PKM2 Subcellular Localization Is Involved in Oxaliplatin Resistance Acquisition in HT29 Human Colorectal Cancer Cell Lines

PubMed Central

Ginés, Alba; Bystrup, Sara; Ruiz de Porras, Vicenç; Guardia, Cristina; Musulén, Eva; Martínez-Cardús, Anna; Manzano, José Luis; Layos, Laura; Abad, Albert; Martínez-Balibrea, Eva

2015-01-01

Chemoresistance is the main cause of treatment failure in advanced colorectal cancer (CRC). However, molecular mechanisms underlying this phenomenon remain to be elucidated. In a previous work we identified low levels of PKM2 as a putative oxaliplatin-resistance marker in HT29 CRC cell lines and also in patients. In order to assess how PKM2 influences oxaliplatin response in CRC cells, we silenced PKM2 using specific siRNAs in HT29, SW480 and HCT116 cells. MTT test demonstrated that PKM2 silencing induced resistance in HT29 and SW480 cells and sensitivity in HCT116 cells. Same experiments in isogenic HCT116 p53 null cells and double silencing of p53 and PKM2 in HT29 cells failed to show an influence of p53. By using trypan blue stain and FITC-Annexin V/PI tests we detected that PKM2 knockdown was associated with an increase in cell viability but not with a decrease in apoptosis activation in HT29 cells. Fluorescence microscopy revealed PKM2 nuclear translocation in response to oxaliplatin in HCT116 and HT29 cells but not in OXA-resistant HTOXAR3 cells. Finally, by using a qPCR Array we demonstrated that oxaliplatin and PKM2 silencing altered cell death gene expression patterns including those of BMF, which was significantly increased in HT29 cells in response to oxaliplatin, in a dose and time-dependent manner, but not in siPKM2-HT29 and HTOXAR3 cells. BMF gene silencing in HT29 cells lead to a decrease in oxaliplatin-induced cell death. In conclusion, our data report new non-glycolytic roles of PKM2 in response to genotoxic damage and proposes BMF as a possible target gene of PKM2 to be involved in oxaliplatin response and resistance in CRC cells. PMID:25955657

Nuclear translocation of PKM2/AMPK complex sustains cancer stem cell populations under glucose restriction stress.

PubMed

Yang, Yi-Chieh; Chien, Ming-Hsien; Liu, Hsin-Yi; Chang, Yu-Chan; Chen, Chi-Kuan; Lee, Wei-Jiunn; Kuo, Tsang-Chih; Hsiao, Michael; Hua, Kuo-Tai; Cheng, Tsu-Yao

2018-05-01

Cancer cells encounter metabolic stresses such as hypoxia and nutrient limitations because they grow and divide more quickly than their normal counterparts. In response to glucose restriction, we found that nuclear translocation of the glycolic enzyme, pyruvate kinase M2 (PKM2), helped cancer cells survive under the metabolic stress. Restriction of glucose stimulated AMPK activation and resulted in co-translocation of AMPK and PKM2 through Ran-mediated nuclear transport. Nuclear PKM2 subsequently bound to Oct4 and promoted the expression of cancer stemness-related genes, which might enrich the cancer stem cell population under the metabolic stress. Nuclear PKM2 was also capable of promoting cancer metastasis in an orthotopic xenograft model. In summary, we found that cytosolic AMPK helped PKM2 carry out its nonmetabolic functions in the nucleus under glucose restriction and that nuclear PKM2 promoted cancer stemness and metastasis. These findings suggested a potential new targeting pathway for cancer therapy in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

PKM2-dependent metabolic reprogramming in CD4+ T cells is crucial for hyperhomocysteinemia-accelerated atherosclerosis.

PubMed

Lü, Silin; Deng, Jiacheng; Liu, Huiying; Liu, Bo; Yang, Juan; Miao, Yutong; Li, Jing; Wang, Nan; Jiang, Changtao; Xu, Qingbo; Wang, Xian; Feng, Juan

2018-06-01

Inflammation mediated by activated T cells plays an important role in the initiation and progression of hyperhomocysteinemia (HHcy)-accelerated atherosclerosis in ApoE -/- mice. Homocysteine (Hcy) activates T cells to secrete proinflammatory cytokines, especially interferon (IFN)-γ; however, the precise mechanisms remain unclear. Metabolic reprogramming is critical for T cell inflammatory activation and effector functions. Our previous study demonstrated that Hcy regulates T cell mitochondrial reprogramming by enhancing endoplasmic reticulum (ER)-mitochondria coupling. In this study, we further explored the important role of glycolysis-mediated metabolic reprogramming in Hcy-activated CD4 + T cells. Mechanistically, Hcy-activated CD4 + T cell increased the protein expression and activity of pyruvate kinase muscle isozyme 2 (PKM2), the final rate-limiting enzyme in glycolysis, via the phosphatidylinositol 3-kinase/AKT/mechanistic target of rapamycin signaling pathway. Knockdown of PKM2 by small interfering RNA reduced Hcy-induced CD4 + T cell IFN-γ secretion. Furthermore, we generated T cell-specific PKM2 knockout mice by crossing LckCre transgenic mice with PKM2 fl/fl mice and observed that Hcy-induced glycolysis and oxidative phosphorylation were both diminished in PKM2-deficient CD4 + T cells with reduced glucose and lipid metabolites, and subsequently reduced IFN-γ secretion. T cell-depleted apolipoprotein E-deficient (ApoE -/- ) mice adoptively transferred with PKM2-deficient CD4 + T cells, compared to mice transferred with control cells, showed significantly decreased HHcy-accelerated early atherosclerotic lesion formation. In conclusion, this work indicates that the PKM2-dependent glycolytic-lipogenic axis, a novel mechanism of metabolic regulation, is crucial for HHcy-induced CD4 + T cell activation to accelerate early atherosclerosis in ApoE -/- mice. Metabolic reprogramming is crucial for Hcy-induced CD4 + T cell inflammatory activation. Hcy activates

PKM2 Thr454 phosphorylation increases its nuclear translocation and promotes xenograft tumor growth in A549 human lung cancer cells

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

Yu, Zhenhai, E-mail: tomsyu@163.com; Huang, Liangqian; Qiao, Pengyun

Pyruvate kinase M2 (PKM2) is a key enzyme of glycolysis which is highly expressed in many tumor cells, and plays an important role in the Warburg effect. In previous study, we found PIM2 phosphorylates PKM2 at Thr454 residue (Yu, etl 2013). However, the functions of PKM2 Thr454 modification in cancer cells still remain unclear. Here we find PKM2 translocates into the nucleus after Thr454 phosphorylation. Replacement of wild type PKM2 with a mutant (T454A) enhances mitochondrial respiration, decreases pentose phosphate pathway, and enhances chemosensitivity in A549 cells. In addition, the mutant (T454A) PKM2 reduces xenograft tumor growth in nude mice. Thesemore » findings demonstrate that PKM2 T454 phosphorylation is a potential therapeutic target in lung cancer.« less

PKM2 Thr454 phosphorylation increases its nuclear translocation and promotes xenograft tumor growth in A549 human lung cancer cells.

PubMed

Yu, Zhenhai; Huang, Liangqian; Qiao, Pengyun; Jiang, Aifang; Wang, Li; Yang, Tingting; Tang, Shengjian; Zhang, Wei; Ren, Chune

2016-05-13

Pyruvate kinase M2 (PKM2) is a key enzyme of glycolysis which is highly expressed in many tumor cells, and plays an important role in the Warburg effect. In previous study, we found PIM2 phosphorylates PKM2 at Thr454 residue (Yu, etl 2013). However, the functions of PKM2 Thr454 modification in cancer cells still remain unclear. Here we find PKM2 translocates into the nucleus after Thr454 phosphorylation. Replacement of wild type PKM2 with a mutant (T454A) enhances mitochondrial respiration, decreases pentose phosphate pathway, and enhances chemosensitivity in A549 cells. In addition, the mutant (T454A) PKM2 reduces xenograft tumor growth in nude mice. These findings demonstrate that PKM2 T454 phosphorylation is a potential therapeutic target in lung cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

MiR-let-7a inhibits cell proliferation, migration, and invasion by down-regulating PKM2 in cervical cancer

PubMed Central

Guo, Man; Zhao, Xinying; Yuan, Xiaolei; Jiang, Jing; Li, Peiling

2017-01-01

In recent decades, miRNA has been reported as a crucial modulator in some biology progressions. This work aims to assess the expression and role of miR-let-7a and pyruvate kinase muscle isozyme M2 (PKM2) in CC tissues and cell lines. Here, we identified that miR-let-7a expression was decreased in CC tissues, and SiHa and HeLa cells (all P < 0.001), however, PKM2 expression was increased in these samples. Statistically, miR-let-7a was inversely associated with PKM2 mRNA or protein (p = 0.013, p = 0.015, respectively). In-vitro assays revealed that ectopic miR-let-7a expression repressed SiHa and HeLa cell proliferation, migration and invasion, and enhanced SiHa and HeLa cell apoptosis. Furthermore, luciferase reporter assays revealed the 3′-UTR of PKM2 was identified a target of miR-let-7a, by which miR-let-7a affected the expression of PKM2 in SiHa and HeLa cells. Besides, PKM2 plasmids partially abrogated the inhibitory effects of miR-let-7a, while si-PKM2 enhanced the inhibitory effects of miR-let-7a. In vivo, miR-let-7a mimics indeed repressed tumor growth in mice xenograft model. In conclusion, our results demonstrated that miR-let-7a inhibits cell proliferation, migration and invasion by down-regulation of PKM2 in cervical cancer. miR-let-7a/PKM2 pathway may be a useful therapeutic target for CC patients. PMID:28415668

Production of high activity Aspergillus niger BCC4525 β-mannanase in Pichia pastoris and its application for mannooligosaccharides production from biomass hydrolysis.

PubMed

Harnpicharnchai, Piyanun; Pinngoen, Waraporn; Teanngam, Wanwisa; Sornlake, Warasirin; Sae-Tang, Kittapong; Manitchotpisit, Pennapa; Tanapongpipat, Sutipa

2016-12-01

A cDNA encoding β-mannanase was cloned from Aspergillus niger BCC4525 and expressed in Pichia pastoris KM71. The secreted enzyme hydrolyzed locust bean gum substrate with very high activity (1625 U/mL) and a relatively high k cat /K m (461 mg -1 s -1  mL). The enzyme is thermophilic and thermostable with an optimal temperature of 70 °C and 40% retention of endo-β-1,4-mannanase activity after preincubation at 70 °C. In addition, the enzyme exhibited broad pH stability with an optimal pH of 5.5. The recombinant enzyme hydrolyzes low-cost biomass, including palm kernel meal (PKM) and copra meal, to produce mannooligosaccharides, which is used as prebiotics to promote the growth of beneficial microflora in animals. An in vitro digestibility test simulating the gastrointestinal tract system of broilers suggested that the recombinant β-mannanase could effectively liberate reducing sugars from PKM-containing diet. These characteristics render this enzyme suitable for utilization as a feed additive to improve animal performance.

L-cysteine reversibly inhibits glucose-induced biphasic insulin secretion and ATP production by inactivating PKM2.

PubMed

Nakatsu, Daiki; Horiuchi, Yuta; Kano, Fumi; Noguchi, Yoshiyuki; Sugawara, Taichi; Takamoto, Iseki; Kubota, Naoto; Kadowaki, Takashi; Murata, Masayuki

2015-03-10

Increase in the concentration of plasma L-cysteine is closely associated with defective insulin secretion from pancreatic β-cells, which results in type 2 diabetes (T2D). In this study, we investigated the effects of prolonged L-cysteine treatment on glucose-stimulated insulin secretion (GSIS) from mouse insulinoma 6 (MIN6) cells and from mouse pancreatic islets, and found that the treatment reversibly inhibited glucose-induced ATP production and resulting GSIS without affecting proinsulin and insulin synthesis. Comprehensive metabolic analyses using capillary electrophoresis time-of-flight mass spectrometry showed that prolonged L-cysteine treatment decreased the levels of pyruvate and its downstream metabolites. In addition, methyl pyruvate, a membrane-permeable form of pyruvate, rescued L-cysteine-induced inhibition of GSIS. Based on these results, we found that both in vitro and in MIN6 cells, L-cysteine specifically inhibited the activity of pyruvate kinase muscle isoform 2 (PKM2), an isoform of pyruvate kinases that catalyze the conversion of phosphoenolpyruvate to pyruvate. L-cysteine also induced PKM2 subunit dissociation (tetramers to dimers/monomers) in cells, which resulted in impaired glucose-induced ATP production for GSIS. DASA-10 (NCGC00181061, a substituted N,N'-diarylsulfonamide), a specific activator for PKM2, restored the tetramer formation and the activity of PKM2, glucose-induced ATP production, and biphasic insulin secretion in L-cysteine-treated cells. Collectively, our results demonstrate that impaired insulin secretion due to exposure to L-cysteine resulted from its direct binding and inactivation of PKM2 and suggest that PKM2 is a potential therapeutic target for T2D.

Enhanced expression of PKM2 associates with the biological properties of cancer stem cells from A549 human lung cancer cells.

PubMed

Guo, Chang-Ying; Yan, Chen; Luo, Lan; Goto, Shinji; Urata, Yoshishige; Xu, Jian-Jun; Wen, Xiao-Ming; Kuang, Yu-Kang; Tou, Fang-Fang; Li, Tao-Sheng

2017-04-01

Cancer cells express the M2 isoform of glycolytic enzyme pyruvate kinase (PKM2) for favoring the survival under a hypoxic condition. Considering the relative low oxygen microenvironment in stem cell niche, we hypothesized that an enhanced PKM2 expression associates with the biological properties of cancer stem cells. We used A549 human lung cancer cell line and surgical resected lung cancer tissue samples from patients for experiments. We confirmed the co-localization of PKM2 and CD44, a popular marker for cancer stem cells in lung cancer tissue samples from patients. The expression of PKM2 was clearly observed in approximately 80% of the A549 human lung cancer cells. Remarkably, enhanced expression of PKM2 was specially observed in these cells that also positively expressed CD44. Downregulation of PKM2 in CD44+ cancer stem cells by siRNA significantly impaired the potency for spheroid formation, decreased the cell survival under fetal bovine serum deprivation and hypoxic conditions, but increased their sensitivity to anti-cancer drug of cisplatin and γ-ray. The enhanced expression of PKM2 seems to associate with the biological properties of cancer stem cells from A549 human lung cancer cells. Selective targeting of PKM2 may provide a new strategy for cancer therapy, especially for patients with therapeutic resistance.

Resveratrol Induces Cancer Cell Apoptosis through MiR-326/PKM2-Mediated ER Stress and Mitochondrial Fission.

PubMed

Wu, Haili; Wang, Yingying; Wu, Changxin; Yang, Peng; Li, Hanqing; Li, Zhuoyu

2016-12-14

Resveratrol (Res), a natural phytoalexin found in a variety of plants, has significant antitumor activity. Pyruvate kinase M2 (PKM2) has abnormally high expression in various tumor cells, and it has been implicated in the survival of tumors. However, whether and how Res inhibits PKM2 expression is poorly understood. In the present study, we found that treatment with Res inhibited cell proliferation and induced cell apoptosis. The IC 50 values of Res against DLD1, HeLa, and MCF-7 cells were 75 ± 4.54, 50 ± 3.65, and 50 ± 3.32 μM, respectively. To elucidate mechanisms underlying its antitumor activities, serial experiments were performed. Results showed that reduction of PKM2 expression in tumor cells by Res treatment increased the expression of ER stress and mitochondrial fission proteins but reduced cell viability and the levels of fusion proteins. These phenomena were reversed by artificial overexpression of PKM2. Quantitative analyses showed that the expression of microRNA-326 (miR-326) was increased upon Res treatment. Treatment with the miR-326 mimic reduced PKM2 expression, promoting recovery from ER stress and mitochondrial fission. Overall, these results demonstrate that miR-326/PKM2-mediated ER stress and mitochondrial dysfunction participate in apoptosis induced by Res. These results provide novel insight into the molecular mechanisms by which Res suppresses tumors and further support for the use of Res as an antitumor drug.

l-cysteine reversibly inhibits glucose-induced biphasic insulin secretion and ATP production by inactivating PKM2

PubMed Central

Nakatsu, Daiki; Horiuchi, Yuta; Kano, Fumi; Noguchi, Yoshiyuki; Sugawara, Taichi; Takamoto, Iseki; Kubota, Naoto; Kadowaki, Takashi; Murata, Masayuki

2015-01-01

Increase in the concentration of plasma l-cysteine is closely associated with defective insulin secretion from pancreatic β-cells, which results in type 2 diabetes (T2D). In this study, we investigated the effects of prolonged l-cysteine treatment on glucose-stimulated insulin secretion (GSIS) from mouse insulinoma 6 (MIN6) cells and from mouse pancreatic islets, and found that the treatment reversibly inhibited glucose-induced ATP production and resulting GSIS without affecting proinsulin and insulin synthesis. Comprehensive metabolic analyses using capillary electrophoresis time-of-flight mass spectrometry showed that prolonged l-cysteine treatment decreased the levels of pyruvate and its downstream metabolites. In addition, methyl pyruvate, a membrane-permeable form of pyruvate, rescued l-cysteine–induced inhibition of GSIS. Based on these results, we found that both in vitro and in MIN6 cells, l-cysteine specifically inhibited the activity of pyruvate kinase muscle isoform 2 (PKM2), an isoform of pyruvate kinases that catalyze the conversion of phosphoenolpyruvate to pyruvate. l-cysteine also induced PKM2 subunit dissociation (tetramers to dimers/monomers) in cells, which resulted in impaired glucose-induced ATP production for GSIS. DASA-10 (NCGC00181061, a substituted N,N′-diarylsulfonamide), a specific activator for PKM2, restored the tetramer formation and the activity of PKM2, glucose-induced ATP production, and biphasic insulin secretion in l-cysteine–treated cells. Collectively, our results demonstrate that impaired insulin secretion due to exposure to l-cysteine resulted from its direct binding and inactivation of PKM2 and suggest that PKM2 is a potential therapeutic target for T2D. PMID:25713368

RACK1 forms a complex with FGFR1 and PKM2, and stimulates the growth and migration of squamous lung cancer cells.

PubMed

Zhou, Chengzhi; Chen, Tao; Xie, Zhanhong; Qin, Yinyin; Ou, Yangming; Zhang, Jiexia; Li, Shiyue; Chen, Rongchang; Zhong, Nanshan

2017-11-01

Phosphorylation of Pyruvate Kinase M2 (PKM2) on Tyr105 by fibroblast growth factor receptor 1 (FGFR1) has been shown to promote its nuclear localization as well as cell growth in lung cancer. Better understanding the regulation of this process would benefit the clinical treatment for lung cancer. Here, it has been found that the adaptor protein receptor for activated PKC kinase (RACK1) formed a complex with FGFR1 and PKM2, and activated the FGFR1/PKM2 signaling. Knocking down the expression of RACK1 impaired the phosphorylation on Tyr105 of PKM2 and inhibited the growth and migration of lung cancer cells, while over-expression of RACK1 in lung cancer cells led to the resistance to Erdafitinib. Moreover, knocking down the expression of RACK1 impaired the tumorigenesis of lung cancer driven by LKB loss and mutated Ras (KrasG12D). Taken together, our study demonstrated the pivotal roles of RACK1 in FGFR1/PKM2 signaling, suggesting FGFR1/RACK1/PKM2 might be a therapeutic target for lung cancer treatment. © 2017 Wiley Periodicals, Inc.

76 FR 48172 - Prospective Grant of Exclusive License: Use of PKM2 Activators for the Treatment of Cancer

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-08

...: The fetal form of Pyruvate Kinase, called PKM2, is expressed in all cancer cells and imparts an important metabolic change on cancer cells which allows them to grow and divide rapidly. That is, PKM2 is normally inactive, which allows cancer cells to create an abundance of molecules for cellular growth and...

PKM2 activation sensitizes cancer cells to growth inhibition by 2-deoxy-D-glucose

PubMed Central

Tee, Sui Seng; Park, Jae Mo; Hurd, Ralph E.; Brimacombe, Kyle R.; Boxer, Matthew B.; Massoud, Tarik F.; Rutt, Brian K.; Spielman, Daniel M.

2017-01-01

Cancer metabolism has emerged as an increasingly attractive target for interfering with tumor growth. Small molecule activators of pyruvate kinase isozyme M2 (PKM2) suppress tumor formation but have an unknown effect on established tumors. We demonstrate that TEPP-46, a PKM2 activator, results in increased glucose consumption, providing the rationale for combining PKM2 activators with the toxic glucose analog, 2-deoxy-D-glucose (2-DG). Combination treatment resulted in reduced viability of a range of cell lines in standard cell culture conditions at concentrations of drugs that had no effect when used alone. This effect was replicated in vivo on established subcutaneous tumors. We further demonstrated the ability to detect acute metabolic differences in combination treatment using hyperpolarized magnetic resonance spectroscopy (MRS). Combination treated tumors displayed a higher pyruvate to lactate 13C-label exchange 2 hr post-treatment. This ability to assess the effect of drugs non-invasively may accelerate the implementation and clinical translation of drugs that target cancer metabolism. PMID:29207616

Moderate DNA damage promotes metabolic flux into PPP via PKM2 Y-105 phosphorylation: a feature that favours cancer cells.

PubMed

Kumar, Bhupender; Bamezai, Rameshwar N K

2015-08-01

Pyruvate kinase M2, an important metabolic enzyme, promotes aerobic glycolysis (Warburg effect) to facilitate cancer cell proliferation. Unravelling the status of this important glycolytic pathway enzyme under sub-lethal doses of etoposide, a commonly used anti-proliferative genotoxic drug to induce mild/moderate DNA damage in HeLa cells as a model system and discern its effect on: PKM2 expression, phosphorylation, dimer: tetramer ratio, activity and associated effects, was pertinent. Protein expression and phosphorylation of PKM2 from HeLa cells was estimated using Western blotting. Same protein lysate was also used to estimate total pyruvate kinase activity and the total dimer: tetramer content evaluated using glycerol gradient ultra-centrifugation. Intracellular PEP was estimated manually using standard curve; while NADPH was assessed by NADPH estimation kit. Unpaired t test and two-way-ANOVA was used for statistical analysis. A relative decrease in PKM2 expression and a subsequent dose and time dependent increase in Y105-phosphorylation were observed. A concomitant increase in PKM2 dimer content and Y105-phosphorylation responsible for reduced PKM2 activity promoted PEP accumulation and NADPH production, representing increased metabolic flux into PPP, a feature that favours cancer cells. It was apparent that the sub-lethal doses of etoposide induced inadequate damage to DNA in cancer cells in culture promoted pro-survival conditions due to Y105-phosphorylation of PKM2, its stable dimerization and inactivation, a unique association not known earlier, indicating what might happen in tumour revivals or recurrences.

