sam Fong Yau

    2013-06-01

    The correct identification of oils and fats is important to consumers from both commercial and health perspectives. Proton nuclear magnetic resonance ((1)H NMR) spectroscopy, gas chromatography-mass spectrometry (GC/MS) fingerprinting and chemometrics were employed successfully for the quality control of oils and fats. Principal component analysis (PCA) of both techniques showed group clustering of 14 types of oils and fats. Partial least squares discriminant analysis (PLS-DA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) using GC/MS data had excellent classification sensitivity and specificity compared to models using NMR data. Depending on the availability of the instruments, data from either technique can effectively be applied for the establishment of an oils and fats database to identify unknown samples. Partial least squares (PLS) models were successfully established for the detection of as low as 5% of lard and beef tallow spiked into canola oil, thus illustrating possible applications in Islamic and Jewish countries. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Partial Deconvolution with Inaccurate Blur Kernel.

    PubMed

    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

  9. 7 CFR 981.9 - Kernel weight.

    Code of Federal Regulations, 2010 CFR

    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...

  10. 40 CFR 112.10 - Spill Prevention, Control, and Countermeasure Plan requirements for onshore oil drilling and...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... Marine Mammal Oils; and Vegetable Oils (Including Oils from Seeds, Nuts, Fruits, and Kernels) § 112.10... Countermeasure Plan requirements for onshore oil drilling and workover facilities. 112.10 Section 112.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS OIL POLLUTION PREVENTION...

  11. 40 CFR 112.10 - Spill Prevention, Control, and Countermeasure Plan requirements for onshore oil drilling and...

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Marine Mammal Oils; and Vegetable Oils (Including Oils from Seeds, Nuts, Fruits, and Kernels) § 112.10... Countermeasure Plan requirements for onshore oil drilling and workover facilities. 112.10 Section 112.10 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS OIL POLLUTION PREVENTION...

  12. [Rapid identification of hogwash oil by using synchronous fluorescence spectroscopy].

    PubMed

    Sun, Yan-Hui; An, Hai-Yang; Jia, Xiao-Li; Wang, Juan

    2012-10-01

    To identify hogwash oil quickly, the characteristic delta lambda of hogwash oil was analyzed by three dimensional fluorescence spectroscopy with parallel factor analysis, and the model was built up by using synchronous fluorescence spectroscopy with support vector machines (SVM). The results showed that the characteristic delta lambda of hogwash oil was 60 nm. Collecting original spectrum of different samples under the condition of characteristic delta lambda 60 nm, the best model was established while 5 principal components were selected from original spectrum and the radial basis function (RBF) was used as the kernel function, and the optimal penalty factor C and kernel function g were 512 and 0.5 respectively obtained by the grid searching and 6-fold cross validation. The discrimination rate of the model was 100% for both training sets and prediction sets. Thus, it is quick and accurate to apply synchronous fluorescence spectroscopy to identification of hogwash oil.

  13. Natural Zeolite Sample and Investigation Its Use in Oil Bleaching Sector

    NASA Astrophysics Data System (ADS)

    Bilgin, Oyku

    2017-12-01

    In the sector of oil bleaching, the stored raw oil is subjected to physical and chemical methods such as degumming, neutralization, bleaching, deodorization and winterization. In the process of oil bleaching, the selection of correct bleaching earth in accordance with oil characteristics matters so much. Bleaching earth is an inorganic product used in removing impurities being available within the structures of vegetable, animal oil (sunflower, soya, corn, palm, tallow, rapeseed, fish oils…etc.) and fatty acids, mineral oils (glycerine, paraffin, mineral motor oils. etc.) with the adsorption process. The factors such as low cost of oil bleaching earth, low ratio of oil retaining, high bleaching capacity in spite of using them in small amounts, filter’s delayed blocking by the earth and non-increase of the free acidity of the oil should be taken into consideration. Bleaching earths are processed with some acids in order to widen their surface areas. During this process, a certain amount of acid is left within oil bleaching earths even if it is very little. These acids also increase oil’s acidity by oxidizing oil in the course of bleaching process. In this study, zeolite sample taken from Manisa -Demirci region was used. Following the processes of crushing and sieving, zeolite sample was subjected to chemical analyses according to their grain thickness, microscopic examination, the analyses of XRD and cation exchange capacity and their ore characteristics were determined. Afterwards, it was searched whether zeolite sample has oil bleaching ability or not or whether it can be used as oil bleaching earth or not.

  14. 7 CFR 51.2295 - Half kernel.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

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

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

    PubMed

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

    2017-06-01

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

  16. Microalgal Oil Supplementation Has an Anti-Obesity Effect in C57BL/6J Mice Fed a High Fat Diet

    PubMed Central

    Yook, Jin-Seon; Kim, Kyung-Ah; Park, Jeong Eun; Lee, Seon-Hwa; Cha, Youn-Soo

    2015-01-01

    This study investigated the impact of microalgal oil (MO) on body weight management in C57BL/6J mice. Obesity was induced for 8 weeks and animals were orally supplemented with the following for 8 additional weeks: beef tallow (BT), corn oil, fish oil (FO), microalgal oil (MO), or none, as a high fat diet control group (HD). A normal control group was fed with a normal diet. After completing the experiment, the FO and MO groups showed significant decreases in body weight gain, epididymal fat pad weights, serum triglycerides, and total cholesterol levels compared to the HD and BT groups. A lower mRNA expression level of lipid anabolic gene and higher levels of lipid catabolic genes were observed in both FO and MO groups. Serum insulin and leptin concentrations were lower in the MO group. These results indicated that microalgal oil has an anti-obesity effect that can combat high fat diet-induced obesity in mice. PMID:26770909

  17. An Experimental Study of Briquetting Process of Torrefied Rubber Seed Kernel and Palm Oil Shell.

    PubMed

    Hamid, M Fadzli; Idroas, M Yusof; Ishak, M Zulfikar; Zainal Alauddin, Z Alimuddin; Miskam, M Azman; Abdullah, M Khalil

    2016-01-01

    Torrefaction process of biomass material is essential in converting them into biofuel with improved calorific value and physical strength. However, the production of torrefied biomass is loose, powdery, and nonuniform. One method of upgrading this material to improve their handling and combustion properties is by densification into briquettes of higher density than the original bulk density of the material. The effects of critical parameters of briquetting process that includes the type of biomass material used for torrefaction and briquetting, densification temperature, and composition of binder for torrefied biomass are studied and characterized. Starch is used as a binder in the study. The results showed that the briquette of torrefied rubber seed kernel (RSK) is better than torrefied palm oil shell (POS) in both calorific value and compressive strength. The best quality of briquettes is yielded from torrefied RSK at the ambient temperature of briquetting process with the composition of 60% water and 5% binder. The maximum compressive load for the briquettes of torrefied RSK is 141 N and the calorific value is 16 MJ/kg. Based on the economic evaluation analysis, the return of investment (ROI) for the mass production of both RSK and POS briquettes is estimated in 2-year period and the annual profit after payback was approximately 107,428.6 USD.

  18. Kernel abortion in maize : I. Carbohydrate concentration patterns and Acid invertase activity of maize kernels induced to abort in vitro.

    PubMed

    Hanft, J M; Jones, R J

    1986-06-01

    Kernels cultured in vitro were induced to abort by high temperature (35 degrees C) and by culturing six kernels/cob piece. Aborting kernels failed to enter a linear phase of dry mass accumulation and had a final mass that was less than 6% of nonaborting field-grown kernels. Kernels induced to abort by high temperature failed to synthesize starch in the endosperm and had elevated sucrose concentrations and low fructose and glucose concentrations in the pedicel during early growth compared to nonaborting kernels. Kernels induced to abort by high temperature also had much lower pedicel soluble acid invertase activities than did nonaborting kernels. These results suggest that high temperature during the lag phase of kernel growth may impair the process of sucrose unloading in the pedicel by indirectly inhibiting soluble acid invertase activity and prevent starch synthesis in the endosperm. Kernels induced to abort by culturing six kernels/cob piece had reduced pedicel fructose, glucose, and sucrose concentrations compared to kernels from field-grown ears. These aborting kernels also had a lower pedicel soluble acid invertase activity compared to nonaborting kernels from the same cob piece and from field-grown ears. The low invertase activity in pedicel tissue of the aborting kernels was probably caused by a lack of substrate (sucrose) for the invertase to cleave due to the intense competition for available assimilates. In contrast to kernels cultured at 35 degrees C, aborting kernels from cob pieces containing all six kernels accumulated starch in a linear fashion. These results indicate that kernels cultured six/cob piece abort because of an inadequate supply of sugar and are similar to apical kernels from field-grown ears that often abort prior to the onset of linear growth.

  19. An Approximate Approach to Automatic Kernel Selection.

    PubMed

    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.

  20. A new species of Gadirtha Walker (Nolidae: Collomeninae): a proposed biological control agent of Chinese tallow (Triadica sebifera (L.) Small) (Euphorbiaceae) in the United States

    USDA-ARS?s Scientific Manuscript database

    Gadirtha fusca, new species, is described from Hong Kong. Adult, male and female genitalia, larva, and pupa are described, illustrated, and compared with Gadirtha impingens Walker. Species is a possible biological control agent for Chinese tallow (Triadica sebifera (L.) Small, Euphorbiaceae) in the ...

  1. Integrating spread dynamics and economics of timber production to manage Chinese tallow invasions in southern U.S. forestlands.

    PubMed

    Wang, Hsiao-Hsuan; Grant, William E; Gan, Jianbang; Rogers, William E; Swannack, Todd M; Koralewski, Tomasz E; Miller, James H; Taylor, John W

    2012-01-01

    Economic costs associated with the invasion of nonnative species are of global concern. We estimated expected costs of Chinese tallow (Triadica sebifera (L.) Small) invasions related to timber production in southern U.S. forestlands under different management strategies. Expected costs were confined to the value of timber production losses plus costs for search and control. We simulated management strategies including (1) no control (NC), and control beginning as soon as the percentage of invaded forest land exceeded (2) 60 (Low Control), (3) 25 (Medium Control), or (4) 0 (High Control) using a spatially-explicit, stochastic, bioeconomic model. With NC, simulated invasions spread northward and westward into Arkansas and along the Gulf of Mexico to occupy ≈1.2 million hectares within 20 years, with associated expected total costs increasing exponentially to ≈$300 million. With LC, MC, and HC, invaded areas reached ≈275, 34, and 2 thousand hectares after 20 years, respectively, with associated expected costs reaching ≈$400, $230, and $200 million. Complete eradication would not be cost-effective; the minimum expected total cost was achieved when control began as soon as the percentage of invaded land exceeded 5%. These results suggest the importance of early detection and control of Chinese tallow, and emphasize the importance of integrating spread dynamics and economics to manage invasive species.

  2. Integrating Spread Dynamics and Economics of Timber Production to Manage Chinese Tallow Invasions in Southern U.S. Forestlands

    PubMed Central

    Wang, Hsiao-Hsuan; Grant, William E.; Gan, Jianbang; Rogers, William E.; Swannack, Todd M.; Koralewski, Tomasz E.; Miller, James H.; Taylor, John W.

    2012-01-01

    Economic costs associated with the invasion of nonnative species are of global concern. We estimated expected costs of Chinese tallow (Triadica sebifera (L.) Small) invasions related to timber production in southern U.S. forestlands under different management strategies. Expected costs were confined to the value of timber production losses plus costs for search and control. We simulated management strategies including (1) no control (NC), and control beginning as soon as the percentage of invaded forest land exceeded (2) 60 (Low Control), (3) 25 (Medium Control), or (4) 0 (High Control) using a spatially-explicit, stochastic, bioeconomic model. With NC, simulated invasions spread northward and westward into Arkansas and along the Gulf of Mexico to occupy ≈1.2 million hectares within 20 years, with associated expected total costs increasing exponentially to ≈$300 million. With LC, MC, and HC, invaded areas reached ≈275, 34, and 2 thousand hectares after 20 years, respectively, with associated expected costs reaching ≈$400, $230, and $200 million. Complete eradication would not be cost-effective; the minimum expected total cost was achieved when control began as soon as the percentage of invaded land exceeded 5%. These results suggest the importance of early detection and control of Chinese tallow, and emphasize the importance of integrating spread dynamics and economics to manage invasive species. PMID:22442731

  3. 7 CFR 51.1441 - Half-kernel.

    Code of Federal Regulations, 2010 CFR

    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...

  4. An introduction to kernel-based learning algorithms.

    PubMed

    Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

    2001-01-01

    This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

  5. A new discriminative kernel from probabilistic models.

    PubMed

    Tsuda, Koji; Kawanabe, Motoaki; Rätsch, Gunnar; Sonnenburg, Sören; Müller, Klaus-Robert

    2002-10-01

    Recently, Jaakkola and Haussler (1999) proposed a method for constructing kernel functions from probabilistic models. Their so-called Fisher kernel has been combined with discriminative classifiers such as support vector machines and applied successfully in, for example, DNA and protein analysis. Whereas the Fisher kernel is calculated from the marginal log-likelihood, we propose the TOP kernel derived; from tangent vectors of posterior log-odds. Furthermore, we develop a theoretical framework on feature extractors from probabilistic models and use it for analyzing the TOP kernel. In experiments, our new discriminative TOP kernel compares favorably to the Fisher kernel.

  6. 75 FR 59666 - Agricultural Swaps

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-28

    ..., grain sorghums, mill feeds, butter, eggs, Solanum tuberosum (Irish potatoes), wool, wool tops, fats and oils (including lard, tallow, cottonseed oil, peanut oil, soybean oil, and all other fats and oils... the Commodity Exchange Act (a) Permitting Eligible Swap Participants To Submit for Clearing and ICE...

  7. Kernel Abortion in Maize 1

    PubMed Central

    Hanft, Jonathan M.; Jones, Robert J.

    1986-01-01

    This study was designed to compare the uptake and distribution of 14C 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 30 and 35°C were transferred to [14C]sucrose media 10 days after pollination. Kernels cultured at 35°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 labeled media. After 8 days in culture on [14C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35°C, respectively. This indicates that some of the sucrose taken up by the cob tissue was cleaved to fructose and glucose in the cob. Of the total carbohydrates, a higher percentage of label was associated with sucrose and a lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35°C compared to kernels cultured at 30°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°C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30°C (89%). Kernels cultured at 35°C had a correspondingly higher proportion of 14C in endosperm fructose, glucose, and sucrose. These results indicate that starch synthesis in the endosperm is strongly inhibited in kernels induced to abort by high temperature even though there is an adequate supply of sugar. PMID:16664847

  8. Comparative Lipidomics and Proteomics of Lipid Droplets in the Mesocarp and Seed Tissues of Chinese Tallow (Triadica sebifera)

    PubMed Central

    Zhi, Yao; Taylor, Matthew C.; Campbell, Peter M.; Warden, Andrew C.; Shrestha, Pushkar; El Tahchy, Anna; Rolland, Vivien; Vanhercke, Thomas; Petrie, James R.; White, Rosemary G.; Chen, Wenli; Singh, Surinder P.; Liu, Qing

    2017-01-01

    Lipid droplets (LDs) are composed of a monolayer of phospholipids (PLs), surrounding a core of non-polar lipids that consist mostly of triacylglycerols (TAGs) and to a lesser extent diacylglycerols. In this study, lipidome analysis illustrated striking differences in non-polar lipids and PL species between LDs derived from Triadica sebifera seed kernels and mesocarp. In mesocarp LDs, the most abundant species of TAG contained one C18:1 and two C16:0 and fatty acids, while TAGs containing three C18 fatty acids with higher level of unsaturation were dominant in the seed kernel LDs. This reflects the distinct differences in fatty acid composition of mesocarp (palmitate-rich) and seed-derived oil (α-linoleneate-rich) in T. sebifera. Major PLs in seed LDs were found to be rich in polyunsaturated fatty acids, in contrast to those with relatively shorter carbon chain and lower level of unsaturation in mesocarp LDs. The LD proteome analysis in T. sebifera identified 207 proteins from mesocarp, and 54 proteins from seed kernel, which belong to various functional classes including lipid metabolism, transcription and translation, trafficking and transport, cytoskeleton, chaperones, and signal transduction. Oleosin and lipid droplets associated proteins (LDAP) were found to be the predominant proteins associated with LDs in seed and mesocarp tissues, respectively. We also show that LDs appear to be in close proximity to a number of organelles including the endoplasmic reticulum, mitochondria, peroxisomes, and Golgi apparatus. This comparative study between seed and mesocarp LDs may shed some light on the structure of plant LDs and improve our understanding of their functionality and cellular metabolic networks in oleaginous plant tissues. PMID:28824675

  9. Comparative Lipidomics and Proteomics of Lipid Droplets in the Mesocarp and Seed Tissues of Chinese Tallow (Triadica sebifera).

    PubMed

    Zhi, Yao; Taylor, Matthew C; Campbell, Peter M; Warden, Andrew C; Shrestha, Pushkar; El Tahchy, Anna; Rolland, Vivien; Vanhercke, Thomas; Petrie, James R; White, Rosemary G; Chen, Wenli; Singh, Surinder P; Liu, Qing

    2017-01-01

    Lipid droplets (LDs) are composed of a monolayer of phospholipids (PLs), surrounding a core of non-polar lipids that consist mostly of triacylglycerols (TAGs) and to a lesser extent diacylglycerols. In this study, lipidome analysis illustrated striking differences in non-polar lipids and PL species between LDs derived from Triadica sebifera seed kernels and mesocarp. In mesocarp LDs, the most abundant species of TAG contained one C18:1 and two C16:0 and fatty acids, while TAGs containing three C18 fatty acids with higher level of unsaturation were dominant in the seed kernel LDs. This reflects the distinct differences in fatty acid composition of mesocarp (palmitate-rich) and seed-derived oil (α-linoleneate-rich) in T. sebifera . Major PLs in seed LDs were found to be rich in polyunsaturated fatty acids, in contrast to those with relatively shorter carbon chain and lower level of unsaturation in mesocarp LDs. The LD proteome analysis in T. sebifera identified 207 proteins from mesocarp, and 54 proteins from seed kernel, which belong to various functional classes including lipid metabolism, transcription and translation, trafficking and transport, cytoskeleton, chaperones, and signal transduction. Oleosin and lipid droplets associated proteins (LDAP) were found to be the predominant proteins associated with LDs in seed and mesocarp tissues, respectively. We also show that LDs appear to be in close proximity to a number of organelles including the endoplasmic reticulum, mitochondria, peroxisomes, and Golgi apparatus. This comparative study between seed and mesocarp LDs may shed some light on the structure of plant LDs and improve our understanding of their functionality and cellular metabolic networks in oleaginous plant tissues.

  10. Local Observed-Score Kernel Equating

    ERIC Educational Resources Information Center

    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…

  11. A comparison of mango seed kernel powder, mango leaf powder and Manilkara zapota seed powder for decolorization of methylene blue dye and antimicrobial activity.

    PubMed

    Sundararaman, B; Muthuramu, K L

    2016-11-01

    The waste mango seed generated from mango pulp industry in India is a major problem in handling the waste and hence, conversion of mango seed kernel. Mango seeds were collected and processed for oil extraction. Decolorization of methylene blue was achieved by mango seed kernel powder, mango leaf powder and Manilkara zapota seed powder. Higher efficiency was attained in mango seed kernel powder when compared to mango leaf powder and Manilkara zapota seed powder. A 60 to 95 % of removal efficiency was achieved by varying concentration. Effect of pH, dye concentration, adsorbent dosage and temperature were studied. Mango seed kernel powder is a better option that can be used as an adsorbent for the removal of methylene blue and basic red dye from its aqueous solutions.

  12. Credit scoring analysis using kernel discriminant

    NASA Astrophysics Data System (ADS)

    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.

  13. 76 FR 6095 - Commodity Options and Agricultural Swaps

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-02-03

    ..., Solanum tuberosum (Irish potatoes), wool, wool tops, fats and oils (including lard, tallow, cottonseed oil, peanut oil, soybean oil, and all other fats and oils), cottonseed meal, cottonseed, peanuts, soybeans... Participants To Submit for Clearing and ICE Clear U.S., Inc. and Futures Commission Merchants To Clear Certain...

  14. Isolation and lipid degradation profile of Raoultella planticola strain 232-2 capable of efficiently catabolizing edible oils under acidic conditions.

    PubMed

    Sugimori, Daisuke; Watanabe, Mika; Utsue, Tomohiro

    2013-01-01

    The lipids (fats and oils) degradation capabilities of soil microorganisms were investigated for possible application in treatment of lipids-contaminated wastewater. We isolated a strain of the bacterium Raoultella planticola strain 232-2 that is capable of efficiently catabolizing lipids under acidic conditions such as in grease traps in restaurants and food processing plants. The strain 232-2 efficiently catabolized a mixture (mixed lipids) of commercial vegetable oil, lard, and beef tallow (1:1:1, w/w/w) at 20-35 °C, pH 3-9, and 1,000-5,000 ppm lipid content. Highly effective degradation rate was observed at 35 °C and pH 4.0, and the 24-h degradation rate was 62.5 ± 10.5 % for 3,000 ppm mixed lipids. The 24-h degradation rate for 3,000 ppm commercial vegetable oil, lard, beef tallow, mixed lipids, and oleic acid was 71.8 %, 58.7 %, 56.1 %, 55.3 ± 8.5 %, and 91.9 % at pH 4 and 30 °C, respectively. R. planticola NBRC14939 (type strain) was also able to efficiently catabolize the lipids after repeated subculturing. The composition of the culture medium strongly influenced the degradation efficiency, with yeast extract supporting more complete dissimilation than BactoPeptone or beef extract. The acid tolerance of strain 232-2 is proposed to result from neutralization of the culture medium by urease-mediated decomposition of urea to NH(3). The rate of lipids degradation increased with the rates of neutralization and cell growth. Efficient lipids degradation using strain 232-2 has been achieved in the batch treatment of a restaurant wastewater.

  15. Modeling adaptive kernels from probabilistic phylogenetic trees.

    PubMed

    Nicotra, Luca; Micheli, Alessio

    2009-01-01

    Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

  16. Nonlinear Deep Kernel Learning for Image Annotation.

    PubMed

    Jiu, Mingyuan; Sahbi, Hichem

    2017-02-08

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

  17. Bioactive compounds in cashew nut (Anacardium occidentale L.) kernels: effect of different shelling methods.

    PubMed

    Trox, Jennifer; Vadivel, Vellingiri; Vetter, Walter; Stuetz, Wolfgang; Scherbaum, Veronika; Gola, Ute; Nohr, Donatus; Biesalski, Hans Konrad

    2010-05-12

    In the present study, the effects of various conventional shelling methods (oil-bath roasting, direct steam roasting, drying, and open pan roasting) as well as a novel "Flores" hand-cracking method on the levels of bioactive compounds of cashew nut kernels were investigated. The raw cashew nut kernels were found to possess appreciable levels of certain bioactive compounds such as beta-carotene (9.57 microg/100 g of DM), lutein (30.29 microg/100 g of DM), zeaxanthin (0.56 microg/100 g of DM), alpha-tocopherol (0.29 mg/100 g of DM), gamma-tocopherol (1.10 mg/100 g of DM), thiamin (1.08 mg/100 g of DM), stearic acid (4.96 g/100 g of DM), oleic acid (21.87 g/100 g of DM), and linoleic acid (5.55 g/100 g of DM). All of the conventional shelling methods including oil-bath roasting, steam roasting, drying, and open pan roasting revealed a significant reduction, whereas the Flores hand-cracking method exhibited similar levels of carotenoids, thiamin, and unsaturated fatty acids in cashew nuts when compared to raw unprocessed samples.

  18. Leaf litter of invasive Chinese tallow (Triadica sebifera) negatively affects hatching success of an aquatic breeding anuran, the southern leopard frog (Lithobates sphenocephalus)

    Treesearch

    C.K. Adams; D. Saenz

    2012-01-01

    Chinese tallow (Triadica sebifera (L.) Small) is an aggressive invasive tree species that can be abundant in parts of its non-native range. This tree species has the capability of producing monocultures, by outcompeting native trees, which can be in or near wetlands that are utilized by breeding amphibians. Existing research suggests that leaf litter from invasive...

  19. Innovations in the development of healthier chicken sausages formulated with different lipid sources.

    PubMed

    Andrés, S C; Zaritzky, N E; Califano, A N

    2009-08-01

    Long-chain polyunsaturated n-3 fatty acids are critical nutrients for human health and the fortification of foods with these fatty acids is an important emerging area from the commercial and academic point of view. Development, characterization, and changes during refrigerated vacuum storage of low-fat chicken sausages formulated with preemulsified squid oil were examined and compared with those formulated with beef tallow. Physicochemical analysis and process yield after heat treatment were determined; the heat-treated sausages were evaluated by purge loss, color, texture, microstructure by SEM, microbial counts, fatty acid profile, lipid oxidation, and sensory analysis during refrigerated vacuum storage. Process yield of both formulations was higher than 97% and purge losses during storage were lower than 7%. Purge losses of oil-formulated sausages were lower than those with beef tallow. Sausages with squid oil resulted in higher lightness, lower redness and yellowness, and lower texture profile analysis parameters than the formulation prepared with beef tallow. Microstructure of both formulations was similar, except for the fat droplets that microscopic observations showed in the sausages made with beef tallow. Low lipid oxidation was detected in formulation with squid oil due to the the combination of ingredients and storage conditions. Microbial counts of both products were less than 5 log cfu/g at the end of 90 d of storage. The sausage formulated with squid oil presented more than 30 and 40 g/100 g of monounsaturated and polyunsaturated fatty acids, respectively. Docosahexaenoic acid was the predominant polyunsaturated fatty acid, followed by eicosapentaenoic acid and linoleic acid. Both products showed safe sanitary conditions, good sensory acceptability, and presented very good stability and quality attributes, but sausages formulated with squid oil showed a better fatty acid profile according to nutritional criteria.

  20. 21 CFR 177.2800 - Textiles and textile fibers.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ..., preparing, treating, packaging, transporting, or holding food, subject to the provisions of this section. (a..., sperm, and tall oils and tallow. Fats, oils, fatty acids, and fatty alcohols described in the preceding...

  1. Non-catalytic steam hydrolysis of fats. Final report

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Deibert, M.C.

