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Sample records for kernel crude protein

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

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Taiyong Li

2016-12-01

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

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Edgardo V. Casas

2015-12-01

Full Text Available Carabao mangoes are among the highly produced fruit crops in the Philippines. The processing and consumption of carabao mangoes leave a significant amount of waste seeds. Mango kernel butter extracted from waste seed kernels is a potential additive to cosmetic products or as a cocoa butter substitute. This study determined the pretreatment conditions that produce optimum yield prior to the mechanical extraction of the crude butter. Moreover, this study provided a general sensory evaluation of the finished product. Microwave power (160, 500, and 850 W, microwave exposure time (2.0, 3.5, and 5.0 min, and size levels (1.5, 3.0, and 4.5 mm were tested for their effects on the yield of the mechanically extracted crude butter in wet basis percentage. The optimization procedures resulted to optimum pretreatment conditions of 160 W, 4.25 min, and 1.5 mm. Size level was the most significant factor in the crude butter yield. Sensory evaluation of the crude butter extracted at optimum pretreatment conditions through acceptance test by a test panel resulted to below neutral scores in visual appearance and odor, and above neutral score in texture, indicating the potential of mango butter as a good substitute to cocoa butter in cosmetic products.
Flour quality and kernel hardness connection in winter wheat

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Szabó B. P.

2016-12-01

Full Text Available Kernel hardness is controlled by friabilin protein and it depends on the relation between protein matrix and starch granules. Friabilin is present in high concentration in soft grain varieties and in low concentration in hard grain varieties. The high gluten, hard wheat our generally contains about 12.0–13.0% crude protein under Mid-European conditions. The relationship between wheat protein content and kernel texture is usually positive and kernel texture influences the power consumption during milling. Hard-textured wheat grains require more grinding energy than soft-textured grains.
Bioconversions of Palm Kernel Cake and Rice Bran Mixtures by Trichoderma viride Toward Nutritional Contents

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Yana Sukaryana

2010-12-01

Full Text Available The objective of the research is to examine the mixtures of palm kernel cake and rice bran of fermented by Trichoderma viride. Completely randomized design in factorial pattern 4 x 4 was used in this experiment. factor I is the doses of inoculums; D1 = 0%, D2 = 0,1% , D3 = 0,2%, D4 = 0,3%, and complement factor II is mixtures of palm kernel cake and rice bran : T1=20:80% ; T2=40:60% ; T3=60:40% ; T4=80:20%. The treatment each of three replicate. Fermentation was conducted at temperature 28 oC as long as 9 days. Determining the best of the mixtures be based on the crude protein increased and the crude fibre decreased. The results showed that the combination of product mix is the best fermentation inoculums doses 0.3% in mixture of palm kernel cake and rice bran ; 80%: 20%, which produces dry matter of 88,12%, crude protein 17.34%, ether extract 5,35%, crude fibre 23.67%, and ash 6.43%. When compared with a mixture of palm kernel cake and rice bran; 80%: 20% without of fermentation is crude protein increase 29.58% and crude fibre decreased 22.53%.
Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

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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.
Protein fold recognition using geometric kernel data fusion.

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

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

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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.
Quantification of Greenhouse Gas Emissions for the Production of Crude Palm Kernel Oil - A Cradle to Gate Study

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Subramaniam, V.

2016-01-01

The Malaysian oil palm industry is one of the major economic backbones of the country. The industry as a whole brought in an export revenue of RM 63 billion just in the year 2015. In the past, the competitiveness of palm products along the supply chain was based on direct economic comparison with other vegetable oil products. However, with increasing attention on sustainable development, the environmental performance of products are now defining issues in trade. This articles presents the greenhouse gas (GHG) emissions for the production of crude palm kernel oil (CPKO). Crude palm oil (CPO) and CPKO both come from the oil palm fresh fruit bunch (FFB). CPO is obtained from the mesocarp of the fruit and the lauric CPKO comes from the kernel at the fruit's core. CPO is produced in the palm oil mill while palm kernels which are the by-product of the production of CPO are transported to kernel crushing plants to be processed into CPKO. The objectives of this study are to quantify the GHG emissions for the production of CPKO and suggest the best solution to reduce the emissions if any. The system boundary starts from the production of oil palm seedlings at the nursery stage right till the production of CPKO at the kernel crushing plant which makes it a cradle to gate study. Inventory data for the production of CPKO was collected from 24 crushing plants which were located near the ports and two kernel crushing plants which were integrated with a palm oil mill. Weight allocation was performed at the kernel crushing plant. The largest GHG contribution came from upstream nursery and plantation with continued land use which amounts to 394.19 kg CO 2 eq/ t CPKO followed by emissions from biogas at the palm oil mill which amounts to 87.48 kg CO 2 eq/ t CPKO even though the scenario chosen is the biogas capture scenario. The third largest GHG emissions comes from the kernel crushing plant due to the processing of CPKO using the electricity from the grid which emits 74.33 kg
Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

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Peiying Ruan

Full Text Available Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.
Learning a peptide-protein binding affinity predictor with kernel ridge regression

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2013-01-01

Background The cellular function of a vast majority of proteins is performed through physical interactions with other biomolecules, which, most of the time, are other proteins. Peptides represent templates of choice for mimicking a secondary structure in order to modulate protein-protein interaction. They are thus an interesting class of therapeutics since they also display strong activity, high selectivity, low toxicity and few drug-drug interactions. Furthermore, predicting peptides that would bind to a specific MHC alleles would be of tremendous benefit to improve vaccine based therapy and possibly generate antibodies with greater affinity. Modern computational methods have the potential to accelerate and lower the cost of drug and vaccine discovery by selecting potential compounds for testing in silico prior to biological validation. Results We propose a specialized string kernel for small bio-molecules, peptides and pseudo-sequences of binding interfaces. The kernel incorporates physico-chemical properties of amino acids and elegantly generalizes eight kernels, comprised of the Oligo, the Weighted Degree, the Blended Spectrum, and the Radial Basis Function. We provide a low complexity dynamic programming algorithm for the exact computation of the kernel and a linear time algorithm for it’s approximation. Combined with kernel ridge regression and SupCK, a novel binding pocket kernel, the proposed kernel yields biologically relevant and good prediction accuracy on the PepX database. For the first time, a machine learning predictor is capable of predicting the binding affinity of any peptide to any protein with reasonable accuracy. The method was also applied to both single-target and pan-specific Major Histocompatibility Complex class II benchmark datasets and three Quantitative Structure Affinity Model benchmark datasets. Conclusion On all benchmarks, our method significantly (p-value ≤ 0.057) outperforms the current state-of-the-art methods at predicting
High-fiber diets with reduced crude protein for commercial layers

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MFFM Praes

2014-06-01

Full Text Available This study aimed at evaluating diets containing different fiber sources and two crude protein levels on the performance, egg quality, and nitrogen metabolism of commercial layers. In total, 392 48-wk-old Isa Brown layers were distributed according to a completely randomized experimental design in a 3x2+1 (control factorial arrangement, resulting in seven treatments with seven replicates of eight birds each. Treatments consisted of three fiber feedstuffs (cottonseed hulls, soybean hulls, and rice hulls and two dietary crude protein levels (12% and 16%. Cottonseed hulls associated with the high crude protein level (16% resulted in the worst feed conversion ratio per dozen eggs. Diets with 16% crude protein resulted in the highest feed intake, egg production, egg weight, egg mass values, and improved feed conversion ratio (kg eggs/kg feed. The dietary inclusion of soybean hulls determined low yolk pigmentation, and of rice hulls, low egg specific gravity. The 16% crude protein diet with rice hulls promoted the best feed conversion ratio. Hens fed the reference diet presented higher egg mass and better feed conversion ratio per kg eggs and per dozen eggs. Hens fed the diets with low crude protein level (12% had reduced nitrogen excretion, but presented worse egg production.
The enhancement of the nutritive value of mango seed kernel through radiation processing and other treatments

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Farag, M.D.E.

1999-01-01

The raw seed kernels of local mango (MSK) varieties (Magnifier indica L.)were analyzed for proximate composition, levels of trypsin inhibitor's, tannins, cyano genetic glucosides, in vitro protein digestibility and apparent metabolizable energy (AME n ) as being affected by boiling, autoclaving, autoclaving as well as radiation processing at doses 5, 10, and 20 KGy. The air-dry mango kernels were found to contain 70, 128, and 67 g kg - 1 of crude protein, crude fat and tannins, respectively. Compared with raw samples the contents of trypsin inhibitory activity (30 TIU g - 1) and cyano genetic glucosides, as hydrocyanic acid, (71 mg g kg - 1) were lowered by boiling, autoclaving and radiation treatments. Only boiling and autoclaving lowered tannins (67.2 g kg - 1) but radiation processing did not have any effect. The in vitro protein digestibility and AME n value by 139% and 72%, respectively. These results indicate that tannins, trypsin inhibitors and cyano genetic glucosides, are responsible for poor nutritive value of MSK
A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature.

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Domonkos Tikk

Full Text Available The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein-protein interactions (PPIs reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate goal is to identify the one method that performs best in real-life scenarios, where information extraction is performed on unseen text and not on specifically prepared evaluation data. We performed a comprehensive benchmarking of nine different methods for PPI extraction that use convolution kernels on rich linguistic information. Methods were evaluated on five different public corpora using cross-validation, cross-learning, and cross-corpus evaluation. Our study confirms that kernels using dependency trees generally outperform kernels based on syntax trees. However, our study also shows that only the best kernel methods can compete with a simple rule-based approach when the evaluation prevents information leakage between training and test corpora. Our results further reveal that the F-score of many approaches drops significantly if no corpus-specific parameter optimization is applied and that methods reaching a good AUC score often perform much worse in terms of F-score. We conclude that for most kernels no sensible estimation of PPI extraction performance on new text is possible, given the current heterogeneity in evaluation data. Nevertheless, our study
Nutrition quality of extraction mannan residue from palm kernel cake on brolier chicken

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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.
Upgrading The Nutritive Value of Mango Seed Kernel for Poultry by Thermal Treatment and Radiation Processing

International Nuclear Information System (INIS)

Farag, M.D

2007-01-01

The raw seed kernels of local mango (MSK) varieties (Magnifera indica L.) were analyzed for composition, levels of trypsin inhibitors, tannins, cyanogenetic glucosides, in vitro protein digestibility and apparent metabolizable energy (AMEn) as being effected by boiling, autoclaving as well as irradiation processing at doses 5, 10, 15, and 20 kGy. The air-dry mango kernels contained 70, 128, and 67 g kg -1 of crude protein, crude fat, and tannins, respectively. Compared with raw samples, the contents of trypsin inhibitory activity (30 TIU g -1 ) and cyanogenetic glucosides, as hydrocyanic acid, (71 mg kg -1 ) were lowered by boiling, autoclaving and radiation treatments. Only boiling and autoclaving lowered tannin content (67.2 g kg -1 in raw kernel), but irradiation does not introduce any effect. The in vitro protein digestibility and AMEn values of raw MSK were low and the processing methods enhanced the in vitro protein digestibility and AMEn of MSK. The improvements paralleled reductions in trypsin inhibitory activity, cyanogenetic glucosides and tannin contents. Greater improvements were noticed with boiling and autoclaving than with irradiation alone. While autoclaving for 30min plus irradiation treatment up to 20 kGy maximized the in vitro protein digestibility and AMEn value by 139% and 72%, respectively. These results indicate that tannins, trypsin inhibitors and cyanogenetic glucosides, are responsible for poor nutritive value of MSK. The results suggested that the combination of autoclaving for 30 min plus irradiation treatment up to 20 kGy upgraded the nutritive value and that this method is more effective in processing MSK to be used as animal feed.
Exploration of Shorea robusta (Sal seeds, kernels and its oil

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Shashi Kumar C.

2016-12-01

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

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Ginting, Nurzainah; Pase, E.

2018-03-01

This study aims to examine the effect of incubation times of sago waste by local microorganism (MOL) “Ginta” to the crude protein and crude fiber content in relation to finding a cheap and good quality ruminants feed alternative. Incubation times were 0 hours to 144 hours. The data obtained were analyzed using Completely Randomize Design consisting of seven treatments and three replications. The result showed that the duration of incubation of sago waste by local microorganism (MOL) “Ginta” caused pH reduction, improved crude protein and crude fiber content. pH reduction was from 7.03 at 0 hour to 4.05 at 144 hours incubation. The highest increased in crude protein was H6U3 (5.58%) : 144 hours incubation and the lowest was H0U2 (3.22%) : 0 hour incubation while the highest crude fiber was H0U1 (19.99%) : 0 hour incubation and the lowest was H6U3 (18.23%) : 144 hours incubation. It can be concluded that incubation of sago waste triggered lower pH, higher crude protein and lower crude fiber than uninoculated. A recommendation could be given on using MOL ‘Ginta” in order to produce a cheap and good quality ruminans feed alternative.
Prediction of protein subcellular localization using support vector machine with the choice of proper kernel

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Al Mehedi Hasan

2017-07-01

Full Text Available The prediction of subcellular locations of proteins can provide useful hints for revealing their functions as well as for understanding the mechanisms of some diseases and, finally, for developing novel drugs. As the number of newly discovered proteins has been growing exponentially, laboratory-based experiments to determine the location of an uncharacterized protein in a living cell have become both expensive and time-consuming. Consequently, to tackle these challenges, computational methods are being developed as an alternative to help biologists in selecting target proteins and designing related experiments. However, the success of protein subcellular localization prediction is still a complicated and challenging problem, particularly when query proteins may have multi-label characteristics, i.e. their simultaneous existence in more than one subcellular location, or if they move between two or more different subcellular locations as well. At this point, to get rid of this problem, several types of subcellular localization prediction methods with different levels of accuracy have been proposed. The support vector machine (SVM has been employed to provide potential solutions for problems connected with the prediction of protein subcellular localization. However, the practicability of SVM is affected by difficulties in selecting its appropriate kernel as well as in selecting the parameters of that selected kernel. The literature survey has shown that most researchers apply the radial basis function (RBF kernel to build a SVM based subcellular localization prediction system. Surprisingly, there are still many other kernel functions which have not yet been applied in the prediction of protein subcellular localization. However, the nature of this classification problem requires the application of different kernels for SVM to ensure an optimal result. From this viewpoint, this paper presents the work to apply different kernels for SVM in protein
ASSESSMENT OF HEAVY METALS AND CRUDE PROTEIN ...

African Journals Online (AJOL)

UNICORN

to quantify heavy metals (Cu, Zn, Pb and Cd) and crude protein content of these species that are sold in ... in protein, omega 3 and low fat content. Furthermore ... high levels of cadmium can cause kidney and liver damage in man [6]. Motivation .... analysis. Determination of heavy metals in the edible tissues of the organisms.

Minimum Information Loss Based Multi-kernel Learning for Flagellar Protein Recognition in Trypanosoma Brucei

KAUST Repository

Wang, Jim Jing-Yan

2014-12-01

Trypanosma brucei (T. Brucei) is an important pathogen agent of African trypanosomiasis. The flagellum is an essential and multifunctional organelle of T. Brucei, thus it is very important to recognize the flagellar proteins from T. Brucei proteins for the purposes of both biological research and drug design. In this paper, we investigate computationally recognizing flagellar proteins in T. Brucei by pattern recognition methods. It is argued that an optimal decision function can be obtained as the difference of probability functions of flagella protein and the non-flagellar protein for the purpose of flagella protein recognition. We propose to learn a multi-kernel classification function to approximate this optimal decision function, by minimizing the information loss of such approximation which is measured by the Kull back-Leibler (KL) divergence. An iterative multi-kernel classifier learning algorithm is developed to minimize the KL divergence for the problem of T. Brucei flagella protein recognition, experiments show its advantage over other T. Brucei flagellar protein recognition and multi-kernel learning methods. © 2014 IEEE.
Optimization of factors affecting the production of biodiesel from crude palm kernel oil and ethanol

Energy Technology Data Exchange (ETDEWEB)

Kuwornoo, David. K. [Faculty of Chemical and Materials Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Private Mail Bag, Kumasi (Ghana); Ahiekpor, Julius C. [Chemical Engineering Department, Kumasi Polytechnic, P.O. Box 854, Kumasi (Ghana)

2010-07-01

Biodiesel, an alternative diesel fuel made from renewable sources such as vegetable oils and animal fats, has been identified by government to play a key role in the socio-economic development of Ghana. The utilization of biodiesel is expected to be about 10% of the total liquid fuel mix of the country by the year 2020. Despite this great potential and the numerous sources from which biodiesel could be developed in Ghana, studies on the sources of biodiesel and their properties as a substitute for fossil diesel have tended to be limited to Jatropha oil. This paper, however, reports the parameters that influences the production of biodiesel from palm kernel oil, one of the vegetable oils obtained from oil palm which is the highest vegetable oil source in Ghana. The parameters studied are; mass ratio of ethanol to oil, reaction temperature, catalyst concentration, and reaction time using completely randomized 24 factorial design. Results indicated that ethanol to oil mass ratio, catalyst concentration and reaction time were the most important factors affecting the ethyl ester yield. There was also an interaction effect between catalyst and time and ethanol- oil ratio and time on the yield. Accordingly, the optimal conditions for the production of ethyl esters from crude palm kernel oil were determined as; 1:5 mass ratio of ethanol to oil, 1% catalyst concentration by weight of oil, 90 minutes reaction time at a temperature of 30 deg C.
Performance of juvenile mojarra supplied with feed containing varying levels of crude protein

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Ricardo Henrique Bastos de Souza

2016-04-01

Full Text Available ABSTRACT The growth of the Brazilian aquaculture has stimulated the development of the productive chain of native species, including marine environment. The objective of this study was to evaluate the growth performance of juvenile mojarra fish (Diapterus rhombeus fed diets containing different concentrations of crude protein (32, 36, 40 and 44 g 100 g-1. The 80 juvenile mojarra (7.2±1.5 g were kept in 16 circular tanks (150 L. The study design used was completely randomized with four treatments and four repetitions. The fish were fed four times a day. At the end of the experiment (60 days the final weight, feed intake, weight gain (WG, feed:gain ratio (FGR, protein efficiency rate (PER, energy efficiency rate, specific growth, survival rate and, body composition were evaluated. It was verified significant effect of protein level on the WG, with the best value at the level of 38.20 g 100 g-1 of crude protein. For FGR, the best estimated value occurred with 38.06 g 100 g-1 of crude protein, similar to that reported for the PER (38.91 g 100 g-1. The other performance parameters and body composition were not influenced by crude protein levels. Diet crude protein concentrations between 38.06 and 38.91 g 100 g-1 provide the best performance indices for juvenile mojarra.
A Kernel for Protein Secondary Structure Prediction

OpenAIRE

Guermeur , Yann; Lifchitz , Alain; Vert , Régis

2004-01-01

http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...
Digestibility of solvent-treated Jatropha curcas kernel by broiler chickens in Senegal.