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.

CHIP/Stub1 regulates the Warburg effect by promoting degradation of PKM2 in ovarian carcinoma.

PubMed

Shang, Y; He, J; Wang, Y; Feng, Q; Zhang, Y; Guo, J; Li, J; Li, S; Wang, Y; Yan, G; Ren, F; Shi, Y; Xu, J; Zeps, N; Zhai, Y; He, D; Chang, Z

2017-07-20

Tumor cells preferentially adopt aerobic glycolysis for their energy supply, a phenomenon known as the Warburg effect. It remains a matter of debate as to how the Warburg effect is regulated during tumor progression. Here, we show that CHIP (carboxyl terminus of Hsc70-interacting protein), a U-box E3 ligase, suppresses tumor progression in ovarian carcinomas by inhibiting aerobic glycolysis. While CHIP is downregulated in ovarian carcinoma, induced expression of CHIP results in significant inhibition of the tumor growth examined by in vitro and in vivo experiments. Reciprocally, depletion of CHIP leads to promotion of tumor growth. By a SiLAD proteomics analysis, we identified pyruvate kinase isoenzyme M2 (PKM2), a critical regulator of glycolysis in tumors, as a target that CHIP mediated for degradation. Accordingly, we show that CHIP regulates PKM2 protein stability and thereafter the energy metabolic processes. Depletion or knockout of CHIP increased the glycolytic products in both tumor and mouse embryonic fibroblast cells. Simultaneously, we observed that CHIP expression inversely correlated with PKM2 levels in human ovarian carcinomas. This study reveals a mechanism that the Warburg effect is regulated by CHIP through its function as an E3 ligase, which mediates the degradation of PKM2 during tumor progression. Our findings shed new light into understanding of ovarian carcinomas and may provide a new therapeutic strategy for ovarian cancer.

LncRNA-FEZF1-AS1 promotes tumor proliferation and metastasis in colorectal cancer by regulating PKM2 signaling.

PubMed

Bian, Zehua; Zhang, Jiwei; Li, Min; Feng, Yuyang; Wang, Xue; Zhang, Jia; Yao, Surui; Jin, Guoying; Du, Jun; Han, Weifeng; Yin, Yuan; Huang, Shenglin; Fei, Bojian; Zou, Jian; Huang, Zhaohui

2018-06-18

Long non-coding RNAs (lncRNAs) play key roles in human cancers. Here, FEZF1-AS1, a highly overexpressed lncRNA in colorectal cancer (CRC), was identified by lncRNA microarrays. We aimed to explore the roles and possible molecular mechanisms of FEZF1-AS1 in CRC. LncRNA expression in CRC tissues was measured by lncRNA microarray and qRT-PCR. The functional roles of FEZF1-AS1 in CRC were demonstrated by a series of in vitro and in vivo experiments. RNA pull-down, RNA immunoprecipitation and luciferase analyses were used to demonstrate the potential mechanisms of FEZF1-AS1. We identified a series of differentially expressed lncRNAs in CRC using lncRNA microarrays, and revealed that FEZF1-AS1 is one of the most overexpressed. Further validation in two expanded CRC cohorts confirmed the upregulation of FEZF1-AS1 in CRC, and revealed that increased FEZF1-AS1 expression is associated with poor survival. Functional assays revealed that FEZF1-AS1 promotes CRC cell proliferation and metastasis. Mechanistically, FEZF1-AS1 could bind and increase the stability of the pyruvate kinase 2 (PKM2) protein, resulting in increased cytoplasmic and nuclear PKM2 levels. Increased cytoplasmic PKM2 promoted pyruvate kinase activity and lactate production (aerobic glycolysis), whereas FEZF1-AS1-induced nuclear PKM2 upregulation further activated STAT3 signaling. In addition, PKM2 was upregulated in CRC tissues and correlated with FEZF1-AS1 expression and patient survival. Together, these data provide mechanistic insights into the regulation of FEZF1-AS1 on both STAT3 signaling and glycolysis by binding PKM2 and increasing its stability. Copyright ©2018, American Association for Cancer Research.

Ferroxitosis: A cell death from modulation of oxidative phosphorylation and PKM2-dependent glycolysis in melanoma

PubMed Central

Lakhter, Alexander J.; Hamilton, James; Dagher, Pierre C.; Mukkamala, Suresh; Hato, Takashi; Dong, X. Charlie; Mayo, Lindsey D.; Harris, Robert A.; Shekhar, Anantha; Ivan, Mircea; Brustovetsky, Nickolay; Naidu, Samisubbu R.

2014-01-01

Reliance on glycolysis is a characteristic of malignancy, yet the development of resistance to BRAF inhibitors in melanoma is associated with gain of mitochondrial function. Concurrent attenuation of oxidative phosphorylation and HIF-1α/PKM2-dependent glycolysis promotes a non-apoptotic, iron- and oxygen-dependent cell death that we term ferroxitosis. The redox cycling agent menadione causes a robust increase in oxygen consumption, accompanied by significant loss of intracellular ATP and rapid cell death. Conversely, either hypoxic adaptation or iron chelation prevents menadione-induced ferroxitosis. Ectopic expression of K213Q HIF-1α mutant blunts the effects of menadione. However, knockdown of HIF-1α or PKM2 restores menadione-induced cytotoxicity in hypoxia. Similarly, exposure of melanoma cells to shikonin, a menadione analog and a potential PKM2 inhibitor, is sufficient to induce ferroxitosis under hypoxic conditions. Collectively, our findings reveal that ferroxitosis curtails metabolic plasticity in melanoma. PMID:25587028

Nuclear EGFR-PKM2 axis induces cancer stem cell-like characteristics in irradiation-resistant cells.

PubMed

Shi, Ying; Liu, Na; Lai, Weiwei; Yan, Bin; Chen, Ling; Liu, Shouping; Liu, Shuang; Wang, Xiang; Xiao, Desheng; Liu, Xiaoli; Mao, Chao; Jiang, Yiqun; Jia, Jiantao; Liu, Yating; Yang, Rui; Cao, Ya; Tao, Yongguang

2018-05-28

Radiation therapy has become an important tool in the treatment of cancer patients, but most patients relapse within 5 years. Relapse is due to the presence of cancer stem cells (CSCs), but the molecular mechanism of radioresistance in CSCs remains largely elusive. Here, we found that irradiation-resistant (IR) cells exhibited increased stem cell-like properties together with elevated anchorage-independent growth and metastasis ability. EGFR not only leads to increased acquisition of endometrial cancer stem cell markers in radioresistant sublines but is critical for the cancer stem-cell phenotype and tumorigenicity. Moreover, PKM2 functions as an interacting partner of EGFR, which induces the EMT phenotype and stem cell-like properties in IR cells. Finally, we found that the regulatory function of the EGFR-PKM2 axis is dependent on nuclear EGFR. In sum, our study indicated that EGFR and PKM2 directly interact and bind with each other to regulate the transcription of stemness-related genes and promote the stem-like phenotype, thus promoting invasion and metastasis. Copyright © 2018 Elsevier B.V. All rights reserved.

PKM2 released by neutrophils at wound site facilitates early wound healing by promoting angiogenesis.

PubMed

Zhang, Yinwei; Li, Liangwei; Liu, Yuan; Liu, Zhi-Ren

2016-03-01

Neutrophils infiltration/activation following wound induction marks the early inflammatory response in wound repair. However, the role of the infiltrated/activated neutrophils in tissue regeneration/proliferation during wound repair is not well understood. Here, we report that infiltrated/activated neutrophils at wound site release pyruvate kinase M2 (PKM2) by its secretive mechanisms during early stages of wound repair. The released extracellular PKM2 facilitates early wound healing by promoting angiogenesis at wound site. Our studies reveal a new and important molecular linker between the early inflammatory response and proliferation phase in tissue repair process. © 2016 by the Wound Healing Society.

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

Effect of HK2, PKM2 and LDHA on Cetuximab efficacy in metastatic colorectal cancer.

PubMed

Wang, Haohua; Peng, Roujun; Chen, Xiuxing; Jia, Rui; Huang, Chunyue; Huang, Yuanyuan; Xia, Liangping; Guo, Guifang

2018-04-01

Although hexokinase (HK) 2, pyruvate kinase muscle (PKM) isozyme 2 and lactate dehydrogenase (LDH) A predict the efficacy of medicines in various solid tumors, their ability to predict the efficacy of cetuximab in metastatic colorectal cancer (mCRC) remains unclear. mCRC patients with pathological specimens who received cetuximab and chemotherapy from 2005 to 2015 in the present institution were enrolled. Immunohistochemistry was used to detect HK2, PKM2 and LDHA expression. SPSS20 was used for statistical analysis. A total of 68 patients were included; 33 received cetuximab plus chemotherapy as first-line therapy, and the rest, as second- or later-line therapy. HK2 expression levels were increased in cancer compared with normal tissue (75.4% vs. 40%; P<0.001), however PKM2 (P=0.243) and LDHA (P=0.067) expression levels were not. For progression-free survival (PFS) with first-line cetuximab plus chemotherapy, patients with high HK2 expression exhibited longer PFS compared with those with low HK2 expression (23.9 months vs. 6.9 months; P=0.021). However, this positive association was absent in 35 cases administered first-line chemotherapy alone (13.4 months vs. 13.5 months; P=0.539). LDHA expression was associated with the PFS of patients receiving first-line chemotherapy (18.3 and 10.1 months for high and low expression, respectively; P=0.005), whereas this association was absent in cetuximab plus chemotherapy cases (19.9 months vs. 12 months; P=0.522). Furthermore, high LDHA expression correlated with high overall response rate (ORR) (72.2% vs. 15.4%, P=0.006) for chemotherapy, however not disease control rate (DCR) (P=0.074). Neither DCR nor ORR were associated with HK2 expression. PKM2 expression did not affect PFS, DCR or ORR. LDHA expression (P=0.005), pathological differentiation (P=0.019) and synchronous/metachronous metastasis (P=0.014) were independent predictive factors of PFS for all first-line patients, and tumor differentiation (P=0.002) was associated

Boundary Conditions for the Maintenance of Memory by PKM[zeta] in Neocortex

ERIC Educational Resources Information Center

Shema, Reul; Hazvi, Shoshi; Sacktor, Todd C.; Dudai, Yadin

2009-01-01

We report here that ZIP, a selective inhibitor of the atypical protein kinase C isoform PKM[zeta], abolishes very long-term conditioned taste aversion (CTA) associations in the insular cortex of the behaving rat, at least 3 mo after encoding. The effect of ZIP is not replicated by a general serine/threonine protein kinase inhibitor that is…

Comparison of hepatic NRF2 and AHR binding in 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) treated mice demonstrates NRF2-independent PKM2 induction.

PubMed

Nault, Rance; Doskey, Claire M; Fader, Kelly A; Rockwell, Cheryl E; Zacharewski, Timothy R

2018-05-11

2,3,7,8-Tetrachlorodibenzo- p -dioxin (TCDD) induces hepatic oxidative stress following activation of the aryl hydrocarbon receptor (AhR). Our recent studies showed TCDD induced pyruvate kinase muscle isoform 2 ( Pkm2 ) as a novel antioxidant response in normal differentiated hepatocytes. To investigate cooperative regulation between nuclear factor, erythroid derived 2, like 2 ( Nrf2 ) and the AhR in the induction of Pkm2 , hepatic ChIP-seq analyses were integrated with RNA-seq time course data from mice treated with TCDD for 2 - 168h. ChIP-seq analysis 2h after TCDD treatment identified genome-wide NRF2 enrichment. Approximately 842 NRF2 enriched regions were located in the regulatory region of differentially expressed genes (DEGs) while 579 DEGs showed both NRF2 and AhR enrichment. Sequence analysis of regions with overlapping NRF2 and AhR enrichment showed over-representation of either antioxidant or dioxin response elements (ARE and DRE, respectively), although 18 possessed both motifs. NRF2 exhibited negligible enrichment within a closed Pkm chromatin region while the AhR was enriched 29-fold. Furthermore, TCDD induced Pkm2 in primary hepatocytes from wild-type and Nrf2 null mice, indicating NRF2 is not required. Although NRF2 and AhR cooperate to regulate numerous antioxidant gene expression responses, the induction of Pkm2 by TCDD is independent of ROS-mediated NRF2 activation. The American Society for Pharmacology and Experimental Therapeutics.

Discovery of 2-((1H-benzo[d]imidazol-1-yl)methyl)-4H-pyrido[1,2-a]pyrimidin-4-ones as novel PKM2 activators.

PubMed

Guo, Chuangxing; Linton, Angelica; Jalaie, Mehran; Kephart, Susan; Ornelas, Martha; Pairish, Mason; Greasley, Samantha; Richardson, Paul; Maegley, Karen; Hickey, Michael; Li, John; Wu, Xin; Ji, Xiaodong; Xie, Zhi

2013-06-01

The M2 isoform of pyruvate kinase is an emerging target for antitumor therapy. In this letter, we describe the discovery of 2-((1H-benzo[d]imidazol-1-yl)methyl)-4H-pyrido[1,2-a]pyrimidin-4-ones as potent and selective PKM2 activators which were found to have a novel binding mode. The original lead identified from high throughput screening was optimized into an efficient series via computer-aided structure-based drug design. Both a representative compound from this series and an activator described in the literature were used as molecular tools to probe the biological effects of PKM2 activation on cancer cells. Our results suggested that PKM2 activation alone is not sufficient to alter cancer cell metabolism. Copyright © 2013 Elsevier Ltd. All rights reserved.

Postprandial effects of test meals including concentrated arabinoxylan and whole grain rye in subjects with the metabolic syndrome: a randomised study.

PubMed

Hartvigsen, M L; Lærke, H N; Overgaard, A; Holst, J J; Bach Knudsen, K E; Hermansen, K

2014-05-01

Prospective studies have shown an inverse relationship between whole grain consumption and the risk of type 2 diabetes, where short chain fatty acids (SCFA) may be involved. Our objective was to determine the effect of isolated arabinoxylan alone or in combination with whole grain rye kernels on postprandial glucose, insulin, free fatty acids (FFA), gut hormones, SCFA and appetite in subjects with the metabolic syndrome (MetS). Fifteen subjects with MetS participated in this acute, randomised, cross-over study. The test meals each providing 50 g of digestible carbohydrate were as follows: semolina porridge added concentrated arabinoxylan (AX), rye kernels (RK) or concentrated arabinoxylan combined with rye kernels (AXRK) and semolina porridge as control (SE). A standard lunch was served 4 h after the test meals. Blood samples were drawn during a 6-h period, and appetite scores and breath hydrogen were assessed every 30 min. The AXRK meal reduced the acute glucose (P=0.005) and insulin responses (P<0.001) and the feeling of hunger (P=0.005; 0-360 min) compared with the control meal. The AX and AXRK meals increased butyrate and acetate concentrations after 6 h. No significant differences were found for the second meal responses of glucose, insulin, FFA, glucagon-like peptide-1 or ghrelin. Our results indicate a stimulatory effect of arabinoxylan on butyrate and acetate production, however, with no detectable effect on the second meal glucose response. It remains to be tested in a long-term study if a beneficial effect on the glucose response of the isolated arabinoxylan will be related to the SCFA production.

Utilization of expeller pressed partially defatted peanut cake meal in the preparation of bakery products.

PubMed

Chavan, J K; Shinde, V S; Kadam, S S

1991-07-01

Expeller pressed partially defatted peanut cake obtained from skin-free kernels was used as graded supplements in the preparation of breads, sweet buns, cupcakes and yeast-raised doughnuts. Incorporation of cake meal lowered the specific volume and sensory properties, but improved the fresh weight, water holding capacity and protein content of the products. The products containing 10% peanut cake meal were found to be acceptable.

Second meal effect on appetite and fermentation of wholegrain rye foods.

PubMed

Ibrügger, Sabine; Vigsnæs, Louise Kristine; Blennow, Andreas; Skuflić, Dan; Raben, Anne; Lauritzen, Lotte; Kristensen, Mette

2014-09-01

Wholegrain rye has been associated with decreased hunger sensations. This may be partly mediated by colonic fermentation. Sustained consumption of fermentable components is known to change the gut microflora and may increase numbers of saccharolytic bacteria. To investigate the effect of wholegrain rye consumption on appetite and colonic fermentation after a subsequent meal. In a randomized, controlled, three-arm cross-over study, twelve healthy male subjects consumed three iso-caloric evening test meals. The test meals were based on white wheat bread (WBB), wholegrain rye kernel bread (RKB), or boiled rye kernels (RK). Breath hydrogen excretion and subjective appetite sensation were measured before and at 30 min intervals for 3 h after a standardized breakfast in the subsequent morning. After the 3 h, an ad libitum lunch meal was served to assess energy intake. In an in vitro study, RKB and RK were subjected to digestion and 24 h-fermentation in order to study SCFA production and growth of selected saccharolytic bacteria. The test meals did not differ in their effect on parameters of subjective appetite sensation the following day. Ad libitum energy intake at lunch was, however, reduced by 11% (P < 0.01) after RKB and 7% (P < 0.05) after RK compared with after WWB evening meal. Breath hydrogen excretion was significantly increased following RKB and RK evening meals compared with WWB (P < 0.01 and P < 0.05, respectively). Overall, RKB and RK were readily fermented in vitro and exhibited similar fermentation profiles, although total SCFA production was higher for RK compared with RKB (P < 0.001). In vitro fermentation of RKB and RK both increased the relative quantities of Bifidobacterium and decreased Bacteroides compared with inoculum (P < 0.001). The C. coccoides group was reduced after RKB (P < 0.001). Consumption of wholegrain rye products reduced subsequent ad libitum energy intake in young healthy men, possibly mediated by

Determination of glycaemic index; some methodological aspects related to the analysis of carbohydrate load and characteristics of the previous evening meal.

PubMed

Granfeldt, Y; Wu, X; Björck, I

2006-01-01

To determine the possible differences in glycaemic index (GI) depending on (1) the analytical method used to calculate the 'available carbohydrate' load, that is, using carbohydrates by difference (total carbohydrate by difference, minus dietary fibre (DF)) as available carbohydrates vs available starch basis (total starch minus resistant starch (RS)) of a food rich in intrinsic RS and (2) the effect of GI characteristics and/or the content of indigestible carbohydrates (RS and DF) of the evening meal prior to GI testing the following morning. Blood glucose and serum insulin responses were studied after subjects consuming (1) two levels of barley kernels rich in intrinsic RS (15.2%, total starch basis) and (2) after a standard breakfast following three different evening meals varying in GI and/or indigestible carbohydrates: pasta, barley kernels and white wheat bread, respectively. Healthy adults with normal body mass index. (1) Increasing the portion size of barley kernels from 79.6 g (50 g 'available carbohydrates') to 93.9 g (50 g available starch) to adjust for its RS content did not significantly affect the GI or insulin index (11). (2) The low GI barley evening meal, as opposed to white wheat bread and pasta evening meals, reduced the postprandial glycaemic and insulinaemic (23 and 29%, respectively, P < 0.05) areas under the curve at a standardized white bread breakfast fed the following morning. (1) Increasing portion size to compensate for the considerable portion of RS in a low GI barley product had no significant impact on GI or II. However, for GI testing, it is recommended to base carbohydrate load on specific analyses of the available carbohydrate content. (2) A low GI barley evening meal containing high levels of indigestible carbohydrates (RS and DF) substantially reduced the GI and II of white wheat bread determined at a subsequent breakfast meal.

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.

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

Rapid detection of kernel rots and mycotoxins in maize by near-infrared reflectance spectroscopy.

PubMed

Berardo, Nicola; Pisacane, Vincenza; Battilani, Paola; Scandolara, Andrea; Pietri, Amedeo; Marocco, Adriano

2005-10-19

Near-infrared (NIR) spectroscopy is a practical spectroscopic procedure for the detection of organic compounds in matter. It is particularly useful because of its nondestructiveness, accuracy, rapid response, and easy operation. This work assesses the applicability of NIR for the rapid identification of micotoxigenic fungi and their toxic metabolites produced in naturally and artificially contaminated products. Two hundred and eighty maize samples were collected both from naturally contaminated maize crops grown in 16 areas in north-central Italy and from ears artificially inoculated with Fusarium verticillioides. All samples were analyzed for fungi infection, ergosterol, and fumonisin B1 content. The results obtained indicated that NIR could accurately predict the incidence of kernels infected by fungi, and by F. verticillioides in particular, as well as the quantity of ergosterol and fumonisin B1 in the meal. The statistics of the calibration and of the cross-validation for mold infection and for ergosterol and fumonisin B1 contents were significant. The best predictive ability for the percentage of global fungal infection and F. verticillioides was obtained using a calibration model utilizing maize kernels (r2 = 0.75 and SECV = 7.43) and maize meals (r2 = 0.79 and SECV = 10.95), respectively. This predictive performance was confirmed by the scatter plot of measured F. verticillioides infection versus NIR-predicted values in maize kernel samples (r2 = 0.80). The NIR methodology can be applied for monitoring mold contamination in postharvest maize, in particular F. verticilliodes and fumonisin presence, to distinguish contaminated lots from clean ones, and to avoid cross-contamination with other material during storage and may become a powerful tool for monitoring the safety of the food supply.

Xue-fu-Zhu-Yu decoction protects rats against retinal ischemia by downregulation of HIF-1α and VEGF via inhibition of RBP2 and PKM2.