    1992-08-28

    Hydrolysis of fats and oils produces fatty acid and glycerol. The catalyzed, liquid phase Colgate-Emry process, state-of-the-art, produces impure products that require extensive energy investment for their purification to commercial grade. Non-catalytic steam hydrolysis may produce products more easily purified. A bench-scale hydrolyzer was designed and constructed to contact descending liquid fat or oil with rising superheated steam. Each of the five stages in the reactor was designed similar to a distillation column stage to promote intimate liquid-gas contact. Degree of hydrolysis achieved in continuous tests using tallow feed were 15% at 280C and 35% at 300C at a tallow-to-steammore » mass feed ratio of 4.2. At a feed ratio of 9.2, the degree of hydrolysis was 21% at 300C. Decomposition was strongly evident at 325C but not at lower temperatures. Soybean oil rapidly polymerized under reaction conditions. Batch tests at 320C produced degrees of hydrolyses of between 44% and 63% using tallow and palm oil feeds. Over 95% fatty acids were present in a clean, readily separated organic portion of the overhead product from most tests. The test reactor had serious hydraulic resistance to liquid down-flow which limited operation to very long liquid residence times. These times are in excess of those that tallow and palm oil are stable at the reaction temperature. Little glycerol and extensive light organics were produced indicating that unexplained competing reactions to hydrolysis occurred in the experimental system. Further tests using an improved reactor will be required.« less

  2. Non-catalytic steam hydrolysis of fats

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Deibert, M.C.

    1992-08-28

    Hydrolysis of fats and oils produces fatty acid and glycerol. The catalyzed, liquid phase Colgate-Emry process, state-of-the-art, produces impure products that require extensive energy investment for their purification to commercial grade. Non-catalytic steam hydrolysis may produce products more easily purified. A bench-scale hydrolyzer was designed and constructed to contact descending liquid fat or oil with rising superheated steam. Each of the five stages in the reactor was designed similar to a distillation column stage to promote intimate liquid-gas contact. Degree of hydrolysis achieved in continuous tests using tallow feed were 15% at 280C and 35% at 300C at a tallow-to-steammore » mass feed ratio of 4.2. At a feed ratio of 9.2, the degree of hydrolysis was 21% at 300C. Decomposition was strongly evident at 325C but not at lower temperatures. Soybean oil rapidly polymerized under reaction conditions. Batch tests at 320C produced degrees of hydrolyses of between 44% and 63% using tallow and palm oil feeds. Over 95% fatty acids were present in a clean, readily separated organic portion of the overhead product from most tests. The test reactor had serious hydraulic resistance to liquid down-flow which limited operation to very long liquid residence times. These times are in excess of those that tallow and palm oil are stable at the reaction temperature. Little glycerol and extensive light organics were produced indicating that unexplained competing reactions to hydrolysis occurred in the experimental system. Further tests using an improved reactor will be required.« less

  3. Manipulation of Host Diet To Reduce Gastrointestinal Colonization by the Opportunistic Pathogen Candida albicans

    PubMed Central

    Tornberg-Belanger, Stephanie N.; Matthan, Nirupa R.; Lichtenstein, Alice H.

    2015-01-01

    ABSTRACT Candida albicans, the most common human fungal pathogen, can cause systemic infections with a mortality rate of ~40%. Infections arise from colonization of the gastrointestinal (GI) tract, where C. albicans is part of the normal microflora. Reducing colonization in at-risk patients using antifungal drugs prevents C. albicans-associated mortalities. C. albicans provides a clinically relevant system for studying the relationship between diet and the microbiota as it relates to commensalism and pathogenicity. As a first step toward a dietary intervention to reduce C. albicans GI colonization, we investigated the impact of dietary lipids on murine colonization by C. albicans. Coconut oil and its constituent fatty acids have antifungal activity in vitro; we hypothesized that dietary coconut oil would reduce GI colonization by C. albicans. Colonization was lower in mice fed a coconut oil-rich diet than in mice fed diets rich in beef tallow or soybean oil. Switching beef tallow-fed mice to a coconut oil diet reduced preexisting colonization. Coconut oil reduced colonization even when the diet also contained beef tallow. Dietary coconut oil also altered the metabolic program of colonizing C. albicans cells. Long-chain fatty acids were less abundant in the cecal contents of coconut oil-fed mice than in the cecal contents of beef tallow-fed mice; the expression of genes involved in fatty acid utilization was lower in C. albicans from coconut oil-fed mice than in C. albicans from beef tallow-fed mice. Extrapolating to humans, these findings suggest that coconut oil could become the first dietary intervention to reduce C. albicans GI colonization. IMPORTANCE Candida albicans, the most common human fungal pathogen, can cause infections with a mortality rate of ~40%. C. albicans is part of the normal gut flora, but when a patient’s immune system is compromised, it can leave the gut and cause infections. By reducing the amount of C. albicans in the gut of

  4. Graph Kernels for Molecular Similarity.

    PubMed

    Rupp, Matthias; Schneider, Gisbert

    2010-04-12

    Molecular similarity measures are important for many cheminformatics applications like ligand-based virtual screening and quantitative structure-property relationships. Graph kernels are formal similarity measures defined directly on graphs, such as the (annotated) molecular structure graph. Graph kernels are positive semi-definite functions, i.e., they correspond to inner products. This property makes them suitable for use with kernel-based machine learning algorithms such as support vector machines and Gaussian processes. We review the major types of kernels between graphs (based on random walks, subgraphs, and optimal assignments, respectively), and discuss their advantages, limitations, and successful applications in cheminformatics. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Beneficial effect of an omega-6 PUFA-rich diet in non-steroidal anti-inflammatory drug-induced mucosal damage in the murine small intestine.

    PubMed

    Ueda, Toshihide; Hokari, Ryota; Higashiyama, Masaaki; Yasutake, Yuichi; Maruta, Koji; Kurihara, Chie; Tomita, Kengo; Komoto, Shunsuke; Okada, Yoshikiyo; Watanabe, Chikako; Usui, Shingo; Nagao, Shigeaki; Miura, Soichiro

    2015-01-07

    To investigate the effect of a fat rich diet on non-steroidal anti-inflammatory drug (NSAID)-induced mucosal damage in the murine small intestine. C57BL6 mice were fed 4 types of diets with or without indomethacin. One group was fed standard laboratory chow. The other groups were fed a fat diet consisting of 8% w/w fat, beef tallow (rich in SFA), fish oil, (rich in omega-3 PUFA), or safflower oil (rich in omega-6 PUFA). Indomethacin (3 mg/kg) was injected intraperitoneally from day 8 to day 10. On day 11, intestines and adhesions to submucosal microvessels were examined. In the indomethacin-treated groups, mucosal damage was exacerbated by diets containing beef tallow and fish oil, and was accompanied by leukocyte infiltration (P < 0.05). The mucosal damage induced by indomethacin was significantly lower in mice fed the safflower oil diet than in mice fed the beef tallow or fish oil diet (P < 0.05). Indomethacin increased monocyte and platelet migration to the intestinal mucosa, whereas safflower oil significantly decreased monocyte and platelet recruitment (P < 0.05). A diet rich in SFA and omega-3 PUFA exacerbated NSAID-induced small intestinal damage via increased leukocyte infiltration. Importantly, a diet rich in omega-6-PUFA did not aggravate inflammation as monocyte migration was blocked.

  6. Beneficial effect of an omega-6 PUFA-rich diet in non-steroidal anti-inflammatory drug-induced mucosal damage in the murine small intestine

    PubMed Central

    Ueda, Toshihide; Hokari, Ryota; Higashiyama, Masaaki; Yasutake, Yuichi; Maruta, Koji; Kurihara, Chie; Tomita, Kengo; Komoto, Shunsuke; Okada, Yoshikiyo; Watanabe, Chikako; Usui, Shingo; Nagao, Shigeaki; Miura, Soichiro

    2015-01-01

    AIM: To investigate the effect of a fat rich diet on non-steroidal anti-inflammatory drug (NSAID)-induced mucosal damage in the murine small intestine. METHODS: C57BL6 mice were fed 4 types of diets with or without indomethacin. One group was fed standard laboratory chow. The other groups were fed a fat diet consisting of 8% w/w fat, beef tallow (rich in SFA), fish oil, (rich in omega-3 PUFA), or safflower oil (rich in omega-6 PUFA). Indomethacin (3 mg/kg) was injected intraperitoneally from day 8 to day 10. On day 11, intestines and adhesions to submucosal microvessels were examined. RESULTS: In the indomethacin-treated groups, mucosal damage was exacerbated by diets containing beef tallow and fish oil, and was accompanied by leukocyte infiltration (P < 0.05). The mucosal damage induced by indomethacin was significantly lower in mice fed the safflower oil diet than in mice fed the beef tallow or fish oil diet (P < 0.05). Indomethacin increased monocyte and platelet migration to the intestinal mucosa, whereas safflower oil significantly decreased monocyte and platelet recruitment (P < 0.05). CONCLUSION: A diet rich in SFA and omega-3 PUFA exacerbated NSAID-induced small intestinal damage via increased leukocyte infiltration. Importantly, a diet rich in omega-6-PUFA did not aggravate inflammation as monocyte migration was blocked. PMID:25574090

  7. Protective Effect of Pulp Oil Extracted from Canarium odontophyllum Miq. Fruit on Blood Lipids, Lipid Peroxidation, and Antioxidant Status in Healthy Rabbits

    PubMed Central

    Shakirin, Faridah Hanim; Azlan, Azrina; Ismail, Amin; Amom, Zulkhairi; Cheng Yuon, Lau

    2012-01-01

    The aim of this paper was to compare the effects of pulp and kernel oils of Canarium odontophyllum Miq. (CO) on lipid profile, lipid peroxidation, and oxidative stress of healthy rabbits. The oils are rich in SFAs and MUFAs (mainly palmitic and oleic acids). The pulp oil is rich in polyphenols. Male New Zealand white (NZW) rabbits were fed for 4 weeks on a normal diet containing pulp (NP) or kernel oil (NK) of CO while corn oil was used as control (NC). Total cholesterol (TC), HDL-C, LDL-c and triglycerides (TG) levels were measured in this paper. Antioxidant enzymes (superoxide dismutase and glutathione peroxidise), thiobarbiturate reactive substances (TBARSs), and plasma total antioxidant status (TAS) were also evaluated. Supplementation of CO pulp oil resulted in favorable changes in blood lipid and lipid peroxidation (increased HDL-C, reduced LDL-C, TG, TBARS levels) with enhancement of SOD, GPx, and plasma TAS levels. Meanwhile, supplementation of kernel oil caused lowering of plasma TC and LDL-C as well as enhancement of SOD and TAS levels. These changes showed that oils of CO could be beneficial in improving lipid profile and antioxidant status as when using part of normal diet. The oils can be used as alternative to present vegetable oil. PMID:22685623

  8. Protective effect of pulp oil extracted from Canarium odontophyllum Miq. Fruit on blood lipids, lipid peroxidation, and antioxidant status in healthy rabbits.

    PubMed

    Shakirin, Faridah Hanim; Azlan, Azrina; Ismail, Amin; Amom, Zulkhairi; Yuon, Lau Cheng

    2012-01-01

    The aim of this paper was to compare the effects of pulp and kernel oils of Canarium odontophyllum Miq. (CO) on lipid profile, lipid peroxidation, and oxidative stress of healthy rabbits. The oils are rich in SFAs and MUFAs (mainly palmitic and oleic acids). The pulp oil is rich in polyphenols. Male New Zealand white (NZW) rabbits were fed for 4 weeks on a normal diet containing pulp (NP) or kernel oil (NK) of CO while corn oil was used as control (NC). Total cholesterol (TC), HDL-C, LDL-c and triglycerides (TG) levels were measured in this paper. Antioxidant enzymes (superoxide dismutase and glutathione peroxidise), thiobarbiturate reactive substances (TBARSs), and plasma total antioxidant status (TAS) were also evaluated. Supplementation of CO pulp oil resulted in favorable changes in blood lipid and lipid peroxidation (increased HDL-C, reduced LDL-C, TG, TBARS levels) with enhancement of SOD, GPx, and plasma TAS levels. Meanwhile, supplementation of kernel oil caused lowering of plasma TC and LDL-C as well as enhancement of SOD and TAS levels. These changes showed that oils of CO could be beneficial in improving lipid profile and antioxidant status as when using part of normal diet. The oils can be used as alternative to present vegetable oil.

  9. The host range and impact of Bikasha collaris (Coleoptera: Chrysomelidae), a promising candidate agent for biological control of Chinese tallow, Triadica sebifera (Euphorbiaceae) in the United States

    USDA-ARS?s Scientific Manuscript database

    Native to China, the Chinese tallow, Triadica sebifera (Euphorbiaceae) is an aggressive woody invader in the southeastern United States. The flea beetle, Bikasha collaris (Coleoptera: Chrysomelidae), is a common herbivore attacking this plant in China. To evaluate its potential as a biological contr...

  10. Comparing Alternative Kernels for the Kernel Method of Test Equating: Gaussian, Logistic, and Uniform Kernels. Research Report. ETS RR-08-12

    ERIC Educational Resources Information Center

    Lee, Yi-Hsuan; von Davier, Alina A.

    2008-01-01

    The kernel equating method (von Davier, Holland, & Thayer, 2004) is based on a flexible family of equipercentile-like equating functions that use a Gaussian kernel to continuize the discrete score distributions. While the classical equipercentile, or percentile-rank, equating method carries out the continuization step by linear interpolation,…

  11. Level of selected toxic elements in meat, liver, tallow and bone marrow of young semi-domesticated reindeer (Rangifer tarandus tarandus L.) from Northern Norway

    PubMed Central

    Hassan, Ammar Ali; Rylander, Charlotta; Brustad, Magritt; Sandanger, Torkjel M.

    2012-01-01

    Objectives To gain knowledge on toxic elements in semi-domesticated reindeer and their distribution in meat, liver, tallow and bone marrow. The correlations between concentrations in meat and liver, as well as the use of the latter as an indicator for toxic elements in meat, were also investigated. Study design Cross-sectional study on population of semi-domesticated reindeer from 2 northern Norwegian counties (Finnmark and Nordland). Methods Semi-domesticated reindeer carcasses (n=31) were randomly selected, from which meat, liver, tallow and bone marrow samples were collected. Selected toxic elements (cadmium, lead, arsenic, nickel and vanadium) were studied. Results Liver was the organ with the highest level of all elements except for nickel, which was highest in bone marrow. Meat had the lowest levels, whereas levels in tallow and bone marrow were between those of meat and liver. Concentrations of cadmium, lead and arsenic were significantly different (p<0.05) between meat and liver, while only arsenic and cadmium were significantly correlated in meat (rs=0.71, p<0.01) and liver (rs=0.72, p<0.01). The cadmium level exceeded the European Commission's (EC) maximum level set for bovine meat and live in 52% of the liver samples (n=29). Nevertheless, the estimated monthly cadmium intake from liver of 2.29 µg/kg body weight was well below the provisional tolerable monthly intake of 25 µg/kg body weight set by the FAO/WHO Joint Expert Committee on Food Additives. Conclusions Based on the measured levels and their relation to the maximum level and to the provisional tolerable weekly/monthly intake limits, it could be inferred that consumption of reindeer meat is not associated with any health risk related to the studied toxic elements for consumers. PMID:22564461

  12. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  13. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  14. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  15. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  16. 7 CFR 981.401 - Adjusted kernel weight.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... based on the analysis of a 1,000 gram sample taken from a lot of almonds weighing 10,000 pounds with less than 95 percent kernels, and a 1,000 gram sample taken from a lot of almonds weighing 10,000... percent kernels containing the following: Edible kernels, 530 grams; inedible kernels, 120 grams; foreign...

  17. 7 CFR 51.1403 - Kernel color classification.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

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

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

    PubMed

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

    2017-12-01

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

  19. Out-of-Sample Extensions for Non-Parametric Kernel Methods.

    PubMed

    Pan, Binbin; Chen, Wen-Sheng; Chen, Bo; Xu, Chen; Lai, Jianhuang

    2017-02-01

    Choosing suitable kernels plays an important role in the performance of kernel methods. Recently, a number of studies were devoted to developing nonparametric kernels. Without assuming any parametric form of the target kernel, nonparametric kernel learning offers a flexible scheme to utilize the information of the data, which may potentially characterize the data similarity better. The kernel methods using nonparametric kernels are referred to as nonparametric kernel methods. However, many nonparametric kernel methods are restricted to transductive learning, where the prediction function is defined only over the data points given beforehand. They have no straightforward extension for the out-of-sample data points, and thus cannot be applied to inductive learning. In this paper, we show how to make the nonparametric kernel methods applicable to inductive learning. The key problem of out-of-sample extension is how to extend the nonparametric kernel matrix to the corresponding kernel function. A regression approach in the hyper reproducing kernel Hilbert space is proposed to solve this problem. Empirical results indicate that the out-of-sample performance is comparable to the in-sample performance in most cases. Experiments on face recognition demonstrate the superiority of our nonparametric kernel method over the state-of-the-art parametric kernel methods.

  20. Computed tomography coronary stent imaging with iterative reconstruction: a trade-off study between medium kernel and sharp kernel.

    PubMed

    Zhou, Qijing; Jiang, Biao; Dong, Fei; Huang, Peiyu; Liu, Hongtao; Zhang, Minming

    2014-01-01

    To evaluate the improvement of iterative reconstruction in image space (IRIS) technique in computed tomographic (CT) coronary stent imaging with sharp kernel, and to make a trade-off analysis. Fifty-six patients with 105 stents were examined by 128-slice dual-source CT coronary angiography (CTCA). Images were reconstructed using standard filtered back projection (FBP) and IRIS with both medium kernel and sharp kernel applied. Image noise and the stent diameter were investigated. Image noise was measured both in background vessel and in-stent lumen as objective image evaluation. Image noise score and stent score were performed as subjective image evaluation. The CTCA images reconstructed with IRIS were associated with significant noise reduction compared to that of CTCA images reconstructed using FBP technique in both of background vessel and in-stent lumen (the background noise decreased by approximately 25.4% ± 8.2% in medium kernel (P kernel (P kernel (P kernel (P kernel showed better visualization of the stent struts and in-stent lumen than that with medium kernel. Iterative reconstruction in image space reconstruction can effectively reduce the image noise and improve image quality. The sharp kernel images constructed with iterative reconstruction are considered the optimal images to observe coronary stents in this study.

  1. Alternative Fuels Data Center: Hydrogenation-Derived Renewable Diesel

    Science.gov Websites

    rapeseed oil; animal tallow; vegetable oil waste or brown trap grease; and other fats and vegetable oils new pipelines, storage tanks, or retail station pumps), can be produced using existing oil refinery manufacturers-including ConocoPhillips, Neste Oil, Petrobras, REG, and UOP-are developing and testing HDRD

  2. Antinutritional factors and hypocholesterolemic effect of wild apricot kernel (Prunus armeniaca L.) as affected by detoxification.

    PubMed

    Tanwar, Beenu; Modgil, Rajni; Goyal, Ankit

    2018-04-25

    The present investigation was aimed to study the effect of detoxification on the nutrients and antinutrients of wild apricot kernel followed by its hypocholesterolemic effect in male Wistar albino rats. The results revealed a non-significant (p > 0.05) effect of detoxification on the proximate composition except total carbohydrates and protein content. However, detoxification led to a significant (p < 0.05) decrease in l-ascorbic acid (76.82%), β-carotene (25.90%), dietary fiber constituents (10.51-28.92%), minerals (4.76-31.08%) and antinutritional factors (23.92-77.05%) (phenolics, tannins, trypsin inhibitor activity, saponins, phytic acid, alkaloids, flavonoids, oxalates) along with the complete removal (100%) of bitter and potentially toxic hydrocyanic acid (HCN). The quality parameters of kernel oil indicated no adverse effects of detoxification on free fatty acids, lipase activity, acid value and peroxide value, which remained well below the maximum permissible limit. Blood lipid profile demonstrated that the detoxified apricot kernel group exhibited significantly (p < 0.05) increased levels of HDL-cholesterol (48.79%) and triglycerides (15.09%), and decreased levels of total blood cholesterol (6.99%), LDL-C (22.95%) and VLDL-C (7.90%) compared to that of the raw (untreated) kernel group. Overall, it can be concluded that wild apricot kernel flour could be detoxified efficiently by employing a simple, safe, domestic and cost-effective method, which further has the potential for formulating protein supplements and value-added food products.

  3. Anisotropic hydrodynamics with a scalar collisional kernel

    NASA Astrophysics Data System (ADS)

    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.

  4. Ranking Support Vector Machine with Kernel Approximation

    PubMed Central

    Dou, Yong

    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. PMID:28293256

  5. Ranking Support Vector Machine with Kernel Approximation.

    PubMed

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

    2017-01-01

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

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

    PubMed

    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.

  7. Applicability of spectral indices on thickness identification of oil slick

    NASA Astrophysics Data System (ADS)

    Niu, Yanfei; Shen, Yonglin; Chen, Qihao; Liu, Xiuguo

    2016-10-01

    Hyperspectral remote sensing technology has played a vital role in the identification and monitoring of oil spill events, and amount of spectral indices have been developed. In this paper, the applicability of six frequently-used indices is analyzed, and a combination of spectral indices in aids of support vector machine (SVM) algorithm is used to identify the oil slicks and corresponding thickness. The six spectral indices are spectral rotation (SR), spectral absorption depth (HI), band ratio of blue and green (BG), band ratio of BG and shortwave infrared index (BGN), 555nm and 645nm normalized by the blue band index (NB) and spectral slope (ND). The experimental study is conducted in the Gulf of Mexico oil spill zone, with Airborne Visible Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery captured in May 17, 2010. The results show that SR index is the best in all six indices, which can effectively distinguish the thickness of the oil slick and identify it from seawater; HI index and ND index can obviously distinguish oil slick thickness; BG, BGN and NB are more suitable to identify oil slick from seawater. With the comparison among different kernel functions of SVM, the classify accuracy show that the polynomial and RBF kernel functions have the best effect on the separation of oil slick thickness and the relatively pure seawater. The applicability of spectral indices of oil slick and the method of oil film thickness identification will in aids of oil/gas exploration and oil spill monitoring.

  8. Wigner functions defined with Laplace transform kernels.

    PubMed

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

    2011-10-24

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

  9. Metabolic network prediction through pairwise rational kernels.

    PubMed

    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

  10. Conversion of vegetable oils and animal fats into paraffinic cetane enhancers for diesel fuels

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wong, A.; Feng, Y.; Hogan, E.

    1995-11-01

    The two principal methods of producing biodiesel fuels are (a) transesterification of vegetable oils and animal fats with a monohydric alcohol, and (b) direct hydrotreating of tree oils, vegetable oils and animal fats. The patented hydrotreating technology is based on the catalytic processing of biomass oils and fats with hydrogen, under elevated temperature and pressure conditions. The typical mix of hydrotreated products is as follows: 5-15% light distillate (naphta), 40-60% middle distillate (cetane), 5-15% heavy distillate and 5-10% burner gas. The naptha fraction may be used as a gasoline supplement. The middle distillate is designed for use as a cetanemore » booster for diesel fuels. Both heavy distillate and light hydrocarbon gases are usable as power boiler fuels. Typically, the cetane enhancer would be admixed with diesel fuel in the range of 5 to 30% by volume. This new diesel blend meets the essential quality characteristics of the basic diesel fuel, for direct use in diesel engines without any modifications. The basic hydrotreatment technology has been evaluated further in the laboratory on degummed soya oil, yellow grease and animal tallow. The preliminary findings suggest that the technology can provide efficient conversion of these materials into cetane enhancers for diesel fuels.« less

  11. Effect of lipid type on growth performance, meat quality and the content of long chain n-3 fatty acids in pork meat.

    PubMed

    Morel, Patrick C H; Leong, Jasmine; Nuijten, Wilhelmina G M; Purchas, Roger W; Wilkinson, Brian H P

    2013-10-01

    The aim of the present study was to produce pork with enhanced nutritive value for humans, both in terms of fatty acid profile (mainly long chain n-3 fatty acids by feeding fish oil) and selenium. Forty-eight female pigs were allocated to one of six treatment groups: animal by-products and plant feedstuffs with tallow, plant feedstuffs with a blend of soybean oil and linseed oil with or without a supplement (CLA, selenium, vitamin E and vitamin C), plant feedstuffs with tallow and supplement, plant feedstuffs with fish oil and supplement. The diets containing the fish oil were fed up to either 49 days or 28 days before slaughter. The dietary treatments had no significant effects on growth performance, carcass characteristics and meat quality. When fish oil was included in the diet, higher levels of EPA, DPA and DHA were measured in the subcutaneous fat (up to 3.74%). Copyright © 2013 Elsevier Ltd. All rights reserved.

  12. Ideal regularization for learning kernels from labels.

    PubMed

    Pan, Binbin; Lai, Jianhuang; Shen, Lixin

    2014-08-01

    In this paper, we propose a new form of regularization that is able to utilize the label information of a data set for learning kernels. The proposed regularization, referred to as ideal regularization, is a linear function of the kernel matrix to be learned. The ideal regularization allows us to develop efficient algorithms to exploit labels. Three applications of the ideal regularization are considered. Firstly, we use the ideal regularization to incorporate the labels into a standard kernel, making the resulting kernel more appropriate for learning tasks. Next, we employ the ideal regularization to learn a data-dependent kernel matrix from an initial kernel matrix (which contains prior similarity information, geometric structures, and labels of the data). Finally, we incorporate the ideal regularization to some state-of-the-art kernel learning problems. With this regularization, these learning problems can be formulated as simpler ones which permit more efficient solvers. Empirical results show that the ideal regularization exploits the labels effectively and efficiently. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. SEMI-SUPERVISED OBJECT RECOGNITION USING STRUCTURE KERNEL

    PubMed Central

    Wang, Botao; Xiong, Hongkai; Jiang, Xiaoqian; Ling, Fan

    2013-01-01

    Object recognition is a fundamental problem in computer vision. Part-based models offer a sparse, flexible representation of objects, but suffer from difficulties in training and often use standard kernels. In this paper, we propose a positive definite kernel called “structure kernel”, which measures the similarity of two part-based represented objects. The structure kernel has three terms: 1) the global term that measures the global visual similarity of two objects; 2) the part term that measures the visual similarity of corresponding parts; 3) the spatial term that measures the spatial similarity of geometric configuration of parts. The contribution of this paper is to generalize the discriminant capability of local kernels to complex part-based object models. Experimental results show that the proposed kernel exhibit higher accuracy than state-of-art approaches using standard kernels. PMID:23666108

  14. The pre-image problem in kernel methods.

    PubMed

    Kwok, James Tin-yau; Tsang, Ivor Wai-hung

    2004-11-01

    In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applications, such as on using kernel principal component analysis (PCA) for image denoising. Unlike the traditional method which relies on nonlinear optimization, our proposed method directly finds the location of the pre-image based on distance constraints in the feature space. It is noniterative, involves only linear algebra and does not suffer from numerical instability or local minimum problems. Evaluations on performing kernel PCA and kernel clustering on the USPS data set show much improved performance.

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

    PubMed

    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

  16. Correlation and classification of single kernel fluorescence hyperspectral data with aflatoxin concentration in corn kernels inoculated with Aspergillus flavus spores.