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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.
Digestion of crude protein and organic matter of leaves by rumen microbes in vitro

Energy Technology Data Exchange (ETDEWEB)

Ciszuk, A.; Murphy, M.

1982-01-01

22 leaf specimens, of which 6 were from an energy-woods project, were studied by incubation in vitro with rumen microbes or pepsin-hydrochloric acid. Several were also examined in situ using the nylon-bag technique. Many leaves, despite their low fiber and high crude protein content, gave low values for organic matter digestibility. The crude protein degradation by rumen microbes or pepsin-hydrochloric acid was low, on average, compared with hay. There was a wide variation among leaf specimens. Variation was also found as regards ammonia production in short-term (4 hours) incubation. No close correlation was found between crude protein content and crude protein degradation, or between the estimates of ruminal degradation and of pepsin-hydrochloric acid digestibility. This suggest that there are leaves that gives ruminants substantial amounts of digestible protein yet escape ruminal fermentation. (Refs. 12).
Effect of Electron Beam Irradiation on Degradability Coefficients and Ruminalpostruminal Digestibility of Dry Matter and Crude Protein of some Plant Protein Sources

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gasem tahan

2016-06-01

Full Text Available Effect of electron beam irradiation on degradability coefficients and ruminal- postruminal digestibility of dry matter and crude protein of soybean meal, canola meal and Lathyrus sativus seed, irradiated at doses of 50, 100 and 150 kGy was investigated. Ruminal degradability of dry matter and crude protein was determined by in situ method using two cannulated Holstein heifers. Ruminal- postruminal digestibility of dry matter and crude protein was determined by in situ (nylon bag-in vitro (daisy digestor techniques. Data analyzed using SAS software as randomized completely design and the treatment means were compared using Tukey test. The results indicated that irradiation had no effect on dry matter, ether extract and ash content of feeds. In soybean meal, washout fraction and potentially degradable fraction of dry matter and crude protein was higher and lower at dose of 150 kGy irradiation than other treatments, respectively, and degradation rate constant and ruminal effective degradability of dry matter and crude protein was lower at all doses of irradiation than untreated soybean meal. In canola meal, irradiation at doses of 50 and 100 kGy decreased washout fraction and increased potentially degradable fraction of crude protein compared with untreated canola meal. In Lathyrus sativus seed, only potentially degradable fraction of dry matter and crude protein was lower at dose of 150 kGy irradiation than untreated Lathyrus sativus seed. Ruminal digestibility of crude protein decreased in soybean meal at doses of 100 and 150 kGy irradiation and for canola meal at all doses of irradiation than untreated samples. Total tract digestibility of crude protein decreased in soybean meal at dose of 150 kGy irradiation and for canola meal at all doses of irradiation than untreated samples. In Lathyrus sativus seed, ruminal-postruminal digestibility and total tract digestibility of dry matter increased at doses of 100 and 150 kGy irradiation than untreated
Influence of feeding varying crude protein and digestible energy ...

African Journals Online (AJOL)

Influence of feeding varying crude protein and digestible energy levels on the development of individual muscles, rate of lean and fat deposition in pigs reared from 9 to 60kg liveweight in a humid tropical environment.
The effect of gamma irradiation on the chemical composition and digestible crude protein of poultry excreta

International Nuclear Information System (INIS)

Al-Masri, M.R.

1994-06-01

The changes in the chemical composition, digestible crude protein and cell-wall constituents for two types of excreta of laying hens were studied. In type I, excreta were dried at 170-180 C for 10 minutes whereas in type II dried at 55-60 C for several days. Each type was divided into two parts, the first stored for 3 months with the control. The second part was irradiated by gamma irradiation at 100 KGy and stored for 3 months with the control. The results indicated that here was significant decrease in the crude fibre (CF), NDF and ADF between the samples and the control, for the types I and II where CF, NDF and ADF values, before and after storage, decreased by 12%, 5% and 6%, respectively, ADL values decreased by 8% (I) and 3%(II). Hemicellulose and soluble carbohydrate (NFE) values increased by 5% and 7% for types I and II respectively as a result of irradiation in comparison to the control before and after storage. Gamma irradiation had no effect on crude protein, crude fat, crude ash and digested crude protein for types I and II before and after storage. Drying type I at high temperature in comparison to type II, before and after storage, decreased the crude protein values by 16%. Digested crude protein and CF, decreased 12% and NDF by 7%. Storage of excreta after drying had no effect on the chemical changes due to irradiation for types I and II. (author). 23 refs., 6 figs., 7 tabs
Biorefinery methods for separation of protein and oil fractions from rubber seed kernel

NARCIS (Netherlands)

Widyarani, R.; Ratnaningsih, E.; Sanders, J.P.M.; Bruins, M.E.

2014-01-01

Biorefinery of rubber seeds can generate additional income for farmers, who already grow rubber trees for latex production. The aim of this study was to find the best method for protein and oil production from rubber seed kernel, with focus on protein recovery. Different pre-treatments and oil
Concentration and entry rate of amino acids in buffalo calves fed on two planes of crude protein

International Nuclear Information System (INIS)

Verma, D.N.; Singh, U.B.; Varma, A.; Ranjhan, S.K.

1974-01-01

Amino acid entry rates into the body pool have been estimated in buffalo calves using a single injection isotope dilution technique. The animals received 2 levels of crude protein, 13 percent lower and 19 percent higher than NRC recommendation. The concentrations of free amino acid in plasma were 5.49 and 7.17 mg/100 ml in animals fed on low and high crude protein diet, respectively. There was significant differences in the plasma amino acid concentration and entry rates between the groups. Amino acid entry rates were 79.17 and 117.78 mg per min in groups fed on low and high plane of crude protein respectively, showing that availability of amino acid is better in animals given ratio high in crude protein contents. (author)
ORGANIC MATTER AND CRUDE PROTEIN DEGRADATION SYNCHRONY IN DIETS SELECTED BY RANGE GOATS.

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Rafael RamÃrez OrduÃ±a

2010-09-01

Full Text Available The study was carried out with the aim to asses the synchrony of organic matter and crude protein degradation in the rumen of diets selected by range goats through two years. Five esophageal cannulated adult male goats were used to collect extrusa samples during summer (August 9â€“13 and autumn (November 29 â€“December 3 of 2006, winter (February 20 â€“ 24, spring (April 29 â€“May 5, summer (September 10â€“15 and autumn (December 4â€“8 of 2007 and winter (February 20 â€“ 25 and spring (May 9 â€“13 of 2008. Extrusa samples were subjected to chemical analysis to determine organic matter (OM, crude protein (CP in situ and in vitro true digestibility of dry matter. OM and CP intake were estimated by total fecal collection. Effective extent of degradation of the OM and CP was calculated hourly and total 24 hours. From the hourly quantity of OM and CP degraded, a synchrony index of CP to OM was calculated, and from the total 24 hours degradation, degraded organic matter intake and crude protein intake were also estimated. Sampling date was the main effect that determined the variation of diet OM and CP degradation parameters. Degraded crude protein intake as a proportion of degraded OM was affected by sampling date and was correlated to rainfall. During winter of the first year degraded crude protein intake was below the requirements for maintenance or to promote growth for range goats weighing 40 kg. Even though, synchrony index between OM and CP degradation was affected by sampling date goats maintained a high synchrony index throughout the years.
Urea metabolism in buffalo calves fed on rations containing two levels of crude protein

International Nuclear Information System (INIS)

Verma, D.N.; Singh, U.B.; Lal, M.; Varma, A.; Ranjhan, S.K.

1974-01-01

Urea entry rates into the body pools of Murrah Buffalo calves have been estimated using a single injection isotope dilution technique using 14 C-urea. The animals were fed two levels of crude proteins, namely, 13 percent lower and 19 percent higher than N.R.C. recommendations. Results show that the recycling of urea is significantly better in animals given low crude protein contents. (M.G.B.)
Influence of Crude Protein Intake on the Duration of Delivery and Litter Size in Sows

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D. Tydlitát

2008-01-01

Full Text Available The aim of the study was to evaluate the influence of different intakes of crude protein during the period from 94 to 100 days of pregnancy to the parturition, lengths of pregnancy and delivery, number and birth weights of piglets and concentrations of progesterone, 17-β estradiol and cortisol on days 100, 110 and 114 of pregnancy in sows. Daily feed intake of the sow represented 2.5 kg of complete mixtures containing 13% (group A, n = 23, 15% (group B, n = 52, 18% (group C, n = 10 and 21% (group D, n = 10 of crude protein. Lengths of pregnancy in experimental groups were not significantly different. The mean durations of delivery synchronously increased with the intake of crude protein; significant difference was found between groups A (4.5 h and D (8.6 h (p p < 0.05. The average birth weights of piglets did not differ between experimental groups. No statistical differences in hormone concentrations were found between experimental groups. High intake of crude protein in sows before parturition prolonged delivery and increased the number of stillborn piglets.
Mineral, vitamin C and crude protein contents in kale (Brassica ...

African Journals Online (AJOL)

ajl yemi

2011-10-27

Oct 27, 2011 ... Key words: Kale (Brassica oleracea var. acephala), harvesting stage, vitamin C, crude protein, mineral content. .... L-ascorbic acid (or vitamin C) in plant tissues. .... Cooking methods of Brassica rapa affect the preservation of.
Proteome analysis of the almond kernel (Prunus dulcis).

Science.gov (United States)

Li, Shugang; Geng, Fang; Wang, Ping; Lu, Jiankang; Ma, Meihu

2016-08-01

Almond (Prunus dulcis) is a popular tree nut worldwide and offers many benefits to human health. However, the importance of almond kernel proteins in the nutrition and function in human health requires further evaluation. The present study presents a systematic evaluation of the proteins in the almond kernel using proteomic analysis. The nutrient and amino acid content in almond kernels from Xinjiang is similar to that of American varieties; however, Xinjiang varieties have a higher protein content. Two-dimensional electrophoresis analysis demonstrated a wide distribution of molecular weights and isoelectric points of almond kernel proteins. A total of 434 proteins were identified by LC-MS/MS, and most were proteins that were experimentally confirmed for the first time. Gene ontology (GO) analysis of the 434 proteins indicated that proteins involved in primary biological processes including metabolic processes (67.5%), cellular processes (54.1%), and single-organism processes (43.4%), the main molecular function of almond kernel proteins are in catalytic activity (48.0%), binding (45.4%) and structural molecule activity (11.9%), and proteins are primarily distributed in cell (59.9%), organelle (44.9%), and membrane (22.8%). Almond kernel is a source of a wide variety of proteins. This study provides important information contributing to the screening and identification of almond proteins, the understanding of almond protein function, and the development of almond protein products. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.
Crude protein changes on grassland along a degradation gradient ...

African Journals Online (AJOL)

The aim with this investigation was to quantify the impact of different veld condition classes, viz. poor, moderate and good on soil-water utilization (SWU: crude protein produced per unit of evapotranspiration), during four growing seasons (2000/01 – 2003/2004). Evapotranspiration was determined by quantifying the ...
Crude protein changes on grassland along a degradation gradient ...

African Journals Online (AJOL)

Evapotranspiration was determined by quantifying the soil-water balance equation with the aid of runoff plots and soil-water content measurements. Crude protein ... The study shows that it is important to keep grassland in optimal condition to utilize limited soil water for sustainable plant and therefore animal production.
Degradation of Crude Protein in Groundnut Cake, Guinea Grass ...

African Journals Online (AJOL)

Three West African dwarf rams fitted with rumen cannula, were used in a completely randomized design for degradation of crude protein (CP) of groundnut cake (GNC), Panicum maximum, rumen epithelial scraping (RES), and diets containing increasing levels of RES. Concentrate diets were formulated such that 0% (A), ...
Effect of dietary crude protein level on the performance and ...

African Journals Online (AJOL)

ویرایه

2013-06-26

Jun 26, 2013 ... The effects of increasing dietary levels of crude protein (CP) on growth, feed intake, feed efficiency and nutrient apparent ... matter intake (DMI) than the kids fed with 10.5, 12.8, .... Food and Agriculture Organization. Database ...

Urea metabolism in Zebu calves fed on diets of dierent crude protein contents

International Nuclear Information System (INIS)

Sharma, P.K.; Singh, U.B.; Verma, D.N.; Lal, M.; Ranjhan, S.K.

1974-01-01

The entry rates of urea into the body pool of urea have been estimated in Zebu calves using a single injection isotope dilution technique using 14 C-urea. The excretion rates of urea were calculated by estimating total urine over 24 h and urea content. The calves were fed 2 levels of crude protein, i.e., 25 percent lower and 25 percent higher than NRC recommendations. Results show that the degradation of urea is significantly better in animals given rations low in crude protein contents. (M.G.B.)
An assessment of differences in the ruminal degradability and intestinal digestibility of crude protein in brewer’s grains and maize draff

Directory of Open Access Journals (Sweden)

Vladimír Majer

2012-01-01

Full Text Available The submitted thesis aims to assess the differences between the ruminal degradability and intestinal digestibility of crude protein contained in brewer’s grains (BG and maize draff (AMG. The effectiveness of ruminal degradability was tested using the “in sacco” method on 3 dry Holstain cows fitted with rumen cannulas. The dynamics of ruminal degradability of crude protein (CP was detected after 0, 4, 8, 16, and 24 hours of samples incubation in the rumen. The intestinal digestibility of crude protein undegradable in the rumen was determined using the “mobile bag” method on 3 dry Holstain cows fitted with duodenal cannulas. The crude protein degradability of BG was detected in the above-mentioned hours (%: 4.06; 18.16; 32.40; 38.56, and 50.70; crude protein degradability of AMG: 42.04; 63.56; 84.47; 85.16, and 87.19. The effectiveness of rumen degradability of BG crude protein at the rate of passage of rumen content 6 % per hour was calculated at 35.33 % and that of AMG, at 76.29 %. Intestinal digestibility of BG crude protein and dry matter at the rate of passage of intestinal content 6 % per hour was calculated at 79.41 % and 22.84 %, respectively, and that of AMG, at 57.01 % and 11.33 %, respectively. The differences between the indicators of both feedstuffs were significant (P < 0.05. The results show that BG are mostly a source of crude protein with higher intestinal digestibility than AMG.
Mineral, vitamin C and crude protein contents in kale ( Brassica ...

African Journals Online (AJOL)

This study compares mineral, vitamin C and crude protein contents at different harvesting stages in kale (Brassica oleraceae var. acephala). Three different harvest periods as first harvest stage (at the rosette stage), second harvest stage (at the budding stage) and third harvest stage (at the flowering/blooming stage) were ...
Effects of reducing dietary crude protein and metabolic energy in ...