PubMed

Tan, Shu-Qiu; Geng, Xue; Liu, Jorn-Hon; Pan, Wynn Hwai-Tzong; Wang, Li-Xiang; Liu, Hui-Kang; Hu, Lei; Chao, Hsiao-Ming

2017-07-14

Retinal ischemia-related eye diseases result in visual dysfunction. This study investigates the protective effects and mechanisms of Xue-Fu-Zhu-Yu decoction (XFZYD) with respect to retinal ischemia. Retinal ischemia (I) was induced in Wistar rats by a high intraocular pressure (HIOP) of 120 mmHg for 1 h, which was followed by reperfusion of the ischemic eye; the fellow untreated eye acted as a control. Electroretinogram (ERG), biochemistry and histopathology investigations were performed. Significant ischemic changes occurred after ischemia including decreased ERG b-wave ratios, less numerous retinal ganglion cells (RGCs), reduced inner retinal thickness, fewer choline acetyltransferase (ChAT) labeled amacrine cell bodies, increased glial fibrillary acidic protein (GFAP) immunoreactivity and increased vimentin Müller immunolabeling. These were accompanied by significant increases in the mRNA/protein concentrations of vascular endothelium growth factor, hypoxia-inducible factor-1α, pyruvate kinase M2 and retinoblastoma-binding protein 2. The ischemic changes were concentration-dependently and significantly altered when XFZYD was given for seven consecutive days before or after retina ischemia, compared to vehicle. These alterations included enhanced ERG b-wave amplitudes, more numerous RGCs, enhanced inner retinal thickness, a greater number of ChAT immunolabeled amacrine cell bodies and decreased GFAP/vimentin immunoreactivity. Furthermore, decreased mRNA levels of VEGF, HIF-1α, PKM2, and RBP2 were also found. Reduced protein concentrations of VEGF, HIF-1α, PKM2, and RBP2 were also demonstrated. Furthermore, there was an inhibition of the ischemia-associated increased ratios (target protein/β-actin) in the protein levels of VEGF, HIF-1α, PKM2, and RBP2, which were induced by Shikonin, JIB-04 or Avastin. XFZYD would seem to protect against well-known retinal ischemic changes via a synergistic inhibition of RBP2 and PKM2, as well as down-regulation of HIF-1�

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

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.

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.

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.

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...

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...

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 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...

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.

Rye-Based Evening Meals Favorably Affected Glucose Regulation and Appetite Variables at the Following Breakfast; A Randomized Controlled Study in Healthy Subjects.

PubMed

Sandberg, Jonna C; Björck, Inger M E; Nilsson, Anne C

2016-01-01

Whole grain has shown potential to prevent obesity, cardiovascular disease and type 2 diabetes. Possible mechanism could be related to colonic fermentation of specific indigestible carbohydrates, i.e. dietary fiber (DF). The aim of this study was to investigate effects on cardiometabolic risk factors and appetite regulation the next day when ingesting rye kernel bread rich in DF as an evening meal. Whole grain rye kernel test bread (RKB) or a white wheat flour based bread (reference product, WWB) was provided as late evening meals to healthy young adults in a randomized cross-over design. The test products RKB and WWB were provided in two priming settings: as a single evening meal or as three consecutive evening meals prior to the experimental days. Test variables were measured in the morning, 10.5-13.5 hours after ingestion of RKB or WWB. The postprandial phase was analyzed for measures of glucose metabolism, inflammatory markers, appetite regulating hormones and short chain fatty acids (SCFA) in blood, hydrogen excretion in breath and subjective appetite ratings. With the exception of serum CRP, no significant differences in test variables were observed depending on length of priming (P>0.05). The RKB evening meal increased plasma concentrations of PYY (0-120 min, P<0.001), GLP-1 (0-90 min, P<0.05) and fasting SCFA (acetate and butyrate, P<0.05, propionate, P = 0.05), compared to WWB. Moreover, RKB decreased blood glucose (0-120 min, P = 0.001), serum insulin response (0-120 min, P<0.05) and fasting FFA concentrations (P<0.05). Additionally, RKB improved subjective appetite ratings during the whole experimental period (P<0.05), and increased breath hydrogen excretion (P<0.001), indicating increased colonic fermentation activity. The results indicate that RKB evening meal has an anti-diabetic potential and that the increased release of satiety hormones and improvements of appetite sensation could be beneficial in preventing obesity. These effects could possibly be

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.

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] ...

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.

The correlation of chemical and physical corn kernel traits with production performance in broiler chickens and laying hens.

PubMed

Moore, S M; Stalder, K J; Beitz, D C; Stahl, C H; Fithian, W A; Bregendahl, K

2008-04-01

A study was conducted to determine the influence on broiler chicken growth and laying hen performance of chemical and physical traits of corn kernels from different hybrids. A total of 720 male 1-d-old Ross-308 broiler chicks were allotted to floor pens in 2 replicated experiments with a randomized complete block design. A total of 240 fifty-two-week-old Hy-Line W-36 laying hens were allotted to cages in a randomized complete block design. Corn-soybean meal diets were formulated for 3 broiler growth phases and one 14-wk-long laying hen phase to be marginally deficient in Lys and TSAA to allow for the detection of differences or correlations attributable to corn kernel chemical or physical traits. The broiler chicken diets were also marginally deficient in Ca and nonphytate P. Within a phase, corn- and soybean-based diets containing equal amounts of 1 of 6 different corn hybrids were formulated. The corn hybrids were selected to vary widely in chemical and physical traits. Feed consumption and BW were recorded for broiler chickens every 2 wk from 0 to 6 wk of age. Egg production was recorded daily, and feed consumption and egg weights were recorded weekly for laying hens between 53 and 67 wk of age. Physical and chemical composition of kernels was correlated with performance measures by multivariate ANOVA. Chemical and physical kernel traits were weakly correlated with performance in broiler chickens from 0 to 2 wk of age (P<0.05, | r |<0.42). However, from 4 to 6 wk of age and 0 to 6 wk of age, only kernel chemical traits were correlated with broiler chicken performance (P<0.05, | r |<0.29). From 53 to 67 wk of age, correlations were observed between both kernel physical and chemical traits and laying hen performance (P<0.05, | r |<0.34). In both experiments, the correlations of performance measures with individual kernel chemical and physical traits for any single kernel trait were not large enough to base corn hybrid selection on for feeding poultry.

A PKM Generated by Calpain Cleavage of a Classical PKC Is Required for Activity-Dependent Intermediate-Term Facilitation in the Presynaptic Sensory Neuron of "Aplysia"

ERIC Educational Resources Information Center

Farah, Carole A.; Hastings, Margaret H.; Dunn, Tyler W.; Gong, Katrina; Baker-Andresen, Danay; Sossin, Wayne S.

2017-01-01

Atypical PKM, a persistently active form of atypical PKC, is proposed to be a molecular memory trace, but there have been few examinations of the role of PKMs generated from other PKCs. We demonstrate that inhibitors used to inhibit PKMs generated from atypical PKCs are also effective inhibitors of other PKMs. In contrast, we demonstrate that…

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...

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...

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...

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.

Comparison of amino acid digestibility coefficients for soybean meal, canola meal, fish meal, and meat and bone meal among 3 different bioassays

USDA-ARS?s Scientific Manuscript database

The objective of this study was to determine amino acid digestibility of 4 feedstuffs [soybean meal (SBM), canola meal, fish meal, and meat and bone meal (MBM)] using the precision-fed cecectomized rooster assay (PFR), the standardized ileal assay (SIAAD), and a newly developed precision-fed ileal b...

What determines real-world meal size? Evidence for pre-meal planning.

PubMed

Fay, Stephanie H; Ferriday, Danielle; Hinton, Elanor C; Shakeshaft, Nicholas G; Rogers, Peter J; Brunstrom, Jeffrey M

2011-04-01

The customary approach to the study of meal size suggests that 'events' occurring during a meal lead to its termination. Recent research, however, suggests that a number of decisions are made before eating commences that may affect meal size. The present study sought to address three key research questions around meal size: the extent to which plate-cleaning occurs; prevalence of pre-meal planning and its influence on meal size; and the effect of within-meal experiences, notably the development of satiation. To address these, a large-cohort internet-based questionnaire was developed. Results showed that plate-cleaning occurred at 91% of meals, and was planned from the outset in 92% of these cases. A significant relationship between plate-cleaning and meal planning was observed. Pre-meal plans were resistant to modification over the course of the meal: only 18% of participants reported consumption that deviated from expected. By contrast, 28% reported continuing eating beyond satiation, and 57% stated that they could have eaten more at the end of the meal. Logistic regression confirmed pre-meal planning as the most important predictor of consumption. Together, our findings demonstrate the importance of meal planning as a key determinant of meal size and energy intake. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

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...

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. ...

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.

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.

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.

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.

Rye-Based Evening Meals Favorably Affected Glucose Regulation and Appetite Variables at the Following Breakfast; A Randomized Controlled Study in Healthy Subjects

PubMed Central

Sandberg, Jonna C.; Björck, Inger M. E.; Nilsson, Anne C.

2016-01-01

Background Whole grain has shown potential to prevent obesity, cardiovascular disease and type 2 diabetes. Possible mechanism could be related to colonic fermentation of specific indigestible carbohydrates, i.e. dietary fiber (DF). The aim of this study was to investigate effects on cardiometabolic risk factors and appetite regulation the next day when ingesting rye kernel bread rich in DF as an evening meal. Method Whole grain rye kernel test bread (RKB) or a white wheat flour based bread (reference product, WWB) was provided as late evening meals to healthy young adults in a randomized cross-over design. The test products RKB and WWB were provided in two priming settings: as a single evening meal or as three consecutive evening meals prior to the experimental days. Test variables were measured in the morning, 10.5–13.5 hours after ingestion of RKB or WWB. The postprandial phase was analyzed for measures of glucose metabolism, inflammatory markers, appetite regulating hormones and short chain fatty acids (SCFA) in blood, hydrogen excretion in breath and subjective appetite ratings. Results With the exception of serum CRP, no significant differences in test variables were observed depending on length of priming (P>0.05). The RKB evening meal increased plasma concentrations of PYY (0–120 min, P<0.001), GLP-1 (0–90 min, P<0.05) and fasting SCFA (acetate and butyrate, P<0.05, propionate, P = 0.05), compared to WWB. Moreover, RKB decreased blood glucose (0–120 min, P = 0.001), serum insulin response (0–120 min, P<0.05) and fasting FFA concentrations (P<0.05). Additionally, RKB improved subjective appetite ratings during the whole experimental period (P<0.05), and increased breath hydrogen excretion (P<0.001), indicating increased colonic fermentation activity. Conclusion The results indicate that RKB evening meal has an anti-diabetic potential and that the increased release of satiety hormones and improvements of appetite sensation could be beneficial in

Easy Meal

NASA Technical Reports Server (NTRS)

1978-01-01

The woman pictured below is sitting down to a nutritious, easily-prepared meal similar to those consumed by Apollo astronauts. The appetizing dishes shown were created simply by adding water to the contents of a Mountain House* Easy Meal package of freeze dried food. The Easy Meal line is produced by Oregon Freeze Dry Foods, Inc., Albany, Oreaon, a pioneer in freeze drying technology and a company long associated with NASA in developing suitable preparations for use on manned spacecraft. Designed to provide nutritionally balanced, attractive hot meals for senior adults, Easy Meal is an offshoot of a 1975-77 demonstration project managed by Johnson Space Center and called Meal System for the Elderly. The project sought ways to help the estimated 3.5 million elderly Americans who are unable to take advantage of existing meal programs. Such services are provided by federal, state and local agencies, but they are not available to many who live in rural areas, or others who are handicapped, temporarily ill or homebound for other reasons. Oregon Freeze Dry Foods was a participant in that multi-agency cooperative project. With its Easy Meal assortment of convenience foods pictured above left, the company is making commercially available meal packages similar to those distributed in the Meal System for the Elderly program. In the freeze drying process, water is extracted from freshly-cooked foods by dehydration at very low temperatures, as low as 50 I degrees below zero. Flavor is locked in by packaging the dried food in pouches which block out moisture and oxygen, the principal causes of food deterioration; thus the food can be stored for long periods without refrigeration. Meals are reconstituted by adding hot or cold water, depending on the type of food, and they are table ready in five to 10 minutes. Oregon Freeze Dry Foods offers five different meal packages and plans to expand the line.

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...

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.

Planning Meals

MedlinePlus

... Your Plate Gluten Free Diets Meal Planning for Vegetarian Diets Cook with Heart-Healthy Foods Holiday Meal Planning ... will please the whole family. Meal Planning for Vegetarian Diets A vegetarian diet is a healthy option, even ...

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.

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

Mothers and meals. The effects of mothers' meal planning and shopping motivations on children's participation in family meals.

PubMed

McIntosh, William Alex; Kubena, Karen S; Tolle, Glen; Dean, Wesley R; Jan, Jie-sheng; Anding, Jenna

2010-12-01

Participation in family meals has been associated with benefits for health and social development of children. The objective of the study was to identify the impact of mothers' work of caring through planning regularly scheduled meals, shopping and cooking, on children's participation in family meals. Parents of children aged 9-11 or 13-15 years from 300 Houston families were surveyed about parents' work, meal planning for and scheduling of meals, motivations for food purchases, importance of family meals, and children's frequency of eating dinner with their families. The children were interviewed about the importance of eating family meals. Hypotheses were tested using path analysis to calculate indirect and total effects of variables on the outcome variable of frequency of children eating dinner with their family. Mothers' belief in the importance of family meals increased likelihood of children eating dinner with families by increasing likelihood that mothers planned dinner and that dinners were regularly scheduled. Mothers' perception of time pressures on meal preparation had a negative, indirect effect on the frequency of children's participation in family dinners by reducing mothers' meal planning. Copyright © 2010 Elsevier Ltd. All rights reserved.

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…

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.

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.

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.

Associations of family meal frequency with family meal habits and meal preparation characteristics among families of youth with type 1 diabetes.

PubMed

Kornides, M L; Nansel, T R; Quick, V; Haynie, D L; Lipsky, L M; Laffel, L M B; Mehta, S N

2014-05-01

While benefits of family mealtimes, such as improved dietary quality and increased family communication, have been well-documented in the general population, less is known about family meal habits that contribute to more frequent family meals in youth with type 1 diabetes. This cross-sectional study surveyed 282 youth ages 8-18 years with type 1 diabetes and their parents on measures regarding diabetes-related and dietary behaviours. T-tests determined significant differences in youth's diet quality, adherence to diabetes management and glycaemic control between those with and without regular family meals (defined as ≥ 5 meals per week). Logistic regression analyses determined unadjusted and adjusted associations of age, socio-demographics, family meal habits, and family meal preparation characteristics with regular family meals. 57% of parents reported having regular family meals. Families with regular family meals had significantly better diet quality as measured by the Healthy Eating Index (P < 0.05) and the NRF9.3 (P < 0.01), and adherence to diabetes management (P < 0.001); the difference in glycaemic control approached statistical significance (P = 0.06). Priority placed on, pleasant atmosphere and greater structure around family meals were each associated with regular family meals (P < 0.05). Meals prepared at home were positively associated with regular family meals, while convenience and fast foods were negatively associated (P < 0.05). Families in which at least one parent worked part-time or stayed at home were significantly more likely to have regular family meals than families in which both parents worked full-time (P < 0.05). In the multivariate logistic regression model, greater parental priority given to family mealtimes (P < 0.001) and more home-prepared meals (P < 0.001) predicted occurrence of regular family meals; adjusting for parent work status and other family meal habits. Strategies for promoting families meals should not only highlight

Associations of family meal frequency with family meal habits and meal preparation characteristics among families of youth with type 1 diabetes

PubMed Central

Kornides, M. L.; Nansel, T. R.; Quick, V.; Haynie, D. L.; Lipsky, L. M.; Laffel, L. M. B.; Mehta, S. N.

2014-01-01

Background While benefits of family mealtimes, such as improved dietary quality and increased family communication, have been well-documented in the general population, less is known about family meal habits that contribute to more frequent family meals in youth with type 1 diabetes. Methods This cross-sectional study surveyed 282 youth ages 8–18 years with type 1 diabetes and their parents on measures regarding diabetes-related and dietary behaviours. T-tests determined significant differences in youth's diet quality, adherence to diabetes management and glycaemic control between those with and without regular family meals (defined as ≥5 meals per week). Logistic regression analyses determined unadjusted and adjusted associations of age, socio-demographics, family meal habits, and family meal preparation characteristics with regular family meals. Results 57% of parents reported having regular family meals. Families with regular family meals had significantly better diet quality as measured by the Healthy Eating Index (P < 0.05) and the NRF9.3 (P < 0.01), and adherence to diabetes management (P < 0.001); the difference in glycaemic control approached statistical significance (P = 0.06). Priority placed on, pleasant atmosphere and greater structure around family meals were each associated with regular family meals (P < 0.05). Meals prepared at home were positively associated with regular family meals, while convenience and fast foods were negatively associated (P < 0.05). Families in which at least one parent worked part-time or stayed at home were significantly more likely to have regular family meals than families in which both parents worked full-time (P < 0.05). In the multivariate logistic regression model, greater parental priority given to family mealtimes (P < 0.001) and more home-prepared meals (P < 0.001) predicted occurrence of regular family meals; adjusting for parent work status and other family meal habits. Conclusions Strategies for promoting

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.

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,…

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...

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...

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...

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...

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...

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...

Learning through school meals?

PubMed

Benn, Jette; Carlsson, Monica

2014-07-01

This article is based on a qualitative multiple case study aimed at evaluating the effects of free school meal interventions on pupils' learning, and on the learning environment in schools. The study was conducted at four schools, each offering free school meals for 20 weeks. At each school individual and focus group interviews were conducted with students in grades 5 to 7 and grades 8 to 9. Furthermore, students were observed during lunch breaks, and interviews were conducted with the class teacher, headmaster and/or the person responsible for school meals. The purpose of the article is to explore the learning potentials of school meals. The cross-case analysis focuses on the involved actors' perceptions of the school meal project and the meals, including places, times and contexts, and the pupils' concepts and competences in relation to food, meals and health, as well as their involvement in the school meal project. The analysis indicates that the pupils have developed knowledge and skills related to novel foods and dishes, and that school meals can contribute to pupils' learning, whether this learning is planned or not. However, if school meals are to be further developed as an arena for learning, greater consideration must be given to the interaction between pupil, school meal and teacher than in the school meal projects presented in this study, and the potentials for learning through school meals clarified and discussed in the schools. Studying the school meal projects raises a number of dilemmas, such as whether the lunch break should be a part of or a break from education, are school meals a common (school) or private (parent) responsibility, and questions about pupils' and teachers' roles and participation in school meals. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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.

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.

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

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.

Comparing childhood meal frequency to current meal frequency, routines, and expectations among parents.

PubMed

Friend, Sarah; Fulkerson, Jayne A; Neumark-Sztainer, Dianne; Garwick, Ann; Flattum, Colleen Freeh; Draxten, Michelle

2015-02-01

Little is known about the continuation of family meals from childhood to parenthood. This study aims to examine associations between parents' report of eating family meals while growing up and their current family meal frequency, routines, and expectations. Baseline data were used from the Healthy Home Offerings via the Mealtime Environment (HOME) Plus study, a randomized controlled trial with a program to promote healthful behaviors and family meals at home. Participants (160 parent/child dyads) completed data collection in 2011-2012 in the Minneapolis/St. Paul, MN metropolitan area. Parents were predominately female (95%) and white (77%) with a mean age of 41.3 years. General linear modeling examined relationships between parents' report of how often they ate family meals while growing up and their current family meal frequency, routines, and expectations as parents, controlling for parent age, education level, and race. Parental report of eating frequent family meals while growing up was positively and significantly associated with age, education, and self-identification as white (all p < .05). Compared to those who ate family meals less than three times/week or four to five times/week, parents who ate six to seven family meals/week while growing up reported significantly more frequent family meals with their current family (4.0, 4.2 vs. 5.3 family meals/week, p = .001). Eating frequent family meals while growing up was also significantly and positively associated with having current regular meal routines and meal expectations about family members eating together (both p < .05). Promoting family meals with children may have long-term benefits over generations. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Comparing Childhood Meal Frequency to Current Meal Frequency, Routines and Expectations Among Parents

PubMed Central

Friend, Sarah; Fulkerson, Jayne A.; Neumark-Sztainer, Dianne; Garwick, Ann; Flattum, Colleen Freech; Draxten, Michelle

2015-01-01

Little is known about the continuation of family meals from childhood to parenthood. This study aims to examine associations between parents’ report of eating family meals while growing up and their current family meal frequency, routines, and expectations. Baseline data were used from the Healthy Home Offerings via the Mealtime Environment (HOME) Plus study, a randomized controlled trial with a program to promote healthful behaviors and family meals at home. Participants (160 parent/child dyads) completed data collection in 2011–2012 in the Minneapolis/St. Paul, MN metropolitan area. Parents were predominately female (95%) and white (77%) with a mean age of 41.3 years. General linear modeling examined relationships between parents’ report of how often they ate family meals while growing up and their current family meal frequency, routines and expectations as parents, controlling for parent age, education level and race. Parental report of eating frequent family meals while growing up was positively and significantly associated with age, education and self-identification as white (all p<0.05). Compared to those who ate family meals less than three times/week or four to five times/week, parents who ate six to seven family meals/week while growing up reported significantly more frequent family meals with their current family (4.0, 4.2 vs 5.3 family meals/week, p=.001). Eating frequent family meals while growing up was also significantly and positively associated with having current regular meal routines and meal expectations about family members eating together (both p<.05). Promoting family meals with children may have long-term benefits over generations. PMID:25485670

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.

College Students’ Perceived Differences Between the Terms Real Meal, Meal, and Snack

PubMed Central

Banna, Jinan; Richards, Rickelle; Brown, Lora Beth

2017-01-01

Objective To assess qualitatively and quantitatively college students’ perceived differences between a real meal, meal, and snack. Design A descriptive study design was used to administer an 11-item online survey to college students. Setting Two university campuses in the western US. Participants Pilot testing was conducted with 20 students. The final survey was completed by 628 ethnically diverse students. Main Outcome Measures Students’ perceptions of the terms real meal, meal, and snack. Analysis Three researchers coded the data independently, reconciled differences via conference calls, and agreed on a final coding scheme. Data were reevaluated based on the coding scheme. Means, frequencies, Pearson chi-square, and t test statistics were used. Results More than half of students perceived a difference between the terms real meal and meal. Most (97.6%) perceived a difference between the terms meal and snack. A marked difference in the way students defined these terms was evident, with a real meal deemed nutritious and healthy and meeting dietary recommendations, compared with meals, which were considered anything to eat. Conclusions and Implications These findings suggest that the term real meal may provide nutrition educators with a simple phrase to use in educational campaigns to promote healthful food intake among college students. PMID:27993555

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

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

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.

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

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.

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

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

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.

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.