    PubMed

    Yao, H; Hruska, Z; Kincaid, R; Brown, R; Cleveland, T; Bhatnagar, D

    2010-05-01

    The objective of this study was to examine the relationship between fluorescence emissions of corn kernels inoculated with Aspergillus flavus and aflatoxin contamination levels within the kernels. Aflatoxin contamination in corn has been a long-standing problem plaguing the grain industry with potentially devastating consequences to corn growers. In this study, aflatoxin-contaminated corn kernels were produced through artificial inoculation of corn ears in the field with toxigenic A. flavus spores. The kernel fluorescence emission data were taken with a fluorescence hyperspectral imaging system when corn kernels were excited with ultraviolet light. Raw fluorescence image data were preprocessed and regions of interest in each image were created for all kernels. The regions of interest were used to extract spectral signatures and statistical information. The aflatoxin contamination level of single corn kernels was then chemically measured using affinity column chromatography. A fluorescence peak shift phenomenon was noted among different groups of kernels with different aflatoxin contamination levels. The fluorescence peak shift was found to move more toward the longer wavelength in the blue region for the highly contaminated kernels and toward the shorter wavelengths for the clean kernels. Highly contaminated kernels were also found to have a lower fluorescence peak magnitude compared with the less contaminated kernels. It was also noted that a general negative correlation exists between measured aflatoxin and the fluorescence image bands in the blue and green regions. The correlation coefficients of determination, r(2), was 0.72 for the multiple linear regression model. The multivariate analysis of variance found that the fluorescence means of four aflatoxin groups, <1, 1-20, 20-100, and >or=100 ng g(-1) (parts per billion), were significantly different from each other at the 0.01 level of alpha. Classification accuracy under a two-class schema ranged from 0.84 to

  17. Adaptive kernel function using line transect sampling

    NASA Astrophysics Data System (ADS)

    Albadareen, Baker; Ismail, Noriszura

    2018-04-01

    The estimation of f(0) is crucial in the line transect method which is used for estimating population abundance in wildlife survey's. The classical kernel estimator of f(0) has a high negative bias. Our study proposes an adaptation in the kernel function which is shown to be more efficient than the usual kernel estimator. A simulation study is adopted to compare the performance of the proposed estimators with the classical kernel estimators.

  18. Kernel K-Means Sampling for Nyström Approximation.

    PubMed

    He, Li; Zhang, Hong

    2018-05-01

    A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to describe most existing Nyström approximations under many popular kernels, including Gaussian kernel and polynomial kernel. We then show that, the matrix approximation error upper bound, in terms of the Frobenius norm, is equal to the -means error of data points in kernel space plus a constant. Thus, the -means centers of data in kernel space, or the kernel -means centers, are the optimal representative points with respect to the Frobenius norm error upper bound. Experimental results, with both Gaussian kernel and polynomial kernel, on real-world data sets and image segmentation tasks show the superiority of the proposed method over the state-of-the-art methods.

  19. 7 CFR 51.2125 - Split or broken kernels.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 2 2010-01-01 2010-01-01 false Split or broken kernels. 51.2125 Section 51.2125 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards... kernels. Split or broken kernels means seven-eighths or less of complete whole kernels but which will not...

  20. Robotic Intelligence Kernel: Driver

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    The INL Robotic Intelligence Kernel-Driver is built on top of the RIK-A and implements a dynamic autonomy structure. The RIK-D is used to orchestrate hardware for sensing and action as well as software components for perception, communication, behavior and world modeling into a single cognitive behavior kernel that provides intrinsic intelligence for a wide variety of unmanned ground vehicle systems.

  1. Bell nozzle kernel analysis program

    NASA Technical Reports Server (NTRS)

    Elliot, J. J.; Stromstra, R. R.

    1969-01-01

    Bell Nozzle Kernel Analysis Program computes and analyzes the supersonic flowfield in the kernel, or initial expansion region, of a bell or conical nozzle. It analyzes both plane and axisymmetric geometrices for specified gas properties, nozzle throat geometry and input line.

  2. 7 CFR 51.2296 - Three-fourths half kernel.

    Code of Federal Regulations, 2010 CFR

    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...

  3. 40 CFR 432.101 - Special definitions.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... animal and poultry trimmings, bones, meat scraps, dead animals, feathers and related usable by-products... 10 million pounds per year, produces meat meal, tankage, animal fats or oils, grease, and tallow, and may cure cattle hides, but excludes marine oils, fish meal, and fish oils. (c) Tankage means dried...

  4. Application of kernel method in fluorescence molecular tomography

    NASA Astrophysics Data System (ADS)

    Zhao, Yue; Baikejiang, Reheman; Li, Changqing

    2017-02-01

    Reconstruction of fluorescence molecular tomography (FMT) is an ill-posed inverse problem. Anatomical guidance in the FMT reconstruction can improve FMT reconstruction efficiently. We have developed a kernel method to introduce the anatomical guidance into FMT robustly and easily. The kernel method is from machine learning for pattern analysis and is an efficient way to represent anatomical features. For the finite element method based FMT reconstruction, we calculate a kernel function for each finite element node from an anatomical image, such as a micro-CT image. Then the fluorophore concentration at each node is represented by a kernel coefficient vector and the corresponding kernel function. In the FMT forward model, we have a new system matrix by multiplying the sensitivity matrix with the kernel matrix. Thus, the kernel coefficient vector is the unknown to be reconstructed following a standard iterative reconstruction process. We convert the FMT reconstruction problem into the kernel coefficient reconstruction problem. The desired fluorophore concentration at each node can be calculated accordingly. Numerical simulation studies have demonstrated that the proposed kernel-based algorithm can improve the spatial resolution of the reconstructed FMT images. In the proposed kernel method, the anatomical guidance can be obtained directly from the anatomical image and is included in the forward modeling. One of the advantages is that we do not need to segment the anatomical image for the targets and background.

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

    PubMed

    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.

  6. 7 CFR 868.254 - Broken kernels determination.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.254 Section 868.254 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Governing Application of Standards § 868.254 Broken kernels determination. Broken kernels shall be...

  7. Evaluating the Gradient of the Thin Wire Kernel

    NASA Technical Reports Server (NTRS)

    Wilton, Donald R.; Champagne, Nathan J.

    2008-01-01

    Recently, a formulation for evaluating the thin wire kernel was developed that employed a change of variable to smooth the kernel integrand, canceling the singularity in the integrand. Hence, the typical expansion of the wire kernel in a series for use in the potential integrals is avoided. The new expression for the kernel is exact and may be used directly to determine the gradient of the wire kernel, which consists of components that are parallel and radial to the wire axis.

  8. KITTEN Lightweight Kernel 0.1 Beta

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Pedretti, Kevin; Levenhagen, Michael; Kelly, Suzanne

    2007-12-12

    The Kitten Lightweight Kernel is a simplified OS (operating system) kernel that is intended to manage a compute node's hardware resources. It provides a set of mechanisms to user-level applications for utilizing hardware resources (e.g., allocating memory, creating processes, accessing the network). Kitten is much simpler than general-purpose OS kernels, such as Linux or Windows, but includes all of the esssential functionality needed to support HPC (high-performance computing) MPI, PGAS and OpenMP applications. Kitten provides unique capabilities such as physically contiguous application memory, transparent large page support, and noise-free tick-less operation, which enable HPC applications to obtain greater efficiency andmore » scalability than with general purpose OS kernels.« less

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

    PubMed

    Kwak, Nojun

    2016-05-20

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

  10. Nutritional value of high fiber co-products from the copra, palm kernel, and rice industries in diets fed to pigs.

    PubMed

    Stein, Hans Henrik; Casas, Gloria Amparo; Abelilla, Jerubella Jerusalem; Liu, Yanhong; Sulabo, Rommel Casilda

    2015-01-01

    High fiber co-products from the copra and palm kernel industries are by-products of the production of coconut oil and palm kernel oil. The co-products include copra meal, copra expellers, palm kernel meal, and palm kernel expellers. All 4 ingredients are very high in fiber and the energy value is relatively low when fed to pigs. The protein concentration is between 14 and 22 % and the protein has a low biological value and a very high Arg:Lys ratio. Digestibility of most amino acids is less than in soybean meal but close to that in corn. However, the digestibility of Lys is sometimes low due to Maillard reactions that are initiated due to overheating during drying. Copra and palm kernel ingredients contain 0.5 to 0.6 % P. Most of the P in palm kernel meal and palm kernel expellers is bound to phytate, but in copra products less than one third of the P is bound to phytate. The digestibility of P is, therefore, greater in copra meal and copra expellers than in palm kernel ingredients. Inclusion of copra meal should be less than 15 % in diets fed to weanling pigs and less than 25 % in diets for growing-finishing pigs. Palm kernel meal may be included by 15 % in diets for weanling pigs and 25 % in diets for growing and finishing pigs. Rice bran contains the pericarp and aleurone layers of brown rice that is removed before polished rice is produced. Rice bran contains approximately 25 % neutral detergent fiber and 25 to 30 % starch. Rice bran has a greater concentration of P than most other plant ingredients, but 75 to 90 % of the P is bound in phytate. Inclusion of microbial phytase in the diets is, therefore, necessary if rice bran is used. Rice bran may contain 15 to 24 % fat, but it may also have been defatted in which case the fat concentration is less than 5 %. Concentrations of digestible energy (DE) and metabolizable energy (ME) are slightly less in full fat rice bran than in corn, but defatted rice bran contains less than 75 % of the DE and ME in

  11. 7 CFR 868.304 - Broken kernels determination.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 7 2011-01-01 2011-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

  12. 7 CFR 868.304 - Broken kernels determination.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 7 2010-01-01 2010-01-01 false Broken kernels determination. 868.304 Section 868.304 Agriculture Regulations of the Department of Agriculture (Continued) GRAIN INSPECTION, PACKERS AND STOCKYARD... Application of Standards § 868.304 Broken kernels determination. Broken kernels shall be determined by the use...

  13. Kernel learning at the first level of inference.

    PubMed

    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.

  14. 40 CFR 432.101 - Special definitions.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... renderer composed of animal and poultry trimmings, bones, meat scraps, dead animals, feathers and related... at rates greater than 10 million pounds per year, produces meat meal, tankage, animal fats or oils, grease, and tallow, and may cure cattle hides, but excludes marine oils, fish meal, and fish oils. (c...

  15. 40 CFR 432.101 - Special definitions.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... renderer composed of animal and poultry trimmings, bones, meat scraps, dead animals, feathers and related... at rates greater than 10 million pounds per year, produces meat meal, tankage, animal fats or oils, grease, and tallow, and may cure cattle hides, but excludes marine oils, fish meal, and fish oils. (c...

  16. 40 CFR 432.101 - Special definitions.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... renderer composed of animal and poultry trimmings, bones, meat scraps, dead animals, feathers and related... at rates greater than 10 million pounds per year, produces meat meal, tankage, animal fats or oils, grease, and tallow, and may cure cattle hides, but excludes marine oils, fish meal, and fish oils. (c...

  17. Multiple kernels learning-based biological entity relationship extraction method.

    PubMed

    Dongliang, Xu; Jingchang, Pan; Bailing, Wang

    2017-09-20

    Automatic extracting protein entity interaction information from biomedical literature can help to build protein relation network and design new drugs. There are more than 20 million literature abstracts included in MEDLINE, which is the most authoritative textual database in the field of biomedicine, and follow an exponential growth over time. This frantic expansion of the biomedical literature can often be difficult to absorb or manually analyze. Thus efficient and automated search engines are necessary to efficiently explore the biomedical literature using text mining techniques. The P, R, and F value of tag graph method in Aimed corpus are 50.82, 69.76, and 58.61%, respectively. The P, R, and F value of tag graph kernel method in other four evaluation corpuses are 2-5% higher than that of all-paths graph kernel. And The P, R and F value of feature kernel and tag graph kernel fuse methods is 53.43, 71.62 and 61.30%, respectively. The P, R and F value of feature kernel and tag graph kernel fuse methods is 55.47, 70.29 and 60.37%, respectively. It indicated that the performance of the two kinds of kernel fusion methods is better than that of simple kernel. In comparison with the all-paths graph kernel method, the tag graph kernel method is superior in terms of overall performance. Experiments show that the performance of the multi-kernels method is better than that of the three separate single-kernel method and the dual-mutually fused kernel method used hereof in five corpus sets.

  18. Production of Mahua Oil Ethyl Ester (MOEE) and its Performance test on four stroke single cylinder VCR engine

    NASA Astrophysics Data System (ADS)

    Soudagar, Manzoor Elahi M.; Kittur, Prasanna; Parmar, Fulchand; Batakatti, Sachin; Kulkarni, Prasad; Kallannavar, Vinayak

    2017-08-01

    Biodiesel is a substitute for gasoline that is produced from vegetable oils and animal fats. It has gained popularity due to depleting fossil fuel resources, its renewable character and comparable combustion properties to diesel fuel. Biodiesel is formed from non-edible oils, edible oils, tallow, animal fats and waste cooked oils. Biodiesels are monoalkyl esters of elongated chain fatty acids. Biodiesel can be a viable choice for satisfying long term energy requirements if they are managed proficiently. The method of the transesterification shows how the reaction occurs and advances. In this study, biodiesel is produced from Madhuca indica seeds commonly known as Mahua by using transesterification process using a low capacity pressure reactor and by-product of transesterification is glycerol, which is used in preparation of soaps. Mahua Oil Ethyl Ester (MOEE) was produced from the Mahua oil and is mixed with diesel to get different ratios of blends. MOEE was tested in a 4-stroke single cylinder VCR diesel engine. The study was extended to understand the effect of biodiesel blend magnitude on the performance of engine parameters like, brake thermal efficiency, brake power and fuel properties like flash point, cloud point, kinematic viscosity, calorific value, cetane number and density were studied.

  19. Lack of promotion of colon carcinogenesis by high-oleic safflower oil.

    PubMed

    Takeshita, M; Ueda, H; Shirabe, K; Higuchi, Y; Yoshida, S

    1997-04-15

    The nonpromoting effect of olive oil on colon carcinogenesis has been attributed to its high oleic acid content, whereas a positive association of monounsaturated fat in beef tallow with colon tumors has been reported. The effect of constituents other than fatty acids could not be neglected in these experiments. In order to minimize the effects of minor constituents in the oils, the authors compared conventional safflower oil with oil from a mutant strain of safflower that is rich in oleic acid. ICR mice were treated with 1,2-dimethylhydrazine (DMH, 20 mg/kg body weight every week for 12 weeks) and then were fed either a high-fat diet (23.5% by weight), containing safflower oil (HF-LA) or high-oleic safflower oil (HF-OA), or a low-fat diet (5% by weight), containing safflower oil (LF-LA) or high-oleic safflower oil (LF-OA). The test diets were continued until termination of the experiment at 30 weeks after the first administration of DMH. Fatty acid composition of colon phospholipids was determined by gas-liquid chromatography-mass spectrometry. Tumor multiplicity in animals fed the HF-OA diet was indistinguishable from that in animals fed LF-LA or LF-OA. In contrast, animals fed the HF-LA diet had a significantly higher incidence of colon tumors (mostly adenocarcinomas) than the other groups. Fatty acid profiles of colon phospholipids reflected those of the diet. Animals fed a HF-LA diet showed a marked decrease of nervonic acid (C24:1, n-9) in the colon sphingomyelin. These data indicate that oleic acid does not enhance DMH-induced colon carcinogenesis in mice, even when they are fed a high-fat diet.

  20. 7 CFR 51.1403 - Kernel color classification.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2013-01-01 2013-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

  1. 7 CFR 51.1403 - Kernel color classification.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... generally conforms to the “light” or “light amber” classification, that color classification may be used to... 7 Agriculture 2 2014-01-01 2014-01-01 false Kernel color classification. 51.1403 Section 51.1403... Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be...

  2. Evidence-based Kernels: Fundamental Units of Behavioral Influence

    PubMed Central

    Biglan, Anthony

    2008-01-01

    This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior. PMID:18712600

  3. Integrating the Gradient of the Thin Wire Kernel

    NASA Technical Reports Server (NTRS)

    Champagne, Nathan J.; Wilton, Donald R.

    2008-01-01

    A formulation for integrating the gradient of the thin wire kernel is presented. This approach employs a new expression for the gradient of the thin wire kernel derived from a recent technique for numerically evaluating the exact thin wire kernel. This approach should provide essentially arbitrary accuracy and may be used with higher-order elements and basis functions using the procedure described in [4].When the source and observation points are close, the potential integrals over wire segments involving the wire kernel are split into parts to handle the singular behavior of the integrand [1]. The singularity characteristics of the gradient of the wire kernel are different than those of the wire kernel, and the axial and radial components have different singularities. The characteristics of the gradient of the wire kernel are discussed in [2]. To evaluate the near electric and magnetic fields of a wire, the integration of the gradient of the wire kernel needs to be calculated over the source wire. Since the vector bases for current have constant direction on linear wire segments, these integrals reduce to integrals of the form

  4. THERMOS. 30-Group ENDF/B Scattered Kernels

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    McCrosson, F.J.; Finch, D.R.

    1973-12-01

    These data are 30-group THERMOS thermal scattering kernels for P0 to P5 Legendre orders for every temperature of every material from s(alpha,beta) data stored in the ENDF/B library. These scattering kernels were generated using the FLANGE2 computer code. To test the kernels, the integral properties of each set of kernels were determined by a precision integration of the diffusion length equation and compared to experimental measurements of these properties. In general, the agreement was very good. Details of the methods used and results obtained are contained in the reference. The scattering kernels are organized into a two volume magnetic tapemore » library from which they may be retrieved easily for use in any 30-group THERMOS library.« less

  5. 21 CFR 172.854 - Polyglycerol esters of fatty acids.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Polyglycerol esters of fatty acids. 172.854... § 172.854 Polyglycerol esters of fatty acids. Polyglycerol esters of fatty acids, up to and including..., safflower oil, sesame oil, soybean oil, and tallow and the fatty acids derived from these substances...

  6. Gas chromatography-mass spectrometry screening for phytochemical 4-desmethylsterols accumulated during development of Tunisian peanut kernels (Arachis hypogaea L.).

    PubMed

    Cherif, Aicha O; Trabelsi, Hajer; Ben Messaouda, Mhamed; Kâabi, Belhassen; Pellerin, Isabelle; Boukhchina, Sadok; Kallel, Habib; Pepe, Claude

    2010-08-11

    4-Desmethylsterols, the main component of the phytosterol fraction, have been analyzed during the development of Tunisian peanut kernels ( Arachis hypogaea L.), Trabelsia (AraT) and Chounfakhi (AraC), which are monocultivar species, and Arbi (AraA), which is a wild species, by gas chromatography-mass spectrometry. Immature wild peanut (AraA) showed the highest contents of beta-sitosterol (554.8 mg/100 g of oil), campesterol (228.6 mg/100 g of oil), and Delta(5)-avenasterol (39.0 mg/100 g of oil) followed by peanut cultivar AraC with beta-sitosterol, campesterol, and Delta(5)-avenasterol averages of 267.7, 92.1, and 28.6 mg/100 g of oil, respectively, and similarly for AraT 309.1, 108.4, and 27.4 mg/100 g of oil, respectively, were found. These results suggest that, in immature stages, phytosterol contents can be important regulator factors for the functional quality of peanut oil for the agro-industry chain from plant to nutraceuticals.

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

  8. Brain tumor image segmentation using kernel dictionary learning.

    PubMed

    Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

    2015-08-01

    Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

  9. Development of a kernel function for clinical data.

    PubMed

    Daemen, Anneleen; De Moor, Bart

    2009-01-01

    For most diseases and examinations, clinical data such as age, gender and medical history guides clinical management, despite the rise of high-throughput technologies. To fully exploit such clinical information, appropriate modeling of relevant parameters is required. As the widely used linear kernel function has several disadvantages when applied to clinical data, we propose a new kernel function specifically developed for this data. This "clinical kernel function" more accurately represents similarities between patients. Evidently, three data sets were studied and significantly better performances were obtained with a Least Squares Support Vector Machine when based on the clinical kernel function compared to the linear kernel function.

  10. Towards the Geometry of Reproducing Kernels

    NASA Astrophysics Data System (ADS)

    Galé, J. E.

    2010-11-01

    It is shown here how one is naturally led to consider a category whose objects are reproducing kernels of Hilbert spaces, and how in this way a differential geometry for such kernels may be settled down.

  11. 21 CFR 177.2800 - Textiles and textile fibers.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ..., manufacturing, packing, processing, preparing, treating, packaging, transporting, or holding food, subject to..., cottonseed, fish, mustardseed, palm, peanut, rapeseed, ricebran, soybean, sperm, and tall oils and tallow...

  12. 21 CFR 177.2800 - Textiles and textile fibers.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ..., manufacturing, packing, processing, preparing, treating, packaging, transporting, or holding food, subject to..., cottonseed, fish, mustardseed, palm, peanut, rapeseed, ricebran, soybean, sperm, and tall oils and tallow...

  13. Effects of supplemental fat source on nutrient digestion and ruminal fermentation in steers.

    PubMed

    Montgomery, S P; Drouillard, J S; Nagaraja, T G; Titgemeyer, E C; Sindt, J J

    2008-03-01

    Five Holstein steers (235 kg of BW) fitted with ruminal, duodenal, and ileal cannulas were used in a 5 x 5 Latin square design experiment to determine the effects of supplemental fat source on site and extent of nutrient digestion and ruminal fermentation. Treatments were diets based on steam-flaked corn containing no supplemental fat (control) or 4% (DM basis) supplemental fat as tallow, dried full-fat corn germ (corn germ), corn oil, or flax oil. Fat supplementation decreased (P < 0.08) ruminal starch digestion but increased (P < 0.03) small intestinal starch digestion as a percentage of intake. Feeding corn germ decreased (P < 0.09) ruminal starch digestion and increased (P < 0.03) large intestinal starch digestion compared with steers fed corn oil. Large intestinal starch digestion was less (P < 0.04), and ruminal NDF digestion was greater (P < 0.09) for steers fed tallow compared with steers fed other fat sources. Small intestinal (P < 0.08) and total tract NDF digestibilities were greater (P < 0.02) for steers fed corn germ than for those fed corn oil. Feeding tallow increased total ruminal VFA (P < 0.03) and NH(3) (P < 0.07) concentrations compared with steers fed the other fat sources. Feeding corn germ led to a greater (P < 0.02) rate of ruminal liquid outflow compared with corn oil. A diet x hour interaction (P < 0.04) occurred for ruminal pH, with steers fed corn oil having the greatest ruminal pH 18 h after feeding, without differences at other time points. Fat supplementation increased (P < 0.09) ruminal concentrations of Fusobacterium necrophorum. Duodenal flow of C18:3n-3 was greater (P < 0.01) for steers fed flax oil compared with those fed corn oil. Feeding corn germ led to less (P < 0.01) ruminal biohydrogenation of fatty acids compared with corn oil. Steers fed tallow had greater small intestinal digestibility of C14:0 (P < 0.02) and C16:1 (P < 0.04) than steers fed the other fat sources. Fat supplementation decreased (P < 0.06) small intestinal

  14. Kernel-PCA data integration with enhanced interpretability

    PubMed Central

    2014-01-01

    Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge. PMID:25032747

  15. Gaussian mass optimization for kernel PCA parameters

    NASA Astrophysics Data System (ADS)

    Liu, Yong; Wang, Zulin

    2011-10-01

    This paper proposes a novel kernel parameter optimization method based on Gaussian mass, which aims to overcome the current brute force parameter optimization method in a heuristic way. Generally speaking, the choice of kernel parameter should be tightly related to the target objects while the variance between the samples, the most commonly used kernel parameter, doesn't possess much features of the target, which gives birth to Gaussian mass. Gaussian mass defined in this paper has the property of the invariance of rotation and translation and is capable of depicting the edge, topology and shape information. Simulation results show that Gaussian mass leads a promising heuristic optimization boost up for kernel method. In MNIST handwriting database, the recognition rate improves by 1.6% compared with common kernel method without Gaussian mass optimization. Several promising other directions which Gaussian mass might help are also proposed at the end of the paper.

  16. Design of CT reconstruction kernel specifically for clinical lung imaging

    NASA Astrophysics Data System (ADS)

    Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

    2005-04-01

    In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

  17. Quality changes in macadamia kernel between harvest and farm-gate.

    PubMed

    Walton, David A; Wallace, Helen M

    2011-02-01

    Macadamia integrifolia, Macadamia tetraphylla and their hybrids are cultivated for their edible kernels. After harvest, nuts-in-shell are partially dried on-farm and sorted to eliminate poor-quality kernels before consignment to a processor. During these operations, kernel quality may be lost. In this study, macadamia nuts-in-shell were sampled at five points of an on-farm postharvest handling chain from dehusking to the final storage silo to assess quality loss prior to consignment. Shoulder damage, weight of pieces and unsound kernel were assessed for raw kernels, and colour, mottled colour and surface damage for roasted kernels. Shoulder damage, weight of pieces and unsound kernel for raw kernels increased significantly between the dehusker and the final silo. Roasted kernels displayed a significant increase in dark colour, mottled colour and surface damage during on-farm handling. Significant loss of macadamia kernel quality occurred on a commercial farm during sorting and storage of nuts-in-shell before nuts were consigned to a processor. Nuts-in-shell should be dried as quickly as possible and on-farm handling minimised to maintain optimum kernel quality. 2010 Society of Chemical Industry.

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

    PubMed

    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.

  19. Quantum kernel applications in medicinal chemistry.

    PubMed

    Huang, Lulu; Massa, Lou

    2012-07-01

    Progress in the quantum mechanics of biological molecules is being driven by computational advances. The notion of quantum kernels can be introduced to simplify the formalism of quantum mechanics, making it especially suitable for parallel computation of very large biological molecules. The essential idea is to mathematically break large biological molecules into smaller kernels that are calculationally tractable, and then to represent the full molecule by a summation over the kernels. The accuracy of the kernel energy method (KEM) is shown by systematic application to a great variety of molecular types found in biology. These include peptides, proteins, DNA and RNA. Examples are given that explore the KEM across a variety of chemical models, and to the outer limits of energy accuracy and molecular size. KEM represents an advance in quantum biology applicable to problems in medicine and drug design.

  20. Visualization of spatial patterns and temporal trends for aerial surveillance of illegal oil discharges in western Canadian marine waters.

    PubMed

    Serra-Sogas, Norma; O'Hara, Patrick D; Canessa, Rosaline; Keller, Peter; Pelot, Ronald

    2008-05-01

    This paper examines the use of exploratory spatial analysis for identifying hotspots of shipping-based oil pollution in the Pacific Region of Canada's Exclusive Economic Zone. It makes use of data collected from fiscal years 1997/1998 to 2005/2006 by the National Aerial Surveillance Program, the primary tool for monitoring and enforcing the provisions imposed by MARPOL 73/78. First, we present oil spill data as points in a "dot map" relative to coastlines, harbors and the aerial surveillance distribution. Then, we explore the intensity of oil spill events using the Quadrat Count method, and the Kernel Density Estimation methods with both fixed and adaptive bandwidths. We found that oil spill hotspots where more clearly defined using Kernel Density Estimation with an adaptive bandwidth, probably because of the "clustered" distribution of oil spill occurrences. Finally, we discuss the importance of standardizing oil spill data by controlling for surveillance effort to provide a better understanding of the distribution of illegal oil spills, and how these results can ultimately benefit a monitoring program.