African Journals Online (AJOL)

The objective of this experiment was to determine the effects of a pure reduction in the dietary crude protein (CP) and metabolic energy (ME) contents on growth performance, nutrient digestibility, blood profile, faecal microflora and odour gas emission in weaned pigs. A total of 80 weaned piglets ((Landrace × Yorkshire) ...
Recovery and subsequent characterization of polyhydroxybutyrate from Rhodococcus equi cells grown on crude palm kernel oil

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Nadia Altaee

2016-07-01

Full Text Available The gram-positive bacterium Rhodococcus equi was isolated from fertile soil, and mineral salt media (MM and trace elements were used to provide the necessary elements for its growth and PHB production in addition to using crude palm kernel oil (CPKO 1% as the carbon source. Gas chromatography (GC demonstrated that the composition of the recovered biopolymer was homopolymer polyhydroxybutyrate (PHB. The strain of the present study has a dry biomass of 1.43 (g/l with 38% PHB, as determined by GC. The recovered PHB was characterized by NMR to study the chemical structure. In addition, DSC and TGA were used to study the thermal properties of the recovered polymer, where the melting temperature (Tm was 173 °C, the glass transition temperature (Tg was 2.79 °C, and the decomposition temperature (Td was 276 °C. Gel permeation chromatography (GPC was used to study the molecular mass of the recovered PHB in addition to comparing the results with other studies using different bacteria and substrates, where the molecular weight was 642 kDa, to enable its usage in many applications. The present study demonstrated the use of an inexpensive substrate for PHB production, i.e., using gram-positive bacteria to produce PHB polymer with characterization.
Use of palm kernel cake for animal feed

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Kuprasert, S.

2001-11-01

Full Text Available Palm kernel cake (PKC, a by-product from the palm-oil industry, has the potential for use as a feed ingredient. Crude protein, fiber and metabolizable energy contents of PKC are 12-18%, 18-13% and 1,940- 2,490 kcal/kg, respectively. Availability of amino acid in PKC are approximately 60-70% for chickens and 65-70% for pigs. With fat supplementation, PKC can be used up to 20% in broiler diet and can be increased to 30-40% with further addition of methionine and lysine. For the diets of pullets and laying hen, PKC can be used 30% and 20% respectively if supplemented with fat, methionine and lysine. PKC can be used 30% in diet for grower (30-60 kg and 50% in diet for finisher pigs (60-90 kg., respectively, if supplemented with lysine and cane molasses.
The influences of ambient temperature and crude protein levels on performance and serum biochemical parameters in broilers.

Science.gov (United States)

Liu, Q W; Feng, J H; Chao, Z; Chen, Y; Wei, L M; Wang, F; Sun, R P; Zhang, M H

2016-04-01

This study was undertaken to investigate the effects of ambient temperature, crude protein levels and their interaction on performance and serum biochemical parameters of broiler chickens. A total of 216 Arbor Acre broiler chickens (108 males and 108 females) were used in a 2 × 3 factorial arrangement and randomly reared at two temperatures (normal temperature: 23 °C; daily cyclic high temperature: 28-32 °C) and fed on three diets with different crude protein levels (153.3, 183.3 or 213.3 g/kg, with constant essential amino acids) from 28 to 42 days of age. Daily cyclic high ambient temperature decreased final body weight, average daily weight gain, average daily feed intake and serum total protein contents (p chickens was interacted by daily cyclic high ambient temperature and dietary crude protein levels (p = 0.003). These results indicated that daily cyclic high ambient temperature had a great effect on performance and serum biochemical parameters in broiler chickens, whereas dietary crude protein levels affected them partially. Journal of Animal Physiology and Animal Nutrition © 2015 Blackwell Verlag GmbH.
EFFECTS OF PROTEIN-XANTHOPHYLL (PX CONCENTRATE OF ALFALFA ADDITIVE TO CRUDE PROTEIN-REDUCED DIETS ON NITROGEN EXCRETION, GROWTH PERFORMANCE AND MEAT QUALITY OF PIGS

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Eugeniusz GRELA

2009-06-01

Full Text Available The infl uence of protein-xanthophyll (PX concentrate of alfalfa supplement to crude protein-reduced diets was examined in relation to nitrogen excretion, performance parameters and pig meat quality. The investigations included 60 growers (PL x PLW x Duroc crossbreeds assigned to 3 groups. The conclusion is that there is a large potential to decrease nitrogen emission to the environment by 10% lowering of dietary crude protein intake along with reduced animal growth rate and elevated mixture utilization. Inclusion of a protein-xanthophyll concentrate (PX of alfalfa to the diet is likely to diminish disadvantageous productive parameters arising from limiting of total crude protein level in relation to the requirements of pigs feeding norms [1993]. At the same time, it improves feed nitrogen utilization and reduces noxious odour emissions from a piggery. The components of a protein-xanthophyll concentrate (PX contribute to increased liver and kidney weight.
Rate and extent of ruminal degradation of crude protein from ...

African Journals Online (AJOL)

Predicted crude protein degradation was calculated at rate constants for outflow of 0.04 and 0.06/h respect- ively. ... as buffers, an ionophore and an antibiotic according to general .... the non-bird resistant ('sweet') varieties. Ruminal .... have been affected by both the particle type and the math- ematical model we used.
Effect Of Crude Protein Levels And Follicle Stimulation On Egg ...

African Journals Online (AJOL)

Two groups received 16% crude protein (CP) level diets and the other two groups, 32%. One each of the two groups received follicle stimulation, induced by administration of Clomifene citrate (1.5mg/kg) via cathetered 5ml syringe through the 10week experimental period, with feed and water offered ad libitum.
Effects of dietary crude protein and calcium/ phosphorus content on ...

African Journals Online (AJOL)

This experiment was conducted to examine the effect of three levels of crude protein (CP) (NRC, 15% more than NRC and 15% less than NRC) and three levels of Ca and available P (Av. P) (NRC, 15% more than NRC and 15% less than NRC) on performance of broilers from hatching until 21 days of age. The experimental ...
Crude protein, fibre and phytic acid in vitro digestibility of selected legume and buckwheat samples

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Petra Vojtíšková

2013-01-01

Full Text Available The aim of this study was to determine crude protein, fibre and phytic acid in vitro digestibility of selected legumes and buckwheat products. All analyses except the phytic acid contents were performed in the line with the Commission Regulation (EC No. 152/2009. A modified version of Holt’s Method was used for phytic acid (phytate determination. None of all samples contained more than 11% of moisture. Soybeans are rich in crude protein; they contain nearly 40% of this compound. The content of crude protein in buckwheat flours was about 14%. The highest amount of phytate was found in common beans and soybeans-about 2 g/100 g of dry matter. On the other hand, the lowest phytate content was observed in buckwheat pasta (F. esculentum groats was 1.9 g per 100 g of dry matter. In vitro digestibility was determined using an incubator Daisy and pepsin enzymes and the combination of pepsin and pancreatin. The highest coefficient of crude protein digestibility was discovered to be in peels and wholemeal flour. The greatest fibre digestibility coefficients were obtained for peels, which contain about 65% of fibre in their dry matter. When pepsin was used, a higher phytic acid digestibility coefficient for G. max, Ph. vulgaris, peels, flour, groats and broken groats was observed; while when the combination of pepsin and pancreatin was used, higher phytic acid digestibility coefficients for peas, lentil and wholemeal flour were observed.
The use of crude protein content to predict concentrations of lysine ...

African Journals Online (AJOL)

Correlations were determined between the crude protein (CP) and lysine or methionine concentrations of grain from wheat (cultivar: palmiet), barley (cultivar: clipper) and triticale (cultivar: usgen 19) grown in the Western Cape region of South Africa. Twenty samples of varying CP content were collected for each grain type ...
Aflatoxin contamination of developing corn kernels.

Science.gov (United States)

Amer, M A

2005-01-01

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

DEFF Research Database (Denmark)

Winning, H.; Viereck, N.; Wollenweber, B.

2009-01-01

at the vegetative growth stage had little effect on the parameters investigated. For the first time, H-1 HR-MAS NMR spectra of grains taken during grain-filling were analysed by an advanced multiway model. In addition to the results from the chemical protein analysis and the H-1 HR-MAS NMR spectra of single kernels...... was to examine the implications of different drought treatments on the protein fractions in grains of winter wheat using H-1 nuclear magnetic resonance spectroscopy followed by chemometric analysis. Triticum aestivum L. cv. Vinjett was studied in a semi-field experiment and subjected to drought episodes either...... at terminal spikelet, during grain-filling or at both stages. Principal component trajectories of the total protein content and the protein fractions of flour as well as the H-1 NMR spectra of single wheat kernels, wheat flour, and wheat methanol extracts were analysed to elucidate the metabolic development...
Robust Kernel (Cross-) Covariance Operators in Reproducing Kernel Hilbert Space toward Kernel Methods

OpenAIRE

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

2016-01-01

To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...
Effect of Protein Molecular Weight Distribution on Kernel and Baking Characteristics and Intra-varietal Variation in Hard Spring Wheats

Science.gov (United States)

Specific wheat protein fractions are known to have distinct associations with wheat quality traits. Research was conducted on 10 hard spring wheat cultivars grown at two North Dakota locations to identify protein fractions that affected wheat kernel characteristics and breadmaking quality. SDS ext...
Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

Directory of Open Access Journals (Sweden)

Ujjwal Maulik

Full Text Available 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.
Protein Profiles Reveal Diverse Responsive Signaling Pathways in Kernels of Two Maize Inbred Lines with Contrasting Drought Sensitivity

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Liming Yang

2014-10-01

Full Text Available Drought stress is a major factor that contributes to disease susceptibility and yield loss in agricultural crops. To identify drought responsive proteins and explore metabolic pathways involved in maize tolerance to drought stress, two maize lines (B73 and Lo964 with contrasting drought sensitivity were examined. The treatments of drought and well water were applied at 14 days after pollination (DAP, and protein profiles were investigated in developing kernels (35 DAP using iTRAQ (isobaric tags for relative and absolute quantitation. Proteomic analysis showed that 70 and 36 proteins were significantly altered in their expression under drought treatments in B73 and Lo964, respectively. The numbers and levels of differentially expressed proteins were generally higher in the sensitive genotype, B73, implying an increased sensitivity to drought given the function of the observed differentially expressed proteins, such as redox homeostasis, cell rescue/defense, hormone regulation and protein biosynthesis and degradation. Lo964 possessed a more stable status with fewer differentially expressed proteins. However, B73 seems to rapidly initiate signaling pathways in response to drought through adjusting diverse defense pathways. These changes in protein expression allow for the production of a drought stress-responsive network in maize kernels.
Nutritional value of high fiber co-products from the copra, palm kernel, and rice industries in diets fed to pigs.

Science.gov (United States)

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

Growth and carcass production responses of EPMp broiler ducks to various levels of crude fiber and protein in the diet

Directory of Open Access Journals (Sweden)

Maijon Purba

2014-10-01

Full Text Available Inclusion of crude fiber in diet is important for duck growth, but there is a limit in its use in order for the ducks to grow normally. The purpose of this study was to evaluate growth and carcass production responses of EPMp broiler ducks under different levels of crude fiber and protein in diets. Four hundreds and twenty day old ducklings were allocated into 7 treatments with 6 replications and each replication consisted of 10 ducks. The treatments were the factorial combinations of crude fiber content of 6 or 9% and protein content of 19, 21, or 23%; and BR-1 (starter diet as positive control. The variables observed were: feed intake, weekly body weight, and percentage of carcass production. The results showed that all variables observed were not significantly affected by CF content, but highly significantly affected by crude protein levels in diet. Protein content of 19 or 21% in diet resulted in a better performance for EPMp ducks. The inclusion of high CF in diet did not affect carcass percentage, except for reduced abdominal fat. The study implies that administration of high CF (6 or 9% with a protein content of 19 or 21% in the diet are still acceptable to EPMp ducks at 12 weeks.
Supplementation of suckling beef calves with different levels of crude protein on tropical pasture.

Science.gov (United States)

Lopes, Sidnei Antonio; Paulino, Mário Fonseca; Detmann, Edenio; de Campos Valadares Filho, Sebastião; Valente, Eriton Egídio Lisboa; Barros, Lívia Vieira; Cardenas, Javier Enrique Garces; Almeida, Daniel Mageste; Martins, Leandro Soares; Silva, Aline Gomes

2014-02-01

The effects of supplementation with different levels of crude protein on performance, intake and nutrient digestibility and efficiency of microbial protein synthesis in suckling beef calves on pasture were assessed. Fifty-five calves, with an average age of 100 days and an initial average body weight of 110 ± 7.5 kg and their respective dams, were used. The experimental design was completely randomised with five treatments and 11 replications. The experimental treatments for calves were as follows: control = calves received only mineral mixture; supplementation levels = calves received supplement containing 8, 19, 30 or 41% of crude protein (CP, at a rate of 0.5% of body weight (BW)). The cows received only mineral mixture ad libitum. Supplemented calves had higher (P calves. There was no difference in total dry matter (DM) intake (P > 0.1). However, intake of dry matter forage (DMF) presented cubic profiles (P calves on creep feeding. The intake of supplements with CP levels between 8 and 30% partially replaces of the pasture ingested by calves and increases the digestibility of the diet.
Complex use of cottonseed kernels

Energy Technology Data Exchange (ETDEWEB)

Glushenkova, A I

1977-01-01

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

NARCIS (Netherlands)

Cone, J.W.; Gelder, van A.H.; Mathijssen-Kamman, A.A.; Hindle, V.A.

2006-01-01

Grass samples were grown on a clay or sandy soil, fertilised with 150 or 300 kg N/ha per year, and harvested on different days during two consecutive growing seasons. The grass samples were stored frozen or ensiled after wilting to approximately 250 or 450 g DM/kg. The recoveries of crude protein
Recognition of higher order patterns in proteins: immunologic kernels.

Directory of Open Access Journals (Sweden)

Robert D Bremel

Full Text Available By applying analysis of the principal components of amino acid physical properties we predicted cathepsin cleavage sites, MHC binding affinity, and probability of B-cell epitope binding of peptides in tetanus toxin and in ten diverse additional proteins. Cross-correlation of these metrics, for peptides of all possible amino acid index positions, each evaluated in the context of a ±25 amino acid flanking region, indicated that there is a strongly repetitive pattern of short peptides of approximately thirty amino acids each bounded by cathepsin cleavage sites and each comprising B-cell linear epitopes, MHC-I and MHC-II binding peptides. Such "immunologic kernel" peptides comprise all signals necessary for adaptive immunologic cognition, response and recall. The patterns described indicate a higher order spatial integration that forms a symbolic logic coordinating the adaptive immune system.
The use of near infrared transmittance kernel sorting technology to salvage high quality grain from grain downgraded due to Fusarium damage

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Michael E. Kautzman

2015-03-01

Full Text Available The mycotoxins associated with specific Fusarium fungal infections of grains are a threat to global food and feed security. These fungal infestations are referred to as Fusarium Head Blight (FHB and lead to Fusarium Damaged Kernels (FDK. Incidence of FDK >0.25% will lower the grade, with a tolerance of 5% FDK for export feed grain. During infestation, the fungi can produce a variety of mycotoxins, the most common being deoxynivalenol (DON. Fusarium Damaged Kernels have been associated with reduced crude protein (CP, lowering nutritional, functional and grade value. New technology has been developed using Near Infrared Transmittance (NIT spectra that estimate CP of individual kernels of wheat, barley and durum. Our objective is to evaluate the technology's capability to reduce FDK and DON of downgraded wheat and ability to salvage high quality safe kernels. In five FDK downgraded sources of wheat, the lowest 20% CP kernels had significantly increased FDK and DON with the high CP fractions having decreased FDK and DON, thousand kernel weights (TKW and bushel weight (Bu. Strong positive correlations were observed between FDK and DON (r = 0.90; FDK and grade (r = 0.62 and DON and grade (r = 0.62. Negative correlations were observed between FDK and DON with CP (r = −0.27 and −0.32; TKW (r = −0.45 and −0.54 and Bu (r = −0.79 and −0.74. Results show improved quality and value of Fusarium downgraded grain using this technology.
Performance and Nutrient Retention of Broilers fed Treated Pumpkin ...

African Journals Online (AJOL)

A study was conducted to examine the Proximate Composition of raw Pumpkin Kernel and to assess its nutritional value with broilers. Analysis showed that the Kernel contained crude protein level (38.51%), crude fibre (13.34%), ether extract (42.69), total ash (5.14%), nitrogen free extract (0.32%), calcium (0.29%) and ...
In vitro crude protein digestibility of Tenebrio molitor and Hermetia illucens insect meals and its correlation with chemical composition traits

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Stefania Marono

2015-07-01

Full Text Available The aims of this study were to evaluate the correlation between in vitro crude protein digestibility coefficients of insect meals from Tenebrio molitor (TI and Hermetia illucens (HI and their chemical composition traits as well as to develop regression equations able to estimate the in vitro crude protein digestibility (CPd from proximate analysis of insect meals. Twelve samples of insect meals (6 from TM larvae, TM 1-6 and 6 from HI larvae, HI 1-6 were obtained from different producers and analysed for chemical composition and in vitro crude protein digestibility by a two-step enzymatic method (digestion with pepsin and trypsin-enriched pancreatin. For both insect meal samples, CPd was negatively correlated to ADF and chitin contents, while just for HI there was a positive correlation (P<0.01 between CP percentage of the samples and CPd. For both insect meals the former variable chosen in the stepwise analysis was the chitin, explaining the 79.45% of CPd variability for Tenebrio molitor samples and the 98.30% for Hermetia illucens. In the second step, the amount of protein linked to ADF was added in the model for T. molitor and CP for H. illucens samples. The coefficients chitin is the main constituent of insect body able to affect the crude protein digestibility of Tenebrio molitor and Hermetia illucens larvae meals estimated by an in vitro enzymatic method.
Exploiting graph kernels for high performance biomedical relation extraction.