Comparative study of growth traits and haematological parameters of Anak and Nigerian heavy ecotype chickens fed with graded levels of mango seed kernel (Mangifera indica) meal.

PubMed

Mbunwen, Ndofor-Foleng Harriet; Ngongeh, Lucas Atehmengo; Okolie, Peter Nzeribe; Okoli, Emeka Linus

2015-08-01

One hundred fifty Anak and 120 Nigerian heavy local ecotype (NHLE) chickens were used to study the effects of feeding graded levels of mango seed kernel meal (MKM) replacing maize diet on growth traits and haematological parameters. A 2 × 5 factorial arrangement was employed: two breeds and five diets. The birds were randomly allocated to five finisher diets formulated such that MKM replaced maize at 0, 10, 20, 30 and 40% (T1, T2, T3, T4 and T5) inclusion levels, respectively. The effect of breed and dietary treatments on growth performance and blood characteristics were determined. The results showed a significant (P < 0.05) breed effect on body weight and gain, shank length, thigh length, body width and body length. The growth traits of Anak breed were found to be superior to NHLE chickens. Within treatments, chicks on T1, T2 and T3, grew heavier than those on T4 and T5. However, feed intake, feed conversion ratio (FCR) and haematological indices (RBC, Hb, MCV, MCH and MCHC count) were not significant (P > 0.05) when the breeds and treatments were compared. It was concluded that inclusion of dietary MKM below 30% could replace maize in the diets of Anak and NHLE growing chickens without adverse effect on growth performance and blood constituents. This work suggests that genetic differences exist in growth traits of these breeds of chickens. This advantage could be useful in breed improvement programmes and better feeding managements of the NHLE and Anak chickens.

Associations between TV viewing at family meals and the emotional atmosphere of the meal, meal healthfulness, child dietary intake, and child weight status.

PubMed

Trofholz, Amanda C; Tate, Allan D; Miner, Michael H; Berge, Jerica M

2017-01-01

Research on family meals has demonstrated that family meals are protective for many aspects of child and adolescent health. It is unclear whether distractions at family meals, such as watching TV, are associated with child weight and weight-related behaviors, the emotional atmosphere at the meal, or family meal healthfulness. Direct observational and objective data were collected on primarily low-income and minority families (n = 120) with 6-12 year old children. Data were collected during home visits and included 24-hr dietary recalls, anthropometry, and video-recorded family meals. Video-recorded family meals were coded to assess the presence of TV, whether the family was paying attention to the TV, family group enjoyment and the dietary healthfulness of the foods served at family meals. The presence of TV was negatively associated with the dietary healthfulness and emotional atmosphere of the meal and the child's overall dietary quality. It was positively associated with serving fast food for family meals. Those families who were paying attention to the TV had significantly worse meal dietary healthfulness and were more likely to have fast food at family meals compared to those who were not paying attention. No significant findings were found between the presence of TV at family meals and child overweight status. Study results show that TV is frequently present at family meals. Even if families are not paying attention to the TV, it appears that simply having the TV on as background noise is associated with deleterious outcomes. In addition to increasing family meals, families should be given guidance on turning off the TV and making the family meal a time to connect with one another. Copyright © 2016 Elsevier Ltd. All rights reserved.

Associations between TV Viewing at Family Meals and the Emotional Atmosphere of the Meal, Meal Healthfulness, Child Dietary Intake, and Child Weight Status

PubMed Central

Trofholz, Amanda C.; Tate, Allan D.; Miner, Michael H.; Berge, Jerica M.

2016-01-01

Background Research on family meals has demonstrated that family meals are protective for many aspects of child and adolescent health. It is unclear whether distractions at family meals, such as watching TV, are associated with child weight and weight-related behaviors, the emotional atmosphere at the meal, or family meal healthfulness. Methods Direct observational and objective data were collected on primarily low-income and minority families (n=120) with 6–12 year old children. Data were collected during home visits and included 24-hr dietary recalls, anthropometry, and video-recorded family meals. Video-recorded family meals were coded to assess the presence of TV, whether the family was paying attention to the TV, family group enjoyment and the dietary healthfulness of the foods served at family meals. Results The presence of TV was negatively associated with the dietary healthfulness and emotional atmosphere of the meal and the child’s overall dietary quality. It was positively associated with serving fast food for family meals. Those families who were paying attention to the TV had significantly worse meal dietary healthfulness and were more likely to have fast food at family meals compared to those who were not paying attention. No significant findings were found between the presence of TV at family meals and child overweight status. Conclusions Study results show that TV is frequently present at family meals. Even if families are not paying attention to the TV, it appears that simply having the TV on as background noise is associated with deleterious outcomes. In addition to increasing family meals, families should be given guidance on turning off the TV and making the family meal a time to connect with one another. PMID:27756638

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...

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.

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.

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...

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.

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.

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...

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.

29 CFR 785.19 - Meal.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false Meal. 785.19 Section 785.19 Labor Regulations Relating to... INTERPRETATION NOT DIRECTLY RELATED TO REGULATIONS HOURS WORKED Application of Principles Rest and Meal Periods § 785.19 Meal. (a) Bona fide meal periods. Bona fide meal periods are not worktime. Bona fide meal...

29 CFR 785.19 - Meal.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 3 2011-07-01 2011-07-01 false Meal. 785.19 Section 785.19 Labor Regulations Relating to... INTERPRETATION NOT DIRECTLY RELATED TO REGULATIONS HOURS WORKED Application of Principles Rest and Meal Periods § 785.19 Meal. (a) Bona fide meal periods. Bona fide meal periods are not worktime. Bona fide meal...

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

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.

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...

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...

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.

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.

Television, Home-Cooked Meals, and Family Meal Frequency: Associations with Adult Obesity.

PubMed

Tumin, Rachel; Anderson, Sarah E

2017-06-01

Adults, regardless of whether they are parents, regularly eat meals with family at home, but few studies have analyzed large, population-based samples to examine how mealtime practices or family meal frequency are associated with health. The aim of this study was to evaluate associations between the frequency of family meals eaten at home, watching television or videos during family meals, and consumption of meals that were cooked and eaten at home and the odds of being obese in adults. This was an analysis of the cross-sectional 2012 Ohio Medicaid Assessment Survey (OMAS), a telephone survey of Ohio's population. The study sample was adult Ohio residents responding to the 2012 OMAS who ate at least one family meal in the past week (n=12,842). Obesity (body mass index [BMI] ≥30), calculated from self-reported height and weight, was the outcome. Logistic regression models were used to examine the association between obesity and family meal practices, adjusted for respondents' employment status, marital status, race/ethnicity, educational attainment, and age. Family meal frequency was not associated with odds of obesity: those who ate family meals most (6-7) days were as likely as those who ate family meals few (1-2) days to be obese (adjusted odds ratio [OR adj ]=1.01, 95% CI=0.86, 1.18). Thirty-six percent of adults never watched television or videos while eating family meals, and 62% ate family meals that were all home-cooked. Adults who never watched television or videos during family meals had 37% lower odds of obesity compared with those who always did (95% CI=0.54, 0.73), regardless of family meal frequency. Adults whose family meals were all home-cooked had 26% lower odds of obesity than those who ate some or no home-cooked family meals (95% CI=0.62, 0.88). This association was more pronounced among adults who ate few family meals. Family meal practices may be associated with obesity in adults, even if they eat few family meals per week. Future research

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...

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...

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

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

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

Circadian Clocks for All Meal-Times: Anticipation of 2 Daily Meals in Rats

PubMed Central

Mistlberger, Ralph E.; Kent, Brianne A.; Chan, Sofina; Patton, Danica F.; Weinberg, Alexander; Parfyonov, Maksim

2012-01-01

Anticipation of a daily meal in rats has been conceptualized as a rest-activity rhythm driven by a food-entrained circadian oscillator separate from the pacemaker generating light-dark (LD) entrained rhythms. Rats can also anticipate two daily mealtimes, but whether this involves independently entrained oscillators, one ‘continuously consulted’ clock, cue-dependent non-circadian interval timing or a combination of processes, is unclear. Rats received two daily meals, beginning 3-h (meal 1) and 13-h (meal 2) after lights-on (LD 14∶10). Anticipatory wheel running began 68±8 min prior to meal 1 and 101±9 min prior to meal 2 but neither the duration nor the variability of anticipation bout lengths exhibited the scalar property, a hallmark of interval timing. Meal omission tests in LD and constant dark (DD) did not alter the timing of either bout of anticipation, and anticipation of meal 2 was not altered by a 3-h advance of meal 1. Food anticipatory running in this 2-meal protocol thus does not exhibit properties of interval timing despite the availability of external time cues in LD. Across all days, the two bouts of anticipation were uncorrelated, a result more consistent with two independently entrained oscillators than a single consulted clock. Similar results were obtained for meals scheduled 3-h and 10-h after lights-on, and for a food-bin measure of anticipation. Most rats that showed weak or no anticipation to one or both meals exhibited elevated activity at mealtime during 1 or 2 day food deprivation tests in DD, suggesting covert operation of circadian timing in the absence of anticipatory behavior. A control experiment confirmed that daytime feeding did not shift LD-entrained rhythms, ruling out displaced nocturnal activity as an explanation for daytime activity. The results favor a multiple oscillator basis for 2-meal anticipatory rhythms and provide no evidence for involvement of cue-dependent interval timing. PMID:22355393

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.

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.

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.

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.

Meals for the Elderly

NASA Technical Reports Server (NTRS)

1977-01-01

NASA is drawing upon its food-preparation expertise to assist in solving a problem affecting a large segment of the American population. In preparation for manned space flight programs, NASA became experienced in providing astronauts simple, easily-prepared, nutritious meals. That experience now is being transferred to the public sector in a cooperative project managed by Johnson Space Center. Called Meal System for the Elderly, the project seeks to fill a gap by supplying nutritionally balanced meal packages to those who are unable to participate in existing meal programs. Many such programs are conducted by federal, state and private organizations, including congregate hot meal services and home-delivered "meals on wheels." But more than 3.5 million elderly Americans are unable to take advantage of these benefits. In some cases, they live in rural areas away from available services; in others, they are handicapped, temporarily ill, or homebound for other reasons. Meal System for the Elderly, a cooperative program in which the food-preparation expertise NASA acquired in manned space projects is being utilized to improve the nutritional status of elderly people. The program seeks to fill a gap by supplying nutritionally-balanced food packages to the elderly who are unable to participate b existing meal service programs.

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

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.

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.

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.

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.

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.

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.

The Healthy Meal Index: A tool for measuring the healthfulness of meals served to children

PubMed Central

Kasper, Nicole; Mandell, Cami; Ball, Sarah; Miller, Alison L.; Lumeng, Julie; Peterson, Karen E

2017-01-01

Family meals have been associated with higher diet quality and reduced risk of obesity in children. Observational studies of the family meal have been employed with increasing frequency, yet there is currently no tool available for measuring the healthfulness of food served during the meal. Here we present the development and validation of the Healthy Meal Index (HMI), a novel tool for scoring the healthfulness of foods served to children during a meal, as well as sociodemographic predictors of meal scores. Parents of 233 children, aged 4–8 years, self-recorded three home dinners. A research assistant obtained a list of foods available during the meal (meal report) via phone call on the night of each video-recorded meal. This meal report was coded into component foods groups. Subsequently, meals were scored based on the availability of more healthy “Adequacy foods” and the absence of “Moderation foods”, (of which reduced consumption is recommended, according to pediatric dietary guidelines). Adjusted linear regression tested the association of sociodemographic characteristics with HMI scores. A validation study was conducted in a separate sample of 133 children with detailed meal data. In adjusted models, female children had higher HMI Moderation scores (p=0.02), but did not differ in HMI Adequacy or Total scores. Parents with more education served meals with higher HMI Adequacy (p=0.001) and Total scores (p=0.001), though no significant difference was seen in HMI Moderation score (p=0.21). The validation study demonstrated that the HMI was highly correlated with servings of foods and nutrients estimated from observations conducted by research staff. The HMI is a valuable tool for measuring the quality of meals served to children. PMID:26994739

The Healthy Meal Index: A tool for measuring the healthfulness of meals served to children.

PubMed

Kasper, Nicole; Mandell, Cami; Ball, Sarah; Miller, Alison L; Lumeng, Julie; Peterson, Karen E

2016-08-01

Family meals have been associated with higher diet quality and reduced risk of obesity in children. Observational studies of the family meal have been employed with increasing frequency, yet there is currently no tool available for measuring the healthfulness of food served during the meal. Here we present the development and validation of the Healthy Meal Index (HMI), a novel tool for scoring the healthfulness of foods served to children during a meal, as well as sociodemographic predictors of meal scores. Parents of 233 children, aged 4-8 years, self-recorded three home dinners. A research assistant obtained a list of foods available during the meal (meal report) via phone call on the night of each video-recorded meal. This meal report was coded into component food groups. Subsequently, meals were scored based on the availability of more healthy "Adequacy foods" and the absence of "Moderation foods", (of which reduced consumption is recommended, according to pediatric dietary guidelines). Adjusted linear regression tested the association of sociodemographic characteristics with HMI scores. A validation study was conducted in a separate sample of 133 children with detailed meal data. In adjusted models, female children had higher HMI Moderation scores (p = 0.02), but did not differ in HMI Adequacy or Total scores. Parents with more education served meals with higher HMI Adequacy (p = 0.001) and Total scores (p = 0.001), though no significant difference was seen in HMI Moderation score (p = 0.21). The validation study demonstrated that the HMI was highly correlated with servings of foods and nutrients estimated from observations conducted by research staff. The HMI is a valuable tool for measuring the quality of meals served to children. Copyright © 2016. Published by Elsevier Ltd.

Dehydration-Anorexia Derives From A Reduction In Meal Size, But Not Meal Number

PubMed Central

Boyle, Christina N.; Lorenzen, Sarah M.; Compton, Douglas; Watts, Alan G.

2011-01-01

The anorexia that results from extended periods of cellular dehydration is an important physiological adaptation that limits the intake of osmolytes from food and helps maintain the integrity of fluid compartments. The ability to experimentally control both the development and reversal of anorexia, together with the understanding of underlying hormonal and neuropeptidergic signals, make dehydration (DE)-anorexia a powerful model for exploring the interactions of neural networks that stimulate and inhibit food intake. However, it is not known which meal parameters are affected by cellular dehydration to generate anorexia. Here we use continuous and high temporal resolution recording of food and fluid intake, together with a drinking-explicit method of meal pattern analysis to explore which meal parameters are modified during DE-anorexia. We find that the most important factor responsible for DE-anorexia is the failure to maintain feeding behavior once a meal has started, rather than the ability to initiate a meal, which remains virtually intact. This outcome is consistent with increased sensitivity to satiation signals and post-prandial satiety mechanisms. We also find that DE-anorexia significantly disrupts the temporal distribution of meals across the day so that the number of nocturnal meals gradually decreases while diurnal meal number increases. Surprisingly, once DE-anorexia is reversed this temporal redistribution is maintained for at least 4 days after normal food intake has resumed, which may allow increased daily food intake even after normal satiety mechanisms are reinstated. Therefore, DE-anorexia apparently develops from a selective targeting of those neural networks that control meal termination, whereas meal initiation mechanisms remain viable. PMID:21854794

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.

Canine gastric emptying of fiber meals: influence of meal viscosity and antroduodenal motility.

PubMed

Russell, J; Bass, P

1985-12-01

Dietary fibers such as psyllium and guar gum have been shown to delay the gastric emptying of liquids and solids, presumably due to an increase in meal viscosity. For liquid test meals containing fats, delayed gastric emptying is associated with a reversal of the usual antral-to-duodenal contractile gradient. The present studies were performed to determine whether the gastric emptying of increasingly viscous psyllium and guar gum meals was associated with antroduodenal motility changes. Dogs were surgically fitted with mid-duodenal cannulas for the measurement of gastric emptying. Strain-gauge force transducers were used to monitor antral and duodenal contractile responses to the test meals. Low-viscosity fiber meals emptied from the stomach rapidly (E 1/2 approximately 10 min) compared with the high-viscosity meals (E 1/2 approximately 40 min). None of the test meals stimulated antral or duodenal motility despite differences in gastric emptying time. Other motor parameters such as the time of reappearance and the duration of the burst interval were also unchanged. We conclude a) as test meals' fiber content and viscosity increase, gastric emptying is slowed; and b) viscosity-related delays in gastric emptying are not due to an effect on postprandial antroduodenal motility.

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%.

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%.

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.

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.

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.

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

Circadian and ultradian components of hunger in human non-homeostatic meal-to-meal eating.

PubMed

Wuorinen, Elizabeth C; Borer, Katarina T

2013-10-02

A unifying physiological explanation of the urge to initiate eating is still not available as human hunger in meal-to-meal eating may not be under homeostatic control. We hypothesized that a central circadian and a gastrointestinal ultradian timing mechanism coordinate non-deprivation meal-to-meal eating. We examined hunger as a function of time of day, inter-meal (IM) energy expenditure (EE), and concentrations of proposed hunger-controlling hormones ghrelin, leptin, and insulin. In two crossover studies, 10 postmenopausal women, BMI 23-26 kg/m(2) engaged in exercise (EX) and sedentary (SED) trials. Weight maintenance meals were provided at 6h intervals with an ad libitum meal at 13 h in study 1 and 21 h snack in study 2. EE during IM intervals was measured by indirect calorimetry and included EX EE of 801 kcal in study 1, and 766-1,051 kcal in study 2. Hunger was assessed with a visual analog scale and blood was collected for hormonal determination. Hunger displayed a circadian variation with acrophase at 13 and 19 h and was unrelated to preceding EE. Hunger was suppressed by EX between 10 and 16 h and bore no relationship to either EE during preceding IM intervals or changes in leptin, insulin, and ghrelin; however leptin reflected IM energy changes and ghrelin and insulin, prandial events. During non-deprivation meal-to-meal eating, hunger appears to be under non-homeostatic central circadian control as it is unrelated to EE preceding meals or concentrations of proposed appetite-controlling hormones. Gastrointestinal meal processing appears to intermittently suppress this control and entrain an ultradian hunger pattern. © 2013 Elsevier Inc. All rights reserved.

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...

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...

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.

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...

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...

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...

Meals for the Elderly

NASA Technical Reports Server (NTRS)

1980-01-01

The aim of Skylab's multi-agency cooperative project was to make simple but nutritious space meals available to handicapped and otherwise homebound senior adults, unable to take advantage of existing meal programs sponsored by federal, state and private organizations. As a spinoff of Meal Systems for the Elderly, commercial food processing firms are now producing astronaut type meals for public distribution. Company offers variety of freeze dried foods which are reconstituted by addition of water, and "retort pouch" meals which need no reconstitution, only heating. The retort pouch is an innovative flexible package that combines the advantage of boil-in bag and metal can. Foods retain their flavor, minerals and vitamins can be stored without refrigeration and are lightweight for easy transportation.

Serve Size and Estimated Energy and Protein Contents of Meals Prepared by 'Meals on Wheels' South Australia Inc.: Findings from a Meal Audit Study.

PubMed

Arjuna, Tony; Miller, Michelle; Soenen, Stijn; Chapman, Ian; Visvanathan, Renuka; Luscombe-Marsh, Natalie D

2018-02-20

An audit of 'standard' (STD) and 'energy and protein fortified' (HEHP) meals from Meals on Wheels (MOW) South Australia's summer menu was conducted to evaluate the consistency, and serve size and nutrient contents, of their menu items. Twenty soups, 20 mains and 20 desserts from each of the STD and HEHP menus were prepared at the MOW South Australia's kitchen and delivered to three 'sham(dummy)-clients' over a 5-week period. Each meal component was weighed in triplicate, to the nearest gram, the variation within the serve weight was calculated, and the overall energy and protein content of each meal was determined using FoodWorks (Xyris Software, Highgate Hill, Queensland, Australia). On average, the variability for soups and mains was ≤6% and for desserts was ≤10% and although the measured serve sizes of the MOW meals were consistently smaller than prescribed serve size, the differences were minor. As a percentage of recommended daily intakes (RDIs) for adults aged over 60 years, we calculated that the STD meals contained 21-39% for energy and 42-63% for protein while the HEHP meals contained 29-55% for energy and 46-69% for protein. These findings demonstrate that MOW meals currently meet the voluntary meal guidelines for energy and protein.

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.

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

The antioxidant uncoupling protein 2 stimulates hnRNPA2/B1, GLUT1 and PKM2 expression and sensitizes pancreas cancer cells to glycolysis inhibition.

PubMed

Brandi, Jessica; Cecconi, Daniela; Cordani, Marco; Torrens-Mas, Margalida; Pacchiana, Raffaella; Dalla Pozza, Elisa; Butera, Giovanna; Manfredi, Marcello; Marengo, Emilio; Oliver, Jordi; Roca, Pilar; Dando, Ilaria; Donadelli, Massimo

2016-12-01

Several evidence indicate that metabolic alterations play a pivotal role in cancer development. Here, we report that the mitochondrial uncoupling protein 2 (UCP2) sustains the metabolic shift from mitochondrial oxidative phosphorylation (mtOXPHOS) to glycolysis in pancreas cancer cells. Indeed, we show that UCP2 sensitizes pancreas cancer cells to the treatment with the glycolytic inhibitor 2-deoxy-D-glucose. Through a bidimensional electrophoresis analysis, we identify 19 protein species differentially expressed after treatment with the UCP2 inhibitor genipin and, by bioinformatic analyses, we show that these proteins are mainly involved in metabolic processes. In particular, we demonstrate that the antioxidant UCP2 induces the expression of hnRNPA2/B1, which is involved in the regulation of both GLUT1 and PKM2 mRNAs, and of lactate dehydrogenase (LDH) increasing the secretion of L-lactic acid. We further demonstrate that the radical scavenger N-acetyl-L-cysteine reverts hnRNPA2/B1 and PKM2 inhibition by genipin indicating a role for reactive oxygen species in the metabolic reprogramming of cancer cells mediated by UCP2. We also observe an UCP2-dependent decrease in mtOXPHOS complex I (NADH dehydrogenase), complex IV (cytochrome c oxidase), complex V (ATPase) and in mitochondrial oxygen consumption, suggesting a role for UCP2 in the counteraction of pancreatic cancer cellular respiration. All these results reveal novel mechanisms through which UCP2 promotes cancer cell proliferation with the concomitant metabolic shift from mtOXPHOS to the glycolytic pathway. Copyright © 2016 Elsevier Inc. All rights reserved.