  1. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    PubMed

    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.

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

    PubMed

    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.

  3. Putting Priors in Mixture Density Mercer Kernels

    NASA Technical Reports Server (NTRS)

    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%.

  4. Increasing accuracy of dispersal kernels in grid-based population models

    USGS Publications Warehouse

    Slone, D.H.

    2011-01-01

    Dispersal kernels in grid-based population models specify the proportion, distance and direction of movements within the model landscape. Spatial errors in dispersal kernels can have large compounding effects on model accuracy. Circular Gaussian and Laplacian dispersal kernels at a range of spatial resolutions were investigated, and methods for minimizing errors caused by the discretizing process were explored. Kernels of progressively smaller sizes relative to the landscape grid size were calculated using cell-integration and cell-center methods. These kernels were convolved repeatedly, and the final distribution was compared with a reference analytical solution. For large Gaussian kernels (σ > 10 cells), the total kernel error was <10 &sup-11; compared to analytical results. Using an invasion model that tracked the time a population took to reach a defined goal, the discrete model results were comparable to the analytical reference. With Gaussian kernels that had σ ≤ 0.12 using the cell integration method, or σ ≤ 0.22 using the cell center method, the kernel error was greater than 10%, which resulted in invasion times that were orders of magnitude different than theoretical results. A goal-seeking routine was developed to adjust the kernels to minimize overall error. With this, corrections for small kernels were found that decreased overall kernel error to <10-11 and invasion time error to <5%.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. Graph wavelet alignment kernels for drug virtual screening.

    PubMed

    Smalter, Aaron; Huan, Jun; Lushington, Gerald

    2009-06-01

    In this paper, we introduce a novel statistical modeling technique for target property prediction, with applications to virtual screening and drug design. In our method, we use graphs to model chemical structures and apply a wavelet analysis of graphs to summarize features capturing graph local topology. We design a novel graph kernel function to utilize the topology features to build predictive models for chemicals via Support Vector Machine classifier. We call the new graph kernel a graph wavelet-alignment kernel. We have evaluated the efficacy of the wavelet-alignment kernel using a set of chemical structure-activity prediction benchmarks. Our results indicate that the use of the kernel function yields performance profiles comparable to, and sometimes exceeding that of the existing state-of-the-art chemical classification approaches. In addition, our results also show that the use of wavelet functions significantly decreases the computational costs for graph kernel computation with more than ten fold speedup.

  7. Small convolution kernels for high-fidelity image restoration

    NASA Technical Reports Server (NTRS)

    Reichenbach, Stephen E.; Park, Stephen K.

    1991-01-01

    An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

  8. Reduced multiple empirical kernel learning machine.

    PubMed

    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

  9. 7 CFR 981.61 - Redetermination of kernel weight.

    Code of Federal Regulations, 2010 CFR

    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...

  10. Enhanced gluten properties in soft kernel durum wheat

    USDA-ARS?s Scientific Manuscript database

    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...

  11. Accelerating the Original Profile Kernel.

    PubMed

    Hamp, Tobias; Goldberg, Tatyana; Rost, Burkhard

    2013-01-01

    One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. Here, we introduce several software improvements that enable significant acceleration. Using various non-redundant data sets, we demonstrate that our new implementation reaches a maximal speed-up as high as 14-fold for calculating the same kernel matrix. Some predictions are over 200 times faster and render the kernel as possibly the top contender in a low ratio of speed/performance. Additionally, we explain how to parallelize various computations and provide an integrative program that reduces creating a production-quality classifier to a single program call. The new implementation is available as a Debian package under a free academic license and does not depend on commercial software. For non-Debian based distributions, the source package ships with a traditional Makefile-based installer. Download and installation instructions can be found at https://rostlab.org/owiki/index.php/Fast_Profile_Kernel. Bugs and other issues may be reported at https://rostlab.org/bugzilla3/enter_bug.cgi?product=fastprofkernel.

  12. Quantifying fat, oil, and grease deposit formation kinetics.

    PubMed

    Iasmin, Mahbuba; Dean, Lisa O; Ducoste, Joel J

    2016-01-01

    Fat, oil, and grease (FOG) deposits formed in sanitary sewers are calcium-based saponified solids that are responsible for a significant number of nationwide sanitary sewer overflows (SSOs) across United States. In the current study, the kinetics of lab-based saponified solids were determined to understand the kinetics of FOG deposit formation in sewers for two types of fat (Canola and Beef Tallow) and two types of calcium sources (calcium chloride and calcium sulfate) under three pH (7 ± 0.5, 10 ± 0.5, and ≈14) and two temperature conditions (22 ± 0.5 and 45 ± 0.5 °C). The results of this study displayed quick reactions of a fraction of fats with calcium ions to form calcium based saponified solids. Results further showed that increased palmitic fatty acid content in source fats, the magnitude of the pH, and temperature significantly affect the FOG deposit formation and saponification rates. The experimental data of the kinetics were compared with two empirical models: a) Cotte saponification model and b) Foubert crystallization model and a mass-action based mechanistic model that included alkali driven hydrolysis of triglycerides. Results showed that the mass action based mechanistic model was able to predict changes in the rate of formation of saponified solids under the different experimental conditions compared to both empirical models. The mass-action based saponification model also revealed that the hydrolysis of Beef Tallow was slower compared to liquid Canola fat resulting in smaller quantities of saponified solids. This mechanistic saponification model, with its ability to track the saponified solids chemical precursors, may provide an initial framework to predict the spatial formation of FOG deposits in municipal sewers using system wide sewer collection modeling software. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. 21 CFR 176.350 - Tamarind seed kernel powder.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... 21 Food and Drugs 3 2014-04-01 2014-04-01 false Tamarind seed kernel powder. 176.350 Section 176... 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, manufacturing, packing, processing, preparing, treating...

  14. 7 CFR 981.60 - Determination of kernel weight.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

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

  15. End-use quality of soft kernel durum wheat

    USDA-ARS?s Scientific Manuscript database

    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...

  16. Deep Restricted Kernel Machines Using Conjugate Feature Duality.

    PubMed

    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.

  17. Improved modeling of clinical data with kernel methods.

    PubMed

    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

  18. Triso coating development progress for uranium nitride kernels

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jolly, Brian C.; Lindemer, Terrence; Terrani, Kurt A.

    2015-08-01

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

  19. The Feasibility of Palm Kernel Shell as a Replacement for Coarse Aggregate in Lightweight Concrete

    NASA Astrophysics Data System (ADS)

    Itam, Zarina; Beddu, Salmia; Liyana Mohd Kamal, Nur; Ashraful Alam, Md; Issa Ayash, Usama

    2016-03-01

    Implementing sustainable materials into the construction industry is fast becoming a trend nowadays. Palm Kernel Shell is a by-product of Malaysia’s palm oil industry, generating waste as much as 4 million tons per annum. As a means of producing a sustainable, environmental-friendly, and affordable alternative in the lightweight concrete industry, the exploration of the potential of Palm Kernel Shell to be used as an aggregate replacement was conducted which may give a positive impact to the Malaysian construction industry as well as worldwide concrete usage. This research investigates the feasibility of PKS as an aggregate replacement in lightweight concrete in terms of compressive strength, slump test, water absorption, and density. Results indicate that by using PKS for aggregate replacement, it increases the water absorption but decreases the concrete workability and strength. Results however, fall into the range acceptable for lightweight aggregates, hence it can be concluded that there is potential to use PKS as aggregate replacement for lightweight concrete.

  20. Improving the Cold Temperature Properties of Tallow-Based Methyl Ester Mixtures Using Fractionation, Blending, and Additives

    NASA Astrophysics Data System (ADS)

    Elwell, Caleb

    Beef tallow is a less common feedstock source for biodiesel than soy or canola oil, but it can have economic benefits in comparison to these traditional feedstocks. However, tallow methyl ester (TME) has the major disadvantage of poor cold temperature properties. Cloud point (CP) is an standard industry metric for evaluating the cold temperature performance of biodiesel and is directly related to the thermodynamic properties of the fuel's constituents. TME has a CP of 14.5°C compared with 2.3°C for soy methyl ester (SME) and -8.3°C for canola methyl ester (CME). In this study, three methods were evaluated to reduce the CP of TME: fractionation, blending with SME and CME, and using polymer additives. TME fractionation (i.e. removal of specific methyl ester constituents) was simulated by creating FAME mixtures to match the FAME profiles of fractionated TME. The fractionation yield was found to be highest at the eutectic point of methyl palmitate (MP) and methyl stearate (MS), which was empirically determined to be at a MP/(MP+MS) ratio of approximately 82%. Since unmodified TME has a MP/(MP+MS) ratio of 59%, initially only MS should be removed to produce a ratio closer to the eutectic point to reduce CP and maximize yield. Graphs relating yield (with 4:1 methyl stearate to methyl oleate carryover) to CP were produced to determine the economic viability of this approach. To evaluate the effect of blending TME with other methyl esters, SME and CME were blended with TME at blend ratios of 0 to 100%. Both the SME/TME and CME/TME blends exhibited decreased CPs with increasing levels of SME and CME. Although the CP of the SME/TME blends varied linearly with SME content, the CP of the CME/TME blends varied quadratically with CME content. To evaluate the potential of fuel additives to reduce the CP of TME, 11 different polymer additives were tested. Although all of these additives were specifically marketed to enhance the cold temperature properties of petroleum diesel or

  1. 21 CFR 176.350 - Tamarind seed kernel powder.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 21 Food and Drugs 3 2011-04-01 2011-04-01 false Tamarind seed kernel powder. 176.350 Section 176... Substances for Use Only as Components of Paper and Paperboard § 176.350 Tamarind seed kernel powder. Tamarind seed kernel powder may be safely used as a component of articles intended for use in producing...

  2. 21 CFR 176.350 - Tamarind seed kernel powder.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 21 Food and Drugs 3 2012-04-01 2012-04-01 false 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...

  3. 21 CFR 176.350 - Tamarind seed kernel powder.

    Code of Federal Regulations, 2010 CFR

    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...

  4. 21 CFR 176.350 - Tamarind seed kernel powder.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... 21 Food and Drugs 3 2013-04-01 2013-04-01 false 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...

  5. Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

    PubMed Central

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

    2014-01-01

    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 regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435

  6. Effects of high-melting methyl esters on crystallization properties of fatty acid methyl ester mixtures

    USDA-ARS?s Scientific Manuscript database

    Biodiesel is a renewable alternative diesel fuel made from vegetable oils and animal fats. The most common form of biodiesel in the United States are fatty acid methyl esters (FAME) from soybean, canola, and used cooking oils, waste greases, and tallow. Cold flow properties of biodiesel depend on th...

  7. A dynamic kernel modifier for linux

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Minnich, R. G.

    2002-09-03

    Dynamic Kernel Modifier, or DKM, is a kernel module for Linux that allows user-mode programs to modify the execution of functions in the kernel without recompiling or modifying the kernel source in any way. Functions may be traced, either function entry only or function entry and exit; nullified; or replaced with some other function. For the tracing case, function execution results in the activation of a watchpoint. When the watchpoint is activated, the address of the function is logged in a FIFO buffer that is readable by external applications. The watchpoints are time-stamped with the resolution of the processor highmore » resolution timers, which on most modem processors are accurate to a single processor tick. DKM is very similar to earlier systems such as the SunOS trace device or Linux TT. Unlike these two systems, and other similar systems, DKM requires no kernel modifications. DKM allows users to do initial probing of the kernel to look for performance problems, or even to resolve potential problems by turning functions off or replacing them. DKM watchpoints are not without cost: it takes about 200 nanoseconds to make a log entry on an 800 Mhz Pentium-Ill. The overhead numbers are actually competitive with other hardware-based trace systems, although it has less 'Los Alamos National Laboratory is operated by the University of California for the National Nuclear Security Administration of the United States Department of Energy under contract W-7405-ENG-36. accuracy than an In-Circuit Emulator such as the American Arium. Once the user has zeroed in on a problem, other mechanisms with a higher degree of accuracy can be used.« less

  8. A new species of Gadirtha Walker (Nolidae, Eligminae): a proposed biological control agent of Chinese tallow (Triadica sebifera (L.) Small) (Euphorbiaceae) in the United States.

    PubMed

    Pogue, Michael G

    2014-01-01

    Gadirtha fusca sp. n., is described from Guangxi Province, China. Gadirtha fusca differs in forewing color and pattern, male and female genitalia, and in larval pattern from all other species of Gadirtha. Gadirtha fusca has been evaluated as a potential biological control agent for Chinese tallow (Triadica sebifera (L.) Small, Euphorbiaceae) in the southeastern United States. Adult, male and female genitalia, larva, and pupa are described, illustrated, and compared with Gadirtha impingens Walker.

  9. Effects of saturated and unsaturated fats with vitamin E supplementation on the antioxidant status of broiler chicken tissues.

    PubMed

    Husvéth, F; Manilla, H A; Gaál, T; Vajdovich, P; Balogh, N; Wágner, L; Lóth, I; Németh, K

    2000-01-01

    The influence of fish oil (highly unsaturated) and beef tallow (highly saturated) with vitamin E (100 IU/kg) supplementation on the antioxidant status of broiler chicken cockerels was investigated. Chicks were fed a control diet with no added fat, 40 g/kg each of fish oil and beef tallow diets, respectively, from 11 to 42 days of age. Tocopherol concentration and the rate of lipid peroxidation, thiobarbituric acid reactive substance (TBARS) in liver, fatty acid composition of the liver lipids, blood serum total antioxidant status (TAS), and reduced glutathione (GSH) content were determined. Vitamin E supplementation of the diet increased liver alpha-tocopherol content in chicks regardless of the type of dietary fat. Fish oil diet resulted in higher liver TBARS value while beef tallow diet showed lower values compared to the control diet. Vitamin E supplementation reduced liver TBARS as well as serum GSH, and raised serum TAS for all diets. Serum GSH was the same for vitamin E supplemented diets regardless of the fat supplement. Fish oil diets resulted in a significant increase in hepatic lipid n-3 PUFA content. A significant positive correlation was found between liver TBARS and n-3 PUFA content. No relationships were established, however, between liver TBARS and n-6 PUFA or saturated fatty acids. The results suggest that feeding oils rich in n-3 PUFA increases tissue concentration of these fatty acids, consequently increasing tissue lipid peroxidation and reducing the antioxidative status of broiler chickens. Supplementing high levels of vitamin E with such oils may increase tissue oxidative stability. Serum TAS or GSH may be used as a measure of antioxidative status in chickens.

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

    PubMed

    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.

  11. Kernel Partial Least Squares for Nonlinear Regression and Discrimination

    NASA Technical Reports Server (NTRS)

    Rosipal, Roman; Clancy, Daniel (Technical Monitor)

    2002-01-01

    This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

  12. Aflatoxin contamination of developing corn kernels.

    PubMed

    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.

  13. Anthraquinones isolated from the browned Chinese chestnut kernels (Castanea mollissima blume)

    NASA Astrophysics Data System (ADS)

    Zhang, Y. L.; Qi, J. H.; Qin, L.; Wang, F.; Pang, M. X.

    2016-08-01

    Anthraquinones (AQS) represent a group of secondary metallic products in plants. AQS are often naturally occurring in plants and microorganisms. In a previous study, we found that AQS were produced by enzymatic browning reaction in Chinese chestnut kernels. To find out whether non-enzymatic browning reaction in the kernels could produce AQS too, AQS were extracted from three groups of chestnut kernels: fresh kernels, non-enzymatic browned kernels, and browned kernels, and the contents of AQS were determined. High performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) methods were used to identify two compounds of AQS, rehein(1) and emodin(2). AQS were barely exists in the fresh kernels, while both browned kernel groups sample contained a high amount of AQS. Thus, we comfirmed that AQS could be produced during both enzymatic and non-enzymatic browning process. Rhein and emodin were the main components of AQS in the browned kernels.

  14. Performance Characteristics of a Kernel-Space Packet Capture Module

    DTIC Science & Technology

    2010-03-01

    Defense, or the United States Government . AFIT/GCO/ENG/10-03 PERFORMANCE CHARACTERISTICS OF A KERNEL-SPACE PACKET CAPTURE MODULE THESIS Presented to the...3.1.2.3 Prototype. The proof of concept for this research is the design, development, and comparative performance analysis of a kernel level N2d capture...changes to kernel code 5. Can be used for both user-space and kernel-space capture applications in order to control comparative performance analysis to

  15. Anatomically-Aided PET Reconstruction Using the Kernel Method

    PubMed Central

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

    2016-01-01

    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 (ROI) 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 (EM) algorithm. PMID:27541810

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

    PubMed

    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.

  17. Anatomically-aided PET reconstruction using the kernel method

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    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.

  18. Embedded real-time operating system micro kernel design

    NASA Astrophysics Data System (ADS)

    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.

  19. Fine tuning of process parameters for improving briquette production from palm kernel shell gasification waste.

    PubMed

    Bazargan, Alireza; Rough, Sarah L; McKay, Gordon

    2018-04-01

    Palm kernel shell biochars (PKSB) ejected as residues from a gasifier have been used for solid fuel briquette production. With this approach, palm kernel shells can be used for energy production twice: first, by producing rich syngas during gasification; second, by compacting the leftover residues from gasification into high calorific value briquettes. Herein, the process parameters for the manufacture of PKSB biomass briquettes via compaction are optimized. Two possible optimum process scenarios are considered. In the first, the compaction speed is increased from 0.5 to 10 mm/s, the compaction pressure is decreased from 80 Pa to 40 MPa, the retention time is reduced from 10 s to zero, and the starch binder content of the briquette is halved from 0.1 to 0.05 kg/kg. With these adjustments, the briquette production rate increases by more than 20-fold; hence capital and operational costs can be reduced and the service life of compaction equipment can be increased. The resulting product satisfactorily passes tensile (compressive) crushing strength and impact resistance tests. The second scenario involves reducing the starch weight content to 0.03 kg/kg, while reducing the compaction pressure to a value no lower than 60 MPa. Overall, in both cases, the PKSB biomass briquettes show excellent potential as a solid fuel with calorific values on par with good-quality coal. CHNS: carbon, hydrogen, nitrogen, sulfur; FFB: fresh fruit bunch(es); HHV: higher heating value [J/kg]; LHV: lower heating value [J/kg]; PKS: palm kernel shell(s); PKSB: palm kernel shell biochar(s); POME: palm oil mill effluent; RDF: refuse-derived fuel; TGA: thermogravimetric analysis.

  20. Kernel Temporal Differences for Neural Decoding

    PubMed Central

    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

  1. Online selective kernel-based temporal difference learning.

    PubMed

    Chen, Xingguo; Gao, Yang; Wang, Ruili

    2013-12-01

    In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

  2. Aqueous enzymatic extraction of Moringa oleifera oil.

    PubMed

    Mat Yusoff, Masni; Gordon, Michael H; Ezeh, Onyinye; Niranjan, Keshavan

    2016-11-15

    This paper reports on the extraction of Moringa oleifera (MO) oil by using aqueous enzymatic extraction (AEE) method. The effect of different process parameters on the oil recovery was discovered by using statistical optimization, besides the effect of selected parameters on the formation of its oil-in-water cream emulsions. Within the pre-determined ranges, the use of pH 4.5, moisture/kernel ratio of 8:1 (w/w), and 300stroke/min shaking speed at 40°C for 1h incubation time resulted in highest oil recovery of approximately 70% (goil/g solvent-extracted oil). These optimized parameters also result in a very thin emulsion layer, indicating minute amount of emulsion formed. Zero oil recovery with thick emulsion were observed when the used aqueous phase was re-utilized for another AEE process. The findings suggest that the critical selection of AEE parameters is key to high oil recovery with minimum emulsion formation thereby lowering the load on the de-emulsification step. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    PubMed

    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 < 0.05) were found between wheat kernel physical properties and pulverizing process of wheat kernel, especially wheat kernel hardness index (obtained on the basis of Single Kernel Characterization System) and vitreousness significantly and positively correlated with the grinding energy indices and the mass fraction of coarse particles (> 0.5 mm). Among the kernel mechanical properties determined on the basis of uniaxial compression test only the rapture force was correlated with the impact grinding results. The results showed also positive and significant relationships between kernel ash content and grinding energy requirements. On the basis of wheat physical properties the multiple linear regression was proposed for predicting the average particle size of pulverized kernel.

  4. Kernel-based Linux emulation for Plan 9.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Minnich, Ronald G.

    2010-09-01

    CNKemu is a kernel-based system for the 9k variant of the Plan 9 kernel. It is designed to provide transparent binary support for programs compiled for IBM's Compute Node Kernel (CNK) on the Blue Gene series of supercomputers. This support allows users to build applications with the standard Blue Gene toolchain, including C++ and Fortran compilers. While the CNK is not Linux, IBM designed the CNK so that the user interface has much in common with the Linux 2.0 system call interface. The Plan 9 CNK emulator hence provides the foundation of kernel-based Linux system call support on Plan 9.more » In this paper we discuss cnkemu's implementation and some of its more interesting features, such as the ability to easily intermix Plan 9 and Linux system calls.« less

  5. Gradient-based adaptation of general gaussian kernels.

    PubMed

    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.

  6. Gabor-based kernel PCA with fractional power polynomial models for face recognition.

    PubMed

    Liu, Chengjun

    2004-05-01

    This paper presents a novel Gabor-based kernel Principal Component Analysis (PCA) method by integrating the Gabor wavelet representation of face images and the kernel PCA method for face recognition. Gabor wavelets first derive desirable facial features characterized by spatial frequency, spatial locality, and orientation selectivity to cope with the variations due to illumination and facial expression changes. The kernel PCA method is then extended to include fractional power polynomial models for enhanced face recognition performance. A fractional power polynomial, however, does not necessarily define a kernel function, as it might not define a positive semidefinite Gram matrix. Note that the sigmoid kernels, one of the three classes of widely used kernel functions (polynomial kernels, Gaussian kernels, and sigmoid kernels), do not actually define a positive semidefinite Gram matrix either. Nevertheless, the sigmoid kernels have been successfully used in practice, such as in building support vector machines. In order to derive real kernel PCA features, we apply only those kernel PCA eigenvectors that are associated with positive eigenvalues. The feasibility of the Gabor-based kernel PCA method with fractional power polynomial models has been successfully tested on both frontal and pose-angled face recognition, using two data sets from the FERET database and the CMU PIE database, respectively. The FERET data set contains 600 frontal face images of 200 subjects, while the PIE data set consists of 680 images across five poses (left and right profiles, left and right half profiles, and frontal view) with two different facial expressions (neutral and smiling) of 68 subjects. The effectiveness of the Gabor-based kernel PCA method with fractional power polynomial models is shown in terms of both absolute performance indices and comparative performance against the PCA method, the kernel PCA method with polynomial kernels, the kernel PCA method with fractional power

  7. A new species of Gadirtha Walker (Nolidae, Eligminae): a proposed biological control agent of Chinese tallow (Triadica sebifera (L.) Small) (Euphorbiaceae) in the United States

    PubMed Central

    Pogue, Michael G.

    2014-01-01

    Abstract Gadirtha fusca sp. n., is described from Guangxi Province, China. Gadirtha fusca differs in forewing color and pattern, male and female genitalia, and in larval pattern from all other species of Gadirtha. Gadirtha fusca has been evaluated as a potential biological control agent for Chinese tallow (Triadica sebifera (L.) Small, Euphorbiaceae) in the southeastern United States. Adult, male and female genitalia, larva, and pupa are described, illustrated, and compared with Gadirtha impingens Walker. PMID:24624017

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

    PubMed

    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.

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

    PubMed

    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.

  10. A Kernel-based Lagrangian method for imperfectly-mixed chemical reactions

    NASA Astrophysics Data System (ADS)

    Schmidt, Michael J.; Pankavich, Stephen; Benson, David A.

    2017-05-01

    Current Lagrangian (particle-tracking) algorithms used to simulate diffusion-reaction equations must employ a certain number of particles to properly emulate the system dynamics-particularly for imperfectly-mixed systems. The number of particles is tied to the statistics of the initial concentration fields of the system at hand. Systems with shorter-range correlation and/or smaller concentration variance require more particles, potentially limiting the computational feasibility of the method. For the well-known problem of bimolecular reaction, we show that using kernel-based, rather than Dirac delta, particles can significantly reduce the required number of particles. We derive the fixed width of a Gaussian kernel for a given reduced number of particles that analytically eliminates the error between kernel and Dirac solutions at any specified time. We also show how to solve for the fixed kernel size by minimizing the squared differences between solutions over any given time interval. Numerical results show that the width of the kernel should be kept below about 12% of the domain size, and that the analytic equations used to derive kernel width suffer significantly from the neglect of higher-order moments. The simulations with a kernel width given by least squares minimization perform better than those made to match at one specific time. A heuristic time-variable kernel size, based on the previous results, performs on par with the least squares fixed kernel size.

  11. Rapid authentication of adulteration of olive oil by near-infrared spectroscopy using support vector machines

    NASA Astrophysics Data System (ADS)

    Wu, Jingzhu; Dong, Jingjing; Dong, Wenfei; Chen, Yan; Liu, Cuiling

    2016-10-01

    A classification method of support vector machines with linear kernel was employed to authenticate genuine olive oil based on near-infrared spectroscopy. There were three types of adulteration of olive oil experimented in the study. The adulterated oil was respectively soybean oil, rapeseed oil and the mixture of soybean and rapeseed oil. The average recognition rate of second experiment was more than 90% and that of the third experiment was reach to 100%. The results showed the method had good performance in classifying genuine olive oil and the adulteration with small variation range of adulterated concentration and it was a promising and rapid technique for the detection of oil adulteration and fraud in the food industry.

  12. Detection of maize kernels breakage rate based on K-means clustering

    NASA Astrophysics Data System (ADS)

    Yang, Liang; Wang, Zhuo; Gao, Lei; Bai, Xiaoping

    2017-04-01

    In order to optimize the recognition accuracy of maize kernels breakage detection and improve the detection efficiency of maize kernels breakage, this paper using computer vision technology and detecting of the maize kernels breakage based on K-means clustering algorithm. First, the collected RGB images are converted into Lab images, then the original images clarity evaluation are evaluated by the energy function of Sobel 8 gradient. Finally, the detection of maize kernels breakage using different pixel acquisition equipments and different shooting angles. In this paper, the broken maize kernels are identified by the color difference between integrity kernels and broken kernels. The original images clarity evaluation and different shooting angles are taken to verify that the clarity and shooting angles of the images have a direct influence on the feature extraction. The results show that K-means clustering algorithm can distinguish the broken maize kernels effectively.

  13. Image quality of mixed convolution kernel in thoracic computed tomography.

    PubMed

    Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

    2016-11-01

    The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

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

    PubMed

    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.