Science.gov (United States)

Panyam, Nagesh C; Verspoor, Karin; Cohn, Trevor; Ramamohanarao, Kotagiri

2018-01-30

Relation extraction from biomedical publications is an important task in the area of semantic mining of text. Kernel methods for supervised relation extraction are often preferred over manual feature engineering methods, when classifying highly ordered structures such as trees and graphs obtained from syntactic parsing of a sentence. Tree kernels such as the Subset Tree Kernel and Partial Tree Kernel have been shown to be effective for classifying constituency parse trees and basic dependency parse graphs of a sentence. Graph kernels such as the All Path Graph kernel (APG) and Approximate Subgraph Matching (ASM) kernel have been shown to be suitable for classifying general graphs with cycles, such as the enhanced dependency parse graph of a sentence. In this work, we present a high performance Chemical-Induced Disease (CID) relation extraction system. We present a comparative study of kernel methods for the CID task and also extend our study to the Protein-Protein Interaction (PPI) extraction task, an important biomedical relation extraction task. We discuss novel modifications to the ASM kernel to boost its performance and a method to apply graph kernels for extracting relations expressed in multiple sentences. Our system for CID relation extraction attains an F-score of 60%, without using external knowledge sources or task specific heuristic or rules. In comparison, the state of the art Chemical-Disease Relation Extraction system achieves an F-score of 56% using an ensemble of multiple machine learning methods, which is then boosted to 61% with a rule based system employing task specific post processing rules. For the CID task, graph kernels outperform tree kernels substantially, and the best performance is obtained with APG kernel that attains an F-score of 60%, followed by the ASM kernel at 57%. The performance difference between the ASM and APG kernels for CID sentence level relation extraction is not significant. In our evaluation of ASM for the PPI task, ASM
DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding.

Science.gov (United States)

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

2017-10-01

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

Directory of Open Access Journals (Sweden)

Wahyu Pamungkas

2011-12-01

Full Text Available Two experiments were conducted to evaluate the hydrolysis of fiber content in palm kernel meal (PKM by sheep rumen liquor enzyme and to know the apparent digestibility coefficient of hydrolyzed PKM for catfish Pangasius hypophthalmus. The first trial examined effectivity of sheep rumen liquor enzyme to decrease crude fiber content of PKM. The added volume of sheep rumen liquor enzyme was 0, 20, 40, 60, 80, and 100 mL/kg PKM and then it was incubated for 0, 12, and 24 hours. A factorial completely randomized experimental design consisted of 2 variables and triplicates were selected. The second trial was conducted to evaluate the apparent digestibility coefficients of hydrolized PKM for catfish. Apparent digestibility coefficients were determined using chromic oxide indicator added to both reference and test diets. The feed ingredients used in the trial were hydrolyzed PKM (PKMe and unhydrolyzed PKM (PKM. Ten fishes with weighing around 20 g were used in the trial and held in 80 l tanks. Feces were collected from three replicate groups of fish using a fecal collection column attached to fish rearing tank. PKM hydrolyzed with 100 mL/kg and incubated for 24 hour showed the lowest crude fiber content (6.99% among the treatments (P<0.05. Apparent digestibility coefficient of hydrolyzed PKM was 57.57% compared with unhydrolyzed PKM 15.31%. Based on the evaluation in those parameters it was concluded that sheep rumen liquor enzyme added to PKM was effective to decrease crude fiber content of PKM and improve apparent digestibility coefficient of PKM for catfish.
Effect of Inoculum Dosage Aspergillus niger and Rhizopus oryzae mixture with Fermentation Time of Oil Seed Cake (Jatropha curcas L) to the content of Protein and Crude Fiber

Science.gov (United States)

Kurniati, T.; Nurlaila, L.; Iim

2017-04-01

Jatropha curcas L already widely cultivated for its seeds pressed oil used as an alternative fuel. This plant productivity per hectare obtained 2.5-5 tonnes of oil/ha / year and jatropha seed cake from 5.5 to 9.5 tonnes/ha/year, nutrient content of Jatropha curcas seed L potential to be used as feed material, However, the constraints faced was the low crude protein and high crude protein. The purpose of the research was to determine the dosage of inoculum and fermentation time of Jatropha seed cake by a mixture of Aspergillus niger and Rhizopus oryzae on crude protein and crude fibre. The study was conducted by an experimental method using a Completely Randomised Design (CRD) factorial design (3×3). The treatment consisted of a mixture of three dosage levels of Aspergillus niger and Rhizopus oryzae (= 0.2% d1, d2 and d3 = 0.3% = 0.4%) and three levels of fermentation time (w1 = 72 hours, 96 hours and w2 = w3 = 120 hours) each repeated three times. The parameters measured were crude protein and crude fibre. The results showed that dosages of 0.3% (Aspergillus niger Rhizopus oryzae 0.15% and 0.15%) and 72 hours (d2w1) is the dosage and the optimal time to generate the highest crude protein content of 21.11% and crude fibre amounted to 21.36%.
In situ ruminal crude protein degradability of by-products from cereals, oilseeds and animal origin

NARCIS (Netherlands)

Habib, G.; Khan, N.A.; Ali, M.; Bezabih, M.

2013-01-01

The aim of this study was to establish a database on in situ ruminal crude protein (CP) degradability characteristics of by-products from cereal grains, oilseeds and animal origin commonly fed to ruminants in Pakistan and South Asian Countries. The oilseed by-products were soybean meal, sunflower
Effects of Cerium and Titanium Oxide Nanoparticles in Soil on the Nutrient Composition of Barley (Hordeum vulgare L. Kernels

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Filip Pošćić

2016-06-01

Full Text Available The implications of metal nanoparticles (MeNPs are still unknown for many food crops. The purpose of this study was to evaluate the effects of cerium oxide (nCeO2 and titanium oxide (nTiO2 nanoparticles in soil at 0, 500 and 1000 mg·kg−1 on the nutritional parameters of barley (Hordeum vulgare L. kernels. Mineral nutrients, amylose, β-glucans, amino acid and crude protein (CP concentrations were measured in kernels. Whole flour samples were analyzed by ICP-AES/MS, HPLC and Elemental CHNS Analyzer. Results showed that Ce and Ti accumulation under MeNPs treatments did not differ from the control treatment. However, nCeO2 and nTiO2 had an impact on composition and nutritional quality of barley kernels in contrasting ways. Both MeNPs left β-glucans unaffected but reduced amylose content by approximately 21%. Most amino acids and CP increased. Among amino acids, lysine followed by proline saw the largest increase (51% and 37%, respectively. Potassium and S were both negatively impacted by MeNPs, while B was only affected by 500 mg nCeO2·kg−1. On the contrary Zn and Mn concentrations were improved by 500 mg nTiO2·kg−1, and Ca by both nTiO2 treatments. Generally, our findings demonstrated that kernels are negatively affected by nCeO2 while nTiO2 can potentially have beneficial effects. However, both MeNPs have the potential to negatively impact malt and feed production.
Locally linear approximation for Kernel methods : the Railway Kernel

OpenAIRE

Muñoz, Alberto; González, Javier

2008-01-01

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

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Senyue Zhang

2016-01-01

Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.
PHOSPHOLIPIDS FROM PUMPKIN (Cucurbita moschata (Duch. Poir SEED KERNEL OIL AND THEIR FATTY ACID COMPOSITION

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Tri Joko Raharjo

2011-07-01

Full Text Available The phospholipids (PL of pumpkin (Cucurbita moschata (Duch Poir seed kernel and their fatty acid composition were investigated. The crude oil was obtained by maceration with isopropanol followed by steps of extraction yielded polar lipids. The quantitative determination of PLs content of the dried pumpkin seed kernel and their polar lipids were calculated based on the elemental phosphorus (P contents which was determined by means of spectrophotometric methods. PL classes were separated from polar lipids via column chromatography. The fatty acid composition of individual PL was identified by gas chromatography-mass spectrometry (GC-MS. The total of PL in the pumpkin seed kernels was 1.27% which consisted of phosphatidylcholine (PC, phosphatidylserine (PS and phosphatidyletanolamine (PE. The predominant fatty acids of PL were oleic and palmitic acid in PC and PE while PS's fatty acid were dominantly consisted of oleic acid and linoleic acid.
Kernel Machine SNP-set Testing under Multiple Candidate Kernels

Science.gov (United States)

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

2013-01-01

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

Science.gov (United States)

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

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

Science.gov (United States)

Zhang, Guangya; Ge, Huihua

2013-10-01

Understanding of proteins adaptive to hypersaline environment and identifying them is a challenging task and would help to design stable proteins. Here, we have systematically analyzed the normalized amino acid compositions of 2121 halophilic and 2400 non-halophilic proteins. The results showed that halophilic protein contained more Asp at the expense of Lys, Ile, Cys and Met, fewer small and hydrophobic residues, and showed a large excess of acidic over basic amino acids. Then, we introduce a support vector machine method to discriminate the halophilic and non-halophilic proteins, by using a novel Pearson VII universal function based kernel. In the three validation check methods, it achieved an overall accuracy of 97.7%, 91.7% and 86.9% and outperformed other machine learning algorithms. We also address the influence of protein size on prediction accuracy and found the worse performance for small size proteins might be some significant residues (Cys and Lys) were missing in the proteins. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Assessment of Grewia oppositifolia leaves as crude protein supplement to low-quality forage diets of sheep

NARCIS (Netherlands)

Khan, N.A.; Habib, G.

2012-01-01

In the tropical arid and semi-arid regions of many developing countries, sheep are predominantly grazed on low-quality pastures and stall-fed on crop residues. This study evaluated the potential of Grewia oppositifolia tree leaves as crude protein (CP) supplement to the low-quality diets of sheep in
Metabolic network prediction through pairwise rational kernels.

Science.gov (United States)

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

2014-09-26

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

Science.gov (United States)

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

2014-10-01

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

Science.gov (United States)

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

2016-12-01

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

Science.gov (United States)

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

2009-08-01

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

Science.gov (United States)

Rajan, S; Thirunalasundari, T; Jeeva, S

2011-04-01

To evaluate the phytochemical and anti-bacterial efficacy of the seed kernel extract of Mangifera indica (M. indica) against the enteropathogen, Shigella dysenteriae (S. dysenteriae), isolated from the diarrhoeal stool specimens. The preliminary phytochemical screening was performed by the standard methods as described by Harborne. Cold extraction method was employed to extract the bioactive compounds from mango seed kernel. Disc diffusion method was adopted to screen antibacterial activity. Minimum inhibitory concentration (MIC) was evaluated by agar dilution method. The crude extracts were partially purified by thin layer chromatography (TLC) and the fractions were analyzed by high performance thin layer chromatography (HPTLC) to identify the bioactive compounds. Phytochemical scrutiny of M. indica indicated the presence of phytochemical constituents such as alkaloids, gums, flavanoids, phenols, saponins, steroids, tannins and xanthoproteins. Antibacterial activity was observed in two crude extracts and various fractions viz. hexane, benzene, chloroform, methanol and water. MIC of methanol fraction was found to be (95±11.8) μg/mL. MIC of other fractions ranged from 130-380 μg/mL. The present study confirmed that each crude extracts and fractions of M. indica have significant antimicrobial activity against the isolated pathogen S. dysenteriae. The antibacterial activity may be due to the phytochemical constituents of the mango seed kernel. The phytochemical tannin could be the reason for its antibacterial activity. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.
Data-variant kernel analysis

CERN Document Server

Motai, Yuichi

2015-01-01

Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include
Investigations of the influence of the content of crude plant protein in the ration on the utilisation of urea in dairy cattle. 2

International Nuclear Information System (INIS)

Voigt, J.; Piatkowski, B.; Krawielitzki, R.; Adam, K.

1984-01-01

The metabolism of 15 N-urea in dairy cows was investigated in dependence on the crude protein content of the rations. With the energy concentration remaining unchanged, the rations contained 10.7(I), 13.7(II) and 17.1(III)% plant crude protein and, after the supplementation of 150 g urea per animal and day, a total of 13.8, 16.7 and 20.2% crude protein in the dry matter. The urea was intraruminally infused during the feeding in the morning and the evening. In the morning feeding of each 1st measuring day it was labelled with 27.5 atom-% 15 N-excess ( 15 N'). The degree of labelling with 15 N' of the N fraction of rumen fluid, contents of the duodenum, feces and milk, precipitable with trichloric acetic acid (TCA) decreased with the rising protein level of the ration. This effect was bigger than could be expected considering the low 15 N' quota in the total N of the ration. In the sequence I..III, 52.7, 32.2 and 30.6% of the 15 N' amount taken in passed the duodenal re-entrant cannula in TCA-precipitable form within 72 hours after 15 N application. 33.3, 21.9 and 22.6% were apparently absorbed in the intestines as TCA-precipitable N within 120 h after the 15 N' application. In the same period 31.7, 43.1 and 72.8% of the 15 N' taken in were excreted in urine. 12.3, 9.6 and 5.8% of the applied 15 N' were found in milk protein. One can conclude that the utilization of urea N decreases with the rising level of crude protein in the ration and that, however, urea N is still biochemically utilized when there is an excess of plant N in the ration. (author)
Increasing levels of crude protein in multiple supplements for grazing beef heifers in rainy season

Directory of Open Access Journals (Sweden)

Lívia Vieira de Barros

2015-06-01

Full Text Available The objective was to evaluate the effect of multiple supplements with differents levels of crude protein (CP or mineral supplements on the nutritional parameters and performance of beef heifers grazing Uruchloa decumbens in the rainy season. A complete random design was employed. The treatments were made up of increasing levels of CP in the multiple supplements and a control treatment (MM in which animals were offered only mineral mixture. Multiple supplements contained 17; 30; 43 and 56% of CP, for treatments CP17; CP30; CP43 and CP56, respectively. Average daily gain (ADG (g was 447.7; 554.6; 638.4; 587.9; 590.4, for treatments MM, CP17; CP30; CP43 and CP56, respectively. A quadratic effect of the levels of crude protein was found (p< 0.10 on ADG. A greater intake of dry matter (DM, organic matter (OM, CP, ether extract (EE, non-fibrous carbohydrates (NFC, total digestible nutrients (TDN, and digested dry matter (p< 0.10 was found in animals supplemented with multiple supplements. Multiple supplements increased the apparent digestibility coefficient of DM, CP, EE and NFC. Supply of multiple multiple supplements for heifers grazing in medium to high quality pastures in the rainy season improves the performance of the animals.
Approximate kernel competitive learning.

Science.gov (United States)

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

2015-03-01

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

Science.gov (United States)

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.
Classification With Truncated Distance Kernel.

Science.gov (United States)

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

2018-05-01

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

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Chenchao Zhao

2018-01-01

Full Text Available Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of using heat diffusion on a hypersphere to measure similarity has been previously proposed and tested by Lafferty and Lebanon [1], demonstrating promising results based on a heuristic heat kernel obtained from the zeroth order parametrix expansion; however, how well this heuristic kernel agrees with the exact hyperspherical heat kernel remains unknown. This paper presents a higher order parametrix expansion of the heat kernel on a unit hypersphere and discusses several problems associated with this expansion method. We then compare the heuristic kernel with an exact form of the heat kernel expressed in terms of a uniformly and absolutely convergent series in high-dimensional angular momentum eigenmodes. Being a natural measure of similarity between sample points dwelling on a hypersphere, the exact kernel often shows superior performance in kernel SVM classifications applied to text mining, tumor somatic mutation imputation, and stock market analysis.
A kernel for open source drug discovery in tropical diseases.