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

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...

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...

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...

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...

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

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

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.

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.

Enzymatic detoxification of jojoba meal and effect of the resulting meal on food intake in rats.

PubMed

Bouali, Abderrahime; Bellirou, Ahmed; Boukhatem, Noureddin; Hamal, Abdellah; Bouammali, Boufelja

2008-05-10

When defatted jojoba meal is used as animal food, it causes food-intake reduction and growth retardation. Detoxification procedures by chemical, microbiological, and solvent extraction methods are reported by several authors. Here we report a successful detoxification of jojoba meal using enzymes. We establish reaction conditions that yield new meal which has the same nutritional qualities in proteins as the original meal. The enzymatic reaction gives rise to one major compound to which the structure of an amide is assigned on the basis of IR, 1H and 13C NMR spectra. The effect of the resulting jojoba meal on the food intake in rats is checked. In contrast, the detoxified meal containing the amide derivatives shows no toxicological activity since rats receiving oral administration of the obtained meal show normal growth. Thus, it is expected that this meal could be used as an animal feed ingredient.

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.

Meal frequencies in early adolescence predict meal frequencies in late adolescence and early adulthood.

PubMed

Pedersen, Trine Pagh; Holstein, Bjørn E; Flachs, Esben Meulengracht; Rasmussen, Mette

2013-05-04

Health and risk behaviours tend to be maintained from adolescence into adulthood. There is little knowledge on whether meal frequencies in adolescence are maintained into adulthood. We investigated whether breakfast, lunch and evening meal frequencies in early adolescence predicted meal frequencies in late adolescence and in early adulthood. Further, the modifying effect of gender and adolescent family structure were investigated. National representative sample of 15-year-olds in Denmark with 4 and 12 year follow-up studies with measurement of breakfast, lunch and evening meal frequencies. A total of 561 persons completed questionnaires at age 15 years (baseline 1990, n=847, response rate 84.6%), age 19 years (n=729, response rate 73.2%) and age 27 years (n=614, response rate 61.6%). Low meal frequencies at age 15 years was a significant predictor for having low meal frequencies at age 19 years (odds ratio (OR, 95% CI)) varying between 2.11, 1.33-3.34 and 7.48, 3.64-15.41). Also, low meal frequencies at age 19 years predicted low meal frequencies at age 27 years (OR varying between 2.26, 1.30-3.91 and 4.38, 2.36-8.13). Significant predictions over the full study period were seen for low breakfast frequency and low lunch frequency (OR varying between 1.78, 1.13-2.81 and 2.58, 1.31-5.07). Analyses stratified by gender showed the same patterns (OR varying between 1.88, 1.13-3.14 and 8.30, 2.85-24.16). However, the observed predictions were not statistical significant among men between age 15 and 27 years. Analyses stratified by adolescent family structure revealed different lunch predictions in strata. Having low meal frequencies in early adolescence predicted low meal frequencies in late adolescence and early adulthood. We propose that promotion of regular meals become a prioritised issue within health education.

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.

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

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

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.

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.

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.

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

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.

Serve Size and Estimated Energy and Protein Contents of Meals Prepared by ‘Meals on Wheels’ South Australia Inc.: Findings from a Meal Audit Study

PubMed Central

Arjuna, Tony; Miller, Michelle; Soenen, Stijn; Chapman, Ian; Visvanathan, Renuka; Luscombe-Marsh, Natalie D

2018-01-01

An audit of ‘standard’ (STD) and ‘energy and protein fortified’ (HEHP) meals from Meals on Wheels (MOW) South Australia’s summer menu was conducted to evaluate the consistency, and serve size and nutrient contents, of their menu items. Twenty soups, 20 mains and 20 desserts from each of the STD and HEHP menus were prepared at the MOW South Australia’s kitchen and delivered to three ‘sham(dummy)-clients’ over a 5-week period. Each meal component was weighed in triplicate, to the nearest gram, the variation within the serve weight was calculated, and the overall energy and protein content of each meal was determined using FoodWorks (Xyris Software, Highgate Hill, Queensland, Australia). On average, the variability for soups and mains was ≤6% and for desserts was ≤10% and although the measured serve sizes of the MOW meals were consistently smaller than prescribed serve size, the differences were minor. As a percentage of recommended daily intakes (RDIs) for adults aged over 60 years, we calculated that the STD meals contained 21–39% for energy and 42–63% for protein while the HEHP meals contained 29–55% for energy and 46–69% for protein. These findings demonstrate that MOW meals currently meet the voluntary meal guidelines for energy and protein. PMID:29461476

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.

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

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.

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

Effects of replacing soybean meal with canola meal or treated canola meal on performance of lactating dairy cows

USDA-ARS?s Scientific Manuscript database

Canola meal (CM) has been shown to be a more effective crude protein (CP) source than soybean meal (SBM) for lactating dairy cows. Treating CM may increase its rumen undegradable protein (RUP) fraction and improve the amount of absorbable amino acids. The objective of this study was to evaluate the ...

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.

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.

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.

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.

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.

Meal-induced thermogenesis and obesity: is a fat meal a risk factor for fat gain in children?

PubMed

Maffeis, C; Schutz, Y; Grezzani, A; Provera, S; Piacentini, G; Tatò, L

2001-01-01

Diet composition, in particular fat intake, has been suggested to be a risk factor for obesity in humans. Several mechanisms may contribute to explain the impact of fat intake on fat gain. One factor may be the low thermogenesis induced by a mixed meal rich in fat. In a group of 11 girls (10.1 +/- 0.3 yr), 6 obese (body mass index, 25.6 +/- 0.6 kg/m(2)), and 5 nonobese (body mass index, 19 +/- 1.6 kg/m(2)), we tested the hypothesis that a mixed meal rich in fat can elicit energy saving compared with an isocaloric and isoproteic meal rich in carbohydrate. The postabsorptive resting energy expenditure and the thermic effect of a meal (TEM) after a low fat (LF; 20% fat, 68% carbohydrate, and 12% protein) or an isocaloric (2500 kJ or 600 Cal) and isoproteic high fat (HF; 48% fat, 40% carbohydrate, and 12% protein) meal were measured by indirect calorimetry. Each girl repeated the test with a different, randomly assigned menu (HF or LF) 1 week after the first test. TEM, expressed as a percentage of energy intake was significantly higher after a LF meal than after a HF meal (6.5 +/- 0.7% vs. 4.3 +/- 0.4%; P < 0.01). The postprandial respiratory quotient (RQ) was significantly higher after a LF meal than after a HF meal (0.86 +/- 0.013 vs. 0.83 +/- 0.014; P < 0.001). The HF low carbohydrate meal induced a significantly lower increase in carbohydrate oxidation than the LF meal (20.3 +/- 6.2 vs. 61.3 +/- 7.8 mg/min; P < 0.001). On the contrary, fat oxidation was significantly higher after a HF meal than after a LF meal (-1.3 +/- 2.4 vs. -15.1 +/- 3.6 mg/min; P < 0.01). However, the postprandial fat storage was 8-fold higher after a HF meal than after a LF meal (17.2 +/- 1.7 vs. 1.9 +/- 1.8 g; P < 0.001). These results suggest that a high fat meal is able to induce lower thermogenesis and a higher positive fat balance than an isocaloric and isoproteic low fat meal. Therefore, diet composition per se must be taken into account among the various risk factors that induce

A study on the meat and bone meal and poultry by-product meal as protein substitutes of fish meal in practical diets for Litopenaeus vannamei juveniles

NASA Astrophysics Data System (ADS)

Zhu, Wei; Mai, Kangsen; Zhang, Baigang; Wang, Fuzhen; Yu, Yu

2004-10-01

A study was conducted to evaluate the effects of meat and bone meal (MBM) and poultry by-product meal (PBM) as the replacement of fish meal in the diets on the growth performance, survival and apparent digestibility coefficients (ADC) of Litopenaeus vannamei. The basal diets were formulated with 22% fish meal and other ingredients which provided about 40% protein and 9% lipid in the diet. The experimental diets included MBM or PBM to replace 0, 20%, 40%, 60% and 80% of total fish meal respectively. All diets were iso-nitrogenous and isocaloric in gross terms. The results showed that there were no significant differences (Pτ;0.05) in growth performance and ADC among the treatments fed with the diets in which 0 60% fish meal had been replaced with MBM, while the percent weight gain (WG, %), body length gain (BLG, %) and ADC significantly decreased when the MBM was up to 80% of the fish meal. There were no significant differences (Pτ;0.05) in growth performance and ADC among all the treatments fed with the diets in which 0 80% fish meal had been replaced with PBM.

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.

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.

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.

Factors related to the number of fast food meals obtained by college meal plan students.

PubMed

Dingman, Deirdre A; Schulz, Mark R; Wyrick, David L; Bibeau, Daniel L; Gupta, Sat N

2014-01-01

This study tested whether days on campus, financial access through a meal plan, and health consciousness were associated with number of meals that college students obtained from fast food restaurants. In April 2013, all students currently enrolled in a meal plan were invited to participate in an online survey (N = 1,246). Students were asked to report the total number of meals eaten in the past week and where they obtained them. Negative binomial regression was used, and it was found that the number of meals obtained from fast food restaurants was positively associated with financial access and negatively associated with health consciousness. An association between days on campus and the number of meals obtained from fast food restaurants was not found. Increasing levels of health consciousness and reducing access to fast food restaurants through flex plans may reduce college students' consumption of fast food.

Evaluation of skate meal and sablefish viscera meal as fish meal replacement in diets for Pacific threadfin (Polydactylus saxfilis)

USDA-ARS?s Scientific Manuscript database

The objectives of this study were to investigate the nutritional value of skate meal (SM) and black cod viscera meal (BCVM) from Alaska and to ascertain their suitability as replacements for commercial pollock fishmeal in diets for Pacific threadfin (Polydactylus sexfilis). Test diets were made by r...

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.

Calculating meal glycemic index by using measured and published food values compared with directly measured meal glycemic index.

PubMed

Dodd, Hayley; Williams, Sheila; Brown, Rachel; Venn, Bernard

2011-10-01

Glycemic index (GI) testing is normally based on individual foods, whereas GIs for meals or diets are based on a formula using a weighted sum of the constituents. The accuracy with which the formula can predict a meal or diet GI is questionable. Our objective was to compare the GI of meals, obtained by using the formula and by using both measured food GI and published values, with directly measured meal GIs. The GIs of 7 foods were tested in 30 healthy people. The foods were combined into 3 meals, each of which provided 50 g available carbohydrate, including a staple (potato, rice, or spaghetti), vegetables, sauce, and pan-fried chicken. The mean (95% CI) meal GIs determined from individual food GI values and by direct measurement were as follows: potato meal [predicted, 63 (56, 70); measured, 53 (46, 62)], rice meal [predicted, 51 (45, 56); measured, 38 (33, 45)], and spaghetti meal [predicted, 54 (49, 60); measured, 38 (33, 44)]. The predicted meal GIs were all higher than the measured GIs (P < 0.001). The extent of the overestimation depended on the particular food, ie, 12, 15, and 19 GI units (or 22%, 40%, and 50%) for the potato, rice, and spaghetti meals, respectively. The formula overestimated the GI of the meals by between 22% and 50%. The use of published food values also overestimated the measured meal GIs. Investigators using the formula to calculate a meal or diet GI should be aware of limitations in the method. This trial is registered with the Australian and New Zealand Clinical Trials Registry as ACTRN12611000210976.

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

Phytate destruction by yeast fermentation in whole wheat meals. Study of high-extraction rate meals.

PubMed

Reinhold, J G

1975-01-01

Destruction of phytate by yeast fermentation is compared in sponges prepared from Iranian whole wheat meals of different extraction rates. Phytate was destroyed rapidly in whole meals of 75 to 85 and 85 to 90 per cent extraction, but destruction was retarded in those of 95 to 100 per cent extraction. Production of acid-soluble phosphorus kept pace with phytate destruction in the two whole meals of lower extraction rates but was delayed with less-than-expected yield in those of 95 to 100 per cent rate. Unleavened whole meal bread contains little acid-soluble phosphorus. Leavened breads made from whole meals of slightly lower extraction rate average five times as much. Since phytate phosphorus appears to remain unavailable in the small intestine in many circumstances, dependece on unleavened whole meal bread may result in critically low intakes of available phosphorus when other sources are lacking in the diet. It is concluded that replacement of the whole meals of 95 to 100 per cent extraction rate, presently the main staple of the diet of rural Iran, by those of somewhat lower rate is an important preliminary to the introduction of leaven and fermentation into village bread-making methods.

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 .

Variety within a cooked meal increases meal energy intake in older women with a poor appetite.

PubMed

Wijnhoven, Hanneke Ah; van der Meij, Barbara S; Visser, Marjolein

2015-12-01

Effective strategies to increase dietary intake in older persons with a poor appetite are needed. Previous studies have shown that increasing diet variety may increase dietary intake. This has not been tested in older adults with a poor appetite. We investigated if an increased variety of foods within a cooked meal results in a higher meal energy intake in older women with a poor appetite. This study was a randomized, controlled, cross-over trial among 19 older (>65 years) women with a poor appetite. Two cooked meals of similar weight and energy density (except starch) were served under standardized conditions on two weekdays: a test meal consisting of three different varieties of vegetables, meat or fish, and starch components, and a control meal without variety. Participants ate ad libitum and the actual consumed amounts and their nutritional content were calculated. Data were analyzed by mixed linear models. Average intake in energy was 427 kcal (SD 119) for the test meal with variety and 341 kcal (SD 115) for the control meal without variety. This resulted in a statistically significant (for period effects adjusted) mean difference of 79 kcal (95% CI = 25-134). Total meal intake in grams was also higher for the test meal with variety (48 g, 95% CI = 1-97) but protein intake (g) was not (3.7 g, 95% CI = -1.4 to 8.8). This was consistent for all meal components except starch and within each component three varieties were consumed equally. The results of the present study suggest that increasing meal variety may be an effective strategy to increase energy intake in older adults with a poor appetite. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Nutrient quality of fast food kids meals

USDA-ARS?s Scientific Manuscript database

Exposure of children to kids’ meals at fast food restaurants is high; however, the nutrient quality of such meals has not been systematically assessed. We assessed the nutrient quality of fast food meals marketed to young children, i.e., "kids meals". The nutrient quality of kids’ meals was assessed...

Adolescents' perceptions and experiences of family meals.

PubMed

Prior, Amie-Louise; Limbert, Caroline

2013-12-01

Benefits of family meals include diet quality, social interaction and wellbeing, yet previous research indicates only one in four adolescents eats a meal with their family every day. This study identified factors relating to the frequency and importance of family meals. A focus group conducted with seven adolescents was analysed thematically. The themes and findings of past research were used to develop a Family Meals Questionnaire (FMQ), completed by 76 adolescents. Regular engagement in healthy family meals eaten around the table was reported, with the majority of participants reporting that their meals included a variety of foods and portions of vegetables. Frequency of family meals was associated with increased family togetherness for both males and females. The nutritional value of meals was found to be most important to females, whereas the impact of family meals on mood was more salient for males. Findings suggest that the views and behaviour of other family members may influence adolescents' enjoyment and perceptions of the importance of family meals, and therefore impact on their frequency. These findings may inform the development of future interventions aimed at increasing adolescent engagement in family meals by adopting a family systems approach to improve the frequency and experience of family meals.

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

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.

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.

Effect of fat replacement by inulin or lupin-kernel fibre on sausage patty acceptability, post-meal perceptions of satiety and food intake in men.

PubMed

Archer, Bridie J; Johnson, Stuart K; Devereux, Helen M; Baxter, Amynta L

2004-04-01

The present study examined whether replacing fat with inulin or lupin-kernel fibre influenced palatability, perceptions of satiety, and food intake in thirty-three healthy men (mean age 52 years, BMI 27.4 kg/m(2)), using a within-subject design. On separate occasions, after fasting overnight, the participants consumed a breakfast consisting primarily of either a full-fat sausage patty (FFP) or a reduced-fat patty containing inulin (INP) or lupin-kernel fibre (LKP). Breakfast variants were alike in mass, protein and carbohydrate content; however the INP and LKP breakfasts were 36 and 37 % lower in fat and 15 and 17 % lower in energy density respectively compared with the FFP breakfast. The participants rated their satiety before breakfast then evaluated patty acceptability. Satiety was rated immediately after consuming the breakfast, then over the subsequent 4.5 h whilst fasting. Food consumed until the end of the following day was recorded. All patties were rated above 'neither acceptable or unacceptable', however the INP rated lower for general acceptability (P=0.039) and the LKP lower for flavour (P=0.023) than the FFP. The LKP breakfast rated more satiating than the INP (P=0.010) and FFP (P=0.016) breakfasts. Total fat intake was 18 g lower on the day of the INP (P=0.035) and 26 g lower on the day of the LKP breakfast (P=0.013) than the FFP breakfast day. Energy intake was lower (1521 kJ) only on the day of the INP breakfast (P=0.039). Both inulin and lupin-kernel fibre appear to have potential as fat replacers in meat products and for reducing fat and energy intake in men.

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.

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.

Meals Served in Public Schools.

ERIC Educational Resources Information Center

Vivigal, Lisa

The Physicians Committee for Responsible Medicine (PCRM) contacted public school districts around the United States to determine if they offered low-fat, healthful meals. The PCRM ranked the schools according to whether they served low-fat and vegetarian meals daily, whether these meals varied through the week, and whether children needed to…

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.

Teachers' interaction with children in the school meal situation: the example of pedagogic meals in Sweden.

PubMed

Persson Osowski, Christine; Göranzon, Helen; Fjellström, Christina

2013-01-01

School meals are also a teaching occasion in which children learn about food and meals, which is referred to as "pedagogic meals" in Sweden. The aim of the present article was to study how the pedagogic meal is practiced in preschool and school settings, with focus on how teachers acted when interacting with the children. Observations, interviews, and focus group interviews. School canteens. Three schools. Teaching in the school meal situation. Social constructionism, new social studies of childhood. The teachers took on 3 different roles. The sociable teacher role entailed turning the school lunch into a social occasion, the educating teacher role involved educating the children, and the evasive teacher role was not associated with the definition of a pedagogic meal. The teacher roles, which ranged from adult-oriented to child-oriented, and which varied in the level of interaction with the children, were summarized in a framework named the Adult- to Child-oriented Teacher Role Framework for School Meals (ACTS). To realize the potential of pedagogic meals, teachers must be educated and become aware of the effects of their behaviors. In this situation, the ACTS framework can constitute a useful tool. Copyright © 2013 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

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.

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.

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…

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.

9 CFR 95.14 - Blood meal, tankage, meat meal, and similar products, for use as fertilizer or animal feed...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Blood meal, tankage, meat meal, and..., tankage, meat meal, and similar products, for use as fertilizer or animal feed; requirements for entry. Dried blood or blood meal, lungs or other organs, tankage, meat meal, wool waste, wool manure, and...

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.

Factors Related to the Number of Fast Food Meals Obtained by College Meal Plan Students

ERIC Educational Resources Information Center

Dingman, Deirdre A.; Schulz, Mark R.; Wyrick, David L.; Bibeau, Daniel L.; Gupta, Sat N.

2014-01-01

Objectives: This study tested whether days on campus, financial access through a meal plan, and health consciousness were associated with number of meals that college students obtained from fast food restaurants. Participants and Methods: In April 2013, all students currently enrolled in a meal plan were invited to participate in an online survey…

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.

9 CFR 95.14 - Blood meal, tankage, meat meal, and similar products, for use as fertilizer or animal feed...

Code of Federal Regulations, 2012 CFR

2012-01-01

... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Blood meal, tankage, meat meal, and... BYPRODUCTS (EXCEPT CASINGS), AND HAY AND STRAW, OFFERED FOR ENTRY INTO THE UNITED STATES § 95.14 Blood meal.... Dried blood or blood meal, lungs or other organs, tankage, meat meal, wool waste, wool manure, and...

9 CFR 95.14 - Blood meal, tankage, meat meal, and similar products, for use as fertilizer or animal feed...

Code of Federal Regulations, 2013 CFR

2013-01-01

... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Blood meal, tankage, meat meal, and... BYPRODUCTS (EXCEPT CASINGS), AND HAY AND STRAW, OFFERED FOR ENTRY INTO THE UNITED STATES § 95.14 Blood meal.... Dried blood or blood meal, lungs or other organs, tankage, meat meal, wool waste, wool manure, and...

9 CFR 95.14 - Blood meal, tankage, meat meal, and similar products, for use as fertilizer or animal feed...

Code of Federal Regulations, 2011 CFR

2011-01-01

... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Blood meal, tankage, meat meal, and... BYPRODUCTS (EXCEPT CASINGS), AND HAY AND STRAW, OFFERED FOR ENTRY INTO THE UNITED STATES § 95.14 Blood meal.... Dried blood or blood meal, lungs or other organs, tankage, meat meal, wool waste, wool manure, and...

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.

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

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...

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

Impossible meals? The food and meal situation of flight attendants in Scandinavia - A qualitative interview study.

PubMed

Nyberg, Maria; Lennernäs Wiklund, Maria

2017-06-01

The working conditions of flight attendants (FAs) often involve extended and irregular working hours, short rest periods, difficulties in planning for breaks and high demands of service provision. Moreover, work schedules including early check-in, shifts during circadian low and time-zone transitions imply constant exposure to alterations in circadian systems and related health risks. The aim of this explorative study was to investigate how the organisation of work, time and place influence the food and meal situation of FAs when at work, focusing on patterns, form and social context of meals. The research questions posed were how food and meals at work were characterised and perceived among the FAs, and what strategies were adopted to manage the food and meal situation. Qualitative, semi-structured interviews were conducted with fourteen FAs working in Scandinavia. The results indicated that the organisation of work, time and place have a major influence on the meal situation at work, and how food and meals are perceived and managed by FAs. The work was defined as fragmented and inconsistent regarding time and place resulting in scattered meals and a more snack-based form of eating. The meal situation was characterised by irregularity as well as unpredictability. Eating took place when food was available and when there was enough time to eat, rather than being guided by hunger or social context. Various strategies such as eating in prevention, using emergency food, avoiding certain food and drinks or eating little or nothing at all were used to manage the unpredictability of the meal situation as well as the gap between organisational and individual times. The findings demonstrated the individual responsibility to solve the meal at work, e.g. to solve organisational times. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

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.

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

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

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.

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.