  15. Stochastic subset selection for learning with kernel machines.

    PubMed

    Rhinelander, Jason; Liu, Xiaoping P

    2012-06-01

    Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

  16. RTOS kernel in portable electrocardiograph

    NASA Astrophysics Data System (ADS)

    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.

  17. A Robustness Testing Campaign for IMA-SP Partitioning Kernels

    NASA Astrophysics Data System (ADS)

    Grixti, Stephen; Lopez Trecastro, Jorge; Sammut, Nicholas; Zammit-Mangion, David

    2015-09-01

    With time and space partitioned architectures becoming increasingly appealing to the European space sector, the dependability of partitioning kernel technology is a key factor to its applicability in European Space Agency projects. This paper explores the potential of the data type fault model, which injects faults through the Application Program Interface, in partitioning kernel robustness testing. This fault injection methodology has been tailored to investigate its relevance in uncovering vulnerabilities within partitioning kernels and potentially contributing towards fault removal campaigns within this domain. This is demonstrated through a robustness testing case study of the XtratuM partitioning kernel for SPARC LEON3 processors. The robustness campaign exposed a number of vulnerabilities in XtratuM, exhibiting the potential benefits of using such a methodology for the robustness assessment of partitioning kernels.

  18. Digestibility of solvent-treated Jatropha curcas kernel by broiler chickens in Senegal.

    PubMed

    Nesseim, Thierry Daniel Tamsir; Dieng, Abdoulaye; Mergeai, Guy; Ndiaye, Saliou; Hornick, Jean-Luc

    2015-12-01

    Jatropha curcas is a drought-resistant shrub belonging to the Euphorbiaceae family. The kernel contains approximately 60 % lipid in dry matter, and the meal obtained after oil extraction could be an exceptional source of protein for family poultry farming, in the absence of curcin and, especially, some diterpene derivatives phorbol esters that are partially lipophilic. The nutrient digestibility of J. curcas kernel meal (JKM), obtained after partial physicochemical deoiling was thus evaluated in broiler chickens. Twenty broiler chickens, 6 weeks old, were maintained in individual metabolic cages and divided into four groups of five animals, according to a 4 × 4 Latin square design where deoiled JKM was incorporated into grinded corn at 0, 4, 8, and 12 % levels (diets 0, 4, 8, and 12 J), allowing measurement of nutrient digestibility by the differential method. The dry matter (DM) and organic matter (OM) digestibility of diets was affected to a low extent by JKM (85 and 86 % in 0 J and 81 % in 12 J, respectively) in such a way that DM and OM digestibility of JKM was estimated to be close to 50 %. The ether extract (EE) digestibility of JKM remained high, at about 90 %, while crude protein (CP) and crude fiber (CF) digestibility were largely impacted by JKM, with values closed to 40 % at the highest levels of incorporation. J. curcas kernel presents various nutrient digestibilities but has adverse effects on CP and CF digestibility of the diet. The effects of an additional heat or biological treatment on JKM remain to be assessed.

  19. Searching for efficient Markov chain Monte Carlo proposal kernels

    PubMed Central

    Yang, Ziheng; Rodríguez, Carlos E.

    2013-01-01

    Markov chain Monte Carlo (MCMC) or the Metropolis–Hastings algorithm is a simulation algorithm that has made modern Bayesian statistical inference possible. Nevertheless, the efficiency of different Metropolis–Hastings proposal kernels has rarely been studied except for the Gaussian proposal. Here we propose a unique class of Bactrian kernels, which avoid proposing values that are very close to the current value, and compare their efficiency with a number of proposals for simulating different target distributions, with efficiency measured by the asymptotic variance of a parameter estimate. The uniform kernel is found to be more efficient than the Gaussian kernel, whereas the Bactrian kernel is even better. When optimal scales are used for both, the Bactrian kernel is at least 50% more efficient than the Gaussian. Implementation in a Bayesian program for molecular clock dating confirms the general applicability of our results to generic MCMC algorithms. Our results refute a previous claim that all proposals had nearly identical performance and will prompt further research into efficient MCMC proposals. PMID:24218600

  20. Scuba: scalable kernel-based gene prioritization.

    PubMed

    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 .

  1. Genomic Prediction of Genotype × Environment Interaction Kernel Regression Models.

    PubMed

    Cuevas, Jaime; Crossa, José; Soberanis, Víctor; Pérez-Elizalde, Sergio; Pérez-Rodríguez, Paulino; Campos, Gustavo de Los; Montesinos-López, O A; Burgueño, Juan

    2016-11-01

    In genomic selection (GS), genotype × environment interaction (G × E) can be modeled by a marker × environment interaction (M × E). The G × E may be modeled through a linear kernel or a nonlinear (Gaussian) kernel. In this study, we propose using two nonlinear Gaussian kernels: the reproducing kernel Hilbert space with kernel averaging (RKHS KA) and the Gaussian kernel with the bandwidth estimated through an empirical Bayesian method (RKHS EB). We performed single-environment analyses and extended to account for G × E interaction (GBLUP-G × E, RKHS KA-G × E and RKHS EB-G × E) in wheat ( L.) and maize ( L.) data sets. For single-environment analyses of wheat and maize data sets, RKHS EB and RKHS KA had higher prediction accuracy than GBLUP for all environments. For the wheat data, the RKHS KA-G × E and RKHS EB-G × E models did show up to 60 to 68% superiority over the corresponding single environment for pairs of environments with positive correlations. For the wheat data set, the models with Gaussian kernels had accuracies up to 17% higher than that of GBLUP-G × E. For the maize data set, the prediction accuracy of RKHS EB-G × E and RKHS KA-G × E was, on average, 5 to 6% higher than that of GBLUP-G × E. The superiority of the Gaussian kernel models over the linear kernel is due to more flexible kernels that accounts for small, more complex marker main effects and marker-specific interaction effects. Copyright © 2016 Crop Science Society of America.

  2. Sepsis mortality prediction with the Quotient Basis Kernel.

    PubMed

    Ribas Ripoll, Vicent J; Vellido, Alfredo; Romero, Enrique; Ruiz-Rodríguez, Juan Carlos

    2014-05-01

    This paper presents an algorithm to assess the risk of death in patients with sepsis. Sepsis is a common clinical syndrome in the intensive care unit (ICU) that can lead to severe sepsis, a severe state of septic shock or multi-organ failure. The proposed algorithm may be implemented as part of a clinical decision support system that can be used in combination with the scores deployed in the ICU to improve the accuracy, sensitivity and specificity of mortality prediction for patients with sepsis. In this paper, we used the Simplified Acute Physiology Score (SAPS) for ICU patients and the Sequential Organ Failure Assessment (SOFA) to build our kernels and algorithms. In the proposed method, we embed the available data in a suitable feature space and use algorithms based on linear algebra, geometry and statistics for inference. We present a simplified version of the Fisher kernel (practical Fisher kernel for multinomial distributions), as well as a novel kernel that we named the Quotient Basis Kernel (QBK). These kernels are used as the basis for mortality prediction using soft-margin support vector machines. The two new kernels presented are compared against other generative kernels based on the Jensen-Shannon metric (centred, exponential and inverse) and other widely used kernels (linear, polynomial and Gaussian). Clinical relevance is also evaluated by comparing these results with logistic regression and the standard clinical prediction method based on the initial SAPS score. As described in this paper, we tested the new methods via cross-validation with a cohort of 400 test patients. The results obtained using our methods compare favourably with those obtained using alternative kernels (80.18% accuracy for the QBK) and the standard clinical prediction method, which are based on the basal SAPS score or logistic regression (71.32% and 71.55%, respectively). The QBK presented a sensitivity and specificity of 79.34% and 83.24%, which outperformed the other kernels

  3. Kernel Methods for Mining Instance Data in Ontologies

    NASA Astrophysics Data System (ADS)

    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.

  4. Biasing anisotropic scattering kernels for deep-penetration Monte Carlo calculations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    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.

  5. Direct Measurement of Wave Kernels in Time-Distance Helioseismology

    NASA Technical Reports Server (NTRS)

    Duvall, T. L., Jr.

    2006-01-01

    Solar f-mode waves are surface-gravity waves which propagate horizontally in a thin layer near the photosphere with a dispersion relation approximately that of deep water waves. At the power maximum near 3 mHz, the wavelength of 5 Mm is large enough for various wave scattering properties to be observable. Gizon and Birch (2002,ApJ,571,966)h ave calculated kernels, in the Born approximation, for the sensitivity of wave travel times to local changes in damping rate and source strength. In this work, using isolated small magnetic features as approximate point-sourc'e scatterers, such a kernel has been measured. The observed kernel contains similar features to a theoretical damping kernel but not for a source kernel. A full understanding of the effect of small magnetic features on the waves will require more detailed modeling.

  6. Dropping macadamia nuts-in-shell reduces kernel roasting quality.

    PubMed

    Walton, David A; Wallace, Helen M

    2010-10-01

    Macadamia nuts ('nuts-in-shell') are subjected to many impacts from dropping during postharvest handling, resulting in damage to the raw kernel. The effect of dropping on roasted kernel quality is unknown. Macadamia nuts-in-shell were dropped in various combinations of moisture content, number of drops and receiving surface in three experiments. After dropping, samples from each treatment and undropped controls were dry oven-roasted for 20 min at 130 °C, and kernels were assessed for colour, mottled colour and surface damage. Dropping nuts-in-shell onto a bed of nuts-in-shell at 3% moisture content or 20% moisture content increased the percentage of dark roasted kernels. Kernels from nuts dropped first at 20%, then 10% moisture content, onto a metal plate had increased mottled colour. Dropping nuts-in-shell at 3% moisture content onto nuts-in-shell significantly increased surface damage. Similarly, surface damage increased for kernels dropped onto a metal plate at 20%, then at 10% moisture content. Postharvest dropping of macadamia nuts-in-shell causes concealed cellular damage to kernels, the effects not evident until roasting. This damage provides the reagents needed for non-enzymatic browning reactions. Improvements in handling, such as reducing the number of drops and improving handling equipment, will reduce cellular damage and after-roast darkening. Copyright © 2010 Society of Chemical Industry.

  7. Compound analysis via graph kernels incorporating chirality.

    PubMed

    Brown, J B; Urata, Takashi; Tamura, Takeyuki; Arai, Midori A; Kawabata, Takeo; Akutsu, Tatsuya

    2010-12-01

    High accuracy is paramount when predicting biochemical characteristics using Quantitative Structural-Property Relationships (QSPRs). Although existing graph-theoretic kernel methods combined with machine learning techniques are efficient for QSPR model construction, they cannot distinguish topologically identical chiral compounds which often exhibit different biological characteristics. In this paper, we propose a new method that extends the recently developed tree pattern graph kernel to accommodate stereoisomers. We show that Support Vector Regression (SVR) with a chiral graph kernel is useful for target property prediction by demonstrating its application to a set of human vitamin D receptor ligands currently under consideration for their potential anti-cancer effects.

  8. Kernel-aligned multi-view canonical correlation analysis for image recognition

    NASA Astrophysics Data System (ADS)

    Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

    2016-09-01

    Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

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

    PubMed

    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.

  10. Improving the Bandwidth Selection in Kernel Equating

    ERIC Educational Resources Information Center

    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…

  11. Nature and composition of fat bloom from palm kernel stearin and hydrogenated palm kernel stearin compound chocolates.

    PubMed

    Smith, Kevin W; Cain, Fred W; Talbot, Geoff

    2004-08-25

    Palm kernel stearin and hydrogenated palm kernel stearin can be used to prepare compound chocolate bars or coatings. The objective of this study was to characterize the chemical composition, polymorphism, and melting behavior of the bloom that develops on bars of compound chocolate prepared using these fats. Bars were stored for 1 year at 15, 20, or 25 degrees C. At 15 and 20 degrees C the bloom was enriched in cocoa butter triacylglycerols, with respect to the main fat phase, whereas at 25 degrees C the enrichment was with palm kernel triacylglycerols. The bloom consisted principally of solid fat and was sharper melting than was the fat in the chocolate. Polymorphic transitions from the initial beta' phase to the beta phase accompanied the formation of bloom at all temperatures.

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

    PubMed

    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.

  13. Kernel analysis of partial least squares (PLS) regression models.

    PubMed

    Shinzawa, Hideyuki; Ritthiruangdej, Pitiporn; Ozaki, Yukihiro

    2011-05-01

    An analytical technique based on kernel matrix representation is demonstrated to provide further chemically meaningful insight into partial least squares (PLS) regression models. The kernel matrix condenses essential information about scores derived from PLS or principal component analysis (PCA). Thus, it becomes possible to establish the proper interpretation of the scores. A PLS model for the total nitrogen (TN) content in multiple Thai fish sauces is built with a set of near-infrared (NIR) transmittance spectra of the fish sauce samples. The kernel analysis of the scores effectively reveals that the variation of the spectral feature induced by the change in protein content is substantially associated with the total water content and the protein hydration. Kernel analysis is also carried out on a set of time-dependent infrared (IR) spectra representing transient evaporation of ethanol from a binary mixture solution of ethanol and oleic acid. A PLS model to predict the elapsed time is built with the IR spectra and the kernel matrix is derived from the scores. The detailed analysis of the kernel matrix provides penetrating insight into the interaction between the ethanol and the oleic acid.

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

    PubMed

    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.

  15. A Multi-Label Learning Based Kernel Automatic Recommendation Method for Support Vector Machine

    PubMed Central

    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. PMID:25893896

  16. Convolution kernels for multi-wavelength imaging

    NASA Astrophysics Data System (ADS)

    Boucaud, A.; Bocchio, M.; Abergel, A.; Orieux, F.; Dole, H.; Hadj-Youcef, M. A.

    2016-12-01

    Astrophysical images issued from different instruments and/or spectral bands often require to be processed together, either for fitting or comparison purposes. However each image is affected by an instrumental response, also known as point-spread function (PSF), that depends on the characteristics of the instrument as well as the wavelength and the observing strategy. Given the knowledge of the PSF in each band, a straightforward way of processing images is to homogenise them all to a target PSF using convolution kernels, so that they appear as if they had been acquired by the same instrument. We propose an algorithm that generates such PSF-matching kernels, based on Wiener filtering with a tunable regularisation parameter. This method ensures all anisotropic features in the PSFs to be taken into account. We compare our method to existing procedures using measured Herschel/PACS and SPIRE PSFs and simulated JWST/MIRI PSFs. Significant gains up to two orders of magnitude are obtained with respect to the use of kernels computed assuming Gaussian or circularised PSFs. A software to compute these kernels is available at https://github.com/aboucaud/pypher

  17. Material flow analysis for resource management towards resilient palm oil production

    NASA Astrophysics Data System (ADS)

    Kamahara, H.; Faisal, M.; Hasanudin, U.; Fujie, K.; Daimon, H.

    2018-03-01

    Biomass waste generated from palm oil mill can be considered not only as the feedstock of renewable energy but also as the nutrient-rich resources to produce organic fertilizer. This study explored the appropriate resource management towards resilient palm oil production by applying material flow analysis. This study was conducted based on two palm oil mills in Lampung, Indonesia. The results showed that the empty fruit bunch (EFB) has the largest potential in terms of amount and energy among the biomass waste. The results also showed that the palm oil mills themselves had already self-managed their energy consumption thatwas obtained from palm kernel shell and palm press fiber. Finally, this study recommended the several utilization options of EFB for improvement of soil sustainability to contribute towards resilient palm oil production.

  18. Unsupervised multiple kernel learning for heterogeneous data integration.

    PubMed

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

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

  19. Protein fold recognition using geometric kernel data fusion.

    PubMed

    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.

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

    PubMed

    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.

  1. Control Transfer in Operating System Kernels

    DTIC Science & Technology

    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

  2. Experimental study of turbulent flame kernel propagation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mansour, Mohy; Peters, Norbert; Schrader, Lars-Uve

    2008-07-15

    Flame kernels in spark ignited combustion systems dominate the flame propagation and combustion stability and performance. They are likely controlled by the spark energy, flow field and mixing field. The aim of the present work is to experimentally investigate the structure and propagation of the flame kernel in turbulent premixed methane flow using advanced laser-based techniques. The spark is generated using pulsed Nd:YAG laser with 20 mJ pulse energy in order to avoid the effect of the electrodes on the flame kernel structure and the variation of spark energy from shot-to-shot. Four flames have been investigated at equivalence ratios, {phi}{submore » j}, of 0.8 and 1.0 and jet velocities, U{sub j}, of 6 and 12 m/s. A combined two-dimensional Rayleigh and LIPF-OH technique has been applied. The flame kernel structure has been collected at several time intervals from the laser ignition between 10 {mu}s and 2 ms. The data show that the flame kernel structure starts with spherical shape and changes gradually to peanut-like, then to mushroom-like and finally disturbed by the turbulence. The mushroom-like structure lasts longer in the stoichiometric and slower jet velocity. The growth rate of the average flame kernel radius is divided into two linear relations; the first one during the first 100 {mu}s is almost three times faster than that at the later stage between 100 and 2000 {mu}s. The flame propagation is slightly faster in leaner flames. The trends of the flame propagation, flame radius, flame cross-sectional area and mean flame temperature are related to the jet velocity and equivalence ratio. The relations obtained in the present work allow the prediction of any of these parameters at different conditions. (author)« less

  3. Bivariate discrete beta Kernel graduation of mortality data.

    PubMed

    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.

  4. A Linear Kernel for Co-Path/Cycle Packing

    NASA Astrophysics Data System (ADS)

    Chen, Zhi-Zhong; Fellows, Michael; Fu, Bin; Jiang, Haitao; Liu, Yang; Wang, Lusheng; Zhu, Binhai

    Bounded-Degree Vertex Deletion is a fundamental problem in graph theory that has new applications in computational biology. In this paper, we address a special case of Bounded-Degree Vertex Deletion, the Co-Path/Cycle Packing problem, which asks to delete as few vertices as possible such that the graph of the remaining (residual) vertices is composed of disjoint paths and simple cycles. The problem falls into the well-known class of 'node-deletion problems with hereditary properties', is hence NP-complete and unlikely to admit a polynomial time approximation algorithm with approximation factor smaller than 2. In the framework of parameterized complexity, we present a kernelization algorithm that produces a kernel with at most 37k vertices, improving on the super-linear kernel of Fellows et al.'s general theorem for Bounded-Degree Vertex Deletion. Using this kernel,and the method of bounded search trees, we devise an FPT algorithm that runs in time O *(3.24 k ). On the negative side, we show that the problem is APX-hard and unlikely to have a kernel smaller than 2k by a reduction from Vertex Cover.

  5. 7 CFR 51.1403 - Kernel color classification.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... classifications provided in this section. When the color of kernels in a lot generally conforms to the “light” or “light amber” classification, that color classification may be used to describe the lot in connection with the grade. (1) “Light” means that the outer surface of the kernel is mostly golden color or...

  6. 7 CFR 51.1403 - Kernel color classification.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... classifications provided in this section. When the color of kernels in a lot generally conforms to the “light” or “light amber” classification, that color classification may be used to describe the lot in connection with the grade. (1) “Light” means that the outer surface of the kernel is mostly golden color or...

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

    PubMed

    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.

  8. Relationship of source and sink in determining kernel composition of maize

    PubMed Central

    Seebauer, Juliann R.; Singletary, George W.; Krumpelman, Paulette M.; Ruffo, Matías L.; Below, Frederick E.

    2010-01-01

    The relative role of the maternal source and the filial sink in controlling the composition of maize (Zea mays L.) kernels is unclear and may be influenced by the genotype and the N supply. The objective of this study was to determine the influence of assimilate supply from the vegetative source and utilization of assimilates by the grain sink on the final composition of maize kernels. Intermated B73×Mo17 recombinant inbred lines (IBM RILs) which displayed contrasting concentrations of endosperm starch were grown in the field with deficient or sufficient N, and the source supply altered by ear truncation (45% reduction) at 15 d after pollination (DAP). The assimilate supply into the kernels was determined at 19 DAP using the agar trap technique, and the final kernel composition was measured. The influence of N supply and kernel ear position on final kernel composition was also determined for a commercial hybrid. Concentrations of kernel protein and starch could be altered by genotype or the N supply, but remained fairly constant along the length of the ear. Ear truncation also produced a range of variation in endosperm starch and protein concentrations. The C/N ratio of the assimilate supply at 19 DAP was directly related to the final kernel composition, with an inverse relationship between the concentrations of starch and protein in the mature endosperm. The accumulation of kernel starch and protein in maize is uniform along the ear, yet adaptable within genotypic limits, suggesting that kernel composition is source limited in maize. PMID:19917600

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu

    2014-08-07

    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 themore » 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.« less

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

    PubMed

    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.

  11. Density Estimation with Mercer Kernels

    NASA Technical Reports Server (NTRS)

    Macready, William G.

    2003-01-01

    We present a new method for density estimation based on Mercer kernels. The density estimate can be understood as the density induced on a data manifold by a mixture of Gaussians fit in a feature space. As is usual, the feature space and data manifold are defined with any suitable positive-definite kernel function. We modify the standard EM algorithm for mixtures of Gaussians to infer the parameters of the density. One benefit of the approach is it's conceptual simplicity, and uniform applicability over many different types of data. Preliminary results are presented for a number of simple problems.

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

    PubMed

    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 < 0.05) but the unbroken kernels became significantly harder. Moisture content and moisture uptake rate were positively correlated, and cooked rice 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.

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

    PubMed

    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.

  14. Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations.

    PubMed

    Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D; Flint-Garcia, Sherry A

    2016-08-09

    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. Copyright © 2016 Liu et al.

  15. Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

    PubMed Central

    Liu, Zhengbin; Garcia, Arturo; McMullen, Michael D.; Flint-Garcia, Sherry A.

    2016-01-01

    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. PMID:27317774

  16. Effects of dietary fats on egg quality and lipid parameters in serum and yolks of Shan Partridge Duck.

    PubMed

    Du, Xue; Liu, Yali; Lu, Lizhi; Wang, Weiqun; Zeng, Tao; Tian, Yong; Xu, Xiaoqin; Shen, Jianliang; Niu, Dong; Lu, Yingru

    2017-05-01

    The effects of different dietary fats with variable levels of polyunsaturated fatty acids (PUFAs) on egg quality of Shan Partridge Duck, serum, and yolk lipid parameters were examined in this study. A flock of 585 optimal produced ducks were selected and diets enriched with 0.5%, 1%, or 2% fish oil (F)/flaxseed oil (FL)/rapeseed oil (R)/tallow (T) plus basal diet were supplied through a 28-d period. Supplemental fat source and fat level had no effects on egg qualities. Proportions of yolk total cholesterol (TC), saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs) were reduced (P < 0.001), while polyunsaturated fatty acids (PUFAs), ω-6 polyunsaturated fatty acids (n-6 PUFAs), ω-3 polyunsaturated fatty acids (n-3 PUFAs), Docosahexaenoic Acid (DHA), and Eicosapentaenoic Acid (EPA) were increased by fish oil, flaxseed oil, or rapeseed oil. Effects of supplementation increasing DHA and EPA were detected in F, FL, and R. Compared with C, fish oil significantly increased low-density lipoprotein cholesterol (LDL-C) in serum, flaxseed oil significantly reduced TC and increased very low-density lipoprotein cholesterol (VLDL-C), rapeseed oil significantly reduced TC and LDL-C in serum and increased VLDL-C, tallow significantly increased LDL-C. It is concluded that unsaturated fatty acids rich diets (fish oil, flaxseed oil, and rapeseed oil) might increase yolk PUFAs, reduce yolk cholesterol, and change serum lipid parameters without evident effect on egg qualities. © 2016 Poultry Science Association Inc.

  17. Investigation of various energy deposition kernel refinements for the convolution/superposition method

    PubMed Central

    Huang, Jessie Y.; Eklund, David; Childress, Nathan L.; Howell, Rebecca M.; Mirkovic, Dragan; Followill, David S.; Kry, Stephen F.

    2013-01-01

    Purpose: Several simplifications used in clinical implementations of the convolution/superposition (C/S) method, specifically, density scaling of water kernels for heterogeneous media and use of a single polyenergetic kernel, lead to dose calculation inaccuracies. Although these weaknesses of the C/S method are known, it is not well known which of these simplifications has the largest effect on dose calculation accuracy in clinical situations. The purpose of this study was to generate and characterize high-resolution, polyenergetic, and material-specific energy deposition kernels (EDKs), as well as to investigate the dosimetric impact of implementing spatially variant polyenergetic and material-specific kernels in a collapsed cone C/S algorithm. Methods: High-resolution, monoenergetic water EDKs and various material-specific EDKs were simulated using the EGSnrc Monte Carlo code. Polyenergetic kernels, reflecting the primary spectrum of a clinical 6 MV photon beam at different locations in a water phantom, were calculated for different depths, field sizes, and off-axis distances. To investigate the dosimetric impact of implementing spatially variant polyenergetic kernels, depth dose curves in water were calculated using two different implementations of the collapsed cone C/S method. The first method uses a single polyenergetic kernel, while the second method fully takes into account spectral changes in the convolution calculation. To investigate the dosimetric impact of implementing material-specific kernels, depth dose curves were calculated for a simplified titanium implant geometry using both a traditional C/S implementation that performs density scaling of water kernels and a novel implementation using material-specific kernels. Results: For our high-resolution kernels, we found good agreement with the Mackie et al. kernels, with some differences near the interaction site for low photon energies (<500 keV). For our spatially variant polyenergetic kernels, we

  18. The oil palm Shell gene controls oil yield and encodes a homologue of SEEDSTICK

    PubMed Central

    Singh, Rajinder; Leslie Low, Eng-Ti; Ooi, Leslie Cheng-Li; Ong-Abdullah, Meilina; Chin, Ting Ngoot; Nagappan, Jayanthi; Nookiah, Rajanaidu; Amiruddin, Mohd Din; Rosli, Rozana; Abdul Manaf, Mohamad Arif; Chan, Kuang-Lim; Halim, Mohd Amin; Azizi, Norazah; Lakey, Nathan; Smith, Steven W; Budiman, Muhammad A; Hogan, Michael; Bacher, Blaire; Van Brunt, Andrew; Wang, Chunyan; Ordway, Jared M; Sambanthamurthi, Ravigadevi; Martienssen, Robert A

    2014-01-01

    A key event in the domestication and breeding of the oil palm, Elaeis guineensis, was loss of the thick coconut-like shell surrounding the kernel. Modern E. guineensis has three fruit forms, dura (thick-shelled), pisifera (shell-less) and tenera (thin-shelled), a hybrid between dura and pisifera1–4. The pisifera palm is usually female-sterile but the tenera yields far more oil than dura, and is the basis for commercial palm oil production in all of Southeast Asia5. Here, we describe the mapping and identification of the Shell gene responsible for the different fruit forms. Using homozygosity mapping by sequencing we found two independent mutations in the DNA binding domain of a homologue of the MADS-box gene SEEDSTICK (STK) which controls ovule identity and seed development in Arabidopsis. The Shell gene is responsible for the tenera phenotype in both cultivated and wild palms from sub-Saharan Africa, and our findings provide a genetic explanation for the single gene heterosis attributed to Shell, via heterodimerization. This gene mutation explains the single most important economic trait in oil palm, and has implications for the competing interests of global edible oil production, biofuels and rainforest conservation6. PMID:23883930

  19. Effects of sample size on KERNEL home range estimates

    USGS Publications Warehouse

    Seaman, D.E.; Millspaugh, J.J.; Kernohan, Brian J.; Brundige, Gary C.; Raedeke, Kenneth J.; Gitzen, Robert A.