Science.gov (United States)

Ortí, Leticia; Carbajo, Rodrigo J; Pieper, Ursula; Eswar, Narayanan; Maurer, Stephen M; Rai, Arti K; Taylor, Ginger; Todd, Matthew H; Pineda-Lucena, Antonio; Sali, Andrej; Marti-Renom, Marc A

2009-01-01

Conventional patent-based drug development incentives work badly for the developing world, where commercial markets are usually small to non-existent. For this reason, the past decade has seen extensive experimentation with alternative R&D institutions ranging from private-public partnerships to development prizes. Despite extensive discussion, however, one of the most promising avenues-open source drug discovery-has remained elusive. We argue that the stumbling block has been the absence of a critical mass of preexisting work that volunteers can improve through a series of granular contributions. Historically, open source software collaborations have almost never succeeded without such "kernels". HERE, WE USE A COMPUTATIONAL PIPELINE FOR: (i) comparative structure modeling of target proteins, (ii) predicting the localization of ligand binding sites on their surfaces, and (iii) assessing the similarity of the predicted ligands to known drugs. Our kernel currently contains 143 and 297 protein targets from ten pathogen genomes that are predicted to bind a known drug or a molecule similar to a known drug, respectively. The kernel provides a source of potential drug targets and drug candidates around which an online open source community can nucleate. Using NMR spectroscopy, we have experimentally tested our predictions for two of these targets, confirming one and invalidating the other. The TDI kernel, which is being offered under the Creative Commons attribution share-alike license for free and unrestricted use, can be accessed on the World Wide Web at http://www.tropicaldisease.org. We hope that the kernel will facilitate collaborative efforts towards the discovery of new drugs against parasites that cause tropical diseases.
Subsampling Realised Kernels

DEFF Research Database (Denmark)

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

2011-01-01

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

Directory of Open Access Journals (Sweden)

Ping Zhou

Full Text Available Dietary protein levels and cysteamine (CS supplementation can affect growth performance and protein metabolism of pigs. However, the influence of dietary protein intake on the growth response of CS-treated pigs is unclear, and the mechanisms involved in protein metabolism remain unknown. Hence, we investigated the interactions between dietary protein levels and CS supplementation and the effects of dietary crude protein levels and CS supplementation on protein synthetic and degradative signaling in skeletal muscle of finishing pigs. One hundred twenty barrows (65.84 ± 0.61 kg were allocated to a 2 × 2 factorial arrangement with five replicates of six pigs each. The primary variations were dietary crude protein (CP levels (14% or 10% and CS supplemental levels (0 or 700 mg/kg. The low-protein (LP diets (10% CP were supplemented with enough essential amino acids (EAA to meet the NRC AA requirements of pigs and maintain the balanced supply of eight EAA including lysine, methionine, threonine, tryptophan, valine, phenylalanine, isoleucine, and leucine. After 41 days, 10 pigs per treatment were slaughtered. We found that LP diets supplemented with EAA resulted in decreased concentrations of plasma somatostatin (SS (P<0.01 and plasma urea nitrogen (PUN (P<0.001, while dietary protein levels did not affect other traits. However, CS supplementation increased the average daily gain (P<0.001 and lean percentage (P<0.05, and decreased the feed conversion ratio (P<0.05 and back fat (P<0.05. CS supplementation also increased the concentrations of plasma insulin-like growth factor 1 (IGF-1 (P<0.001, and reduced the concentrations of leptin, SS, and PUN (P<0.001. Increased mRNA abundance of Akt1 and IGF-1 signaling (P<0.001 and decreased mRNA abundance of Forkhead Box O (FOXO 4 (P<0.01 and muscle atrophy F-box (P<0.001 were observed in pigs receiving CS. Additionally, CS supplementation increased the protein levels for the phosphorylated mammalian target of
Kernel abortion in maize. II. Distribution of 14C among kernel carboydrates

International Nuclear Information System (INIS)

Hanft, J.M.; Jones, R.J.

1986-01-01

This study was designed to compare the uptake and distribution of 14 C among fructose, glucose, sucrose, and starch in the cob, pedicel, and endosperm tissues of maize (Zea mays L.) kernels induced to abort by high temperature with those that develop normally. Kernels cultured in vitro at 309 and 35 0 C were transferred to [ 14 C]sucrose media 10 days after pollination. Kernels cultured at 35 0 C aborted prior to the onset of linear dry matter accumulation. Significant uptake into the cob, pedicel, and endosperm of radioactivity associated with the soluble and starch fractions of the tissues was detected after 24 hours in culture on atlageled media. After 8 days in culture on [ 14 C]sucrose media, 48 and 40% of the radioactivity associated with the cob carbohydrates was found in the reducing sugars at 30 and 35 0 C, respectively. Of the total carbohydrates, a higher percentage of label was associated with sucrose and lower percentage with fructose and glucose in pedicel tissue of kernels cultured at 35 0 C compared to kernels cultured at 30 0 C. These results indicate that sucrose was not cleaved to fructose and glucose as rapidly during the unloading process in the pedicel of kernels induced to abort by high temperature. Kernels cultured at 35 0 C had a much lower proportion of label associated with endosperm starch (29%) than did kernels cultured at 30 0 C (89%). Kernels cultured at 35 0 C had a correspondingly higher proportion of 14 C in endosperm fructose, glucose, and sucrose
Heavy crude oil and synthetic crude market outlook

International Nuclear Information System (INIS)

Crandall, G.R.

1997-01-01

This presentation included an outline of the international heavy crude supply and demand versus Canadian heavy crude supply and disposition, and pricing outlook for synthetic crudes. Differences among crude oils such as light sweet, light sour, heavy and bitumen were described and illustrated with respect to their gravity, API, percentage of sulphur, metals and nitrogen. Internationally, heavy and sour crude supplies are forecast to increase significantly over the next four years. Discoveries of light sour crude in offshore Gulf of Mexico will provide a major new source of sour crude to U.S. Gulf Coast refineries. Venezuela's supplies of heavy and sour crude are also expected to increase over the next few years. Mexico and Canada have plans to increase their heavy crude production. All of the crudes will be aimed at the U.S. Gulf Coast and Midwest markets. Pentanes and condensates are also expected to increase based on the growing Canadian natural gas production. Diluent demand will also grow to match Canadian heavy crude/bitumen production. U.S. midwest refiners are proposing expansions to allow them to process more Canadian heavy crude oil. At present, only a few refineries are equipped to process significant amounts of synthetic crude. It was suggested that to absorb available heavy and synthetic production, increased penetration into both Canadian and U.S. markets will be required. Some refineries may have to be modified to process heavy and synthetic oil supplies. Heavy oil and synthetic producers may need to develop relationships with refiners such as joint ventures and term supply agreements to secure markets. 2 tabs., 12 figs
Optimized Kernel Entropy Components.

Science.gov (United States)

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

2017-06-01

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

Science.gov (United States)

Mawati, S.; Restitrisnani, V.; Soedarsono

2018-02-01

This study was undertaken to evaluate the effect of crude protein (CP) content on meat protein and fat production in sheep. Twenty four male thin tail sheep aged 6-7 months with average body weight of 13±1.56 kg were used in this study. The sheep were fed 10-14% CP. Sheep with the average body weight amount 16.75 kg were slaughter after 4 months rising. Parameters observed in this study were carcass weight, meat weight and fat weight of thin tail sheep. The data were analyzed using correlation analysis. The result of this study showed that CP content on diet had weak and negative correlation with meat production (r = -0.06) (y = -0.148x + 62.54) but had weak and possitive correlation with fat production (r = 0.3) (y = 0.807x2 -18.40x + 119.1). Based on the result, it can be concluded that the optimum CP content for sheep is 12.5% CP.

Dynamic Proteomic Characteristics and Network Integration Revealing Key Proteins for Two Kernel Tissue Developments in Popcorn.

Directory of Open Access Journals (Sweden)

Yongbin Dong

Full Text Available The formation and development of maize kernel is a complex dynamic physiological and biochemical process that involves the temporal and spatial expression of many proteins and the regulation of metabolic pathways. In this study, the protein profiles of the endosperm and pericarp at three important developmental stages were analyzed by isobaric tags for relative and absolute quantification (iTRAQ labeling coupled with LC-MS/MS in popcorn inbred N04. Comparative quantitative proteomic analyses among developmental stages and between tissues were performed, and the protein networks were integrated. A total of 6,876 proteins were identified, of which 1,396 were nonredundant. Specific proteins and different expression patterns were observed across developmental stages and tissues. The functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the development of the tissues. The whole, endosperm-specific and pericarp-specific protein networks integrated 125, 9 and 77 proteins, respectively, which were involved in 54 KEGG pathways and reflected their complex metabolic interactions. Confirmation for the iTRAQ endosperm proteins by two-dimensional gel electrophoresis showed that 44.44% proteins were commonly found. However, the concordance between mRNA level and the protein abundance varied across different proteins, stages, tissues and inbred lines, according to the gene cloning and expression analyses of four relevant proteins with important functions and different expression levels. But the result by western blot showed their same expression tendency for the four proteins as by iTRAQ. These results could provide new insights into the developmental mechanisms of endosperm and pericarp, and grain formation in maize.
Chemical Composition and Food Potential of Pachymerus nucleorum Larvae Parasitizing Acrocomia aculeata Kernels.

Directory of Open Access Journals (Sweden)

Ariana Vieira Alves

Full Text Available Insect consumption as food is culturally practiced in various regions of the world. In Brazil, there are more than 130 species of edible insects registered, from nine orders, among which stands out the Coleoptera. The larva of the beetle Pachymerus nucleorum Fabricius, 1792, grows into the bocaiuva fruit (Acrocomia aculeata (Jacq. Lodd. Ex Mart., 1845, which has proven nutritional quality. The aim of this work was to evaluate the nutritional potential of P. nucleorum larvae compared to bocaiuva kernels for human consumption. Proteins were the second largest portion of the larvae nutritional composition (33.13%, with percentage higher than the bocaiuva kernels (14.21%. The larval lipid content (37.87% was also high, very close to the kernels (44.96%. The fraction corresponding to fatty acids in the oil extracted from the larvae was 40.17% for the saturated and 46.52% for the unsaturated. The antioxidant activity value was 24.3 uM trolox/g of oil extracted from larvae. The larvae tryptic activity was 0.032±0.006 nmol BAPNA/min. Both the larvae and the bocaiuva kernel presented absence of anti-nutritional factors. These results favor the use of P. nucleorum larvae as food, which are a great protein and lipid sources with considerable concentrations of unsaturated fatty acids compared to the bocaiuva kernel.
A novel adaptive kernel method with kernel centers determined by a support vector regression approach

NARCIS (Netherlands)

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

2012-01-01

The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an
Effect of crude oil petroleum hydrocarbons on protein expression of the prawn Macrobrachium borellii.

Science.gov (United States)

Pasquevich, M Y; Dreon, M S; Gutierrez Rivera, J N; Vázquez Boucard, C; Heras, H

2013-05-01

Hydrocarbon pollution is a major environmental threat to ecosystems in marine and freshwater environments, but its toxicological effect on aquatic organisms remains little studied. A proteomic approach was used to analyze the effect of a freshwater oil spill on the prawn Macrobrachium borellii. To this aim, proteins were extracted from midgut gland (hepatopancreas) of male and female prawns exposed 7 days to a sublethal concentration (0.6 ppm) of water-soluble fraction of crude oil (WSF). Exposure to WSF induced responses at the protein expression level. Two-dimensional gel electrophoresis (2-DE) revealed 10 protein spots that were differentially expressed by WSF exposure. Seven proteins were identified using MS/MS and de novo sequencing. Nm23 oncoprotein, arginine methyltransferase, fatty aldehyde dehydrogenase and glutathione S-transferase were down-regulated, whereas two glyceraldehyde-3-phosphate dehydrogenase isoforms and a lipocalin-like crustacyanin (CTC) were up-regulated after WSF exposure. CTC mRNA levels were further analyzed by quantitative real-time PCR showing an increased expression after WSF exposure. The proteins identified are involved in carbohydrate and amino acid metabolism, detoxification, transport of hydrophobic molecules and cellular homeostasis among others. These results provide evidence for better understanding the toxic mechanisms of hydrocarbons. Moreover, some of these differentially expressed proteins would be employed as potential novel biomarkers. Copyright © 2013 Elsevier Inc. All rights reserved.
Hubungan antara konsumsi protein dengan produksi, protein dan laktosa susu kambing Peranakan Ettawa

Directory of Open Access Journals (Sweden)

Galuh Estu Prihatiningsih

2015-09-01

Full Text Available The study aimed to determine a correlation between crude protein intake, milk production, milk protein and milk lactose. This study used purposive sampling method. The sample used in this study were 35 Etawa crossbred goats with months of lactation 4-5 and lactation periods 2-3. Parameters observed were crude protein intake, milk production, milk protein and milk lactose. Data were analyzed using correlation analysis and simple linear regression. The result showed that crude protein intake, total milk production concentrations of milk protein and lactose were 0.77 kg/day; 0.30 kg/day; 0.196% and 3.32% respectively. There was a medium positive linear correlation between the crude protein intake with total milk production, protein and lactose content of milk. The correlation coefficient (r were 0.258; 0.254 and 0,255 respectively. It could be concluded that the higher crude protein intake would increase the amount of milk production, protein and lactose contents. Keywords: crude protein intake, total milk production, milk protein, milk lactose
Development of nondestructive screening methods for single kernel characterization of wheat

DEFF Research Database (Denmark)

Nielsen, J.P.; Pedersen, D.K.; Munck, L.

2003-01-01

predictability. However, by applying an averaging approach, in which single seed replicate measurements are mathematically simulated, a very good NIT prediction model was achieved. This suggests that the single seed NIT spectra contain hardness information, but that a single seed hardness method with higher......The development of nondestructive screening methods for single seed protein, vitreousness, density, and hardness index has been studied for single kernels of European wheat. A single kernel procedure was applied involving, image analysis, near-infrared transmittance (NIT) spectroscopy, laboratory...
7 CFR 981.7 - Edible kernel.

Science.gov (United States)

2010-01-01

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

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

Kernel versions of orthogonal transformations such as principal components are based on a dual formulation also termed Q-mode analysis in which the data enter into the analysis via inner products in the Gram matrix only. In the kernel version the inner products of the original data are replaced...... by inner products between nonlinear mappings into higher dimensional feature space. Via kernel substitution also known as the kernel trick these inner products between the mappings are in turn replaced by a kernel function and all quantities needed in the analysis are expressed in terms of this kernel...... function. This means that we need not know the nonlinear mappings explicitly. Kernel principal component analysis (PCA) and kernel minimum noise fraction (MNF) analyses handle nonlinearities by implicitly transforming data into high (even infinite) dimensional feature space via the kernel function...
Model Selection in Kernel Ridge Regression

DEFF Research Database (Denmark)

Exterkate, Peter

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

OpenAIRE

Sitompul, Monica Angelina

2015-01-01

Have been conducted Determination of Iodin Value by method titration to some Hydrogenated Palm Kernel Oil (HPKO) and Refined Bleached Deodorized Palm Kernel Oil (RBDPKO). The result of analysis obtained the Iodin Value in Hydrogenated Palm Kernel Oil (A) = 0,16 gr I2/100gr, Hydrogenated Palm Kernel Oil (B) = 0,20 gr I2/100gr, Hydrogenated Palm Kernel Oil (C) = 0,24 gr I2/100gr. And in Refined Bleached Deodorized Palm Kernel Oil (A) = 17,51 gr I2/100gr, Refined Bleached Deodorized Palm Kernel ...
7 CFR 981.8 - Inedible kernel.

Science.gov (United States)

2010-01-01

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

Directory of Open Access Journals (Sweden)

Eric Haydt Castello Branco van Cleef

2014-02-01

Full Text Available Two studies were conducted to evaluate the effects of crude glycerin on feed intake, performance, carcass characteristics, and total digestibility of Nellore bulls. In experiment 1, cattle (n = 30 were fed a control diet without crude glycerin and diets containing 7.5, 15, 22.5, and 30% crude glycerin, for 103 d. Animals were harvested and data of carcass characteristics were collected. In experiment 2, a digestibility trial was performed using indigestible acid detergent fiber (iADF as internal marker, and five rumen-cannulated steers. Both experiments were conducted as a randomized complete block design and data were analyzed using mixed procedures. In experiment 1 no differences were observed among treatments on dry matter intake, and performance variables. Regarding carcass characteristics, no effect was observed, except for carcass fat estimates, which were greater in treatments with crude glycerin. In experiment 2, crude glycerin promoted a decrease in digestibility of fibrous fractions NDF and HEM, and increased digestibility of crude protein by 6%. Although it caused negative effect on digestibility of fibrous fraction of diets, crude glycerin can be a good energy source for Nellore bulls, since no losses are observed on performance and carcass characteristics when animals are fed up to 30% of this by-product.
7 CFR 981.408 - Inedible kernel.