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...

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...

Mind over platter: pre-meal planning and the control of meal size in humans.

PubMed

Brunstrom, J M

2014-07-01

It is widely accepted that meal size is governed by psychological and physiological processes that generate fullness towards the end of a meal. However, observations of natural eating behaviour suggest that this preoccupation with within-meal events may be misplaced and that the role of immediate post-ingestive feedback (for example, gastric stretch) has been overstated. This review considers the proposition that the locus of control is more likely to be expressed in decisions about portion size, before a meal begins. Consistent with this idea, we have discovered that people are extremely adept at estimating the 'expected satiety' and 'expected satiation' of different foods. These expectations are learned over time and they are highly correlated with the number of calories that end up on our plate. Indeed, across a range of foods, the large variation in expected satiety/satiation may be a more important determinant of meal size than relatively subtle differences in palatability. Building on related advances, it would also appear that memory for portion size has an important role in generating satiety after a meal has been consumed. Together, these findings expose the importance of planning and episodic memory in the control of appetite and food intake in humans.

Effects of replacing soybean meal with canola meal or treated canola meal on ruminal digestion, fermentation pattern, omasal nutrient flow, and performance in lactating dairy cows

USDA-ARS?s Scientific Manuscript database

Extrusion-treated canola meal (TCM) was produced in an attempt to increase the rumen undegradable protein (RUP) fraction of canola meal (CM). The objective of this study was to evaluate the effects of replacing soybean meal (SBM) with CM or TCM on ruminal digestion, fermentation pattern, omasal nutr...

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.

Development of a Quality of Meals and Meal Service Set of Indicators for Residential Facilities for Elderly.

PubMed

Van Damme, N; Buijck, B; Van Hecke, A; Verhaeghe, S; Goossens, E; Beeckman, D

2016-01-01

To develop a content validated set of indicators to evaluate the quality of meals and meal service in residential facilities for elderly. Inadequate food intake is an important risk factor for malnutrition in residential facilities for elderly. Through better meeting the needs and preferences of residents and optimization of meals and meal service, residents' food intake can improve. No indicators were available which could help to guide strategies to improve the quality of meals and meal service. The indicator set was developed according to the Indicator Development Manual of the Dutch Institute for Health Care Improvement (CBO). The working group consisted of three nurse researchers and one expert in gastrology and had expertise in elderly care, malnutrition, indicator development, and food quality. A preliminary list of potential indicators was compiled using the literature and the working group's expertise. Criteria necessary to measure the indicator in practice were developed for each potential indicator. In a double Delphi procedure, the list of potential indicators and respective criteria were analyzed for content validity, using a multidisciplinary expert panel of 11 experts in elderly meal care. A preliminary list of 20 quality indicators, including 45 criteria, was submitted to the expert panel in a double Delphi procedure. After the second Delphi round, 13 indicators and 25 criteria were accepted as having content validity. The content validity index (CVI) ranged from 0.83 to 1. The indicator set consisted of six structural, four result, and three outcome indicators covering the quality domains food, service and choice, as well as nutritional screening. The criteria measure diverse aspects of meal care which are part of the responsibility of kitchen staff and health care professionals. The 'quality of meals and meal service' set of indicators is a resource to map meal quality in residential facilities for elderly. As soon as feasibility tests in practice

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

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

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.

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.

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.

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.

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.

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

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

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.

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.

Evaluation of Nigerian hospital meal carts

NASA Astrophysics Data System (ADS)

Ayodeji, Sesan P.; Adeyeri, Michael K.; Omoniyi, Olaoluwa

2015-09-01

Hospital meal carts are used to deliver meals, drugs and some other materials to patients in the hospital environment. These carts which are moved manually by operators, the health workers, mostly do not comply with ergonomics guidelines and physical requirements of the equipment users in terms of anthropometry data of the region thus increasing the risk of musculoskeletal disorder among the meal cart users. This study carried out ergonomic evaluation of the available meal carts in some western Nigeria hospitals. A well-structured questionnaire has two major segments: Operational survey and biomechanical survey, which were administered to the health workers using hospital meal carts in some hospitals in southwestern Nigeria, and physical assessment, which was undertaken to collect data for the ergonomic evaluation. The responses from the questionnaires show that some areas on the existing hospital meal carts are of concern to the users which need to be improved upon.

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

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.

Influence of Paclobutrazol (PP333) and Sridiamin (Human hair-derived aminoacid mixture) on growth and quality of Tomato PKM-1

NASA Astrophysics Data System (ADS)

Suja, S.; Anusuya, N.

2018-03-01

Tomato is one of the most popular vegetable in subtropics and tropics. Plant growth regulators have potential for manipulating growth of many agricultural crops. Among the plant growth retardants, paclobutrazol (PP333) has been reported to exert profound effects on improving the yield of certain vegetables. Aminoacids are essential prerequisite for plant growth. Sridiamin a natural blend of 17 essential L-aminoacids, fortified with vitamins ensuring better crop growth and higher productivity. Therefore the present study was designed with 5mg and 10 mg concentration of PP333 as soil drench and a foliar spray of sridiamin of 0.5% and 1% concentration as individual and as combined treatment improved the yield and quality of tomato PKM1. Various biometric parameters, along with chlorophyll, starch, aminoacid and protein content were analysed in the leaves. In fruit analysis like titrable acidity, total soluble solids, ascorbic acid, lycopene, total sugars, macronutrients and micronutrients were analysed.

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

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.

Improving meal context in nursing homes. Impact of four strategies on food intake and meal pleasure.

PubMed

Divert, Camille; Laghmaoui, Rachid; Crema, Célia; Issanchou, Sylvie; Wymelbeke, Virginie Van; Sulmont-Rossé, Claire

2015-01-01

In France, in most nursing homes, the composition of menus, the time and the place at which meals are served, the choice of one's place at the table are imposed on residents. Yet, the act of eating cannot be restricted to nutritional and sensory aspects alone. It also includes a psycho-affective dimension, which relates to the context in which the meal is served. We tested the impact of four contextual factors, considered individually, on food intake and meal pleasure in elderly people living in nursing homes: the way the main course was named on the menu, the size and the variety of portions of vegetables served to residents, the presence or not of condiments in the middle of the table and the presence or not of elements to modify the surroundings such as a decorative object on the table or background music. Twelve experimental meals were served to 42 nursing home residents. For each factor, we compared a control condition with two experimental conditions. Our study showed that changing a single contextual element of the meal in nursing homes could be sufficient to improve residents' satisfaction with their meals and increase the quantities of meat or vegetables consumed, as long as this factor had a direct impact on what was going to be consumed (increased variety on the plate, condiments on the table). Factors affecting the context of the meal (names of dishes, decor) proved to be ineffective. Given the budgetary constraints faced by nursing homes, this study proposes interesting and inexpensive ideas to increase satisfaction with meals and food intake in elderly people who are dependent on others for their meals. Copyright © 2014 Elsevier Ltd. All rights reserved.

Shelf stable meals for public sector uses

NASA Technical Reports Server (NTRS)

Schmandt, J. (Editor)

1977-01-01

The NASA Meal System was developed with three simple concepts in mind: (1) nutritious, conventional foods are packaged in single-serving units and assembled into complete meals; (2) the meals have an extended shelf-life and can be transported and stored without need for refrigeration or freezing; (3) preparation of the meal by the consumer is an easy task which is accomplished in ten minutes or less. The meal system was tested in 1975 and 1976 by different groups of elderly individuals. NASA and the LBJ School of Public Affairs sponsored a national conference to report on the demonstration of the meal system for the elderly and to explore potential uses of the system for social services, institutional feeding programs, disaster relief, and international aid. The proceedings of the conference and how different groups assessed the potential of the meal system are reported.

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...

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.

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

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.

Dietary soya saponins increase gut permeability and play a key role in the onset of soyabean-induced enteritis in Atlantic salmon ( Salmo salar L.).

PubMed

Knudsen, David; Jutfelt, Fredrik; Sundh, Henrik; Sundell, Kristina; Koppe, Wolfgang; Frøkiaer, Hanne

2008-07-01

Saponins are naturally occurring amphiphilic molecules and have been associated with many biological activities. The aim of the present study was to investigate whether soya saponins trigger the onset of soyabean-induced enteritis in Atlantic salmon (Salmo salar L.), and to examine if dietary soya saponins increase the epithelial permeability of the distal intestine in Atlantic salmon. Seven experimental diets containing different levels of soya saponins were fed to seawater-adapted Atlantic salmon for 53 d. The diets included a fishmeal-based control diet, two fishmeal-based diets with different levels of added soya saponins, one diet containing 25% lupin kernel meal, two diets based on 25% lupin kernel meal with different levels of added soya saponins, and one diet containing 25% defatted soyabean meal. The effect on intestinal morphology, intestinal epithelial permeability and faecal DM content was examined. Fish fed 25% defatted soyabean meal displayed severe enteritis, whereas fish fed 25% lupin kernel meal had normal intestinal morphology. The combination of soya saponins and fishmeal did not induce morphological changes but fish fed soya saponins in combination with lupin kernel meal displayed significant enteritis. Increased epithelial permeability was observed in fish fed 25% defatted soyabean meal and in fish fed soya saponin concentrate independent of the protein source in the feed. The study demonstrates that soya saponins, in combination with one or several unidentified components present in legumes, induce an inflammatory reaction in the distal intestine of Atlantic salmon. Soya saponins increase the intestinal epithelial permeability but do not, per se, induce enteritis.

Meal pattern among Norwegian primary-school children and longitudinal associations between meal skipping and weight status.

PubMed

Stea, Tonje H; Vik, Frøydis N; Bere, Elling; Svendsen, Martin V; Oellingrath, Inger M

2015-02-01

To investigate meal pattern longitudinally and explore whether meal skipping was associated with overweight among Norwegian children and adolescents. Longitudinal study. Children's meal frequencies were reported by their parents using a retrospective FFQ. Weight and height were measured by public health nurses. Descriptive data comparing 4th and 7th grade were analysed by paired-sample t tests for continuous variables and χ 2 tests for categorical variables. Odds ratio estimates, including confidence intervals, with BMI category (normal/overweight) as the dependent variable, were determined through logistic regression analyses. Primary schools, Telemark County, Norway. A cohort of 428 Norwegian boys and girls; 4th graders in 2007, 7th graders in 2010. The number of children eating four main meals per day (regular meal frequency) decreased from 4th grade (47 %) to 7th grade (38 %; P = 0·001). Those who ate regular meals in 4th grade but not in 7th grade had higher odds (OR = 3·1; 95 % CI 1·1, 9·0) of being overweight in 7th grade after adjusting for gender, maternal education and physical activity, but the odds ratio was not statistically significant after adjusting for overweight in 4th grade (OR = 2·8; 95 % CI 0·7, 11·6). The present study showed significant increases in overall meal skipping among children between 4th and 7th grade. The results indicate an association between overweight and meal skipping, but additional prospective and longitudinal analyses and intervention trials are warranted to confirm this relationship.

Effect of meal environment on diet quality rating.

PubMed

Woodruff, Sarah J; Hanning, Rhona M

2009-01-01

Family meals have been associated with improved dietary quality in children and adolescents, and yet very little is known about family meals beyond their frequency. Specific aspects of the breakfast, lunch, and dinner meal environments were described and compared, and the associations with overall diet quality were investigated. Data on food intake and meal environments were obtained in northern Ontario, southern Ontario, and Nova Scotia grades six, seven, and eight classrooms over the 2005 to 2006 school year. Specific aspects of the meal environments described were where the meal was consumed, with whom participants consumed each meal, who prepared the meal, and where the food was originally purchased. Diet quality was assessed using the Canadian version of the Healthy Eating Index. Cluster K-means procedures were used to classify into groups observations about the four meal environment variables. Three, eight, and six clusters of meal environments were identified for breakfast, lunch, and dinner, respectively. Diet quality was negatively associated with consuming/ purchasing meals outside the home, and with skipping breakfast, lunch, and/or dinner. Results have immediate relevance for family-based and/or school programs and policies aimed at educating and feeding children and adolescents.

21 CFR 137.275 - Yellow corn meal.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 2 2011-04-01 2011-04-01 false Yellow corn meal. 137.275 Section 137.275 Food and... Related Products § 137.275 Yellow corn meal. Yellow corn meal conforms to the definition and standard of identity prescribed by § 137.250 for white corn meal except that cleaned yellow corn is used instead of...

21 CFR 137.275 - Yellow corn meal.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Yellow corn meal. 137.275 Section 137.275 Food and... Related Products § 137.275 Yellow corn meal. Yellow corn meal conforms to the definition and standard of identity prescribed by § 137.250 for white corn meal except that cleaned yellow corn is used instead of...

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.

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.

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

The associations of meals and snacks on family meals among a sample of grade 7 students from Southwestern Ontario.

PubMed

Woodruff, Sarah J; Campbell, Katherine; Campbell, Ty; Cole, Mary

2014-11-01

Research has shown the positive associations of family meals and diet quality. However, little is known about how other meals/snacks may be associated with family meals. The purpose was to determine the associations among the frequency and calorie consumption of meals/snacks and family dinners. Cross-sectional. Data were collected using Web-based Eating Behaviour Questionnaire (WEB-Q), including a 24-h diet recall for breakfast, morning snack, lunch, afternoon snack, dinner, and evening snack. Measured height and weight were used to determine body weight status (BMI). Participants included 1068 grade 7 students (52% males) from 26 schools in Windsor Essex County, Ontario, Canada. Meal, snack, and total daily caloric intake; meal and snack frequency; with whom dinner was consumed, and weekly family dinner frequency. Exploratory one-way ANOVAs and chi-square tests; nominal and ordinal logistic regression. Ninety-three percent of participants consumed dinner with family members on the night prior to the survey and 77% reported usually consuming dinner/supper with at least one parent on six to seven nights/week. Those who had dinner with family members consumed 4.88 (SD 1.1) meals/snacks per day compared with 4.40 (SD 1.3) and 4.40 (SD 1.3) times/day for consuming dinner alone or with friends, respectively (p=0.006). On the day prior to the survey, participants were less likely to consume a family meal if they consumed a lower number of meals and snacks per day (OR=0.69 (95% CI: 0.55, 0.87), p<0.001). Similarly, participants were less likely to consume regular family meals if they consumed a lower number of meals and snacks per day (OR=0.84 (95% CI: 0.74, 0.96), p=0.009). While specific meals and snacks were not associated with family dinner, overall eating frequency was positively associated with family meals. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

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

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.

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 ...

Does children's energy intake at one meal influence their intake at subsequent meals? Or do we just think it does?

PubMed

Hanley, James A; Hutcheon, Jennifer A

2010-05-01

It is widely believed that young children are able to adjust their energy intake across successive meals to compensate for higher or lower intakes at a given meal. This conclusion is based on past observations that although children's intake at individual meals is highly variable, total daily intakes are relatively constant. We investigated how much of this reduction in variability could be explained by the statistical phenomenon of the variability of individual components (each meal) always being relatively larger than the variability of their sum (total daily intake), independent of any physiological compensatory mechanism. We calculated, theoretically and by simulation, how variable a child's daily intake would be if there was no correlation between intakes at individual meals. We simulated groups of children with meal/snack intakes and variability in meal/snack intakes based on previously published values. Most importantly, we assumed that there was no correlation between intakes on successive meals. In both approaches, the coefficient of variation of the daily intakes was roughly 15%, considerably less than the 34% for individual meals. Thus, most of the reduction in variability found in past studies was explained without positing strong 'compensation'. Although children's daily energy intakes are indeed considerably less variable than their individual components, this phenomenon was observed even when intakes at each meal were simulated to be totally independent. We conclude that the commonly held belief that young children have a strong physiological compensatory mechanism to adjust intake at one meal based on intake at prior meals is likely to be based on flawed statistical reasoning.

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…

21 CFR 137.250 - White corn meal.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 2 2010-04-01 2010-04-01 false White corn meal. 137.250 Section 137.250 Food and... Related Products § 137.250 White corn meal. (a) White corn meal is the food prepared by so grinding... fiber content of the finished corn meal is not less than 1.2 percent and not more than that of the...

21 CFR 137.250 - White corn meal.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 2 2011-04-01 2011-04-01 false White corn meal. 137.250 Section 137.250 Food and... Related Products § 137.250 White corn meal. (a) White corn meal is the food prepared by so grinding... fiber content of the finished corn meal is not less than 1.2 percent and not more than that of the...

Effect of Pseudocereal-Based Breakfast Meals on the First and Second Meal Glucose Tolerance in Healthy and Diabetic Subjects

PubMed Central

Gabrial, Shreef G. N.; Shakib, Marie-Christine R.; Gabrial, Gamal N.

2016-01-01

BACKGROUND: Many studies have indicated that the incidence of serious diabetic complications may be reduced through strict glycemic control. A low glycemic index diet is one tool to improve insulin resistance and improve glycemic control in type 2 diabetes mellitus (T2DM). AIM: The objective was to study the effect of pseudocereals-based breakfasts (quinoa and buckwheat) on glucose variations at first meal (breakfast) and second meal (standardised lunch) in healthy and diabetic subjects. SUBJECTS AND METHODS: Twelve healthy subjects and 12 patients with Type 2 DM (not- insulin dependent) were recruited in the study. Subjects were provided with quinoa and buckwheat breakfast meals. A standardised lunch was provided 4 h after breakfast. Postprandial blood glucose response after breakfast and the second meal effect was measured in healthy and diabetic subjects. Incremental area under the curve (IAUC) values for glucose was measured in response to the breakfast and lunch. The glycemic index of the 2 pseudocereals-based test breakfasts was determined. A white wheat bread (WWB) was served as a reference breakfast meal. RESULTS: In post-breakfast analyses, healthy subjects showed that buckwheat meal had significantly lower IAUC values for blood glucose compared to WWB reference meal (P < 0.001) while quinoa meal showed no significance. In diabetic subjects, buckwheat and quinoa meals had significantly lower IAUC values for blood glucose compared to WWB reference meal (P < 0.001 and P < 0.05 respectively). Blood glucose concentrations started to decline gradually for the quinoa and buckwheat but not for WWB in all healthy and diabetic subjects and returned to near-fasting baseline levels by 210 min. Post-lunch analyses indicated higher IAUC for the two breakfast types in healthy and diabetic subjects. In addition, the quinoa and buckwheat breakfast meals were followed by a significantly flatter blood glucose response to the second meal for the period between 270 and 330

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.

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.

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.

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...

Composition and Use of Common Carp Meal as a Marine Fish Meal Replacement in Yellow Perch Diets

USDA-ARS?s Scientific Manuscript database

We evaluated the use of fish meal derived from a locally abundant, non-native fish species – common carp Cyprinus carpio – with the objective of offsetting the cost of marine fish meal (MFM, ~$1,200/ton) in yellow perch Perca flavescens feed. Biochemical analyses of meals showed that crude protein a...

Family meals and body weight in US adults.

PubMed

Sobal, Jeffery; Hanson, Karla

2011-09-01

Family meals are an important ritual in contemporary societies and many studies have reported associations of family meals with several biopsychosocial outcomes among children and adolescents. However, few representative analyses of family meals have been conducted in samples of adults, and adults may differ from young people in predictors and outcomes of family meal consumption. We examined the prevalence and predictors of adult family meals and body weight outcomes. The cross-sectional 2009 Cornell National Social Survey (CNSS) included questions about the frequency of family meals, body weight as BMI and sociodemographic characteristics. The CNSS telephone survey used random digit dialling to sample individuals. We analysed data from 882 adults living with family members in a nationally representative US sample. Prevalence of family meals among these adults revealed that 53 % reported eating family meals seven or more times per week. Predictive results revealed that adults who more frequently ate family meals were more likely to be married and less likely to be employed full-time, year-round. Outcome results revealed that the overall frequency of family meals among adults was not significantly associated with any measure of body weight. However, interaction term analysis suggested an inverse association between frequency of family meals and BMI for adults with children in the household, and no association among adults without children. These findings suggest that family meals among adults are commonplace, associated with marital and work roles, and marginally associated with body weight only in households with children.

Transmission blocking effects of neem (Azadirachta indica) seed kernel limonoids on Plasmodium berghei early sporogonic development.

PubMed

Tapanelli, Sofia; Chianese, Giuseppina; Lucantoni, Leonardo; Yerbanga, Rakiswendé Serge; Habluetzel, Annette; Taglialatela-Scafati, Orazio

2016-10-01

Azadirachta indica, known as neem tree and traditionally called "nature's drug store" makes part of several African pharmacopeias and is widely used for the preparation of homemade remedies and commercial preparations against various illnesses, including malaria. Employing a bio-guided fractionation approach, molecules obtained from A. indica ripe and green fruit kernels were tested for activity against early sporogonic stages of Plasmodium berghei, the parasite stages that develop in the mosquito mid gut after an infective blood meal. The limonoid deacetylnimbin (3) was identified as one the most active compounds of the extract, with a considerably higher activity compared to that of the close analogue nimbin (2). Pure deacetylnimbin (3) appeared to interfere with transmissible Plasmodium stages at a similar potency as azadirachtin A. Considering its higher thermal and chemical stability, deacetylnimbin could represent a suitable alternative to azadirachtin A for the preparation of transmission blocking antimalarials. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

[Can family meals protect adolescents from obesity?].

PubMed

Tabak, Izabela; Jodkowska, Maria; Oblacińska, Anna; Mikiel-Kostyra, Krystyna

2012-01-01

To analyse the relationship between the frequency of family meals and the body weight of 13-year-olds and its selected determinants. The study was conducted in 2008 as the last stage in a prospective cohort study of 605 children. Questionnaires containing questions about the frequency of family meals, the general regularity of meals, fruit and vegetable consumption, physical activity and the number of hours spent watching television or at the computer were sent to 13-year-olds by mail. School nurses performed anthropometric measurements of the pupils' weight and height. Statistical analyses were performed, i.e. Pearson's correlations, the two-step cluster analysis and the logistic regression analysis. Most of the young people (80-90%) eat each of the main meals in the company of their parents at least once a week, 21% have breakfast with their parents every day, 41% - dinner, and 45% - supper. The frequency of family meals correlated negatively with the girls' BMI and the number of hours they spent watching television or at the computer, while positively with physical activity, regular meals and vegetable consumption in adolescents of both genders. The lowest mean values of BMI were found in a group of adolescents often eating family meals, the highest - in the group of young people who rarely ate family meals (over 20% of young people in this group were overweight), but the differences were statistically significant only for girls (p=0.025). The probability of less than 2 hours of sedentary behaviour daily, physical activity of at least 60 minutes per day and everyday vegetable and fruit consumption is twice as high in adolescents often consuming meals with their parents, and with the daily consumption of all the meals in this way - more than fourfold higher than in other groups. Family meals treated as a predictor of a healthy lifestyle can indirectly protect adolescents from overweight and obesity. Promoting family meals should be an important method of

29 CFR 553.223 - Meal time.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false Meal time. 553.223 Section 553.223 Labor Regulations... Enforcement Employees of Public Agencies Tour of Duty and Compensable Hours of Work Rules § 553.223 Meal time... personnel in accordance with section 7(a)(1) of the Act, the public agency may exclude meal time from hours...