    1999-01-01

    Kernel methods for estimating home range are being used increasingly in wildlife research, but the effect of sample size on their accuracy is not known. We used computer simulations of 10-200 points/home range and compared accuracy of home range estimates produced by fixed and adaptive kernels with the reference (REF) and least-squares cross-validation (LSCV) methods for determining the amount of smoothing. Simulated home ranges varied from simple to complex shapes created by mixing bivariate normal distributions. We used the size of the 95% home range area and the relative mean squared error of the surface fit to assess the accuracy of the kernel home range estimates. For both measures, the bias and variance approached an asymptote at about 50 observations/home range. The fixed kernel with smoothing selected by LSCV provided the least-biased estimates of the 95% home range area. All kernel methods produced similar surface fit for most simulations, but the fixed kernel with LSCV had the lowest frequency and magnitude of very poor estimates. We reviewed 101 papers published in The Journal of Wildlife Management (JWM) between 1980 and 1997 that estimated animal home ranges. A minority of these papers used nonparametric utilization distribution (UD) estimators, and most did not adequately report sample sizes. We recommend that home range studies using kernel estimates use LSCV to determine the amount of smoothing, obtain a minimum of 30 observations per animal (but preferably a?Y50), and report sample sizes in published results.

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

    PubMed

    Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong

    2014-01-01

    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.

  1. Hyperspectral Image Classification via Kernel Sparse Representation

    DTIC Science & Technology

    2013-01-01

    classification algorithms. Moreover, the spatial coherency across neighboring pixels is also incorporated through a kernelized joint sparsity model , where...joint sparsity model , where all of the pixels within a small neighborhood are jointly represented in the feature space by selecting a few common training...hyperspectral imagery, joint spar- sity model , kernel methods, sparse representation. I. INTRODUCTION HYPERSPECTRAL imaging sensors capture images

  2. Effects of Amygdaline from Apricot Kernel on Transplanted Tumors in Mice.

    PubMed

    Yamshanov, V A; Kovan'ko, E G; Pustovalov, Yu I

    2016-03-01

    The effects of amygdaline from apricot kernel added to fodder on the growth of transplanted LYO-1 and Ehrlich carcinoma were studied in mice. Apricot kernels inhibited the growth of both tumors. Apricot kernels, raw and after thermal processing, given 2 days before transplantation produced a pronounced antitumor effect. Heat-processed apricot kernels given in 3 days after transplantation modified the tumor growth and prolonged animal lifespan. Thermal treatment did not considerably reduce the antitumor effect of apricot kernels. It was hypothesized that the antitumor effect of amygdaline on Ehrlich carcinoma and LYO-1 lymphosarcoma was associated with the presence of bacterial genome in the tumor.

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

    Science.gov Websites

    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

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

    PubMed

    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.

  5. Identification of spilled oils by NIR spectroscopy technology based on KPCA and LSSVM

    NASA Astrophysics Data System (ADS)

    Tan, Ailing; Bi, Weihong

    2011-08-01

    Oil spills on the sea surface are seen relatively often with the development of the petroleum exploitation and transportation of the sea. Oil spills are great threat to the marine environment and the ecosystem, thus the oil pollution in the ocean becomes an urgent topic in the environmental protection. To develop the oil spill accident treatment program and track the source of the spilled oils, a novel qualitative identification method combined Kernel Principal Component Analysis (KPCA) and Least Square Support Vector Machine (LSSVM) was proposed. The proposed method adapt Fourier transform NIR spectrophotometer to collect the NIR spectral data of simulated gasoline, diesel fuel and kerosene oil spills samples and do some pretreatments to the original spectrum. We use the KPCA algorithm which is an extension of Principal Component Analysis (PCA) using techniques of kernel methods to extract nonlinear features of the preprocessed spectrum. Support Vector Machines (SVM) is a powerful methodology for solving spectral classification tasks in chemometrics. LSSVM are reformulations to the standard SVMs which lead to solving a system of linear equations. So a LSSVM multiclass classification model was designed which using Error Correcting Output Code (ECOC) method borrowing the idea of error correcting codes used for correcting bit errors in transmission channels. The most common and reliable approach to parameter selection is to decide on parameter ranges, and to then do a grid search over the parameter space to find the optimal model parameters. To test the proposed method, 375 spilled oil samples of unknown type were selected to study. The optimal model has the best identification capabilities with the accuracy of 97.8%. Experimental results show that the proposed KPCA plus LSSVM qualitative analysis method of near infrared spectroscopy has good recognition result, which could work as a new method for rapid identification of spilled oils.

  6. Dietary safflower phospholipid reduces liver lipids in laying hens.

    PubMed

    An, B K; Nishiyama, H; Tanaka, K; Ohtani, S; Iwata, T; Tsutsumi, K; Kasai, M

    1997-05-01

    This experiment was conducted to determine the effects of dietary safflower phospholipids (crude safflower phospholipid and purified safflower phospholipid) on performance and lipid metabolism of laying hens. Sixty-week-old Single Comb White Leghorn laying hens were divided into four groups of seven birds each, and were given one of four experimental diets containing 5% beef tallow (served as a control, tallow), a mixture of safflower oil and palm oil (SP-oil), crude safflower phospholipid (Saf-PLcrude), or purified safflower phospholipid (Saf-PL) for 7 wk. Egg production ratio and daily egg mass were significantly higher in hens fed Saf-PLcrude diets than in hens of the other diet groups. There were no significant differences in egg weight among groups. Liver cholesterol and triglyceride contents were significantly decreased in all treated groups as compared with the control. The activity of hepatic 3-hydroxy-3 methylglutaryl coenzyme A reductase was the highest in hens fed the Saf-PLcrude diet. Serum esterified cholesterol concentration was decreased by feeding of SP-oil, Saf-PLcrude, or Saf-PL diets. Serum lecithin-cholesterol acyltransferase activity was highest in hens fed the tallow diet. Excreta neutral steroid excretion was significantly increased in the Saf-PLcrude or Saf-PL diet groups, although acidic steroid excretion was not affected by dietary treatments. Total cholesterol, triglyceride, and phospholipid contents in egg yolks were not different for any dietary treatments. The fatty acid compositions of egg yolks from hens fed Saf-PLcrude diets were not different with those fed the SP-oil diet, although eggs of hens fed the Saf-PL diet showed lower total polyunsaturated fatty acids. These results suggest that dietary safflower phospholipids may be a valuable ingredient to layers for reducing liver triglycerides and serum cholesterol without any adverse effects.

  7. 21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed...

  8. 21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed...

  9. 21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed...

  10. High speed sorting of Fusarium-damaged wheat kernels

    USDA-ARS?s Scientific Manuscript database

    Recent studies have found that resistance to Fusarium fungal infection can be inherited in wheat from one generation to another. However, there is not yet available a cost effective method to separate Fusarium-damaged wheat kernels from undamaged kernels so that wheat breeders can take advantage of...

  11. CW-SSIM kernel based random forest for image classification

    NASA Astrophysics Data System (ADS)

    Fan, Guangzhe; Wang, Zhou; Wang, Jiheng

    2010-07-01

    Complex wavelet structural similarity (CW-SSIM) index has been proposed as a powerful image similarity metric that is robust to translation, scaling and rotation of images, but how to employ it in image classification applications has not been deeply investigated. In this paper, we incorporate CW-SSIM as a kernel function into a random forest learning algorithm. This leads to a novel image classification approach that does not require a feature extraction or dimension reduction stage at the front end. We use hand-written digit recognition as an example to demonstrate our algorithm. We compare the performance of the proposed approach with random forest learning based on other kernels, including the widely adopted Gaussian and the inner product kernels. Empirical evidences show that the proposed method is superior in its classification power. We also compared our proposed approach with the direct random forest method without kernel and the popular kernel-learning method support vector machine. Our test results based on both simulated and realworld data suggest that the proposed approach works superior to traditional methods without the feature selection procedure.

  12. Insights from Classifying Visual Concepts with Multiple Kernel Learning

    PubMed Central

    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

  13. Nonparametric entropy estimation using kernel densities.

    PubMed

    Lake, Douglas E

    2009-01-01

    The entropy of experimental data from the biological and medical sciences provides additional information over summary statistics. Calculating entropy involves estimates of probability density functions, which can be effectively accomplished using kernel density methods. Kernel density estimation has been widely studied and a univariate implementation is readily available in MATLAB. The traditional definition of Shannon entropy is part of a larger family of statistics, called Renyi entropy, which are useful in applications that require a measure of the Gaussianity of data. Of particular note is the quadratic entropy which is related to the Friedman-Tukey (FT) index, a widely used measure in the statistical community. One application where quadratic entropy is very useful is the detection of abnormal cardiac rhythms, such as atrial fibrillation (AF). Asymptotic and exact small-sample results for optimal bandwidth and kernel selection to estimate the FT index are presented and lead to improved methods for entropy estimation.

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

    PubMed

    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.

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

    PubMed

    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.

  16. Fast generation of sparse random kernel graphs

    DOE PAGES

    Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo

    2015-09-10

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

  17. Ultra-stable self-foaming oils.

    PubMed

    Binks, Bernard P; Marinopoulos, Ioannis

    2017-05-01

    This paper is concerned with the foaming of a range of fats in the absence of added foaming agent/emulsifier. By controlling the temperature on warming from the solid or cooling from the melt, crystals of high melting triglycerides form in a continuous phase of low melting triglycerides. Such crystal dispersions in oil can be aerated to produce whipped oils of high foamability and extremely high stability. The foams do not exhibit drainage and bubbles neither coarsen nor coalesce as they become coated with solid crystals. The majority of the findings relate to coconut oil but the same phenomenon occurs in shea butter, cocoa butter and palm kernel stearin. For each fat, there exists an optimum temperature for foaming at which the solid fat content reaches up to around 30%. We demonstrate that the oil foams are temperature-responsive and foam collapse can be controllably triggered by warming the foam to around the melting point of the crystals. Our hypothesis is given credence in the case of the pure system of tristearin crystals in liquid tricaprylin. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Wavelet SVM in Reproducing Kernel Hilbert Space for hyperspectral remote sensing image classification

    NASA Astrophysics Data System (ADS)

    Du, Peijun; Tan, Kun; Xing, Xiaoshi

    2010-12-01

    Combining Support Vector Machine (SVM) with wavelet analysis, we constructed wavelet SVM (WSVM) classifier based on wavelet kernel functions in Reproducing Kernel Hilbert Space (RKHS). In conventional kernel theory, SVM is faced with the bottleneck of kernel parameter selection which further results in time-consuming and low classification accuracy. The wavelet kernel in RKHS is a kind of multidimensional wavelet function that can approximate arbitrary nonlinear functions. Implications on semiparametric estimation are proposed in this paper. Airborne Operational Modular Imaging Spectrometer II (OMIS II) hyperspectral remote sensing image with 64 bands and Reflective Optics System Imaging Spectrometer (ROSIS) data with 115 bands were used to experiment the performance and accuracy of the proposed WSVM classifier. The experimental results indicate that the WSVM classifier can obtain the highest accuracy when using the Coiflet Kernel function in wavelet transform. In contrast with some traditional classifiers, including Spectral Angle Mapping (SAM) and Minimum Distance Classification (MDC), and SVM classifier using Radial Basis Function kernel, the proposed wavelet SVM classifier using the wavelet kernel function in Reproducing Kernel Hilbert Space is capable of improving classification accuracy obviously.

  19. Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

    PubMed Central

    Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

    2017-01-01

    Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

  20. Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

    PubMed

    Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

    2017-01-01

    Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

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

    USDA-ARS?s Scientific Manuscript database

    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 ...

  2. Atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry of friction modifier additives analyzed directly from base oil solutions.

    PubMed

    Widder, Lukas; Brennerb, Josef; Huttera, Herbert

    2014-01-01

    To develop new products and to apply measures of quality control quick and simple accessibility of additive composition in automo- tive lubrication is important. The aim of this study was to investigate the possibility of analyzing organic friction modifier additives by means of atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry [AP-MALDI-MS] from lubricant solu- tions without the use of additional separation techniques. Analyses of selected friction modifier ethoxylated tallow amines and oleic acid amide were compared using two ionization methods, positive-ion electrospray ionization (ESI) and AP-MALDI, using a LTQ Orbitrap mass spectrometer. Pure additives were characterized from solvent solutions, as well as from synthetic and mineral base oil mixtures. Detected ions of pure additive samples consisted mainly of [M + H]+, but also alkaLi metal adducts [M + Na]+ and [M + K]+ could be seen. Characterizations of blends of both friction modifiers from the base oil mixtures were carried out as well and showed significant inten- sities for several additive peaks. Thus, this work shows a method to directly analyze friction modifier additives used in the automotive industry from an oil blend via the use of AP-MALDI without any further separation steps. The method presented will further simplify the acquisition of data on lubricant composition and additives. Furthermore, it allows the perspective of analyzing additive reaction products directly from formulated oil blends.

  3. Evidence-Based Kernels: Fundamental Units of Behavioral Influence

    ERIC Educational Resources Information Center

    Embry, Dennis D.; Biglan, Anthony

    2008-01-01

    This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior-influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of…

  4. Noise kernels of stochastic gravity in conformally-flat spacetimes

    NASA Astrophysics Data System (ADS)

    Cho, H. T.; Hu, B. L.

    2015-03-01

    The central object in the theory of semiclassical stochastic gravity is the noise kernel, which is the symmetric two point correlation function of the stress-energy tensor. Using the corresponding Wightman functions in Minkowski, Einstein and open Einstein spaces, we construct the noise kernels of a conformally coupled scalar field in these spacetimes. From them we show that the noise kernels in conformally-flat spacetimes, including the Friedmann-Robertson-Walker universes, can be obtained in closed analytic forms by using a combination of conformal and coordinate transformations.

  5. Travel-time sensitivity kernels in long-range propagation.

    PubMed

    Skarsoulis, E K; Cornuelle, B D; Dzieciuch, M A

    2009-11-01

    Wave-theoretic travel-time sensitivity kernels (TSKs) are calculated in two-dimensional (2D) and three-dimensional (3D) environments and their behavior with increasing propagation range is studied and compared to that of ray-theoretic TSKs and corresponding Fresnel-volumes. The differences between the 2D and 3D TSKs average out when horizontal or cross-range marginals are considered, which indicates that they are not important in the case of range-independent sound-speed perturbations or perturbations of large scale compared to the lateral TSK extent. With increasing range, the wave-theoretic TSKs expand in the horizontal cross-range direction, their cross-range extent being comparable to that of the corresponding free-space Fresnel zone, whereas they remain bounded in the vertical. Vertical travel-time sensitivity kernels (VTSKs)-one-dimensional kernels describing the effect of horizontally uniform sound-speed changes on travel-times-are calculated analytically using a perturbation approach, and also numerically, as horizontal marginals of the corresponding TSKs. Good agreement between analytical and numerical VTSKs, as well as between 2D and 3D VTSKs, is found. As an alternative method to obtain wave-theoretic sensitivity kernels, the parabolic approximation is used; the resulting TSKs and VTSKs are in good agreement with normal-mode results. With increasing range, the wave-theoretic VTSKs approach the corresponding ray-theoretic sensitivity kernels.

  6. Validation of Born Traveltime Kernels

    NASA Astrophysics Data System (ADS)

    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.

  7. End-use quality of soft kernel durum wheat

    USDA-ARS?s Scientific Manuscript database

    Kernel texture is a major determinant of end-use quality of wheat. Durum wheat is known for its very hard texture, which influences how it is milled and for what products it is well suited. We developed soft kernel durum wheat lines via Ph1b-mediated homoeologous recombination with Dr. Leonard Joppa...

  8. Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.

    PubMed

    Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K

    2016-03-01

    Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.

  9. Prioritizing individual genetic variants after kernel machine testing using variable selection.

    PubMed

    He, Qianchuan; Cai, Tianxi; Liu, Yang; Zhao, Ni; Harmon, Quaker E; Almli, Lynn M; Binder, Elisabeth B; Engel, Stephanie M; Ressler, Kerry J; Conneely, Karen N; Lin, Xihong; Wu, Michael C

    2016-12-01

    Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach. © 2016 WILEY PERIODICALS, INC.

  10. New oilseed crops on the horizon

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Princen, L.H.

    Fats and oils for food uses are now plentiful on a worldwide basis. Tallow, lard and fish oils, as well as vegetable oils, such as those derived from soybean, sunflower, palm, rapeseed, peanut and cottonseed, are often overproduced. Although many of these products are also used for industrial chemicals, they often are not of the most favorable composition for nonfood applications. A search for new oilseed crops with more advantageous oil composition has led to the development of excellent candidates that are now close to commercial acceptance. Among them are Crambe, Limnanthes, Vernonia, Sapium and Simmondsia. Other crops are atmore » a much lower stage of development but also have excellent potential. They include Cuphea, Foeniculum, Stokesia, Lesquerella and Lunaria. One new oilseed crop which is being considered for hydrocarbon-like fuel is the Chinese tallow tree (Sapium Sebiferum). Recent research estimates predict that seed yield could amount to 10,000 lbs. per acre. At 40% seed lipid levels, this can translate to 4000 lbs. per acre of fuel, more than any other plant species now growing in the US. 24 references, 6 figures, 5 tables.« less

  11. Multitasking kernel for the C and Fortran programming languages

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Brooks, E.D. III

    1984-09-01

    A multitasking kernel for the C and Fortran programming languages which runs on the Unix operating system is presented. The kernel provides a multitasking environment which serves two purposes. The first is to provide an efficient portable environment for the coding, debugging and execution of production multiprocessor programs. The second is to provide a means of evaluating the performance of a multitasking program on model multiprocessors. The performance evaluation features require no changes in the source code of the application and are implemented as a set of compile and run time options in the kernel.

  12. Deep kernel learning method for SAR image target recognition

    NASA Astrophysics Data System (ADS)

    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.

  13. Estimating Potential Effects of Hypothetical Oil Spills on Polar Bears

    USGS Publications Warehouse

    Amstrup, Steven C.; Durner, George M.; McDonald, T.L.; Johnson, W.R.

    2006-01-01

    Much is known about the transport and fate of oil spilled into the sea and its toxicity to exposed wildlife. Previously, however, there has been no way to quantify the probability that wildlife dispersed over the seascape would be exposed to spilled oil. Polar bears, the apical predator of the arctic, are widely dispersed near the continental shelves of the Arctic Ocean, an area also undergoing considerable hydrocarbon exploration and development. We used 15,308 satellite locations from 194 radiocollared polar bears to estimate the probability that polar bears could be exposed to hypothetical oil spills. We used a true 2 dimensional Gausian kernel density estimator, to estimate the number of bears likely to occur in each 1.00 km2 cell of a grid superimposed over near shore areas surrounding 2 oil production facilities: the existing Northstar oil production facility, and the proposed offshore site for the Liberty production facility. We estimated the standard errors of bear numbers per cell with bootstrapping. Simulated oil spill footprints for September and October, the times during which we hypothesized effects of an oil-spill would be worst, were estimated using real wind and current data collected between 1980 and 1996. We used ARC/Info software to calculate overlap (numbers of bears oiled) between simulated oil-spill footprints and polar bear grid-cell values. Numbers of bears potentially oiled by a hypothetical 5912 barrel spill (the largest spill thought probable from a pipeline breach) ranged from 0 to 27 polar bears for September open water conditions, and from 0 to 74 polar bears in October mixed ice conditions. Median numbers oiled by the 5912 barrel hypothetical spill from the Liberty simulation in September and October were 1 and 3 bears, equivalent values for the Northstar simulation were 3 and 11 bears. In October, 75% of trajectories from the 5912 barrel simulated spill at Liberty oiled 9 or fewer bears while 75% of the trajectories affected 20 or

  14. PERI - Auto-tuning Memory Intensive Kernels for Multicore

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bailey, David H; Williams, Samuel; Datta, Kaushik

    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 developmore » 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.« less

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

    NASA Technical Reports Server (NTRS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

    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

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

    PubMed

    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.

  19. Pressure Sensitivity Kernels Applied to Time-reversal Acoustics

    DTIC Science & Technology

    2009-06-29

    experimental data, along with an internal wave model, using various metrics. The linear limitations of the kernels are explored in the context of time...Acknowledgments . . . . . . . . . . . . . . . . . . . . . . 82 3.A Internal wave modeling . . . . . . . . . . . . . . . . . . . 82 Bibliography...multipaths corresponding to direct path, single surface/bottom bounce, double bounce off the surface and bot- tom, Bottom: Time-domain sensitivity kernel for

  20. Optimal Bandwidth Selection in Observed-Score Kernel Equating

    ERIC Educational Resources Information Center

    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…

  1. Unconventional Signal Processing Using the Cone Kernel Time-Frequency Representation.

    DTIC Science & Technology

    1992-10-30

    Wigner - Ville distribution ( WVD ), the Choi- Williams distribution , and the cone kernel distribution were compared with the spectrograms. Results were...ambiguity function. Figures A-18(c) and (d) are the Wigner - Ville Distribution ( WVD ) and CK-TFR Doppler maps. In this noiseless case all three exhibit...kernel is the basis for the well known Wigner - Ville distribution . In A-9(2), the cone kernel defined by Zhao, Atlas and Marks [21 is described

  2. Kernel structures for Clouds

    NASA Technical Reports Server (NTRS)

    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.

  3. Influence of different dietary doses of n-3- or n-6-rich vegetable fats and alpha-tocopheryl acetate supplementation on raw and cooked rabbit meat composition and oxidative stability.

    PubMed

    Tres, Alba; Bou, Ricard; Codony, Rafael; Guardiola, Francesc

    2008-08-27

    This study evaluates the effects of replacing beef tallow added to rabbit feeds (3% w/w) by different doses (0%, 1.5% and 3% w/w) of n-6- or n-3-rich vegetable fat sources (sunflower and linseed oil, respectively) and alpha-tocopheryl acetate supplementation (0 and 100 mg/kg) on the fatty acid composition, alpha-tocopherol content, and oxidation levels [assessed by analyzing thiobarbituric acid (TBA) and lipid hydroperoxide values] in rabbit meat. We also measured these parameters after cooking and refrigerated storage of cooked rabbit meat. Both dietary alpha-tocopheryl acetate supplementation and the dose and source of fat added to feeds influenced meat fatty acid composition, modifying the n-6/n-3 ratio, which was more nutritionally favorable when linseed oil was used. Furthermore, the addition of linseed oil and the supplementation with alpha-tocopheryl acetate enhanced long-chain PUFA biosynthesis. However, the addition of 3% linseed oil increased meat oxidation, and although it was reduced by dietary supplementation with alpha-tocopheryl acetate in raw meat, this reduction was not as effective after cooking. Therefore, dietary supplementation with 1.5% linseed oil plus 1.5% beef tallow and with alpha-tocopheryl acetate would be recommended to improve the nutritional quality of rabbit meat.

  4. Soluble lipase-catalyzed synthesis of methyl esters using a blend of edible and nonedible raw materials.

    PubMed

    Wancura, João H C; Rosset, Daniela V; Brondani, Michel; Mazutti, Marcio A; Oliveira, J Vladimir; Tres, Marcus V; Jahn, Sérgio L

    2018-04-26

    This work investigates the use of blends of edible and nonedible raw materials as an alternative feedstock to fatty acid methyl esters (FAME) production through enzymatic catalysis. As biocatalyst, liquid lipase from Thermomyces lanuginosus (Callera™ Trans L), was used. Under reaction conditions of 35 °C, methanol to feedstock molar ratio of 4.5:1 and 1.45% of catalyst load, the best process performance was reached using 9% of water concentration in the medium-yield of 79.9% after 480 min of reaction. In terms of use of tallow mixed with soybean oil, the best yield was obtained when 100% of tallow was used in the process-84.6% after 480 min of reaction-behavior that was associated with the degree of unsaturation of the feedstock, something by that time, not addressed in papers of the area. The results show that tallow can be used as an alternative to FAME production, catalyzed by soluble lipase.

  5. TICK: Transparent Incremental Checkpointing at Kernel Level

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Petrini, Fabrizio; Gioiosa, Roberto

    2004-10-25

    TICK is a software package implemented in Linux 2.6 that allows the save and restore of user processes, without any change to the user code or binary. With TICK a process can be suspended by the Linux kernel upon receiving an interrupt and saved in a file. This file can be later thawed in another computer running Linux (potentially the same computer). TICK is implemented as a Linux kernel module, in the Linux version 2.6.5

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

    PubMed

    Maranz, Steven; Wiesman, Zeev; Garti, Nissim

    2003-10-08

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

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

    USDA-ARS?s Scientific Manuscript database

    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...

  8. Finite-frequency sensitivity kernels for head waves

    NASA Astrophysics Data System (ADS)

    Zhang, Zhigang; Shen, Yang; Zhao, Li

    2007-11-01

    Head waves are extremely important in determining the structure of the predominantly layered Earth. While several recent studies have shown the diffractive nature and the 3-D Fréchet kernels of finite-frequency turning waves, analogues of head waves in a continuous velocity structure, the finite-frequency effects and sensitivity kernels of head waves are yet to be carefully examined. We present the results of a numerical study focusing on the finite-frequency effects of head waves. Our model has a low-velocity layer over a high-velocity half-space and a cylindrical-shaped velocity perturbation placed beneath the interface at different locations. A 3-D finite-difference method is used to calculate synthetic waveforms. Traveltime and amplitude anomalies are measured by the cross-correlation of synthetic seismograms from models with and without the velocity perturbation and are compared to the 3-D sensitivity kernels constructed from full waveform simulations. The results show that the head wave arrival-time and amplitude are influenced by the velocity structure surrounding the ray path in a pattern that is consistent with the Fresnel zones. Unlike the `banana-doughnut' traveltime sensitivity kernels of turning waves, the traveltime sensitivity of the head wave along the ray path below the interface is weak, but non-zero. Below the ray path, the traveltime sensitivity reaches the maximum (absolute value) at a depth that depends on the wavelength and propagation distance. The sensitivity kernels vary with the vertical velocity gradient in the lower layer, but the variation is relatively small at short propagation distances when the vertical velocity gradient is within the range of the commonly accepted values. Finally, the depression or shoaling of the interface results in increased or decreased sensitivities, respectively, beneath the interface topography.