Science.gov (United States)

2010-01-01

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

DEFF Research Database (Denmark)

Exterkate, Peter

2013-01-01

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

DEFF Research Database (Denmark)

Puscasu, Ruslan; Todd, Billy; Daivis, Peter

2010-01-01

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

CERN Document Server

Li, Jun-Bao; Pan, Jeng-Shyang

2013-01-01

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new
Nível de proteína bruta para codornas de corte durante o período de crescimento Crude protein level for meat type quail during the growing period

Directory of Open Access Journals (Sweden)

G.S.S. Corrêa

2008-02-01

peito e peso e rendimento de fígado das fêmeas foram maiores que os dos machos. As exigências de proteína bruta estimada para o máximo ganho de peso de machos e fêmeas de codornas de corte, do nascimento ao 21º e do nascimento ao 42º dia de idade são 30,65% e 29,81%, respectivamente. A exigência para pesos de carcaça e peito é de 33,0% de proteína bruta da dieta.The crude protein requirements for EV2 quail meat type genetic group during the growing period were estimated in a completely randomized experimental design, using 288 quails of both sex, six levels of crude protein (23, 25, 27, 29, 31 and 33% and four replicates of 12 quails per experimental unit. Body weight (g, weight gain (g, feed intake (g and feed:weight gain ratio (g/g were recorded in each period (from hatch to 21 days and from hatch to 42 days of age. At 42 days of age, four quails were randomly sampled from each experimental unit (two males and two females and slaughtered to record weights and yields of carcass, main cuts (thigh and breast edible giblets (liver, gizzard and heart and abdominal fat. Quadratic effects of crude protein level on body weight, weight gain and feed intake from hatch to 21 days of age, with maximum performances estimated for quails fed 30.64; 30.65 and 29.02% crude protein diets, respectively. Feed:weight gain ratio during this period showed a linear response in function of protein level of diet. Quadratic effect of protein level on body weight at 42 days of age was observed, with maximum performances estimated for quails fed 29.93 crude protein diets, while weight gain showed a linear response. Quadratic effects of crude protein level on weight gain and feed intake were also observed, with estimated maximum for quails fed 29.81 and 29.11% crude protein diets, respectively while body weight and carcass and breast weights were linearly affected. Higher performance were observed for quails fed diets with the highest protein level. A significant crude protein level x
The production of corn kernel miso based on rice-koji fermented by Aspergillus oryzae and Rhizopus oligosporus

Directory of Open Access Journals (Sweden)

Diah Ratnaningrum

2018-04-01

Full Text Available The suitability of corn kernel as raw material to produce miso fermented by rice-koji containing Aspergillus oryzae and Rhizopus oligosporus has been investigated. The optimization was conducted on two important factors in miso production namely mold composition in rice-koji and salt concentration. The mold composition was prepared by inoculating the spores of 2% A. oryzae, 2% R. oligosporus, and 2% the mixture of both in a ratio of 1:1, 2:1, and 1:2 (v/v into different rice media. The mold composition was optimized to produce rice-koji with high α-amylase and protease activity. Different NaCl concentrations of 10%, 15%, and 20% were subjected to optimization process and added to each mixture after five days of fermentation. The salt concentration was also optimized to produce corn kernel miso with high glucose and high dissolved protein concentration. The result showed that rice-koji containing A. oryzae and R. oligosporus in the ratio of 1:1 had the highest α-amylase and protease activity of 0.42 U/mL and 0.45 U/mL respectively. In addition, the presence of 10% NaCl in corn kernel miso fermented by A. oryzae and R. oligosporus in the ratio of 1:1 exhibited the highest glucose and dissolved protein concentration of 0.64 mg/mL and 8.80 mg/mL respectively. The optimized corn kernel miso by A. oryzae and R. oligosporus in the ratio of 1:1 with 10% NaCl was subjected to nutrient content analysis and compared to the result before the corn kernel was fermented. The nutrient content analysis showed nutrient enhancement after corn kernel was fermented and transformed into a miso. Glucose, dissolved protein, and fat content increased 6.74, 1.34, 7.63 times respectively. This study concludes corn kernel could be utilized to produce a novel corn kernel miso for dietary diversification and for improving nutritional and health status.
Partial Deconvolution with Inaccurate Blur Kernel.

Science.gov (United States)

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

2017-10-17

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

OpenAIRE

Cho, Youngmin

2012-01-01

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

Kinetics of palm kernel oil and ethanol transesterification

Energy Technology Data Exchange (ETDEWEB)

Ahiekpor, Julius C. [Centre for Energy, Environment and Sustainable Development (CEESD), P.O. Box FN 793, Kumasi (Ghana); Kuwornoo, David K. [Faculty of Chemical and Materials Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Private Mail Bag, Kumasi (Ghana)

2010-07-01

Biodiesel, an alternative diesel fuel made from renewable sources such as vegetable oils and animal fats, has been identified by government to play a key role in the socio-economic development of Ghana. The utilization of biodiesel is expected to be about 10% of the total liquid fuel mix of the country by the year 2020. Despite this great potential and the numerous sources from which biodiesel could be developed in Ghana, there are no available data on the kinetics and mechanisms of transesterification of local vegetable oils. The need for local production of biodiesel necessitates that the mechanism and kinetics of the process is well understood, since the properties of the biodiesel depends on the type of oil use for the transesterification process. The objective of this work is to evaluate the appropriate kinetics mechanism and to find out the reaction rate constants for palm kernel oil transesterification with ethanol when KOH was used as a catalyst. In this present work, 16 biodiesel samples were prepared at specified times based on reported optimal conditions and the samples analysed by gas chromatography. The experimental mass fractions were calibrated and fitted to mathematical models of different proposed mechanisms in previous works.The rate data fitted well to second-order kinetics without shunt mechanism. It was also observed that, although transesterification reaction of crude palm kernel oil is a reversible reaction, the reaction rate constants indicated that the forward reactions were the most prominent.
7 CFR 981.9 - Kernel weight.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Kernel weight. 981.9 Section 981.9 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Marketing Agreements... Regulating Handling Definitions § 981.9 Kernel weight. Kernel weight means the weight of kernels, including...
The influence of dietary crude protein intake on bone and mineral metabolism in sheep

Directory of Open Access Journals (Sweden)

T.S. Brand

1999-07-01

Full Text Available Increased dietary protein consumption is thought to cause calciuresis, a negative calcium balance and increased bone loss that may result in skeletal deformities and fracture. To explore this hypothesis, 40 approximately 100-day-old meat-type Merino ram lambs were fed, for 6 months, diets with an increasing crude protein (CP content (114, 142, 171 and 190 g/kg DM but approximately on an iso-nutrient basis with regard to metabolisable energy, calcium and phosphorus. Increased protein consumption modestly (NS enhanced calciuresis and resulted in significant (P < 0.01 limb skewness. This could not, however, be ascribed to osteopaenic bones, and compared with animals consuming lower protein rations, the bone mineral density (BMD and vertebral trabecular bone volume of animals fed high protein diets were significantly increased: theBMDof thoracic vertebrae was positively related to the CP intake (r=0.62; P < 0.001. In animals consuming higher protein diets, skeletal radiology and quantitative bone histology revealed no evidence of increased bone turnover as would be expected in animals that are in negative calcium balance. No relationship existed between limb skewness and the growth rate of lambs. However, the ratio of Ca:P in the forelimb (r = -0.98, vertebrae (r = -0.72 and rib (r = -0.42 was found to be inversely correlated with increased protein intake and resulted from an increase in the phosphorus content of bone, while the amount of bone calcium was unaffected. We conclude that qualitative micro-architectural abnormalities, and not mere bone loss, may underlie the skeletal deformities induced by increased protein consumption in sheep.
Níveis de Proteína Bruta da Ração para Marrãs em Gestação Levels of Crude Protein of the Ration for Gilts in Gestation

Directory of Open Access Journals (Sweden)

Kedson Raul de Souza Lima

2002-02-01

Full Text Available Foram utilizadas 50 marrãs mestiças (Landrace, Large White e Pietrain com média de peso de 136,34 ±16,05 kg e idade média de 220 dias, respectivamente, para avaliar diferentes níveis de proteína bruta da ração desses animais. Foi empregado o delineamento de blocos ao acaso, com cinco tratamento, 10 repetições e um animal por unidade experimental. Os tratamentos corresponderam a rações com 10,0; 11,5; 13,0; 14,5; e 16,0% de proteína bruta. O ganho de peso das marrãs até os 90 dias de gestação e o peso dos leitões e da leitegada se elevaram de forma linear com o aumento do nível de proteína da ração. Houve efeito quadrático dos níveis de proteína sobre o consumo da porca na lactação, que aumentou até o nível de 12,96% de PB. Não se verificou efeito dos tratamentos sobre o número de leitões nascidos, o número de dias desmame-cio e sobre o ganho de peso da porca durante todo o ciclo reprodutivo. Entretanto, houve efeito quadrático sobre o número de leitões desmamados, que aumentou até o nível de 13,33% de PB. Os níveis de proteína bruta que propiciaram menor taxa de mortalidade dos leitões na fase de lactação situaram-se entre 11,5 e 16% de PB. O melhor nível de proteína bruta nas dietas no período de gestação para marrãs pesando 136,34 ±16,05 kg e idade média de 220 dias foi de 13,31%, correspondendo a um consumo estimado de 240 g de proteína/dia ou 0,67% de lisina (12,06 g/dia, respectivamente.Fifty crossbreed gilts (Landrace, Large White and Pietrain with 136.34±16.05 and 220 days of average weight and age, respectively, were used to evaluate diets with different crude protein levels, at the gestation period. A complete randomized blocks design, with five treatments, ten replicates and one animal per experimental unit, was used. The treatments corresponded to the diets with 10.0, 11.5, 13.0, 14.5 and 16.0% of crude protein. The weight gains of the gilts at the 90 days of the gestation period
Veto-Consensus Multiple Kernel Learning

NARCIS (Netherlands)

Zhou, Y.; Hu, N.; Spanos, C.J.

2016-01-01

We propose Veto-Consensus Multiple Kernel Learning (VCMKL), a novel way of combining multiple kernels such that one class of samples is described by the logical intersection (consensus) of base kernelized decision rules, whereas the other classes by the union (veto) of their complements. The
7 CFR 51.2295 - Half kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Half kernel. 51.2295 Section 51.2295 Agriculture... Standards for Shelled English Walnuts (Juglans Regia) Definitions § 51.2295 Half kernel. Half kernel means the separated half of a kernel with not more than one-eighth broken off. ...
Chemical Characteristics of Mango (Mangifera Indica L.) Kernel Oil and Palm Oil Blends for Probable use as Vanaspati

International Nuclear Information System (INIS)

Atta Muhammad Arif; Irman Javed; Muhammad Abdullah; Muhammad Irman; Athar Mahmud; Muhammad Nadeem; Muhammad Ayaz

2016-01-01

Chemical characteristics of blends of palm oil and mango kernel oil for their probable use as vanaspati was studied. Crude mango kernel oil was blended with refined, bleached and deodorised palm oil from 10 %, 20 %, 30 %, 40 % and 50 % (T 1 , T 2 , T 3 , T 4 and T 5 ) market vanaspati was used as control. Concentration of trans fatty acids in control was 22.7 %, whereas, all the vanaspati samples were virtually trans-free. Slip melting points (degree Celsius) of control, T 1 , T 2 , T 3 , T 4 and T 5 were 37.5, 37.3, 36.4, 35.6, 34.8 and 34. Free fatty acids of control and T5 were respectively 0.11, 0.12 %. Polymer contents of control, T 1 , T 2 , T 3 , T 4 and T 5 , after three heating cycles (18 degree Celsius, for 8 hr) were 21.55 %, 20.97 %, 18.66 %, 17.61 % and 10.22 %, respectively with lower solid fat index (p<0.05). Blends of mango kernel oil and palm oil can be used for the formulation of trans-free vanaspati. (author)
An Approximate Approach to Automatic Kernel Selection.

Science.gov (United States)

Ding, Lizhong; Liao, Shizhong

2016-02-02

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

Energy Technology Data Exchange (ETDEWEB)

Duff, I.

1994-12-31

This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.
Viscozyme L pretreatment on palm kernels improved the aroma of palm kernel oil after kernel roasting.

Science.gov (United States)

Zhang, Wencan; Leong, Siew Mun; Zhao, Feifei; Zhao, Fangju; Yang, Tiankui; Liu, Shaoquan

2018-05-01

With an interest to enhance the aroma of palm kernel oil (PKO), Viscozyme L, an enzyme complex containing a wide range of carbohydrases, was applied to alter the carbohydrates in palm kernels (PK) to modulate the formation of volatiles upon kernel roasting. After Viscozyme treatment, the content of simple sugars and free amino acids in PK increased by 4.4-fold and 4.5-fold, respectively. After kernel roasting and oil extraction, significantly more 2,5-dimethylfuran, 2-[(methylthio)methyl]-furan, 1-(2-furanyl)-ethanone, 1-(2-furyl)-2-propanone, 5-methyl-2-furancarboxaldehyde and 2-acetyl-5-methylfuran but less 2-furanmethanol and 2-furanmethanol acetate were found in treated PKO; the correlation between their formation and simple sugar profile was estimated by using partial least square regression (PLS1). Obvious differences in pyrroles and Strecker aldehydes were also found between the control and treated PKOs. Principal component analysis (PCA) clearly discriminated the treated PKOs from that of control PKOs on the basis of all volatile compounds. Such changes in volatiles translated into distinct sensory attributes, whereby treated PKO was more caramelic and burnt after aqueous extraction and more nutty, roasty, caramelic and smoky after solvent extraction. Copyright © 2018 Elsevier Ltd. All rights reserved.
A kernel version of spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

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

Science.gov (United States)

Da Silva, Helena Sofia Pereira

2009-01-01

Maize ("Zea mays L.") is a model species well suited for the dissection of complex traits which are often of commercial value. The purpose of this research was to gain a deeper understanding of the genetic control of maize kernel composition traits starch, protein, and oil concentration, and also kernel weight and grain yield. Germplasm with…
7 CFR 51.1441 - Half-kernel.

Science.gov (United States)

2010-01-01

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

Science.gov (United States)

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

2014-01-01

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

Science.gov (United States)

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

2018-05-01

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

International Nuclear Information System (INIS)

Kirmani, Z.; Khurshid, A.; Alam, N.; Gul, S.; Ahmed, N.

2009-01-01

Attock Refinery Limited (ARL) is based at Rawalpindi, Pakistan and operates a 40,000 Barrels per Stream Day (BPSD) refinery. The Heavy Crude Unit (HCU) of ARL is a fully integrated two-stage 10,000 BPSD Atmospheric and 5,700 BPSD Vacuum Distillation Unit. A 3-stage desalter designed to reduce salt and BS and W content from 2,000 parts per thousand barrels (PTB) and 2% to less than 5 PTB and 0.1% respectively, is part of HCU. The feedstock is a composite blend of 14 local Heavy Crudes received at the Refinery. Although in the past this desalter had been giving good performance, over the last one year, period since August 2005, at least nine shutdowns of the unit took place due to salt slippage and consequential tube leakages at the overhead Crude-Naphtha vapor Heat Exchanger where partial condensation of naphtha takes place. Final condensation is achieved in trim condenser. High salted water carry-over with the crude caused increased hydrolysis, formation of Hydrochloric acid and increase of tail water chlorides. Salt contents at the outlet of third desalter at times increased up to 400 PTB with 3.2% BS and W during the above mentioned upsets, as compared to normal 5-10 PTB. Fallout from this loss of desalter control was the creation of large quantities of slop due to draining of strong water oil emulsion from the desalters. Individual crudes of the blend were analyzed for affinity of water and emulsion stability. It was observed that 3 of the 14 crudes formed very strong while the remaining crudes formed weak oil water emulsion, which easily separated water from oil in desalter without any operational problem. Study was further narrowed down to one crude evaluation. Alkaline earth metallic naphthenate surfactants were detected and isolated as responsible for the strong water oil and sediments emulsion. The isolated crude was next withdrawn from the Heavy Crude blend. As soon as it was isolated and its ratio in heavy crude tank came down to 0.7 %, the problem began
DEGRADABILIDADE IN SITU DA MATÉRIA SECA, DA PROTEÍNA BRUTA E DA FRAÇÃO FIBROSA DE CONCENTRADOS E SUBPRODUTOS AGROINDUSTRIAIS IN SITU DEGRADABILITY OF DRY MATTER, CRUDE PROTEIN AND FIBROUS FRACTION OF CONCENTRATE AND AGROINDUSTRIAL BY-PRODUCTS

Directory of Open Access Journals (Sweden)

Gleidson Giordano Pinto de Carvalho Carvalho

2009-09-01

Full Text Available Objetivou-se avaliar a degradabilidade ruminal da matéria seca (MS, da proteína bruta (PB, da fibra em detergente neutro (FDN e da fibra em detergente ácido (FDA do milho (Zea mays, do farelo de soja (Glicyne max L., da torta de dendê (Elaeis guineensis Jacq. e do farelo de cacau (Theobroma cacao L.. Incubaram-se amostras de cada alimento no rúmen de três novilhos por períodos de 0; 3; 6; 12; 24 e 48 horas. As degradabilidades efetivas da MS, PB, FDN e FDA, para a taxa de passagem de 5%/hora, foram relativamente baixas (abaixo de 60%, exceto para a PB do farelo de soja (acima de 65%. O farelo de soja apresentou os maiores coeficientes de degradação, tanto para MS e PB como também para os constituintes da parede celular, seguido do milho, torta de dendê e farelo de cacau. O farelo de cacau apresentou as menores taxas de degradação ruminal.

PALAVRAS-CHAVES: Farelo de cacau, incubação ruminal, torta de dendê. The objective of the experiment was to evaluate the dry matter (DM, crude protein (CP, neutral detergent fiber (NDF and acid detergent fiber (ADF ruminal degradability of corn (Zea mays, soybean meal (Glicyne max L., palm kernel cake (Elaeis guineensis Jacq. and cocoa meal (Theobroma cacao L.. Samples of each feed were incubated in rumens of three steers for periods of 0; 3; 6; 12; 24 and 48 hours. The DM, CP, NDF and ADF effective degradabilities, for a passage rate of 5%/hour, were relatively low (lower than 60%, except for soybean meal CP (higher than 65%. Soybean meal showed the greatest degradation coefficients for DM and CP as so as for cellular wall constituents, followed by corn, palm kernel cake and cocoa meal. Cocoa meal showed the lowest ruminal degradation rates.