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.

41 CFR 301-11.17 - If my agency authorizes per diem reimbursement, will it reduce my M&IE allowance for a meal(s...

Code of Federal Regulations, 2010 CFR

2010-07-01

... for a complimentary meal(s) provided by a hotel/motel? 301-11.17 Section 301-11.17 Public Contracts... complimentary meal(s) provided by a hotel/motel? No. A meal provided by a common carrier or a complimentary meal provided by a hotel/motel does not affect your per diem. ...

41 CFR 301-11.17 - If my agency authorizes per diem reimbursement, will it reduce my M&IE allowance for a meal(s...

Code of Federal Regulations, 2011 CFR

2011-07-01

... for a complimentary meal(s) provided by a hotel/motel? 301-11.17 Section 301-11.17 Public Contracts... complimentary meal(s) provided by a hotel/motel? No. A meal provided by a common carrier or a complimentary meal provided by a hotel/motel does not affect your per diem. ...

Effects of meal size, meal type, and body temperature on the specific dynamic action of anurans.

PubMed

Secor, Stephen M; Wooten, Jessica A; Cox, Christian L

2007-02-01

Specific dynamic action (SDA), the increase in metabolism stemming from meal digestion and assimilation, varies as a function of meal size, meal type, and body temperature. To test predictions of these three determinants of SDA, we quantified and compared the SDA responses of nine species of anurans, Bombina orientalis, Bufo cognatus, Ceratophrys ornata, Dyscophus antongilli, Hyla cinerea, Kassina maculata, Kassina senegalensis, Pyxicephalus adspersus, and Rana catesbeiana subjected to meal size, meal type, and body temperature treatments. Over a three to seven-fold increase in meal size, anurans experienced predicted increases in postprandial rates of oxygen consumption (VO(2)) the duration of elevated VO(2) and SDA. Meal type had a significant influence on the SDA response, as the digestion and assimilation of hard-bodied, chitinous crickets, mealworms, and superworms required 76% more energy than the digestion and assimilation of soft-bodied earthworms, waxworms, and neonate rodents. Body temperature largely effected the shape of the postprandial metabolic profile; peak VO(2) increased and the duration of the response decreased with an increase in body temperature. Variation in body temperature did not significantly alter SDA for four species, whereas both H. cinerea and R. catesbeiana experienced significant increases in SDA with body temperature. For 13 or 15 species of anurans ranging in mass from 2.4 to 270 g, SMR, postprandial peak VO(2) and SDA scaled with body mass (log-log) with mass exponents of 0.79, 0.93, and 1.05, respectively.

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.

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.

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

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.

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.

Eating in the absence of hunger in adolescents: intake after a large-array meal compared with that after a standardized meal.

PubMed

Shomaker, Lauren B; Tanofsky-Kraff, Marian; Zocca, Jaclyn M; Courville, Amber; Kozlosky, Merel; Columbo, Kelli M; Wolkoff, Laura E; Brady, Sheila M; Crocker, Melissa K; Ali, Asem H; Yanovski, Susan Z; Yanovski, Jack A

2010-10-01

Eating in the absence of hunger (EAH) is typically assessed by measuring youths' intake of palatable snack foods after a standard meal designed to reduce hunger. Because energy intake required to reach satiety varies among individuals, a standard meal may not ensure the absence of hunger among participants of all weight strata. The objective of this study was to compare adolescents' EAH observed after access to a very large food array with EAH observed after a standardized meal. Seventy-eight adolescents participated in a randomized crossover study during which EAH was measured as intake of palatable snacks after ad libitum access to a very large array of lunch-type foods (>10,000 kcal) and after a lunch meal standardized to provide 50% of the daily estimated energy requirements. The adolescents consumed more energy and reported less hunger after the large-array meal than after the standardized meal (P values < 0.001). They consumed ≈70 kcal less EAH after the large-array meal than after the standardized meal (295 ± 18 compared with 365 ± 20 kcal; P < 0.001), but EAH intakes after the large-array meal and after the standardized meal were positively correlated (P values < 0.001). The body mass index z score and overweight were positively associated with EAH in both paradigms after age, sex, race, pubertal stage, and meal intake were controlled for (P values ≤ 0.05). EAH is observable and positively related to body weight regardless of whether youth eat in the absence of hunger from a very large-array meal or from a standardized meal. This trial was registered at clinicaltrials.gov as NCT00631644.

29 CFR 553.223 - Meal time.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 3 2011-07-01 2011-07-01 false Meal time. 553.223 Section 553.223 Labor Regulations... Enforcement Employees of Public Agencies Tour of Duty and Compensable Hours of Work Rules § 553.223 Meal time... exclude meal time from hours worked if all the tests in § 785.19 of this title are met. (b) If a public...

29 CFR 553.223 - Meal time.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 3 2014-07-01 2014-07-01 false Meal time. 553.223 Section 553.223 Labor Regulations... Enforcement Employees of Public Agencies Tour of Duty and Compensable Hours of Work Rules § 553.223 Meal time... exclude meal time from hours worked if all the tests in § 785.19 of this title are met. (b) If a public...

29 CFR 553.223 - Meal time.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 3 2012-07-01 2012-07-01 false Meal time. 553.223 Section 553.223 Labor Regulations... Enforcement Employees of Public Agencies Tour of Duty and Compensable Hours of Work Rules § 553.223 Meal time... exclude meal time from hours worked if all the tests in § 785.19 of this title are met. (b) If a public...

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

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.

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.

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

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…

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

Effects of replacing soybean meal with canola meal or treated canola meal on nitrogen metabolism and total tract digestibility in lactating dairy cows

USDA-ARS?s Scientific Manuscript database

Dietary canola meal (CM) has been shown to improve N efficiency in dairy cows when compared with soybean meal (SBM). Treating CM may increase amino acid (AA) supply from the rumen undegradable protein fraction and improve absorbable AA in the metabolizable protein. The objective of this study was to...

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.

A generic coding approach for the examination of meal patterns.

PubMed

Woolhead, Clara; Gibney, Michael J; Walsh, Marianne C; Brennan, Lorraine; Gibney, Eileen R

2015-08-01

Meal pattern analysis can be complex because of the large variability in meal consumption. The use of aggregated, generic meal data may address some of these issues. The objective was to develop a meal coding system and use it to explore meal patterns. Dietary data were used from the National Adult Nutrition Survey (2008-2010), which collected 4-d food diary information from 1500 healthy adults. Self-recorded meal types were listed for each food item. Common food group combinations were identified to generate a number of generic meals for each meal type: breakfast, light meals, main meals, snacks, and beverages. Mean nutritional compositions of the generic meals were determined and substituted into the data set to produce a generic meal data set. Statistical comparisons were performed against the original National Adult Nutrition Survey data. Principal component analysis was carried out by using these generic meals to identify meal patterns. A total of 21,948 individual meals were reduced to 63 generic meals. Good agreement was seen for nutritional comparisons (original compared with generic data sets mean ± SD), such as fat (75.7 ± 29.4 and 71.7 ± 12.9 g, respectively, P = 0.243) and protein (83.3 ± 26.9 and 80.1 ± 13.4 g, respectively, P = 0.525). Similarly, Bland-Altman plots demonstrated good agreement (<5% outside limits of agreement) for many nutrients, including protein, saturated fat, and polyunsaturated fat. Twelve meal types were identified from the principal component analysis ranging in meal-type inclusion/exclusion, varying in energy-dense meals, and differing in the constituents of the meals. A novel meal coding system was developed; dietary intake data were recoded by using generic meal consumption data. Analysis revealed that the generic meal coding system may be appropriate when examining nutrient intakes in the population. Furthermore, such a coding system was shown to be suitable for use in determining meal-based dietary patterns. © 2015

Meals based on vegetable protein sources (beans and peas) are more satiating than meals based on animal protein sources (veal and pork) - a randomized cross-over meal test study.

PubMed

Kristensen, Marlene D; Bendsen, Nathalie T; Christensen, Sheena M; Astrup, Arne; Raben, Anne

2016-01-01

Recent nutrition recommendations advocate a reduction in protein from animal sources (pork, beef) because of environmental concerns. Instead, protein from vegetable sources (beans, peas) should be increased. However, little is known about the effect of these vegetable protein sources on appetite regulation. To examine whether meals based on vegetable protein sources (beans/peas) are comparable to meals based on animal protein sources (veal/pork) regarding meal-induced appetite sensations. In total, 43 healthy, normal-weight, young men completed this randomized, double-blind, placebo-controlled, three-way, cross-over meal test. The meals (all 3.5 MJ, 28 energy-% (E%) fat) were either high protein based on veal and pork meat, HP-Meat (19 E% protein, 53 E% carbohydrate, 6 g fiber/100 g); high protein based on legumes (beans and peas), HP-Legume (19 E% protein, 53 E% carbohydrate, 25 g fiber/100 g); or low-protein based on legumes, LP-Legume (9 E% protein, 62 E% carbohydrate, 10 g fiber/100 g). Subjective appetite sensations were recorded at baseline and every half hour using visual analog scales until the ad libitum meal 3 h after the test meal. Repeated measurements analyses and summary analyses were performed using ANCOVA (SAS). HP-Legume induced lower composite appetite score, hunger, prospective food consumption, and higher fullness compared to HP-Meat and LP-Legume ( p <0.05). Furthermore, satiety was higher after HP-Legume than HP-Meat ( p <0.05). When adjusting for palatability, HP-Legume still resulted in lower composite appetite scores, hunger, prospective consumption, and higher fullness compared to HP-Meat ( p <0.05). Furthermore, HP-Legume induced higher fullness than LP-Legume ( p <0.05). A 12% and 13% lower energy intake, respectively, was seen after HP-Legume compared to HP-Meat or LP-Legume ( p <0.01). Vegetable-based meals (beans/peas) influenced appetite sensations favorably compared to animal-based meals (pork/veal) with similar energy and protein

Shared meals among young adults are associated with better diet quality and predicted by family meal patterns during adolescence.

PubMed

Larson, Nicole; Fulkerson, Jayne; Story, Mary; Neumark-Sztainer, Dianne

2013-05-01

To describe shared meal patterns and examine associations with dietary intake among young adults. Population-based, longitudinal cohort study (Project EAT: Eating and Activity in Teens and Young Adults). Participants completed surveys and FFQ in high-school classrooms in Minneapolis/St. Paul, MN, USA in 1998-1999 (mean age = 15·0 years, 'adolescence') and follow-up measures online or by mail in 2008-2009 (mean age = 25·3 years, 'young adulthood'). There were 2052 participants who responded to the 10-year follow-up survey and reported on frequency of having shared meals. Among young adults, the frequency of shared meals during the past week was as follows: never (9·9 %), one or two times (24·7 %), three to six times (39·1 %) and seven or more times (26·3 %). Having more frequent family meals during adolescence predicted a higher frequency of shared meals in young adulthood above and beyond other relevant sociodemographic factors such as household composition and parental status. Compared with young adults who never had family meals during adolescence, those young adults who reported seven or more family meals per week during adolescence had an average of one additional shared meal per week. Having more frequent shared meals in young adulthood was associated with greater intake of fruit among males and females, and with higher intakes of vegetables, milk products and some key nutrients among females. Nutrition professionals should encourage families of adolescents to share meals often and establish the tradition of eating together, and work with young adults to ensure that healthy food and beverage choices are offered at mealtimes.

Shared meals among young adults are associated with better diet quality and predicted by family meal patterns during adolescence

PubMed Central

Fulkerson, Jayne; Story, Mary; Neumark-Sztainer, Dianne

2012-01-01

Objective To describe shared meal patterns and examine associations with dietary intake among young adults. Design Population-based, longitudinal cohort study (Project EAT: Eating and Activity in Teens and Young Adults). Setting Participants completed surveys and food frequency questionnaires in Minneapolis/St. Paul, Minnesota high school classrooms in 1998–1999 (mean age=15.0, “adolescence”) and follow-up measures online or by mail in 2008–2009 (mean age=25.3, “young adulthood”). Subjects There were 2,052 participants who responded to the 10-year follow-up survey and reported on frequency of having shared meals. Results Among young adults, the frequency of shared meals during the past week was as follows: never (9.9%), one or two times (24.7%), three to six times (39.1%), and seven or more times (26.3%). Having more frequent family meals during adolescence predicted a higher frequency of shared meals in young adulthood above and beyond other relevant sociodemographic factors such as household composition and parental status. Compared to young adults who never had family meals during adolescence, those young adults who reported seven or more family meals per week during adolescence had an average of one additional shared meal per week. Having more frequent shared meals in young adulthood was associated with greater intake of fruit among males and females, and with higher intakes of vegetables, milk products, and some key nutrients among females. Conclusions Nutrition professionals should encourage families of adolescents to share meals often and establish the tradition of eating together, and work with young adults to ensure that healthy food and beverage choices are offered at mealtimes. PMID:22857517

Effects of replacing soybean meal with canola meal or treated canola meal on ruminal digestion, and omasal nutrient flow in lactating dairy cows

USDA-ARS?s Scientific Manuscript database

Treated canola meal (TCM) was produced as an attempt to increase the rumen undegradable protein (RUP) fraction of canola meal (CM) with the goal of enhancing amino acid (AA) availability for absorption in the small intestine of dairy cows. The objective of this study was to measure nutrient and micr...

Nutritional assessment of a jackfruit (Artocarpus heterophyllus) meal.

PubMed

Hettiaratchi, U P K; Ekanayake, S; Welihinda, J

2011-06-01

The mature jackfruit (Artocarpus heterophyllus) is consumed in Sri Lanka either as a main meal or a meal accompaniment. However, there is no scientific data on the nutrient compositions of cooked jackfruit meals. Thus, the objective of the study was to carry out a nutritional assessment of a composite jackfruit breakfast meal comprising seeds and flesh. A jackfruit meal comprising of flesh (80% available carbohydrate) and seeds (20% available carbohydrate) was included in the study. The study was carried out in a random cross over design. Setting University of Sri Jayewardenepura. Study participants Healthy individuals (n=10, age: 20-30 yrs). The macronutrient contents, rapidly and slowly available glucose (SAG) contents, water solubility index of the jackfruit meal were determined according to standard methods. The GI of the meal was calculated according to FAO/WHO guidelines. The moisture content of the boiled jackfruit flesh was high (82% FW). Jack seeds contained 4.7% protein (FW), 11.1% total dietary fibre (FW) and 8% resistant starch (FW). Jackfruit meal elicited a GI of 75. The Glycaemic Load (GL) of the normal serving size of the meal is medium. The slowly available glucose (SAG) percentage of jackfruit meal (30%) was twice that of the standard. The boiled jackfruit flesh contained disintegrated starch granules while seeds contained intact swollen and disintegrated granules. The jackfruit seeds are a good source of starch (22%) and dietary fibre. The meal is categorized as a low GI meal. The low GI could be dueto the collective contributions from dietary fibre, slowly available glucose and un-gelatinised (intact) starch granules in the seeds.

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

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.

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...

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.

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.

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.

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.

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.

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.

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.

Palatable Meal Anticipation in Mice

PubMed Central

Hsu, Cynthia T.; Patton, Danica F.; Mistlberger, Ralph E.; Steele, Andrew D.

2010-01-01

The ability to sense time and anticipate events is a critical skill in nature. Most efforts to understand the neural and molecular mechanisms of anticipatory behavior in rodents rely on daily restricted food access, which induces a robust increase of locomotor activity in anticipation of daily meal time. Interestingly, rats also show increased activity in anticipation of a daily palatable meal even when they have an ample food supply, suggesting a role for brain reward systems in anticipatory behavior, and providing an alternate model by which to study the neurobiology of anticipation in species, such as mice, that are less well adapted to “stuff and starve” feeding schedules. To extend this model to mice, and exploit molecular genetic resources available for that species, we tested the ability of wild-type mice to anticipate a daily palatable meal. We observed that mice with free access to regular chow and limited access to highly palatable snacks of chocolate or “Fruit Crunchies” avidly consumed the snack but did not show anticipatory locomotor activity as measured by running wheels or video-based behavioral analysis. However, male mice receiving a snack of high fat chow did show increased food bin entry prior to access time and a modest increase in activity in the two hours preceding the scheduled meal. Interestingly, female mice did not show anticipation of a daily high fat meal but did show increased activity at scheduled mealtime when that meal was withdrawn. These results indicate that anticipation of a scheduled food reward in mice is behavior, diet, and gender specific. PMID:20941366

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.

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.

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.

Anticipating the next meal using meal behavioral profiles: a hybrid model-based stochastic predictive control algorithm for T1DM.

PubMed

Hughes, C S; Patek, S D; Breton, M; Kovatchev, B P

2011-05-01

Automatic control of Type 1 Diabetes Mellitus (T1DM) with subcutaneous (SC) measurement of glucose concentration and subcutaneous (SC) insulin infusion is of great interest within the diabetes technology research community. The main challenge with the so-called "SC-SC" route to control is sensing and actuation delay, which tends to either destabilize the system or inhibit the aggressiveness of the controller in responding to meals and exercise. Model predictive control (MPC) is one strategy for mitigating delay, where optimal insulin infusions can be given in anticipation of future meal disturbances. Unfortunately, exact prior knowledge of meals can only be assured in a clinical environment and uncertainty about when and if meals will arrive could lead to catastrophic outcomes. As a follow-on to our recent paper in the IFAC symposium on Biological and Medical Systems (MCBMS 2009), we develop a control law that can anticipate meals given a probabilistic description of the patient's eating behavior in the form of a random meal (behavioral) profile. Preclinical in silico trials using the oral glucose meal model of Dalla Man et al. show that the control strategy provides a convenient means of accounting for uncertain prior knowledge of meals without compromising patient safety, even in the event that anticipated meals are skipped. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

21 CFR 137.285 - Degerminated yellow corn meal.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 2 2011-04-01 2011-04-01 false Degerminated yellow corn meal. 137.285 Section 137... Cereal Flours and Related Products § 137.285 Degerminated yellow corn meal. Degerminated yellow corn meal, degermed yellow corn meal, conforms to the definition and standard of identity prescribed by § 137.265 for...

21 CFR 137.285 - Degerminated yellow corn meal.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Degerminated yellow corn meal. 137.285 Section 137... Cereal Flours and Related Products § 137.285 Degerminated yellow corn meal. Degerminated yellow corn meal, degermed yellow corn meal, conforms to the definition and standard of identity prescribed by § 137.265 for...

Skipping meals or carbohydrate-free meals in order to determine Basal insulin requirements in subjects with type 1 diabetes mellitus?

PubMed

Uthoff, H; Lehmann, R; Sprenger, M; Wiesli, P

2010-05-01

Basal insulin dose requirements in patients with type 1 diabetes may be derived from the course of glucose concentrations in the fasting state; i. e. by skipping meals. The present study examined whether fasting tests could be replaced by carbohydrate-free meals. 16 adult patients with type 1 diabetes (10 male) on intensive insulin therapy participated in this prospective intervention study. Mean age (+/-SD) was 44+/-12 years, BMI 24+/-3 kg/m (2), mean HbA1c was 7.5+/-0.6% and duration of diabetes 15+/-12 years. All participants skipped dinner and plasma glucose concentrations were hourly monitored from 7 p.m. to 11 p.m. This blood glucose profile was compared with three test meals given at 7 p.m. at day 2-4, consumed either in the hospital (meal 1) or at home (meal 2 and 3). No insulin injection (except to basal insulin) was allowed. Test meals consisted of 2.5 g carbohydrate, 32.4 g protein, 52.0 g fat (according to 612 kcal). During 16 fasting tests plasma glucose concentration remained stable between 7.2+/-2.4 mmol/l at 7 p.m. and 6.8+/-2.8 mmol/l at 11 p.m. (p=0.461). Following the intake of near carbohydrate-free meals (48 tests), plasma glucose concentrations rose within 4 h from 6.7+/-2.0 at 7 p.m. to 9.8+/-3.4 mmol/l at 11 p.m. (p<0.0001). The increase in plasma glucose concentrations was similar in all three different meals tested. Plasma glucose concentrations significantly increase in patients with type 1 diabetes following the intake of carbohydrate-free meals. Carbohydrate-free meal-tests cannot replace skipping meal tests to determine the basal insulin requirement in patients with type 1 diabetes.

Meals based on vegetable protein sources (beans and peas) are more satiating than meals based on animal protein sources (veal and pork) – a randomized cross-over meal test study

PubMed Central

Kristensen, Marlene D.; Bendsen, Nathalie T.; Christensen, Sheena M.; Astrup, Arne; Raben, Anne

2016-01-01

Background Recent nutrition recommendations advocate a reduction in protein from animal sources (pork, beef) because of environmental concerns. Instead, protein from vegetable sources (beans, peas) should be increased. However, little is known about the effect of these vegetable protein sources on appetite regulation. Objective To examine whether meals based on vegetable protein sources (beans/peas) are comparable to meals based on animal protein sources (veal/pork) regarding meal-induced appetite sensations. Design In total, 43 healthy, normal-weight, young men completed this randomized, double-blind, placebo-controlled, three-way, cross-over meal test. The meals (all 3.5 MJ, 28 energy-% (E%) fat) were either high protein based on veal and pork meat, HP-Meat (19 E% protein, 53 E% carbohydrate, 6 g fiber/100 g); high protein based on legumes (beans and peas), HP-Legume (19 E% protein, 53 E% carbohydrate, 25 g fiber/100 g); or low-protein based on legumes, LP-Legume (9 E% protein, 62 E% carbohydrate, 10 g fiber/100 g). Subjective appetite sensations were recorded at baseline and every half hour using visual analog scales until the ad libitum meal 3 h after the test meal. Repeated measurements analyses and summary analyses were performed using ANCOVA (SAS). Results HP-Legume induced lower composite appetite score, hunger, prospective food consumption, and higher fullness compared to HP-Meat and LP-Legume (p<0.05). Furthermore, satiety was higher after HP-Legume than HP-Meat (p<0.05). When adjusting for palatability, HP-Legume still resulted in lower composite appetite scores, hunger, prospective consumption, and higher fullness compared to HP-Meat (p<0.05). Furthermore, HP-Legume induced higher fullness than LP-Legume (p<0.05). A 12% and 13% lower energy intake, respectively, was seen after HP-Legume compared to HP-Meat or LP-Legume (p<0.01). Conclusion Vegetable-based meals (beans/peas) influenced appetite sensations favorably compared to animal-based meals (pork

21 CFR 137.280 - Bolted yellow corn meal.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 2 2011-04-01 2011-04-01 false Bolted yellow corn meal. 137.280 Section 137.280... Flours and Related Products § 137.280 Bolted yellow corn meal. Bolted yellow corn meal conforms to the definition and standard of identity prescribed by § 137.255 for bolted white corn meal except that cleaned...