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

    PubMed

    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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Semisupervised kernel marginal Fisher analysis for face recognition.

    PubMed

    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.

  13. Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

    PubMed

    Maulik, Ujjwal; Sarkar, Anasua

    2013-01-01

    Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. sarkar@labri.fr.

  14. A dry-inoculation method for nut kernels.

    PubMed

    Blessington, Tyann; Theofel, Christopher G; Harris, Linda J

    2013-04-01

    A dry-inoculation method for almonds and walnuts was developed to eliminate the need for the postinoculation drying required for wet-inoculation methods. The survival of Salmonella enterica Enteritidis PT 30 on wet- and dry-inoculated almond and walnut kernels stored under ambient conditions (average: 23 °C; 41 or 47% RH) was then compared over 14 weeks. For wet inoculation, an aqueous Salmonella preparation was added directly to almond or walnut kernels, which were then dried under ambient conditions (3 or 7 days, respectively) to initial nut moisture levels. For the dry inoculation, liquid inoculum was mixed with sterilized sand and dried for 24 h at 40 °C. The dried inoculated sand was mixed with kernels, and the sand was removed by shaking the mixture in a sterile sieve. Mixing procedures to optimize the bacterial transfer from sand to kernel were evaluated; in general, similar levels were achieved on walnuts (4.8-5.2 log CFU/g) and almonds (4.2-5.1 log CFU/g). The decline of Salmonella Enteritidis populations was similar during ambient storage (98 days) for both wet-and dry-inoculation methods for both almonds and walnuts. The dry-inoculation method mimics some of the suspected routes of contamination for tree nuts and may be appropriate for some postharvest challenge studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

    NASA Astrophysics Data System (ADS)

    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.

  16. Design of a multiple kernel learning algorithm for LS-SVM by convex programming.

    PubMed

    Jian, Ling; Xia, Zhonghang; Liang, Xijun; Gao, Chuanhou

    2011-06-01

    As a kernel based method, the performance of least squares support vector machine (LS-SVM) depends on the selection of the kernel as well as the regularization parameter (Duan, Keerthi, & Poo, 2003). Cross-validation is efficient in selecting a single kernel and the regularization parameter; however, it suffers from heavy computational cost and is not flexible to deal with multiple kernels. In this paper, we address the issue of multiple kernel learning for LS-SVM by formulating it as semidefinite programming (SDP). Furthermore, we show that the regularization parameter can be optimized in a unified framework with the kernel, which leads to an automatic process for model selection. Extensive experimental validations are performed and analyzed. Copyright © 2011 Elsevier Ltd. All rights reserved.

  17. Acute and Subchronic Toxicity of Self Nanoemulsifying Drug Delivery Systems (SNEDDS) from Chloroform Bay Leaf Extract (Eugenia Polyantha W.) with Palm Kernel Oil as A Carrier

    NASA Astrophysics Data System (ADS)

    Prihapsara, F.; Mufidah; Artanti, A. N.; Harini, M.

    2018-03-01

    The present study was aimed to study the acute and subchronic toxicity of Self Nanoemulsifying Drug Delivery Systems (SNEDDS) from chloroform bay leaf extract with Palm Kernel Oil as carrier. In acute toxicity test, five groups of rat (n=5/groups) were orally treated with Self Nanoemulsifying Drug Delivery Systems (SNEDDS) from chloroform bay leaf extract with doses at 48, 240, 1200 and 6000 mg/kg/day respectively, then the median lethal dose LD50, advers effect and mortality were recorded up to 14 days. Meanwhile, in subchronic toxicity study, 4 groups of rats (n=6/group) received by orally treatment of SNEDDS from chloroform bay leaf extract with doses at 91.75; 183.5; 367 mg/kg/day respectively for 28 days, and biochemical, hematological and histopatological change in tissue such as liver, kidney, and pancreatic were determined. The result show that LD50 is 1045.44 mg/kg. Although histopathological examination of most of the organs exhibited no structural changes, some moderate damage was observed in high‑ dose group animals (367 mg/kg/day). The high dose of SNEDDS extract has shown mild signs of toxicity on organ function test.

  18. Quasi-kernel polynomials and convergence results for quasi-minimal residual iterations

    NASA Technical Reports Server (NTRS)

    Freund, Roland W.

    1992-01-01

    Recently, Freund and Nachtigal have proposed a novel polynominal-based iteration, the quasi-minimal residual algorithm (QMR), for solving general nonsingular non-Hermitian linear systems. Motivated by the QMR method, we have introduced the general concept of quasi-kernel polynomials, and we have shown that the QMR algorithm is based on a particular instance of quasi-kernel polynomials. In this paper, we continue our study of quasi-kernel polynomials. In particular, we derive bounds for the norms of quasi-kernel polynomials. These results are then applied to obtain convergence theorems both for the QMR method and for a transpose-free variant of QMR, the TFQMR algorithm.

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

    PubMed

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

    2017-07-01

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

  20. Effect of feeding quandong (Santalum acuminatum) oil to rats on tissue lipids, hepatic cytochrome P-450 and tissue histology.

    PubMed

    Jones, G P; Birkett, A; Sanigorski, A; Sinclair, A J; Hooper, P T; Watson, T; Rieger, V

    1994-06-01

    Quandong kernels are a traditional Aboriginal food item; they are rich in oil and contain large amounts of an unusual fatty acid, trans-11-octadecen-9-ynoic acid (santalbic acid), but it is not known whether this acid is absorbed and/or metabolized. The oil was fed at 12.6% of total energy content in semi-synthetic diets to groups of male Sprague-Dawley rats for 10 and 20 days. Santalbic acid was found in the lipids of plasma, adipose tissue, skeletal muscle, kidney, heart and liver but not in brain. Hepatic microsomal cytochrome P-450 activity in animals fed for 20 days was significantly higher (P < 0.05) than in controls. Histopathological examination did not reveal any lesions in the tissues of any animal fed quandong oil. The fact that santalbic acid was readily absorbed, widely distributed in tissues and was associated with an elevated level of hepatic cytochrome P-450 indicates that further studies are required to investigate whether or not there is a hazard associated with the human practice of consuming quandong kernels.

  1. Weighted Feature Gaussian Kernel SVM for Emotion Recognition

    PubMed Central

    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. PMID:27807443

  2. Searching Remote Homology with Spectral Clustering with Symmetry in Neighborhood Cluster Kernels

    PubMed Central

    Maulik, Ujjwal; Sarkar, Anasua

    2013-01-01

    Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of “recent” paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request. Contact: sarkar@labri.fr. PMID:23457439

  3. Multiple kernel learning in protein-protein interaction extraction from biomedical literature.

    PubMed

    Yang, Zhihao; Tang, Nan; Zhang, Xiao; Lin, Hongfei; Li, Yanpeng; Yang, Zhiwei

    2011-03-01

    Knowledge about protein-protein interactions (PPIs) unveils the molecular mechanisms of biological processes. The volume and content of published biomedical literature on protein interactions is expanding rapidly, making it increasingly difficult for interaction database administrators, responsible for content input and maintenance to detect and manually update protein interaction information. The objective of this work is to develop an effective approach to automatic extraction of PPI information from biomedical literature. We present a weighted multiple kernel learning-based approach for automatic PPI extraction from biomedical literature. The approach combines the following kernels: feature-based, tree, graph and part-of-speech (POS) path. In particular, we extend the shortest path-enclosed tree (SPT) and dependency path tree to capture richer contextual information. Our experimental results show that the combination of SPT and dependency path tree extensions contributes to the improvement of performance by almost 0.7 percentage units in F-score and 2 percentage units in area under the receiver operating characteristics curve (AUC). Combining two or more appropriately weighed individual will further improve the performance. Both on the individual corpus and cross-corpus evaluation our combined kernel can achieve state-of-the-art performance with respect to comparable evaluations, with 64.41% F-score and 88.46% AUC on the AImed corpus. As different kernels calculate the similarity between two sentences from different aspects. Our combined kernel can reduce the risk of missing important features. More specifically, we use a weighted linear combination of individual kernels instead of assigning the same weight to each individual kernel, thus allowing the introduction of each kernel to incrementally contribute to the performance improvement. In addition, SPT and dependency path tree extensions can improve the performance by including richer context information

  4. Relationship between processing score and kernel-fraction particle size in whole-plant corn silage.

    PubMed

    Dias Junior, G S; Ferraretto, L F; Salvati, G G S; de Resende, L C; Hoffman, P C; Pereira, M N; Shaver, R D

    2016-04-01

    Kernel processing increases starch digestibility in whole-plant corn silage (WPCS). Corn silage processing score (CSPS), the percentage of starch passing through a 4.75-mm sieve, is widely used to assess degree of kernel breakage in WPCS. However, the geometric mean particle size (GMPS) of the kernel-fraction that passes through the 4.75-mm sieve has not been well described. Therefore, the objectives of this study were (1) to evaluate particle size distribution and digestibility of kernels cut in varied particle sizes; (2) to propose a method to measure GMPS in WPCS kernels; and (3) to evaluate the relationship between CSPS and GMPS of the kernel fraction in WPCS. Composite samples of unfermented, dried kernels from 110 corn hybrids commonly used for silage production were kept whole (WH) or manually cut in 2, 4, 8, 16, 32 or 64 pieces (2P, 4P, 8P, 16P, 32P, and 64P, respectively). Dry sieving to determine GMPS, surface area, and particle size distribution using 9 sieves with nominal square apertures of 9.50, 6.70, 4.75, 3.35, 2.36, 1.70, 1.18, and 0.59 mm and pan, as well as ruminal in situ dry matter (DM) digestibilities were performed for each kernel particle number treatment. Incubation times were 0, 3, 6, 12, and 24 h. The ruminal in situ DM disappearance of unfermented kernels increased with the reduction in particle size of corn kernels. Kernels kept whole had the lowest ruminal DM disappearance for all time points with maximum DM disappearance of 6.9% at 24 h and the greatest disappearance was observed for 64P, followed by 32P and 16P. Samples of WPCS (n=80) from 3 studies representing varied theoretical length of cut settings and processor types and settings were also evaluated. Each WPCS sample was divided in 2 and then dried at 60 °C for 48 h. The CSPS was determined in duplicate on 1 of the split samples, whereas on the other split sample the kernel and stover fractions were separated using a hydrodynamic separation procedure. After separation, the

  5. Boundary conditions for gas flow problems from anisotropic scattering kernels

    NASA Astrophysics Data System (ADS)

    To, Quy-Dong; Vu, Van-Huyen; Lauriat, Guy; Léonard, Céline

    2015-10-01

    The paper presents an interface model for gas flowing through a channel constituted of anisotropic wall surfaces. Using anisotropic scattering kernels and Chapman Enskog phase density, the boundary conditions (BCs) for velocity, temperature, and discontinuities including velocity slip and temperature jump at the wall are obtained. Two scattering kernels, Dadzie and Méolans (DM) kernel, and generalized anisotropic Cercignani-Lampis (ACL) are examined in the present paper, yielding simple BCs at the wall fluid interface. With these two kernels, we rigorously recover the analytical expression for orientation dependent slip shown in our previous works [Pham et al., Phys. Rev. E 86, 051201 (2012) and To et al., J. Heat Transfer 137, 091002 (2015)] which is in good agreement with molecular dynamics simulation results. More important, our models include both thermal transpiration effect and new equations for the temperature jump. While the same expression depending on the two tangential accommodation coefficients is obtained for slip velocity, the DM and ACL temperature equations are significantly different. The derived BC equations associated with these two kernels are of interest for the gas simulations since they are able to capture the direction dependent slip behavior of anisotropic interfaces.

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

    PubMed

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

    2017-06-21

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

  7. 21 CFR 182.40 - Natural extractives (solvent-free) used in conjunction with spices, seasonings, and flavorings.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... the Act, are as follows: Common name Botanical name of plant source Apricot kernel (persic oil) Prunus armeniaca L. Peach kernel (persic oil) Prunus persica Sieb. et Zucc. Peanut stearine Arachis hypogaea L. Persic oil (see apricot kernel and peach kernel) Quince seed Cydonia oblonga Miller. [42 FR 14640, Mar...

  8. Ambered kernels in stenospermocarpic fruit of eastern black walnut

    Treesearch

    Michele R. Warmund; J.W. Van Sambeek

    2014-01-01

    "Ambers" is a term used to describe poorly filled, shriveled eastern black walnut (Juglans nigra L.) kernels with a dark brown or black-colored pellicle that are unmarketable. Studies were conducted to determine the incidence of ambered black walnut kernels and to ascertain when symptoms were apparent in specific tissues. The occurrence of...

  9. Antioxidant and antimicrobial activities of bitter and sweet apricot (Prunus armeniaca L.) kernels.

    PubMed

    Yiğit, D; Yiğit, N; Mavi, A

    2009-04-01

    The present study describes the in vitro antimicrobial and antioxidant activity of methanol and water extracts of sweet and bitter apricot (Prunus armeniaca L.) kernels. The antioxidant properties of apricot kernels were evaluated by determining radical scavenging power, lipid peroxidation inhibition activity and total phenol content measured with a DPPH test, the thiocyanate method and the Folin method, respectively. In contrast to extracts of the bitter kernels, both the water and methanol extracts of sweet kernels have antioxidant potential. The highest percent inhibition of lipid peroxidation (69%) and total phenolic content (7.9 +/- 0.2 microg/mL) were detected in the methanol extract of sweet kernels (Hasanbey) and in the water extract of the same cultivar, respectively. The antimicrobial activities of the above extracts were also tested against human pathogenic microorganisms using a disc-diffusion method, and the minimal inhibitory concentration (MIC) values of each active extract were determined. The most effective antibacterial activity was observed in the methanol and water extracts of bitter kernels and in the methanol extract of sweet kernels against the Gram-positive bacteria Staphylococcus aureus. Additionally, the methanol extracts of the bitter kernels were very potent against the Gram-negative bacteria Escherichia coli (0.312 mg/mL MIC value). Significant anti-candida activity was also observed with the methanol extract of bitter apricot kernels against Candida albicans, consisting of a 14 mm in diameter of inhibition zone and a 0.625 mg/mL MIC value.

  10. Acute cyanide toxicity caused by apricot kernel ingestion.

    PubMed

    Suchard, J R; Wallace, K L; Gerkin, R D

    1998-12-01

    A 41-year-old woman ingested apricot kernels purchased at a health food store and became weak and dyspneic within 20 minutes. The patient was comatose and hypothermic on presentation but responded promptly to antidotal therapy for cyanide poisoning. She was later treated with a continuous thiosulfate infusion for persistent metabolic acidosis. This is the first reported case of cyanide toxicity from apricot kernel ingestion in the United States since 1979.

  11. Nutrition quality of extraction mannan residue from palm kernel cake on brolier chicken

    NASA Astrophysics Data System (ADS)

    Tafsin, M.; Hanafi, N. D.; Kejora, E.; Yusraini, E.

    2018-02-01

    This study aims to find out the nutrient residue of palm kernel cake from mannan extraction on broiler chicken by evaluating physical quality (specific gravity, bulk density and compacted bulk density), chemical quality (proximate analysis and Van Soest Test) and biological test (metabolizable energy). Treatment composed of T0 : palm kernel cake extracted aquadest (control), T1 : palm kernel cake extracted acetic acid (CH3COOH) 1%, T2 : palm kernel cake extracted aquadest + mannanase enzyme 100 u/l and T3 : palm kernel cake extracted acetic acid (CH3COOH) 1% + enzyme mannanase 100 u/l. The results showed that mannan extraction had significant effect (P<0.05) in improving the quality of physical and numerically increase the value of crude protein and decrease the value of NDF (Neutral Detergent Fiber). Treatments had highly significant influence (P<0.01) on the metabolizable energy value of palm kernel cake residue in broiler chickens. It can be concluded that extraction with aquadest + enzyme mannanase 100 u/l yields the best nutrient quality of palm kernel cake residue for broiler chicken.

  12. The site, size, spatial stability, and energetics of an X-ray flare kernel

    NASA Technical Reports Server (NTRS)

    Petrasso, R.; Gerassimenko, M.; Nolte, J.

    1979-01-01

    The site, size evolution, and energetics of an X-ray kernel that dominated a solar flare during its rise and somewhat during its peak are investigated. The position of the kernel remained stationary to within about 3 arc sec over the 30-min interval of observations, despite pulsations in the kernel X-ray brightness in excess of a factor of 10. This suggests a tightly bound, deeply rooted magnetic structure, more plausibly associated with the near chromosphere or low corona rather than with the high corona. The H-alpha flare onset coincided with the appearance of the kernel, again suggesting a close spatial and temporal coupling between the chromospheric H-alpha event and the X-ray kernel. At the first kernel brightness peak its size was no larger than about 2 arc sec, when it accounted for about 40% of the total flare flux. In the second rise phase of the kernel, a source power input of order 2 times 10 to the 24th ergs/sec is minimally required.

  13. Processing of palm oil mill wastes based on zero waste technology

    NASA Astrophysics Data System (ADS)

    Irvan

    2018-02-01

    Indonesia is currently the main producer of palm oil in the world with a total production reached 33.5 million tons per year. In the processing of fresh fruit bunches (FFB) besides producing palm oil and kernel oil, palm oil mills also produce liquid and solid wastes. The increase of palm oil production will be followed by an increase in the production of waste generated. It will give rise to major environmental issues especially the discharge of liquid waste to the rivers, the emission of methane from digestion pond and the incineration of empty fruit bunches (EFB). This paper describes a zero waste technology in processing palm oil mill waste after the milling process. The technology involves fermentation of palm oil mill effluent (POME) to biogas by using continuous stirred tank reactor (CSTR) in the presence of thermophilic microbes, producing activated liquid organic fertilizer (ALOF) from discharge of treated waste effluent from biogas digester, composting EFB by spraying ALOF on the EFB in the composter, and producing pellet or biochar from EFB by pyrolysis process. This concept can be considered as a promising technology for palm oil mills with the main objective of eliminating the effluent from their mills.

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

    PubMed

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

    2016-01-19

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

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

    PubMed Central

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

    2016-01-01

    The efficacy of color sorting on reducing aflatoxin levels in shelled apricot kernels was assessed. Naturally-contaminated kernels were submitted to an electronic optical sorter or blanched, peeled, and manually sorted to visually identify and sort discolored kernels (dark and spotted) from healthy ones. The samples obtained from the two sorting approaches were ground, homogenized, and analysed by HPLC-FLD for their aflatoxin content. A mass balance approach was used to measure the distribution of aflatoxins in the collected fractions. Aflatoxin B1 and B2 were identified and quantitated in all collected fractions at levels ranging from 1.7 to 22,451.5 µg/kg of AFB1 + AFB2, whereas AFG1 and AFG2 were not detected. Excellent results were obtained by manual sorting of peeled kernels since the removal of discolored kernels (2.6%–19.9% of total peeled kernels) removed 97.3%–99.5% of total aflatoxins. The combination of peeling and visual/manual separation of discolored kernels is a feasible strategy to remove 97%–99% of aflatoxins accumulated in naturally-contaminated samples. Electronic optical sorter gave highly variable results since the amount of AFB1 + AFB2 measured in rejected fractions (15%–18% of total kernels) ranged from 13% to 59% of total aflatoxins. An improved immunoaffinity-based HPLC-FLD method having low limits of detection for the four aflatoxins (0.01–0.05 µg/kg) was developed and used to monitor the occurrence of aflatoxins in 47 commercial products containing apricot kernels and/or almonds commercialized in Italy. Low aflatoxin levels were found in 38% of the tested samples and ranged from 0.06 to 1.50 μg/kg for AFB1 and from 0.06 to 1.79 μg/kg for total aflatoxins. PMID:26797635

  16. Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

    NASA Astrophysics Data System (ADS)

    Canas, Liane S.; Yvernault, Benjamin; Cash, David M.; Molteni, Erika; Veale, Tom; Benzinger, Tammie; Ourselin, Sébastien; Mead, Simon; Modat, Marc

    2018-02-01

    Gaussian Processes (GP) are a powerful tool to capture the complex time-variations of a dataset. In the context of medical imaging analysis, they allow a robust modelling even in case of highly uncertain or incomplete datasets. Predictions from GP are dependent of the covariance kernel function selected to explain the data variance. To overcome this limitation, we propose a framework to identify the optimal covariance kernel function to model the data.The optimal kernel is defined as a composition of base kernel functions used to identify correlation patterns between data points. Our approach includes a modified version of the Compositional Kernel Learning (CKL) algorithm, in which we score the kernel families using a new energy function that depends both the Bayesian Information Criterion (BIC) and the explained variance score. We applied the proposed framework to model the progression of neurodegenerative diseases over time, in particular the progression of autosomal dominantly-inherited Alzheimer's disease, and use it to predict the time to clinical onset of subjects carrying genetic mutation.

  17. A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

    PubMed

    Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

    2018-06-12

    Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

  18. 9 CFR 95.29 - Certification for certain materials.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... described in paragraph (b) of this section: (1) Processed animal protein, tankage, offal, and tallow other... derived from ruminants; (3) Processed fats and oils, and derivatives of processed animal protein, tankage..., as described in paragraph (b) of this section: (1) Processed animal protein, tankage, offal, and...

  19. 40 CFR 432.100 - Applicability.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... AND POULTRY PRODUCTS POINT SOURCE CATEGORY Renderers § 432.100 Applicability. This part applies to discharges of process wastewater resulting from the production of meat meal, dried animal by-product residues (tankage), animal oils, grease and tallow, and in some cases hide curing, by a renderer. ...

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

    PubMed Central

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

    2017-01-01

    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. PMID:28629202

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

    PubMed

    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.

  2. Improved scatter correction using adaptive scatter kernel superposition

    NASA Astrophysics Data System (ADS)

    Sun, M.; Star-Lack, J. M.

    2010-11-01

    Accurate scatter correction is required to produce high-quality reconstructions of x-ray cone-beam computed tomography (CBCT) scans. This paper describes new scatter kernel superposition (SKS) algorithms for deconvolving scatter from projection data. The algorithms are designed to improve upon the conventional approach whose accuracy is limited by the use of symmetric kernels that characterize the scatter properties of uniform slabs. To model scatter transport in more realistic objects, nonstationary kernels, whose shapes adapt to local thickness variations in the projection data, are proposed. Two methods are introduced: (1) adaptive scatter kernel superposition (ASKS) requiring spatial domain convolutions and (2) fast adaptive scatter kernel superposition (fASKS) where, through a linearity approximation, convolution is efficiently performed in Fourier space. The conventional SKS algorithm, ASKS, and fASKS, were tested with Monte Carlo simulations and with phantom data acquired on a table-top CBCT system matching the Varian On-Board Imager (OBI). All three models accounted for scatter point-spread broadening due to object thickening, object edge effects, detector scatter properties and an anti-scatter grid. Hounsfield unit (HU) errors in reconstructions of a large pelvis phantom with a measured maximum scatter-to-primary ratio over 200% were reduced from -90 ± 58 HU (mean ± standard deviation) with no scatter correction to 53 ± 82 HU with SKS, to 19 ± 25 HU with fASKS and to 13 ± 21 HU with ASKS. HU accuracies and measured contrast were similarly improved in reconstructions of a body-sized elliptical Catphan phantom. The results show that the adaptive SKS methods offer significant advantages over the conventional scatter deconvolution technique.

  3. Notes on a storage manager for the Clouds kernel

    NASA Technical Reports Server (NTRS)

    Pitts, David V.; Spafford, Eugene H.

    1986-01-01

    The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

  4. Metabolite identification through multiple kernel learning on fragmentation trees.

    PubMed

    Shen, Huibin; Dührkop, Kai; Böcker, Sebastian; Rousu, Juho

    2014-06-15

    Metabolite identification from tandem mass spectrometric data is a key task in metabolomics. Various computational methods have been proposed for the identification of metabolites from tandem mass spectra. Fragmentation tree methods explore the space of possible ways in which the metabolite can fragment, and base the metabolite identification on scoring of these fragmentation trees. Machine learning methods have been used to map mass spectra to molecular fingerprints; predicted fingerprints, in turn, can be used to score candidate molecular structures. Here, we combine fragmentation tree computations with kernel-based machine learning to predict molecular fingerprints and identify molecular structures. We introduce a family of kernels capturing the similarity of fragmentation trees, and combine these kernels using recently proposed multiple kernel learning approaches. Experiments on two large reference datasets show that the new methods significantly improve molecular fingerprint prediction accuracy. These improvements result in better metabolite identification, doubling the number of metabolites ranked at the top position of the candidates list. © The Author 2014. Published by Oxford University Press.

  5. Efficient Multiple Kernel Learning Algorithms Using Low-Rank Representation.

    PubMed

    Niu, Wenjia; Xia, Kewen; Zu, Baokai; Bai, Jianchuan

    2017-01-01

    Unlike Support Vector Machine (SVM), Multiple Kernel Learning (MKL) allows datasets to be free to choose the useful kernels based on their distribution characteristics rather than a precise one. It has been shown in the literature that MKL holds superior recognition accuracy compared with SVM, however, at the expense of time consuming computations. This creates analytical and computational difficulties in solving MKL algorithms. To overcome this issue, we first develop a novel kernel approximation approach for MKL and then propose an efficient Low-Rank MKL (LR-MKL) algorithm by using the Low-Rank Representation (LRR). It is well-acknowledged that LRR can reduce dimension while retaining the data features under a global low-rank constraint. Furthermore, we redesign the binary-class MKL as the multiclass MKL based on pairwise strategy. Finally, the recognition effect and efficiency of LR-MKL are verified on the datasets Yale, ORL, LSVT, and Digit. Experimental results show that the proposed LR-MKL algorithm is an efficient kernel weights allocation method in MKL and boosts the performance of MKL largely.

  6. Adsorption of N-tallow 1,3-propanediamine-dioleate collector on albite and quartz minerals, and selective flotation of albite from greek stefania feldspar ore.

    PubMed

    Vidyadhar, A; Hanumantha Rao, K; Forssberg, K S E

    2002-04-01

    The adsorption behavior of tallow 1,3-propanediamine-dioleate (Duomeen TDO) collector on albite and quartz minerals is assessed through Hallimond flotation, zeta potential, and diffuse reflectance FTIR investigations, together with the species distribution of the collector. The collector performance on albite separation from a natural feldspar material is evaluated in bench scale flotation tests. The Hallimond flotation responses of the minerals as a function of pH and collector concentration indicate that albite can be selectively floated from quartz at pH 2 where the doubly positively charged collector species adsorb on albite but not on quartz. However, the zeta potential and infrared spectra reveal that the adsorption behavior of the collector is similar on both minerals. The discrepancy in the flotation and adsorption results is attributed to the coarse and fine particle size fractions, and the shorter and longer equilibration periods employed in these studies respectively. The comparable adsorption on fine particles of albite and quartz at pH 2 is explained by the interaction of ammonium ions on silanol groups by hydrogen bonding as well as electrostatic interactions. The changes in zeta potentials are in good agreement with the formation of ionic species and free molecular forms of the collector. The IR spectra show the coexistence of neutral oleic acid together with charged amine species at low pH values in accordance with the species distribution diagram. Selective flotation of albite is accomplished from a natural feldspar material with tallow diamine-dioleate collector at pH 2 using sulfuric acid, only when the feed is deslimed prior to the bench scale flotation tests. An albite recovery exceeding 85% is achieved from a feed material containing about 50% albite.