KEY WORDS: Cocoa meal, incubation ruminal, palm kernel cake.
Crude petroleum

International Nuclear Information System (INIS)

1990-01-01

Crude petroleum statistics by country of production, export values and import values from 1983 to 1988 are given. Table A.1 of the Annex includes free market prices and price indices for crude petroleum based on average of Dubai, United Kingdom Brent and Alaska N Slope crude prices (price expressed in dollars/barrel). The data sources are: Crude petroleum United Nations Statistical Office; OPEC Annual Statistical Bulletin, and Petroleum Economist. For trade the sources of data are: National trade statistics; United Nations international trade statistics; International Moneytary Fund (IMF); Organization of the Petroleum Exporting Countries (OPEC); UNCTAD secretariat estimates. Tabs
Kernel parameter dependence in spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2010-01-01

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

Science.gov (United States)

van Laarhoven, Twan; Nabuurs, Sander B; Marchiori, Elena

2011-11-01

The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug-target pairs in current datasets are experimentally validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. We show that a simple machine learning method that uses the drug-target network as the only source of information is capable of predicting true interaction pairs with high accuracy. Specifically, we introduce interaction profiles of drugs (and of targets) in a network, which are binary vectors specifying the presence or absence of interaction with every target (drug) in that network. We define a kernel on these profiles, called the Gaussian Interaction Profile (GIP) kernel, and use a simple classifier, (kernel) Regularized Least Squares (RLS), for prediction drug-target interactions. We test comparatively the effectiveness of RLS with the GIP kernel on four drug-target interaction networks used in previous studies. The proposed algorithm achieves area under the precision-recall curve (AUPR) up to 92.7, significantly improving over results of state-of-the-art methods. Moreover, we show that using also kernels based on chemical and genomic information further increases accuracy, with a neat improvement on small datasets. These results substantiate the relevance of the network topology (in the form of interaction profiles) as source of information for predicting drug-target interactions. Software and Supplementary Material are available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2011/. tvanlaarhoven@cs.ru.nl; elenam@cs.ru.nl. Supplementary data are available at Bioinformatics online.

Multiple Kernel Learning with Data Augmentation

Science.gov (United States)

2016-11-22

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

CERN Document Server

Halvorsen, Ole Henry

2011-01-01

OS X and iOS Kernel Programming combines essential operating system and kernel architecture knowledge with a highly practical approach that will help you write effective kernel-level code. You'll learn fundamental concepts such as memory management and thread synchronization, as well as the I/O Kit framework. You'll also learn how to write your own kernel-level extensions, such as device drivers for USB and Thunderbolt devices, including networking, storage and audio drivers. OS X and iOS Kernel Programming provides an incisive and complete introduction to the XNU kernel, which runs iPhones, i
Model selection for Gaussian kernel PCA denoising

DEFF Research Database (Denmark)

Jørgensen, Kasper Winther; Hansen, Lars Kai

2012-01-01

We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...
E+ subgroup PPR protein defective kernel 36 is required for multiple mitochondrial transcripts editing and seed development in maize and Arabidopsis.

Science.gov (United States)

Wang, Gang; Zhong, Mingyu; Shuai, Bilian; Song, Jiandong; Zhang, Jie; Han, Liang; Ling, Huiling; Tang, Yuanping; Wang, Guifeng; Song, Rentao

2017-06-01

Mitochondria are semi-autonomous organelles that are the powerhouse of the cells. Plant mitochondrial RNA editing guided by pentatricopeptide repeat (PPR) proteins is essential for energy production. We identify a maize defective kernel mutant dek36, which produces small and collapsed kernels, leading to embryos and/or seedlings lethality. Seed filling in dek36 is drastically impaired, in line with the defects observed in the organization of endosperm transfer tissue. Positional cloning reveals that DEK36, encoding a mitochondria-targeted E+ subgroup PPR protein, is required for mitochondrial RNA editing at atp4-59, nad7-383 and ccmF N -302, thus resulting in decreased activities of mitochondrial complex I, complex III and complex IV in dek36. Loss-of-function of its Arabidopsis ortholog At DEK36 causes arrested embryo and endosperm development, leading to embryo lethality. At_dek36 also has RNA editing defects in atp4, nad7, ccmF N 1 and ccmF N 2 , but at the nonconserved sites. Importantly, efficiency of all editing sites in ccmF N 1 , ccmF N 2 and rps12 is severely decreased in At_dek36, probably caused by the impairment of their RNA stabilization. These results suggest that the DEK36 orthologue pair are essential for embryo and endosperm development in both maize and Arabidopsis, but through divergent function in regulating RNA metabolism of their mitochondrial targets. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.
Paramecium: An Extensible Object-Based Kernel

NARCIS (Netherlands)

van Doorn, L.; Homburg, P.; Tanenbaum, A.S.

1995-01-01

In this paper we describe the design of an extensible kernel, called Paramecium. This kernel uses an object-based software architecture which together with instance naming, late binding and explicit overrides enables easy reconfiguration. Determining which components reside in the kernel protection
Theory of reproducing kernels and applications

CERN Document Server

Saitoh, Saburou

2016-01-01

This book provides a large extension of the general theory of reproducing kernels published by N. Aronszajn in 1950, with many concrete applications. In Chapter 1, many concrete reproducing kernels are first introduced with detailed information. Chapter 2 presents a general and global theory of reproducing kernels with basic applications in a self-contained way. Many fundamental operations among reproducing kernel Hilbert spaces are dealt with. Chapter 2 is the heart of this book. Chapter 3 is devoted to the Tikhonov regularization using the theory of reproducing kernels with applications to numerical and practical solutions of bounded linear operator equations. In Chapter 4, the numerical real inversion formulas of the Laplace transform are presented by applying the Tikhonov regularization, where the reproducing kernels play a key role in the results. Chapter 5 deals with ordinary differential equations; Chapter 6 includes many concrete results for various fundamental partial differential equations. In Chapt...
Kernels for structured data

CERN Document Server

Gärtner, Thomas

2009-01-01

This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by
7 CFR 981.401 - Adjusted kernel weight.

Science.gov (United States)

2010-01-01

... 7 Agriculture 8 2010-01-01 2010-01-01 false Adjusted kernel weight. 981.401 Section 981.401... Administrative Rules and Regulations § 981.401 Adjusted kernel weight. (a) Definition. Adjusted kernel weight... kernels in excess of five percent; less shells, if applicable; less processing loss of one percent for...
Moisture Adsorption Isotherm and Storability of Hazelnut Inshells and Kernels Produced in Oregon, USA.

Science.gov (United States)

Jung, Jooyeoun; Wang, Wenjie; McGorrin, Robert J; Zhao, Yanyun

2018-02-01

Moisture adsorption isotherms and storability of dried hazelnut inshells and kernels produced in Oregon were evaluated and compared among cultivars, including Barcelona, Yamhill, and Jefferson. Experimental moisture adsorption data fitted to Guggenheim-Anderson-de Boer (GAB) model, showing less hygroscopic properties in Yamhill than other cultivars of inshells and kernels due to lower content of carbohydrate and protein, but higher content of fat. The safe levels of moisture content (MC, dry basis) of dried inshells and kernels for reaching kernel water activity (a w ) ≤0.65 were estimated using the GAB model as 11.3% and 5.0% for Barcelona, 9.4% and 4.2% for Yamhill, and 10.7% and 4.9% for Jefferson, respectively. Storage conditions (2 °C at 85% to 95% relative humidity [RH], 10 °C at 65% to 75% RH, and 27 °C at 35% to 45% RH), times (0, 4, 8, or 12 mo), and packaging methods (atmosphere vs. vacuum) affected MC, a w , bioactive compounds, lipid oxidation, and enzyme activity of dried hazelnut inshells or kernels. For inshells packaged at woven polypropylene bag, MC and a w of inshells and kernels (inside shells) increased at 2 and 10 °C, but decreased at 27 °C during storage. For kernels, lipid oxidation and polyphenol oxidase activity also increased with extended storage time (P adsorption and physicochemical and enzymatic stability during storage. Moisture adsorption isotherm of hazelnut inshells and kernels is useful for predicting the storability of nuts. This study found that water adsorption and storability varied among the different cultivars of nuts, in which Yamhill was less hygroscopic than Barcelona and Jefferson, thus more stable during storage. For ensuring food safety and quality of nuts during storage, each cultivar of kernels should be dried to a certain level of MC. Lipid oxidation and enzyme activity of kernel could be increased with extended storage time. Vacuum packaging was recommended to kernels for reducing moisture adsorption
Testing Infrastructure for Operating System Kernel Development

DEFF Research Database (Denmark)

Walter, Maxwell; Karlsson, Sven

2014-01-01

Testing is an important part of system development, and to test effectively we require knowledge of the internal state of the system under test. Testing an operating system kernel is a challenge as it is the operating system that typically provides access to this internal state information. Multi......-core kernels pose an even greater challenge due to concurrency and their shared kernel state. In this paper, we present a testing framework that addresses these challenges by running the operating system in a virtual machine, and using virtual machine introspection to both communicate with the kernel...... and obtain information about the system. We have also developed an in-kernel testing API that we can use to develop a suite of unit tests in the kernel. We are using our framework for for the development of our own multi-core research kernel....
RHAGOLETIS COMPLETA (DIPTERA; TEPHRITIDAE DISTRIBUTION, FLIGHT DYNAMICS AND INFLUENCE ON WALNUT KERNEL QUALITY IN THE CONTINENTAL CROATIA

Directory of Open Access Journals (Sweden)

Božena Barić

2015-06-01

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

Science.gov (United States)

Wang, Lin; Nakanishi, Takashi; Sato, Yoshiaki; Oishi, Kazato; Hirooka, Hiroyuki; Takahashi, Kei; Kumagai, Hajime

2017-03-01

This study was to examine in vivo digestibility, nitrogen balance and ruminal fermentation of tamarind ( Tamarind indica ) kernel powder extract residue (TKPER) compared to soybean products and by-products in wethers. Four wethers with initial body weight (BW) of 51.6±5.5 kg were assigned in a 4×4 Latin square design to investigate nutritional characteristics of TKPER, dry heat soybean (SB), dry soybean curd residue (SBCR) and soybean meal (SBM) feeding with ryegrass straw (R) at a ratio of 1:1 at 2% of BW in dry matter (DM) on a daily basis. The digestibility of DM, crude protein, and ether extract (EE) of TKPER-R diet were 57.0%, 87.0%, and 86.0%, respectively. Higher non-fiber carbohydrates digestibility was observed in TKPER-R diet (83.2%) than in SB-R diet (73.9%, pruminal ammonia nitrogen (NH 3 -N) contents at 4 h after feeding than those fed the SBM-R diet (pcontent, as well as lower acetate to propionate ratio (C2:C3) in rumen fluid than SBM feeding at 4 h after feeding (pruminants.
7 CFR 51.1403 - Kernel color classification.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Kernel color classification. 51.1403 Section 51.1403... STANDARDS) United States Standards for Grades of Pecans in the Shell 1 Kernel Color Classification § 51.1403 Kernel color classification. (a) The skin color of pecan kernels may be described in terms of the color...
Characterization of gamma irradiated peanut kernels stored one year under ambient and frozen conditions

International Nuclear Information System (INIS)

Chiou, R.Y.Y.; Shyu, S.L.; Tsai, C.L.

1991-01-01

Peanut kernels were gamma irradiated at 0, 2.5, 5.0, 10, and 20 KGy, and stored 1 yr at ambient and frozen (-14 degrees C) conditions. Irradiated peanuts lost germination capabilities during storage. Molds were detected only on peanuts irradiated with 2.5 KGy and stored at ambient temperature. Peanut oil in kernels stored at -14 degrees C was comparatively more stable than that in peanuts stored at ambient temperature. Oxidation of oil was not significantly changed by irradiation. Changes in fatty acid content varied slightly with exception of linoleic and linolenic acids which decreased with increased radiation depending on storage temperature. The SDS-PAGE protein patterns of peanuts revealed no noticeable variation of protein subunits resulting from irradiation and storage
ANALISA KADAR PROTEIN CRUDE ENZIM SELULASE DARI KAPANG Rhizopuz Sp PADA SUBSTRAT AMPAS TEBU HASIL ISOLASI DARI KEBUN CENGKEH, KARE, MADIUN

Directory of Open Access Journals (Sweden)

Pujiati pujiati

2017-01-01

Full Text Available Kapang Rhizopus sp merupakan salah satu mikroorganisme yang memiliki kemampuan tinggi untuk menghasilkan enzim selulase.Enzim selulase merupakan enzim yang dapat menghidrolisis selulosa. Hidrolisis meliputi proses pemecahan polisakarida di dalam biomassa lignoselulosa, yaitu: selulosa dan hemiselulosa menjadi monomer gula penyususnnya. Penelitian ini bertujuan untuk mengetahui produksi dan aktivitas enzim selulase terhadap aktivitas crude enzim selulase dari kapang Rhizopus sp dengan subsrtat ampas tebu (bagase. Metode penelitian menggunakan kuantitatif eksperimen dengan pola rancangan acak lengkap (RAL dua faktorial. Perlakuan penelitian meliputi perbedan inokulum (K yaitu 5% (K1, 15% (K2, 25% (K3 dan lama fermentasi (T yaitu 3hari (T1, 6hari (T2, 9hari (T3, dan 12hari (T4. Data yang diambil dari perlakuan tersebut adalah kadar protein dengan metode brownstead lowry. Analisis data menggunakan variansi anava dua jalur dengan taraf signifikansi 5% setelah itu dilanjutkan dengan uji Beda Nyata Terkecil (BNT . Hasil penelitian menunjukkan bahwa: Fhit > Ftab sehingga ada pengaruh antara konsentrasi inokulum dan lama fermentasi terhadap aktivitas crude enzim selulase dari kapang Rhizopus sp, Perlakuan perbedaan konsentrasi dan lama fermentasi mendapatkan kadar protein tertinggi 0,715 dengan konsentrasi 25% dan lama fementasi 25%
Antinutritional factors and hypocholesterolemic effect of wild apricot kernel (Prunus armeniaca L.) as affected by detoxification.

Science.gov (United States)

Tanwar, Beenu; Modgil, Rajni; Goyal, Ankit

2018-04-25

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

Science.gov (United States)

Dentinho, M T P; Moreira, O C; Pereira, M S; Bessa, R J B

2007-06-01

Cistus ladanifer L. (CL) is a perennial shrub abundant in dry woods and dry land of Mediterranean zone, with high level of tannins. Tannins bind to protein, preventing its degradation in the digestive compartments. This tannin/protein complex may be advantageous when partially protecting good-quality feed protein from excessive rumen protein degradation. The objective of this trial was to use a CL phenol crude extract to prevent excessive rumen degradation of soya-bean meal protein. The phenolic compounds were extracted using an acetone/water solution (70:30, v/v). Soya-bean meal was then treated with this crude CL extract, containing 640 g of total phenols (TP) per kg of dry matter (DM), in order to obtain mixtures with 0, 12.5, 25, 50, 100 and 150 g of TP per kg DM. Three rumen-cannulated rams were used to assess in sacco rumen degradability of DM and nitrogen (N). The three-step in vitro procedure was used to determine intestinal digestibility. Increasing extract concentrations quadratically decreased the N-soluble fraction a (R2 = 0.96, P = 0.0001) and increased the non-soluble degradable fraction b (R2 = 0.92, P = 0.005). The rate of degradation c linearly decreased with CL extract doses (R2 = 0.44, P = 0.0065). For the effective rumen degradability of N, a linear reduction (R2 = 0.94, P < 0.0001) was observed. The in vitro intestinal digestibility of protein (ivID) quadratically decreased (R2 = 0.99, P < 0.0001) with TP inclusion and the rumen undegradable protein (RUP) showed a quadratic increase (R2 = 0.94, P = 0.0417). Total intestinal protein availability, computed from the RUP and ivID, linearly decreased with TP inclusion level (R2 = 0.45, P = 0.0033).
Simulating non-Newtonian flows with the moving particle semi-implicit method with an SPH kernel

International Nuclear Information System (INIS)

Xiang, Hao; Chen, Bin

2015-01-01

The moving particle semi-implicit (MPS) method and smoothed particle hydrodynamics (SPH) are commonly used mesh-free particle methods for free surface flows. The MPS method has superiority in incompressible flow simulation and simple programing. However, the crude kernel function is not accurate enough for the discretization of the divergence of the shear stress tensor by the particle inconsistency when the MPS method is extended to non-Newtonian flows. This paper presents an improved MPS method with an SPH kernel to simulate non-Newtonian flows. To improve the consistency of the partial derivative, the SPH cubic spline kernel and the Taylor series expansion are combined with the MPS method. This approach is suitable for all non-Newtonian fluids that can be described with τ = μ(|γ|) Δ (where τ is the shear stress tensor, μ is the viscosity, |γ| is the shear rate, and Δ is the strain tensor), e.g., the Casson and Cross fluids. Two examples are simulated including the Newtonian Poiseuille flow and container filling process of the Cross fluid. The results of Poiseuille flow are more accurate than the traditional MPS method, and different filling processes are obtained with good agreement with previous results, which verified the validation of the new algorithm. For the Cross fluid, the jet fracture length can be correlated with We 0.28 Fr 0.78 (We is the Weber number, Fr is the Froude number). (paper)
Efficient protein structure search using indexing methods.