21 CFR 137.280 - Bolted yellow corn meal.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Bolted yellow corn meal. 137.280 Section 137.280... Flours and Related Products § 137.280 Bolted yellow corn meal. Bolted yellow corn meal conforms to the definition and standard of identity prescribed by § 137.255 for bolted white corn meal except that cleaned...

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.

Relation between cognitive and hedonic responses to a meal.

PubMed

Ciccantelli, B; Pribic, T; Malagelada, C; Accarino, A; Azpiroz, F

2017-05-01

Ingestion of a meal induces cognitive and hedonic sensations and our aim was to determine the relation between both dimensions. In three groups of healthy non-obese men (n=10 per group) three types of meals with equivalent levels of palatability were tested: a liquid meal, a solid-liquid low-calorie meal, and a solid-liquid high-calorie meal. The cognitive and hedonic responses were measured on 10-cm scales before and during the 30-minute postprandial period. The liquid meal induced a relatively strong cognitive response with satiation (4.7±0.7 score increment), fullness (3.3±0.7 score increment), and inhibition of desire of eating a food of choice; in contrast, its impact on sensation of digestive well-being and satisfaction was not significant (0.7±0.7 score increment). The high-calorie solid-liquid meal, with larger volume load and caloric content, induced much lower satiation (2.4±0.8 score increment; P=.041 vs liquid meal) and fullness sensation (1.3±0.6 score increment; P=.031 vs liquid meal), but a markedly higher level of satisfaction (2.7±0.4 score increment; P=.021 vs liquid meal); the low-calorie mixed meal had less prominent effects with significantly lower satisfaction (1.0±0.4 score increment; P=.039 vs high-calorie meal). The cognitive (satiation, fullness) and hedonic responses (satisfaction) to meals with equivalent levels of palatability, that is, equally likable, are dissociable. The characteristics of meals in terms of satiation and rewarding power could be adapted to specific clinical targets, whether nutritional supplementation or restriction. © 2017 John Wiley & Sons Ltd.

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.

Family meals then and now: A qualitative investigation of intergenerational transmission of family meal practices in a racially/ethnically diverse and immigrant population.

PubMed

Trofholz, Amanda C; Thao, Mai See; Donley, Mia; Smith, Mireya; Isaac, Hassan; Berge, Jerica M

2018-02-01

Having frequent family meals has consistently been associated with better health outcomes in children/adolescents. It is important to identify how intergenerational transmission of family meal practices occurs to help families benefit from the protective nature of family meals. Limited studies exist that explore the intergenerational transmission of family meal practices, particularly among racially/ethnically diverse and immigrant populations. This study explores how parents describe differences and similarities between meals "then" and "now", lessons they learned as children about family meals, lessons they passed onto their children, the challenges of carrying out family meals, and how families handle the barriers/challenges to intergenerational transmission of family meal practices. The study was conducted with a sample of African American, Native American, Latino, Hmong, Somali, and White families (25/category). Qualitative themes were explored with the overall sample, by race/ethnicity, immigrant status, and by time in the United States (US) as an immigrant. Parents overwhelmingly reported learning as children that family meals were important and conveying this message to their own children. Differences existed among racial/ethnic groups and time in the US as an immigrant. For example, Somali parents frequently endorsed having no challenges with intergenerational transmission of family meal practices. Immigrant parents in the US for a longer period of time were more likely to endorse learning/teaching about family meal importance, that the food eaten now is different than growing up, that a chaotic environment is a challenge to having family meals, and that they accommodate family member's schedules when planning family meals. Results demonstrate that exploring a parent's early family meal experiences may be important when intervening with parents from diverse racial/ethnic and immigrant populations when trying to improve or increase family meal practices

Childhood Obesity and Interpersonal Dynamics During Family Meals

PubMed Central

Rowley, Seth; Trofholz, Amanda; Hanson, Carrie; Rueter, Martha; MacLehose, Richard F.; Neumark-Sztainer, Dianne

2014-01-01

BACKGROUND: Family meals have been found to be associated with a number of health benefits for children; however, associations with obesity have been less consistent, which raises questions about the specific characteristics of family meals that may be protective against childhood obesity. The current study examined associations between interpersonal and food-related family dynamics at family meals and childhood obesity status. METHODS: The current mixed-methods, cross-sectional study included 120 children (47% girls; mean age: 9 years) and parents (92% women; mean age: 35 years) from low-income and minority communities. Families participated in an 8-day direct observational study in which family meals were video-recorded in their homes. Family meal characteristics (eg, length of the meal, types of foods served) were described and associations between dyadic (eg, parent-child, child-sibling) and family-level interpersonal and food-related dynamics (eg, communication, affect management, parental food control) during family meals and child weight status were examined. RESULTS: Significant associations were found between positive family- and parent-level interpersonal dynamics (ie, warmth, group enjoyment, parental positive reinforcement) at family meals and reduced risk of childhood overweight. In addition, significant associations were found between positive family- and parent-level food-related dynamics (ie, food warmth, food communication, parental food positive reinforcement) and reduced risk of childhood obesity. CONCLUSIONS: Results extend previous findings on family meals by providing a better understanding of interpersonal and food-related family dynamics at family meals by childhood weight status. Findings suggest the importance of working with families to improve the dyadic and family-level interpersonal and food-related dynamics at family meals. PMID:25311603

21 CFR 73.185 - Haematococcus algae meal.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 1 2012-04-01 2012-04-01 false Haematococcus algae meal. 73.185 Section 73.185... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.185 Haematococcus algae meal. (a) Identity. (1) The color additive haematococcus algae meal consists of the comminuted and dried cells of the alga...

21 CFR 73.185 - Haematococcus algae meal.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 1 2014-04-01 2014-04-01 false Haematococcus algae meal. 73.185 Section 73.185... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.185 Haematococcus algae meal. (a) Identity. (1) The color additive haematococcus algae meal consists of the comminuted and dried cells of the alga...

21 CFR 73.185 - Haematococcus algae meal.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Haematococcus algae meal. 73.185 Section 73.185... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.185 Haematococcus algae meal. (a) Identity. (1) The color additive haematococcus algae meal consists of the comminuted and dried cells of the alga...

21 CFR 73.185 - Haematococcus algae meal.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 1 2011-04-01 2011-04-01 false Haematococcus algae meal. 73.185 Section 73.185... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.185 Haematococcus algae meal. (a) Identity. (1) The color additive haematococcus algae meal consists of the comminuted and dried cells of the alga...

21 CFR 73.185 - Haematococcus algae meal.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 1 2013-04-01 2013-04-01 false Haematococcus algae meal. 73.185 Section 73.185... COLOR ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.185 Haematococcus algae meal. (a) Identity. (1) The color additive haematococcus algae meal consists of the comminuted and dried cells of the alga...

Healthy School Meals: Promotion Ideas That Work.

ERIC Educational Resources Information Center

Minnesota State Dept. of Children, Families, and Learning, Roseville. Food and Nutrition Service.

"Healthy School Meals: Promotion Ideas That Work" is a Minnesota program based on the USDA's Team Nutrition program. The program's goal is to improve the health of children through school meals and nutrition education. This is accomplished by empowering schools to serve meals meeting the Dietary Guidelines for Americans, and motivating…

Adolescent and parent views of family meals.

PubMed

Fulkerson, Jayne A; Neumark-Sztainer, Dianne; Story, Mary

2006-04-01

To examine and compare the family mealtime environment from the perspectives of both adolescents and parents. Adolescents completed a school-based survey and parents participated in a telephone interview as part of Project EAT (Eating Among Teens). Participants were 902 adolescent females (n=424) and males (n=478) and one of their guardians/parents. Frequencies, chi(2) analyses, and Spearman correlations were used to assess relationships. Parents were more likely than adolescents to report eating five or more family meals per week, the importance of eating together, and scheduling difficulties (P<0.001). Younger adolescents were more likely than older adolescents to report eating five or more family meals per week, higher importance of eating together, and more rule expectations at mealtime (P<0.001), whereas older adolescents were more likely to report scheduling difficulties (P<0.001). Girls reported more family meals per week and more scheduling conflicts than boys did; boys reported more rules at mealtime than girls did (P<0.001). Family meals are perceived positively by both adolescents and parents. Family meals may be a useful mechanism for enhancing family togetherness, and for role modeling behaviors that parents would like their children to emulate. Dietetics professionals can capitalize on positive attitudes toward family meals to help promote their frequency. Helping families learn to cook healthful, quick meals may reduce dependency on less healthful meal options, reduce the frequency of eating outside of the home, and promote greater nutritional intake.

SH2 domain-containing phosphatase 1 regulates pyruvate kinase M2 in hepatocellular carcinoma.

PubMed

Tai, Wei-Tien; Hung, Man-Hsin; Chu, Pei-Yi; Chen, Yao-Li; Chen, Li-Ju; Tsai, Ming-Hsien; Chen, Min-Husan; Shiau, Chung-Wai; Boo, Yin-Pin; Chen, Kuen-Feng

2016-04-19

Pyruvate kinase M2 (PKM2) is known to promote tumourigenesis through dimer formation of p-PKM2Y105. Here, we investigated whether SH2-containing protein tyrosine phosphatase 1 (SHP-1) decreases p-PKM2Y105 expression and, thus, determines the sensitivity of sorafenib through inhibiting the nuclear-related function of PKM2. Immunoprecipitation and immunoblot confirmed the effect of SHP-1 on PKM2Y105 dephosphorylation. Lactate production was assayed in cells and tumor samples to determine whether sorafenib reversed the Warburg effect. Clinical hepatocellular carcinoma (HCC) tumor samples were assessed for PKM2 expression. SHP-1 directly dephosphorylated PKM2 at Y105 and further decreased the proliferative activity of PKM2; similar effects were found in sorafenib-treated HCC cells. PKM2 was also found to determine the sensitivity of targeted drugs, such as sorafenib, brivanib, and sunitinib, by SHP-1 activation. Significant sphere-forming activity was found in HCC cells stably expressing PKM2. Clinical findings suggest that PKM2 acts as a predicting factor of early recurrence in patients with HCC, particularly those without known risk factors (63.6%). SHP-1 dephosphorylates PKM2 at Y105 to inhibit nuclear function of PKM2 and determines the efficacy of targeted drugs. Targeting PKM2 by SHP-1 might provide new therapeutic insights for patients with HCC.

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

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

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.

More Than A Meal? A Randomized Control Trial Comparing the Effects of Home-Delivered Meals Programs on Participants' Feelings of Loneliness.

PubMed

Thomas, Kali S; Akobundu, Ucheoma; Dosa, David

2016-11-01

Nutrition service providers are seeking alternative delivery models to control costs and meet the growing need for home-delivered meals. The objective of this study was to evaluate the extent to which the home-delivered meals program, and the type of delivery model, reduces homebound older adults' feelings of loneliness. This project utilizes data from a three-arm, fixed randomized control study conducted with 626 seniors on waiting lists at eight Meals on Wheels programs across the United States. Seniors were randomly assigned to either (i) receive daily meal delivery; (ii) receive once-weekly meal delivery; or (iii) remain on the waiting list. Participants were surveyed at baseline and again at 15 weeks. Analysis of covariance was used to test for differences in loneliness between groups, over time and logistic regression was used to assess differences in self-rated improvement in loneliness. Participants receiving meals had lower adjusted loneliness scores at follow-up compared with the control group. Individuals who received daily-delivered meals were more likely to self-report that home-delivered meals improved their loneliness than the group receiving once-weekly delivered meals. This article includes important implications for organizations that provide home-delivered meals in terms of cost, delivery modality, and potential recipient benefits. Published by Oxford University Press on behalf of the Gerontological Society of America 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Replacing dietary soybean meal with canola meal improves production and efficiency of lactating dairy cows

USDA-ARS?s Scientific Manuscript database

Previous research suggested that crude protein (CP) from canola meal (CM) is used more efficiently than CP from solvent soybean meal (SBM) by lactating dairy cows. We tested whether dietary CP content influenced relative effectiveness of equal supplemental CP from either CM or SBM. Fifty lactating H...

21 CFR 137.260 - Enriched corn meals.

Code of Federal Regulations, 2010 CFR

2010-04-01

... HUMAN CONSUMPTION CEREAL FLOURS AND RELATED PRODUCTS Requirements for Specific Standardized Cereal Flours and Related Products § 137.260 Enriched corn meals. (a) Enriched corn meals are the foods, each of... 21 Food and Drugs 2 2010-04-01 2010-04-01 false Enriched corn meals. 137.260 Section 137.260 Food...

21 CFR 137.260 - Enriched corn meals.

Code of Federal Regulations, 2011 CFR

2011-04-01

... HUMAN CONSUMPTION CEREAL FLOURS AND RELATED PRODUCTS Requirements for Specific Standardized Cereal Flours and Related Products § 137.260 Enriched corn meals. (a) Enriched corn meals are the foods, each of... 21 Food and Drugs 2 2011-04-01 2011-04-01 false Enriched corn meals. 137.260 Section 137.260 Food...

21 CFR 137.260 - Enriched corn meals.

Code of Federal Regulations, 2013 CFR

2013-04-01

... HUMAN CONSUMPTION CEREAL FLOURS AND RELATED PRODUCTS Requirements for Specific Standardized Cereal Flours and Related Products § 137.260 Enriched corn meals. (a) Enriched corn meals are the foods, each of... 21 Food and Drugs 2 2013-04-01 2013-04-01 false Enriched corn meals. 137.260 Section 137.260 Food...

21 CFR 137.260 - Enriched corn meals.

Code of Federal Regulations, 2012 CFR

2012-04-01

... HUMAN CONSUMPTION CEREAL FLOURS AND RELATED PRODUCTS Requirements for Specific Standardized Cereal Flours and Related Products § 137.260 Enriched corn meals. (a) Enriched corn meals are the foods, each of... 21 Food and Drugs 2 2012-04-01 2012-04-01 false Enriched corn meals. 137.260 Section 137.260 Food...

21 CFR 137.260 - Enriched corn meals.

Code of Federal Regulations, 2014 CFR

2014-04-01

... HUMAN CONSUMPTION CEREAL FLOURS AND RELATED PRODUCTS Requirements for Specific Standardized Cereal Flours and Related Products § 137.260 Enriched corn meals. (a) Enriched corn meals are the foods, each of... 21 Food and Drugs 2 2014-04-01 2014-04-01 false Enriched corn meals. 137.260 Section 137.260 Food...

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

Interactions of corn meal or molasses with a soybean-sunflower meal mix or flaxseed meal on production, milk fatty acids composition, and nutrient utilization in dairy cows fed grass hay-based diets

USDA-ARS?s Scientific Manuscript database

We investigated the interactions of molasses or corn meal [nonstructural carbohydrate (NSC) sources] with flaxseed meal or a soybean-sunflower meal protein mix [rumen-degradable protein (RDP) sources] on animal production, milk fatty acids profile, and nutrient utilization in organic Jersey cows fed...

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

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.

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.

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...

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.

The epidemiology of family meals among Ohio's adults.

PubMed

Tumin, Rachel; Anderson, Sarah E

2015-06-01

The epidemiology of family meals among adults at a population level is poorly characterized and whether living with children impacts this health behaviour is uncertain. We determined the prevalence of family meals among US adults in a mid-western state whose families did and did not include minor children and described how it varied by sociodemographic characteristics. The cross-sectional 2012 Ohio Medicaid Assessment Survey is representative of Ohio adults and included questions on their sociodemographic characteristics and the frequency with which they eat family meals at home. Trained interviewers administered landline and cell phone surveys to adults sampled from Ohio's non-institutionalized population. We analysed data from 5766 adults living with minor children and 8291 adults not living alone or with children. The prevalence of family meals was similar for adults who did and did not live with minor children: 47 % (95 % CI 46, 49 %) of adults living with and 51 % (95 % CI 50, 53 %) of adults living without children reported eating family meals on most (six or seven) days of the week. Family meal frequency varied by race/ethnicity, marital and employment status in both groups. Non-Hispanic African-American adults, those who were not married and those who were employed ate family meals less often. Adults in Ohio frequently shared meals with their family and family meal frequency was not strongly related to living with children. Broadening the scope of future studies to include adults who are not parents could enhance our understanding of the potential health benefits of sharing meals.

Pyruvate kinase M2 interacts with DNA damage-binding protein 2 and reduces cell survival upon UV irradiation

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

Xie, Xiao; Wang, Mingsong; Mei, Ju, E-mail: jumei_xinhua@163.com

Pyruvate Kinase M2 (PKM2) is highly expressed in many solid tumors and associated with metabolism reprogramming and proliferation of tumors. Here, we report that PKM2 can bind to DNA Damage-Binding Protein 2 (DDB2), which is necessary for global nucleotide excision repair of UV induced DNA damage. The binding is promoted by UV irradiation and K433 acetylation of PKM2. Over expression of PKM2 facilitates phosphorylation of DDB2 and impairs DDB2-DDB1 binding. Furthermore, knocking down of PKM2 increases cell survival upon UV irradiation, while over expression of PKM2 reduces cell survival and over expression of DDB2-DDB1 reverts this effect. These results revealmore » a previously unknown regulation of PKM2 on DDB2 and provide a possible mechanism for UV induced tumorigenesis. - Highlights: • PKM2 interacts with DDB2. • UV irradiation increases PKM2-DDB2 binding via up regulation of PKM2 K433 acetylation. • PKM2 facilitates DDB2 phosphorylation and impairs DDB2-DDB1 binding. • PKM2 reduces cell survival upon UV irradiation.« less

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.

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.

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.

21 CFR 73.275 - Dried algae meal.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 1 2012-04-01 2012-04-01 false Dried algae meal. 73.275 Section 73.275 Food and... ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.275 Dried algae meal. (a) Identity. The color additive dried algae meal is a dried mixture of algae cells (genus Spongiococcum, separated from its culture broth...

21 CFR 73.275 - Dried algae meal.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 21 Food and Drugs 1 2011-04-01 2011-04-01 false Dried algae meal. 73.275 Section 73.275 Food and... ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.275 Dried algae meal. (a) Identity. The color additive dried algae meal is a dried mixture of algae cells (genus Spongiococcum, separated from its culture broth...

21 CFR 73.275 - Dried algae meal.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Dried algae meal. 73.275 Section 73.275 Food and... ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.275 Dried algae meal. (a) Identity. The color additive dried algae meal is a dried mixture of algae cells (genus Spongiococcum, separated from its culture broth...

21 CFR 73.275 - Dried algae meal.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 21 Food and Drugs 1 2014-04-01 2014-04-01 false Dried algae meal. 73.275 Section 73.275 Food and... ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.275 Dried algae meal. (a) Identity. The color additive dried algae meal is a dried mixture of algae cells (genus Spongiococcum, separated from its culture broth...

21 CFR 73.275 - Dried algae meal.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 1 2013-04-01 2013-04-01 false Dried algae meal. 73.275 Section 73.275 Food and... ADDITIVES EXEMPT FROM CERTIFICATION Foods § 73.275 Dried algae meal. (a) Identity. The color additive dried algae meal is a dried mixture of algae cells (genus Spongiococcum, separated from its culture broth...

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.

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

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.

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.

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

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.

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.

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.

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.

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.

Do Sri Lankan meals help decrease blood glucose response?

PubMed

Hettiaratchi, U P K; Ekanayake, S; Welihinda, J

2009-06-01

The prevalence of diabetes mellitus (DM) has rapidly increased in Asian countries including Sri Lanka during the past decade. Scientific data on postprandial glycaemic influence of common meals is essential when formulating diets. Objectives of this study were to analyse glycaemic indices (GI) of five common meals and effects of macronutrients, sources of carbohydrates, and physicochemical properties of starch on observed GI values. The meals analysed were; 1 - red rice (AT 353) meal, 2 - red rice mixed meal, 3 - stringhopper (wheat flour) meal, 4 - stringhopper (rice flour) meal, 5 - manioc (Manihot esculenta) meal. University of Sri Jayewardenepura. Healthy individuals (n=10; age: 20-30 years). GI of each meal was calculated according to FAO/WHO guidelines by taking the ratio of incremental area under blood glucose curve (IAUC) of test and the standard. GI of meals 1-5 were 99 +/- 10, 60 +/- 5, 104 +/- 7, 102 +/- 11 and 120 +/- 9 respectively. The glycaemic response to rice mixed meal was significantly lower (p<0.05) than the others. The total dietary fibre content showed a significant negative correlation (p=0.044) with the GI value while the protein showed a non-significant negative relationship (p>0.05). Red rice had a combination of intact, swollen and disintegrated starch granules while string hoppers and manioc showed only the latter two types. The rice mixed meal has the lowest glycaemic index. Presence of dietary fibre and a legume reduces the glycaemic response. Cooking may change the glycaemic response of certain food.

School meals: a nutritional and environmental perspective.

PubMed

Demas, Antonia; Kindermann, Dana; Pimentel, David

2010-01-01

In light of the rise in childhood obesity rates and the influence of the food system on fossil fuel use, this article analyzes current school meals in Baltimore and makes suggestions for school meal reform based on both childhood nutrition and environmental resource use. The nutrient content and estimated energy costs of a typical school lunch are compared with a proposed alternate meal. The study indicates that healthier meals can significantly limit fossil fuel energy inputs for harvesting, production, processing, packaging, and transportation. The authors also provide strategies for developing menus that are both more nutritious and more energy efficient.