  7. Classification of corn kernels contaminated with aflatoxins using fluorescence and reflectance hyperspectral images analysis

    NASA Astrophysics Data System (ADS)

    Zhu, Fengle; Yao, Haibo; Hruska, Zuzana; Kincaid, Russell; Brown, Robert; Bhatnagar, Deepak; Cleveland, Thomas

    2015-05-01

    Aflatoxins are secondary metabolites produced by certain fungal species of the Aspergillus genus. Aflatoxin contamination remains a problem in agricultural products due to its toxic and carcinogenic properties. Conventional chemical methods for aflatoxin detection are time-consuming and destructive. This study employed fluorescence and reflectance visible near-infrared (VNIR) hyperspectral images to classify aflatoxin contaminated corn kernels rapidly and non-destructively. Corn ears were artificially inoculated in the field with toxigenic A. flavus spores at the early dough stage of kernel development. After harvest, a total of 300 kernels were collected from the inoculated ears. Fluorescence hyperspectral imagery with UV excitation and reflectance hyperspectral imagery with halogen illumination were acquired on both endosperm and germ sides of kernels. All kernels were then subjected to chemical analysis individually to determine aflatoxin concentrations. A region of interest (ROI) was created for each kernel to extract averaged spectra. Compared with healthy kernels, fluorescence spectral peaks for contaminated kernels shifted to longer wavelengths with lower intensity, and reflectance values for contaminated kernels were lower with a different spectral shape in 700-800 nm region. Principal component analysis was applied for data compression before classifying kernels into contaminated and healthy based on a 20 ppb threshold utilizing the K-nearest neighbors algorithm. The best overall accuracy achieved was 92.67% for germ side in the fluorescence data analysis. The germ side generally performed better than endosperm side. Fluorescence and reflectance image data achieved similar accuracy.

  8. Influence of Kernel Age on Fumonisin B1 Production in Maize by Fusarium moniliforme

    PubMed Central

    Warfield, Colleen Y.; Gilchrist, David G.

    1999-01-01

    Production of fumonisins by Fusarium moniliforme on naturally infected maize ears is an important food safety concern due to the toxic nature of this class of mycotoxins. Assessing the potential risk of fumonisin production in developing maize ears prior to harvest requires an understanding of the regulation of toxin biosynthesis during kernel maturation. We investigated the developmental-stage-dependent relationship between maize kernels and fumonisin B1 production by using kernels collected at the blister (R2), milk (R3), dough (R4), and dent (R5) stages following inoculation in culture at their respective field moisture contents with F. moniliforme. Highly significant differences (P ≤ 0.001) in fumonisin B1 production were found among kernels at the different developmental stages. The highest levels of fumonisin B1 were produced on the dent stage kernels, and the lowest levels were produced on the blister stage kernels. The differences in fumonisin B1 production among kernels at the different developmental stages remained significant (P ≤ 0.001) when the moisture contents of the kernels were adjusted to the same level prior to inoculation. We concluded that toxin production is affected by substrate composition as well as by moisture content. Our study also demonstrated that fumonisin B1 biosynthesis on maize kernels is influenced by factors which vary with the developmental age of the tissue. The risk of fumonisin contamination may begin early in maize ear development and increases as the kernels reach physiological maturity. PMID:10388675

  9. Differential metabolome analysis of field-grown maize kernels in response to drought stress

    USDA-ARS?s Scientific Manuscript database

    Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

  10. Considering causal genes in the genetic dissection of kernel traits in common wheat.

    PubMed

    Mohler, Volker; Albrecht, Theresa; Castell, Adelheid; Diethelm, Manuela; Schweizer, Günther; Hartl, Lorenz

    2016-11-01

    Genetic factors controlling thousand-kernel weight (TKW) were characterized for their association with other seed traits, including kernel width, kernel length, ratio of kernel width to kernel length (KW/KL), kernel area, and spike number per m 2 (SN). For this purpose, a genetic map was established utilizing a doubled haploid population derived from a cross between German winter wheat cultivars Pamier and Format. Association studies in a diversity panel of elite cultivars supplemented genetic analysis of kernel traits. In both populations, genomic signatures of 13 candidate genes for TKW and kernel size were analyzed. Major quantitative trait loci (QTL) for TKW were identified on chromosomes 1B, 2A, 2D, and 4D, and their locations coincided with major QTL for kernel size traits, supporting the common belief that TKW is a function of other kernel traits. The QTL on chromosome 2A was associated with TKW candidate gene TaCwi-A1 and the QTL on chromosome 4D was associated with dwarfing gene Rht-D1. A minor QTL for TKW on chromosome 6B coincided with TaGW2-6B. The QTL for kernel dimensions that did not affect TKW were detected on eight chromosomes. A major QTL for KW/KL located at the distal tip of chromosome arm 5AS is being reported for the first time. TaSus1-7A and TaSAP-A1, closely linked to each other on chromosome 7A, could be related to a minor QTL for KW/KL. Genetic analysis of SN confirmed its negative correlation with TKW in this cross. In the diversity panel, TaSus1-7A was associated with TKW. Compared to the Pamier/Format bi-parental population where TaCwi-A1a was associated with higher TKW, the same allele reduced grain yield in the diversity panel, suggesting opposite effects of TaCwi-A1 on these two traits.

  11. Comparison of different classification methods for analyzing electronic nose data to characterize sesame oils and blends.

    PubMed

    Shao, Xiaolong; Li, Hui; Wang, Nan; Zhang, Qiang

    2015-10-21

    An electronic nose (e-nose) was used to characterize sesame oils processed by three different methods (hot-pressed, cold-pressed, and refined), as well as blends of the sesame oils and soybean oil. Seven classification and prediction methods, namely PCA, LDA, PLS, KNN, SVM, LASSO and RF, were used to analyze the e-nose data. The classification accuracy and MAUC were employed to evaluate the performance of these methods. The results indicated that sesame oils processed with different methods resulted in different sensor responses, with cold-pressed sesame oil producing the strongest sensor signals, followed by the hot-pressed sesame oil. The blends of pressed sesame oils with refined sesame oil were more difficult to be distinguished than the blends of pressed sesame oils and refined soybean oil. LDA, KNN, and SVM outperformed the other classification methods in distinguishing sesame oil blends. KNN, LASSO, PLS, and SVM (with linear kernel), and RF models could adequately predict the adulteration level (% of added soybean oil) in the sesame oil blends. Among the prediction models, KNN with k = 1 and 2 yielded the best prediction results.

  12. Kernel machines for epilepsy diagnosis via EEG signal classification: a comparative study.

    PubMed

    Lima, Clodoaldo A M; Coelho, André L V

    2011-10-01

    We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely, Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs

  13. Sparse Event Modeling with Hierarchical Bayesian Kernel Methods

    DTIC Science & Technology

    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...which adds specificity to the model and can make nonlinear data more manageable. Early results show that the 1. REPORT DATE (DD-MM-YYYY) 4. TITLE

  14. Omnibus Risk Assessment via Accelerated Failure Time Kernel Machine Modeling

    PubMed Central

    Sinnott, Jennifer A.; Cai, Tianxi

    2013-01-01

    Summary Integrating genomic information with traditional clinical risk factors to improve the prediction of disease outcomes could profoundly change the practice of medicine. However, the large number of potential markers and possible complexity of the relationship between markers and disease make it difficult to construct accurate risk prediction models. Standard approaches for identifying important markers often rely on marginal associations or linearity assumptions and may not capture non-linear or interactive effects. In recent years, much work has been done to group genes into pathways and networks. Integrating such biological knowledge into statistical learning could potentially improve model interpretability and reliability. One effective approach is to employ a kernel machine (KM) framework, which can capture nonlinear effects if nonlinear kernels are used (Scholkopf and Smola, 2002; Liu et al., 2007, 2008). For survival outcomes, KM regression modeling and testing procedures have been derived under a proportional hazards (PH) assumption (Li and Luan, 2003; Cai et al., 2011). In this paper, we derive testing and prediction methods for KM regression under the accelerated failure time model, a useful alternative to the PH model. We approximate the null distribution of our test statistic using resampling procedures. When multiple kernels are of potential interest, it may be unclear in advance which kernel to use for testing and estimation. We propose a robust Omnibus Test that combines information across kernels, and an approach for selecting the best kernel for estimation. The methods are illustrated with an application in breast cancer. PMID:24328713

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

    PubMed

    Sinnott, Jennifer A; Cai, Tianxi

    2013-12-01

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

  16. Kernel Wiener filter and its application to pattern recognition.

    PubMed

    Yoshino, Hirokazu; Dong, Chen; Washizawa, Yoshikazu; Yamashita, Yukihiko

    2010-11-01

    The Wiener filter (WF) is widely used for inverse problems. From an observed signal, it provides the best estimated signal with respect to the squared error averaged over the original and the observed signals among linear operators. The kernel WF (KWF), extended directly from WF, has a problem that an additive noise has to be handled by samples. Since the computational complexity of kernel methods depends on the number of samples, a huge computational cost is necessary for the case. By using the first-order approximation of kernel functions, we realize KWF that can handle such a noise not by samples but as a random variable. We also propose the error estimation method for kernel filters by using the approximations. In order to show the advantages of the proposed methods, we conducted the experiments to denoise images and estimate errors. We also apply KWF to classification since KWF can provide an approximated result of the maximum a posteriori classifier that provides the best recognition accuracy. The noise term in the criterion can be used for the classification in the presence of noise or a new regularization to suppress changes in the input space, whereas the ordinary regularization for the kernel method suppresses changes in the feature space. In order to show the advantages of the proposed methods, we conducted experiments of binary and multiclass classifications and classification in the presence of noise.

  17. Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

    PubMed

    Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

    2014-01-01

    The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

  18. Kernelization

    NASA Astrophysics Data System (ADS)

    Fomin, Fedor V.

    Preprocessing (data reduction or kernelization) as a strategy of coping with hard problems is universally used in almost every implementation. The history of preprocessing, like applying reduction rules simplifying truth functions, can be traced back to the 1950's [6]. A natural question in this regard is how to measure the quality of preprocessing rules proposed for a specific problem. For a long time the mathematical analysis of polynomial time preprocessing algorithms was neglected. The basic reason for this anomaly was that if we start with an instance I of an NP-hard problem and can show that in polynomial time we can replace this with an equivalent instance I' with |I'| < |I| then that would imply P=NP in classical complexity.

  19. Electrochemical Immunosensor for the Detection of Aflatoxin B₁ in Palm Kernel Cake and Feed Samples.

    PubMed

    Azri, Farah Asilah; Selamat, Jinap; Sukor, Rashidah

    2017-11-30

    Palm kernel cake (PKC) is the solid residue following oil extraction of palm kernels and useful to fatten animals either as a single feed with only minerals and vitamins supplementation, or mixed with other feedstuffs such as corn kernels or soy beans. The occurrence of mycotoxins (aflatoxins, ochratoxins, zearalenone, and fumonisins) in feed samples affects the animal's health and also serves as a secondary contamination to humans via consumption of eggs, milk and meats. Of these, aflatoxin B₁ (AFB₁) is the most toxically potent and a confirmed carcinogen to both humans and animals. Methods such as High Performance Liquid Chromatography (HPLC) and Liquid Chromatography-Mass Spectrometry (LC-MS/MS) are common in the determination of mycotoxins. However, these methods usually require sample pre-treatment, extensive cleanup and skilled operator. Therefore, in the present work, a rapid method of electrochemical immunosensor for the detection of AFB₁ was developed based on an indirect competitive enzyme-linked immunosorbent assay (ELISA). Multi-walled carbon nanotubes (MWCNT) and chitosan (CS) were used as the electrode modifier for signal enhancement. N -ethyl- N '-(3-dimethylaminopropyl)-carbodiimide (EDC) and N -hydroxysuccinimide (NHS) activated the carboxyl groups at the surface of nanocomposite for the attachment of AFB₁-BSA antigen by covalent bonding. An indirect competitive reaction occurred between AFB₁-BSA and free AFB₁ for the binding site of a fixed amount of anti-AFB₁ antibody. A catalytic signal based on horseradish peroxidase (HRP) in the presence of hydrogen peroxide (H₂O₂) and 3,3',5,5'-tetramethylbenzidine (TMB) mediator was observed as a result of attachment of the secondary antibody to the immunoassay system. As a result, the reduction peak of TMB (Ox) was measured by using differential pulse voltammetry (DPV) analysis. Based on the results, the electrochemical surface area was increased from 0.396 cm² to 1.298 cm² due to the

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

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    Bao, X.; Shen, Y.

    2017-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Shiju, S.; Sumitra, S.

    2017-12-01

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

  3. On supervised graph Laplacian embedding CA model & kernel construction and its application

    NASA Astrophysics Data System (ADS)

    Zeng, Junwei; Qian, Yongsheng; Wang, Min; Yang, Yongzhong

    2017-01-01

    There are many methods to construct kernel with given data attribute information. Gaussian radial basis function (RBF) kernel is one of the most popular ways to construct a kernel. The key observation is that in real-world data, besides the data attribute information, data label information also exists, which indicates the data class. In order to make use of both data attribute information and data label information, in this work, we propose a supervised kernel construction method. Supervised information from training data is integrated into standard kernel construction process to improve the discriminative property of resulting kernel. A supervised Laplacian embedding cellular automaton model is another key application developed for two-lane heterogeneous traffic flow with the safe distance and large-scale truck. Based on the properties of traffic flow in China, we re-calibrate the cell length, velocity, random slowing mechanism and lane-change conditions and use simulation tests to study the relationships among the speed, density and flux. The numerical results show that the large-scale trucks will have great effects on the traffic flow, which are relevant to the proportion of the large-scale trucks, random slowing rate and the times of the lane space change.

  4. Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

    NASA Astrophysics Data System (ADS)

    Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

    2017-03-01

    Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

  5. Increasing the concentration of linolenic acid in diets fed to Jersey cows in late lactation does not affect methane production

    USDA-ARS?s Scientific Manuscript database

    Oil and fat products has shown to reduce methane, however, limited research compares different fat sources effects on methane production. A study using 8 multiparous (325 ± 17 DIM) (mean ± SD) lactating dairy cows, was conducted to determine effects of feeding canola/tallow vs. extruded byproduct co...

  6. 9 CFR 95.29 - Certification for certain materials.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... described in paragraph (b) of this section: (1) Processed animal protein, tankage, offal, and tallow other... derived from ruminants; (3) Processed fats and oils, and derivatives of processed animal protein, tankage... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Certification for certain materials...

  7. 9 CFR 95.29 - Certification for certain materials.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... described in paragraph (b) of this section: (1) Processed animal protein, tankage, offal, and tallow other... derived from ruminants; (3) Processed fats and oils, and derivatives of processed animal protein, tankage... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Certification for certain materials...

  8. 9 CFR 95.29 - Certification for certain materials.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... described in paragraph (b) of this section: (1) Processed animal protein, tankage, offal, and tallow other... derived from ruminants; (3) Processed fats and oils, and derivatives of processed animal protein, tankage... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Certification for certain materials...

  9. 9 CFR 95.29 - Certification for certain materials.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... described in paragraph (b) of this section: (1) Processed animal protein, tankage, offal, and tallow other... derived from ruminants; (3) Processed fats and oils, and derivatives of processed animal protein, tankage... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Certification for certain materials...

  10. Diversity of plant oil seed-associated fungi isolated from seven oil-bearing seeds and their potential for the production of lipolytic enzymes.

    PubMed

    Venkatesagowda, Balaji; Ponugupaty, Ebenezer; Barbosa, Aneli M; Dekker, Robert F H

    2012-01-01

    Commercial oil-yielding seeds (castor, coconut, neem, peanut, pongamia, rubber and sesame) were collected from different places in the state of Tamil Nadu (India) from which 1279 endophytic fungi were isolated. The oil-bearing seeds exhibited rich fungal diversity. High Shannon-Index H' was observed with pongamia seeds (2.847) while a low Index occurred for coconut kernel-associated mycoflora (1.018). Maximum Colonization Frequency (%) was observed for Lasiodiplodia theobromae (176). Dominance Index (expressed in terms of the Simpson's Index D) was high (0.581) for coconut kernel-associated fungi, and low for pongamia seed-borne fungi. Species Richness (Chao) of the fungal isolates was high (47.09) in the case of neem seeds, and low (16.6) for peanut seeds. All 1279 fungal isolates were screened for lipolytic activity employing a zymogram method using Tween-20 in agar. Forty isolates showed strong lipolytic activity, and were morphologically identified as belonging to 19 taxa (Alternaria, Aspergillus, Chalaropsis, Cladosporium, Colletotrichum, Curvularia, Drechslera, Fusarium, Lasiodiplodia, Mucor, Penicillium, Pestalotiopsis, Phoma, Phomopsis, Phyllosticta, Rhizopus, Sclerotinia, Stachybotrys and Trichoderma). These isolates also exhibited amylolytic, proteolytic and cellulolytic activities. Five fungal isolates (Aspergillus niger, Chalaropsis thielavioides, Colletotrichum gloeosporioides, Lasiodiplodia theobromae and Phoma glomerata) exhibited highest lipase activities, and the best producer was Lasiodiplodia theobromae (108 U/mL), which was characterized by genomic sequence analysis of the ITS region of 18S rDNA.

  11. Reconstruction of noisy and blurred images using blur kernel

    NASA Astrophysics Data System (ADS)

    Ellappan, Vijayan; Chopra, Vishal

    2017-11-01

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

  12. Photon Counting Computed Tomography With Dedicated Sharp Convolution Kernels: Tapping the Potential of a New Technology for Stent Imaging.

    PubMed

    von Spiczak, Jochen; Mannil, Manoj; Peters, Benjamin; Hickethier, Tilman; Baer, Matthias; Henning, André; Schmidt, Bernhard; Flohr, Thomas; Manka, Robert; Maintz, David; Alkadhi, Hatem

    2018-05-23

    The aims of this study were to assess the value of a dedicated sharp convolution kernel for photon counting detector (PCD) computed tomography (CT) for coronary stent imaging and to evaluate to which extent iterative reconstructions can compensate for potential increases in image noise. For this in vitro study, a phantom simulating coronary artery stenting was prepared. Eighteen different coronary stents were expanded in plastic tubes of 3 mm diameter. Tubes were filled with diluted contrast agent, sealed, and immersed in oil calibrated to an attenuation of -100 HU simulating epicardial fat. The phantom was scanned in a modified second generation 128-slice dual-source CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Erlangen, Germany) equipped with both a conventional energy integrating detector and PCD. Image data were acquired using the PCD part of the scanner with 48 × 0.25 mm slices, a tube voltage of 100 kVp, and tube current-time product of 100 mAs. Images were reconstructed using a conventional convolution kernel for stent imaging with filtered back-projection (B46) and with sinogram-affirmed iterative reconstruction (SAFIRE) at level 3 (I463). For comparison, a dedicated sharp convolution kernel with filtered back-projection (D70) and SAFIRE level 3 (Q703) and level 5 (Q705) was used. The D70 and Q70 kernels were specifically designed for coronary stent imaging with PCD CT by optimizing the image modulation transfer function and the separation of contrast edges. Two independent, blinded readers evaluated subjective image quality (Likert scale 0-3, where 3 = excellent), in-stent diameter difference, in-stent attenuation difference, mathematically defined image sharpness, and noise of each reconstruction. Interreader reliability was calculated using Goodman and Kruskal's γ and intraclass correlation coefficients (ICCs). Differences in image quality were evaluated using a Wilcoxon signed-rank test. Differences in in-stent diameter difference, in

  13. Structured Kernel Subspace Learning for Autonomous Robot Navigation.

    PubMed

    Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

    2018-02-14

    This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

  14. An Adaptive Genetic Association Test Using Double Kernel Machines

    PubMed Central

    Zhan, Xiang; Epstein, Michael P.; Ghosh, Debashis

    2014-01-01

    Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study. PMID:26640602

  15. An Adaptive Genetic Association Test Using Double Kernel Machines.

    PubMed

    Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

    2015-10-01

    Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

  16. Virgin coconut oil maintains redox status and improves glycemic conditions in high fructose fed rats.

    PubMed

    Narayanankutty, Arunaksharan; Mukesh, Reshma K; Ayoob, Shabna K; Ramavarma, Smitha K; Suseela, Indu M; Manalil, Jeksy J; Kuzhivelil, Balu T; Raghavamenon, Achuthan C

    2016-01-01

    Virgin Coconut Oil (VCO), extracted from fresh coconut kernel possess similar fatty acid composition to that of Copra Oil (CO), a product of dried kernel. Although CO forms the predominant dietary constituent in south India, VCO is being promoted for healthy life due to its constituent antioxidant molecules. High fructose containing CO is an established model for insulin resistance and steatohepatitis in rodents. In this study, replacement of CO with VCO in high fructose diet markedly improved the glucose metabolism and dyslipidemia. The animals fed VCO diet had only 17 % increase in blood glucose level compared to CO fed animals (46 %). Increased level of GSH and antioxidant enzyme activities in VCO fed rats indicate improved hepatic redox status. Reduced lipid peroxidation and carbonyl adducts in VCO fed rats well corroborate with the histopathological findings that hepatic damage and steatosis were comparatively reduced than the CO fed animals. These results suggest that VCO could be an efficient nutraceutical in preventing the development of diet induced insulin resistance and associated complications possibly through its antioxidant efficacy.

  17. Salt stress reduces kernel number of corn by inhibiting plasma membrane H+-ATPase activity.

    PubMed

    Jung, Stephan; Hütsch, Birgit W; Schubert, Sven

    2017-04-01

    Salt stress affects yield formation of corn (Zea mays L.) at various physiological levels resulting in an overall grain yield decrease. In this study we investigated how salt stress affects kernel development of two corn cultivars (cvs. Pioneer 3906 and Fabregas) at and shortly after pollination. In an earlier study, we found an accumulation of hexoses in the kernel tissue. Therefore, it was hypothesized that hexose uptake into developing endosperm and embryo might be inhibited. Hexoses are transported into the developing endosperm by carriers localized in the plasma membrane (PM). The transport is driven by the pH gradient which is built up by the PM H + -ATPase. It was investigated whether the PM H + -ATPase activity in developing corn kernels was inhibited by salt stress, which would cause a lower pH gradient resulting in impaired hexose import and finally in kernel abortion. Corn grown under control and salt stress conditions was harvested 0 and 2 days after pollination (DAP). Under salt stress sucrose and hexose concentrations in kernel tissue were higher 0 and 2 DAP. Kernel PM H + -ATPase activity was not affected at 0 DAP, but it was reduced at 2 DAP. This is in agreement with the finding, that kernel growth and thus kernel setting was not affected in the salt stress treatment at pollination, but it was reduced 2 days later. It is concluded that inhibition of PM H + -ATPase under salt stress impaired the energization of hexose transporters into the cells, resulting in lower kernel growth and finally in kernel abortion. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  18. Adaptive kernel regression for freehand 3D ultrasound reconstruction

    NASA Astrophysics Data System (ADS)

    Alshalalfah, Abdel-Latif; Daoud, Mohammad I.; Al-Najar, Mahasen

    2017-03-01

    Freehand three-dimensional (3D) ultrasound imaging enables low-cost and flexible 3D scanning of arbitrary-shaped organs, where the operator can freely move a two-dimensional (2D) ultrasound probe to acquire a sequence of tracked cross-sectional images of the anatomy. Often, the acquired 2D ultrasound images are irregularly and sparsely distributed in the 3D space. Several 3D reconstruction algorithms have been proposed to synthesize 3D ultrasound volumes based on the acquired 2D images. A challenging task during the reconstruction process is to preserve the texture patterns in the synthesized volume and ensure that all gaps in the volume are correctly filled. This paper presents an adaptive kernel regression algorithm that can effectively reconstruct high-quality freehand 3D ultrasound volumes. The algorithm employs a kernel regression model that enables nonparametric interpolation of the voxel gray-level values. The kernel size of the regression model is adaptively adjusted based on the characteristics of the voxel that is being interpolated. In particular, when the algorithm is employed to interpolate a voxel located in a region with dense ultrasound data samples, the size of the kernel is reduced to preserve the texture patterns. On the other hand, the size of the kernel is increased in areas that include large gaps to enable effective gap filling. The performance of the proposed algorithm was compared with seven previous interpolation approaches by synthesizing freehand 3D ultrasound volumes of a benign breast tumor. The experimental results show that the proposed algorithm outperforms the other interpolation approaches.

  19. A locally adaptive kernel regression method for facies delineation

    NASA Astrophysics Data System (ADS)

    Fernàndez-Garcia, D.; Barahona-Palomo, M.; Henri, C. V.; Sanchez-Vila, X.

    2015-12-01

    Facies delineation is defined as the separation of geological units with distinct intrinsic characteristics (grain size, hydraulic conductivity, mineralogical composition). A major challenge in this area stems from the fact that only a few scattered pieces of hydrogeological information are available to delineate geological facies. Several methods to delineate facies are available in the literature, ranging from those based only on existing hard data, to those including secondary data or external knowledge about sedimentological patterns. This paper describes a methodology to use kernel regression methods as an effective tool for facies delineation. The method uses both the spatial and the actual sampled values to produce, for each individual hard data point, a locally adaptive steering kernel function, self-adjusting the principal directions of the local anisotropic kernels to the direction of highest local spatial correlation. The method is shown to outperform the nearest neighbor classification method in a number of synthetic aquifers whenever the available number of hard data is small and randomly distributed in space. In the case of exhaustive sampling, the steering kernel regression method converges to the true solution. Simulations ran in a suite of synthetic examples are used to explore the selection of kernel parameters in typical field settings. It is shown that, in practice, a rule of thumb can be used to obtain suboptimal results. The performance of the method is demonstrated to significantly improve when external information regarding facies proportions is incorporated. Remarkably, the method allows for a reasonable reconstruction of the facies connectivity patterns, shown in terms of breakthrough curves performance.

  20. Kernel analysis in TeV gamma-ray selection

    NASA Astrophysics Data System (ADS)

    Moriarty, P.; Samuelson, F. W.

    2000-06-01

    We discuss the use of kernel analysis as a technique for selecting gamma-ray candidates in Atmospheric Cherenkov astronomy. The method is applied to observations of the Crab Nebula and Markarian 501 recorded with the Whipple 10 m Atmospheric Cherenkov imaging system, and the results are compared with the standard Supercuts analysis. Since kernel analysis is computationally intensive, we examine approaches to reducing the computational load. Extension of the technique to estimate the energy of the gamma-ray primary is considered. .

Some links on this page may take you to non-federal websites. Their policies may differ from this site.