Science.gov (United States)

Kim, Sungchul; Sael, Lee; Yu, Hwanjo

2013-01-01

Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively.
The definition of kernel Oz

OpenAIRE

Smolka, Gert

1994-01-01

Oz is a concurrent language providing for functional, object-oriented, and constraint programming. This paper defines Kernel Oz, a semantically complete sublanguage of Oz. It was an important design requirement that Oz be definable by reduction to a lean kernel language. The definition of Kernel Oz introduces three essential abstractions: the Oz universe, the Oz calculus, and the actor model. The Oz universe is a first-order structure defining the values and constraints Oz computes with. The ...

Fabrication of Uranium Oxycarbide Kernels for HTR Fuel

International Nuclear Information System (INIS)

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

2010-01-01

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

Science.gov (United States)

Almaalol, Dekrayat; Strickland, Michael

2018-04-01

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

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2014-01-01

Context information is important in object representation. By embedding context cue of image attributes into kernel descriptors, we propose a set of novel kernel descriptors called Context Kernel Descriptors (CKD) for object classification and detection. The motivation of CKD is to use spatial...... consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature selection, Kernel Entropy Component Analysis (KECA) is exploited to learn a subset of discriminative CKD. Different from Kernel Principal Component...
Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

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

2017-01-01

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

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

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

International Nuclear Information System (INIS)

Prestwich, W.V.; Chan, L.B.; Kwok, C.S.; Wilson, B.

1986-01-01

Knowledge of the dose point kernel corresponding to a specific radionuclide is required to calculate the spatial dose distribution produced in a homogeneous medium by a distributed source. Dose point kernels for commonly used radionuclides have been calculated previously using as a basis monoenergetic dose point kernels derived by numerical integration of a model transport equation. The treatment neglects fluctuations in energy deposition, an effect which has been later incorporated in dose point kernels calculated using Monte Carlo methods. This work describes new calculations of dose point kernels using the Monte Carlo results as a basis. An analytic representation of the monoenergetic dose point kernels has been developed. This provides a convenient method both for calculating the dose point kernel associated with a given beta spectrum and for incorporating the effect of internal conversion. An algebraic expression for allowed beta spectra has been accomplished through an extension of the Bethe-Bacher approximation, and tested against the exact expression. Simplified expression for first-forbidden shape factors have also been developed. A comparison of the calculated dose point kernel for 32 P with experimental data indicates good agreement with a significant improvement over the earlier results in this respect. An analytic representation of the dose point kernel associated with the spectrum of a single beta group has been formulated. 9 references, 16 figures, 3 tables
Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT).

Science.gov (United States)

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

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

Science.gov (United States)

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

2011-10-24

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

Directory of Open Access Journals (Sweden)

Sukma D

2008-08-01

Full Text Available The research was aimed to study morphology, growth, development, pest and disease of 3 Trichosanthes species, initiate shoots, callus and hairy root culture in vitro, analyze chitinase and peroxidase activities and the effect of salicylic acid (SA and etefon (ETF on the chitinase and peroxidase activities of crude protein extract from Trichosanthes, and evaluate in vitro antifungal activity of crude protein extract of Trichosanthes. The results of the research showed the differences of morphological characters, growth habit of T. cucumerina var. anguina, T.tricuspidata and the differences of pest and diseases problem of T. quinquangulata. T. cucumerina var. anguina and T. quinquangulata. T. tricuspidata had the highest chitinase activity in crude protein extract of in vitro shoots, calli and plant roots and peroxidase activity in plant roots grown in field. T. cucumerina var. anguina showed the highest chitinase and peroxidase activities in crude protein extract of plant roots grown in field and calli. Chitinase and peroxidase activities of calli crude protein extract of T. tricuspidata could be increased by SA and ETF. Adversely, ETF decreased the peroxidase activity of calli crude protein exract ofT. tricuspidata. In T. cucumerina var. anguina, SA could not increase the chitinase activity but increase the peroxidase activity. The crude protein from in vitro shoots of T. tricuspidata could inhibited the spore germination of Fusarium sp. from T. cucumerina var. anguina, Fusarium oxysporum from shallot, Puccinia arachidis from peanut and Pseudoperonospora cubensis from cucumber. The protein could not inhibit spore germination of Curvularia eragrostidis from Dendrobium orchids
Influence Function and Robust Variant of Kernel Canonical Correlation Analysis

OpenAIRE

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

2017-01-01

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

African Journals Online (AJOL)

AGROSEARCH UIL

INTRODUCTION ... Sheabutter tree, Vitellaria paradoxa is a tropical plant of numerous domestic and ... adoptable by rural farmers for increased productivity. ... crude protein requirements (NRC, 1981) for maintenance and weight gain in the goat. ... Total faeces and urine produced daily by each goat were collected and ...
The Linux kernel as flexible product-line architecture

NARCIS (Netherlands)

M. de Jonge (Merijn)

2002-01-01

textabstractThe Linux kernel source tree is huge ($>$ 125 MB) and inflexible (because it is difficult to add new kernel components). We propose to make this architecture more flexible by assembling kernel source trees dynamically from individual kernel components. Users then, can select what
Entomology contribution in animal immunity: Determination of the crude thoraxial glandular protein extract of Stomoxys calcitrans as an antibody production enhancer in young horses

Directory of Open Access Journals (Sweden)

L. Rumokoy

2017-12-01

Full Text Available This experiment was conducted to evaluate the level of antigens protein contained in the crude thoraxial glandular protein (TGP extract of Stomoxys calcitrans which function as immunity enhancer in young horses. The detection of protein content of the thoraxial glandular samples was performed by using a spectrophotometer Nano Drop-1000. This result showed that the lowest level of antigen protein was 0.54 mg/mL, the highest was 72 mg/mL, and the average was 0.675 mg/mL. Six foals were used and divided into two groups. The first group was treated with a solution of 100 μg of TGP by subcutaneous injection, the other group acted as control. The TGP extract was injected on the first day of the experiment. Three ml of blood were sampled from the jugular vein on the 14th day after TGP injection. The blood sampled was centrifuged and its serum placed in micro-tubes to observe the IgG level. The injection of TGP had a significant effect on the IgG level of the experiment animals (P<0.05. This experiment emphasized an important relation between entomology and animal husbandry; health improvement in the young animals was observed after the injection of the insect antigen, so it can be concluded that crude thoraxial glandular proteins of S. calcitrans can be used to improve the immunoglobulin-G circulation in foals.
Effect of crude protein levels and organic selenium supplementation in the diets fed during the breeding season on reproductive parameters of red-winged tinamous (Rhynchotus rufescens

Directory of Open Access Journals (Sweden)

L Felipe

2010-03-01

Full Text Available There is little information on the nutrition of red-winged tinamous (Rhynchotus rufescens reared in captivity, and their nutritional requirements still need to be determined. This study aimed at determining dietary crude protein requirements and testing four organic selenium supplementation levels in the diet of red-winged tinamous during the breeding season. Birds were housed in a conventional broiler house divided in 16 boxes with one male and three females each. Iso-energy (2800kcal ME/kg pelleted feeds, based on corn and soybean meal, were supplied in tube feeders. In the first experiment, treatments consisted of four different diets containing different crude protein (CP contents (15, 18, 21, or 24% and in the second experiment, the four diets contained equal protein level (22.5% and four different organic selenium levels (0, 0.2, 0.4, or 0.8ppm. Data were analyzed by the least square method. The best egg weight and eggshell thickness were obtained with 22.5% dietary CP. Organic selenium did not influence the studied reproductive traits of red-winged tinamous (Rhynchotus rufescens males or females.
Intensive liquid feeding of dairy calves with a medium crude protein milk replacer: Effects on performance, rumen, and blood parameters.

Science.gov (United States)

de Paula, M R; Oltramari, C E; Silva, J T; Gallo, M P C; Mourão, G B; Bittar, C M M

2017-06-01

The objective of this study was to evaluate the effects of different liquid-feeding systems using a medium crude protein milk replacer on performance, rumen, and blood parameters. Thirty newborn Holstein calves were blocked according to birth weight and date of birth, and randomly distributed to different liquid-feeding systems: conventional (4 L/d), intensive (8 L/d), or step-up/step-down (wk 1, 4 L/d; wk 2 to 6, 8 L/d; wk 7 and 8, 4 L/d). The commercial milk replacer (12.5% solids, 20.2% crude protein, 15.6% fat) was fed twice daily (0700 and 1700 h) until calves were weaned, at 8 wk of age. Calves were individually housed in wood hutches, with free access to water and starter concentrate, and to hay only after weaning. They were followed through 10 wk of age. Milk replacer and starter intake were inversely affected by feeding system. After weaning, starter intake and hay intake were similar among feeding systems. Total dry matter intake was higher during the liquid-feeding period for calves on the intensive system compared to calves on the conventional system, but conventional feeding resulted in the highest dry matter intake after weaning. Feed efficiency was similar among feeding systems before and after weaning. Average body weight and daily gain were not affected by feeding system before or after weaning. During liquid feeding, diarrhea occurrence was lower for calves on the conventional system; however, when calves on the step-up/step-down system were fed lower volumes of liquid feed, diarrhea occurrence was similar to that of calves on the conventional system. Plasma concentrations of β-hydroxybutyrate were higher for calves on the conventional system, reflecting starter intake. Rumen pH, short-chain fatty acids, and N-NH 3 were not affected by feeding system. Feeding higher volumes of milk replacer with a medium crude protein content had no beneficial effect on the performance of calves up to 10 wk of age. Copyright © 2017 American Dairy Science
Relationship between content of crude protein in rations for dairy cows and milk yield, concentration of urea in milk and ammonia emissions.

Science.gov (United States)

Frank, B; Swensson, C

2002-07-01

During recent decades, efforts have been made in several countries to diminish the negative environmental influence of dairy production. The main focus has been on nitrogen and phosphorus. Modern dairy production in Western Europe is often based on imported feed-stuffs, mostly protein-rich feeds. In Sweden at least, it is wished that the use of imported feedstuffs in animal production will decrease due to the risk of contamination with Salmonella and the ban of using GMO crops in Swedish dairy production. An experiment was carried out to investigate whether a lower content of crude protein in the diet would decrease the ammonia release from cow manure and whether a well-balanced diet using only feedstuffs of Swedish origin would maintain milk production. Five treatments were arranged in a Latin square design. Two different protein supplements made of ingredients of Swedish origin were each fed at two protein levels, and a fifth imported commercial protein mix was fed at the higher level. The treatments with low protein levels (13.1 to 13.5%) had a significantly lower milk yield, kilograms of ECM, but, on the other hand the net profit, milk income minus feed cost was nearly the same in all treatments except diet C, which had lower feed cost but also lower net profit due to lower milk yield. The content of urea in milk was higher with diets high in crude protein (17%) content. A decreased protein level in the diets did not influence the content of casein or whey protein, but the commercial concentrate showed a tendency to give lower values than the Swedish mixtures. The low protein diets gave significantly lower ammonia release from manure compared with the high protein diets. There were no production differences between the diets of Swedish feeds compared with the imported control. The readily fermentable beet pulp should have helped cows use the higher N diet more efficiently and increased the response. This gives the rumen microbes a possibility to match the
Reducing crude protein content with supplementation of synthetic lysine and threonine in barley - rapeseed meal - pea diets for growing pigs

Directory of Open Access Journals (Sweden)

Jarmo Valaja

1993-03-01

Full Text Available This study was conducted to determine the possibility to use synthetic amino acids to lower the nitrogen output from pig production. A performance experiment was carried out with 120triplet-fed growing pigs whose dietary crude protein was reduced from 179 g/feed unit (FU= 0.7 kg starch equivalent to 160, 140 and 122 g/FU, respectively. The diets were supplemented with synthetic lysine and threonine to keep the level of these amino acids constant. Dietary protein reduction did not affect the growth performance or feed conversion ratio of the pigs, but it did linearly increase the portion of fat to lean in the carcass. Significant linear effect was found in back fat (p
GRIM : Leveraging GPUs for Kernel integrity monitoring

NARCIS (Netherlands)

Koromilas, Lazaros; Vasiliadis, Giorgos; Athanasopoulos, Ilias; Ioannidis, Sotiris

2016-01-01

Kernel rootkits can exploit an operating system and enable future accessibility and control, despite all recent advances in software protection. A promising defense mechanism against rootkits is Kernel Integrity Monitor (KIM) systems, which inspect the kernel text and data to discover any malicious
7 CFR 51.2296 - Three-fourths half kernel.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Three-fourths half kernel. 51.2296 Section 51.2296 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards...-fourths half kernel. Three-fourths half kernel means a portion of a half of a kernel which has more than...
Induction of reactive oxygen species in marine phytoplankton under crude oil exposure.

Science.gov (United States)

Ozhan, Koray; Zahraeifard, Sara; Smith, Aaron P; Bargu, Sibel

2015-12-01

Exposure of phytoplankton to the water-accommodated fraction of crude oil can elicit a number of stress responses, but the mechanisms that drive these responses are unclear. South Louisiana crude oil was selected to investigate its effects on population growth, chlorophyll a (Chl a) content, antioxidative defense, and lipid peroxidation, for the marine diatom, Ditylum brightwellii, and the dinoflagellate, Heterocapsa triquetra, in laboratory-based microcosm experiments. The transcript levels of several possible stress-responsive genes in D. brightwellii were also measured. The microalgae were exposed to crude oil for up to 96 h, and Chl a content, superoxide dismutase (SOD), the glutathione pool (GSH and GSSG), and lipid peroxidation content were analyzed. The cell growth of both phytoplankton species was inhibited with increasing crude oil concentrations. Crude oil exposure did not affect Chl a content significantly in cells. SOD activities showed similar responses in both species, being enhanced at 4- and 8-mg/L crude oil exposure. Only H. triquetra demonstrated enhanced activity in GSSG pool and lipid peroxidation at 8-mg/L crude oil exposure, suggesting that phytoplankton species have distinct physiological responses and tolerance levels to crude oil exposure. This study indicated the activation of reactive oxygen species (ROS) in phytoplankton under crude oil exposure; however, the progressive damage in cells is still unknown. Thus, ROS-related damage in nucleic acid, lipids, proteins, and DNA, due to crude oil exposure could be a worthwhile subject of study to better understand crude oil toxicity at the base of the food web.

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

Science.gov (United States)

Cid, Jaime A; von Davier, Alina A

2015-05-01

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

African Journals Online (AJOL)

This paper proposes the use of adaptive kernel in a meshsize boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...
Canada's crude oil resources : crude oil in our daily lives

International Nuclear Information System (INIS)

Bott, R.

2001-10-01

Created in 1975, the Petroleum Communication Foundation is a not-for-profit organization. The objective of the Foundation is to inform Canadians about the petroleum industry in Canada. It produces educational, fact-based publications and programs, employing a multi-stakeholder review process. The first section of this publication is devoted to crude oil and the benefits that are derived from it. It begins by providing a brief definition of crude oil, then moves to the many uses in our daily lives and the environmental impacts like air pollution, spills, and footprint on the land from exploration and production activities. Section 2 details the many uses of crude oil and identifies the major oil producing regions of Canada. A quick mention is made of non-conventional sources of crude oil. The search for crude oil is the topic of section 3 of the document, providing an overview of the exploration activities, the access rights that must be obtained before gaining access to the resource. The drilling of oil is discussed in section 4. Section 5 deals with issues pertaining to reservoirs within rocks, while section 6 covers the feeding of the refineries, discussing topics from the movement of oil to market to the refining of the crude oil, and the pricing issues. In section 7, the uncertain future is examined with a view of balancing the supply and demand, as crude oil is a non-renewable resource. Supplementary information is provided concerning additional publications published by various organizations and agencies. figs
Effect of kernel size and mill type on protein, milling yield, and baking quality of hard red spring wheat

Science.gov (United States)

Optimization of flour yield and quality is important in the milling industry. The objective of this study was to determine the effect of kernel size and mill type on flour yield and end-use quality. A hard red spring wheat composite sample was segregated, based on kernel size, into large, medium, ...
A kernel version of multivariate alteration detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

2013-01-01

Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....
Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

Science.gov (United States)

Kwak, Nojun

2016-05-20

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

Directory of Open Access Journals (Sweden)

Dinh Van Dung

2014-06-01

Full Text Available The effect of concentrate mixtures with crude protein (CP levels 10%, 13%, 16%, and 19% and diets with roughage to concentrate ratios 80:20, 60:40, 40:60, and 20:80 (w/w were determined on dry matter (DM and organic matter (OM digestibility, and fermentation metabolites using an in vitro fermentation technique. In vitro fermented attributes were measured after 4, 24, and 48 h of incubation respectively. The digestibility of DM and OM, and total volatile fatty acid (VFA increased whereas pH decreased with the increased amount of concentrate in the diet (p<0.001, however CP levels of concentrate did not have any influence on these attributes. Gas production reduced with increased CP levels, while it increased with increasing concentrate levels. Ammonia nitrogen (NH3-N concentration and microbial CP production increased significantly (p<0.05 by increasing CP levels and with increasing concentrate levels in diet as well, however, no significant difference was found between 16% and 19% CP levels. Therefore, 16% CP in concentrate and increasing proportion of concentrate up to 80% in diet all had improved digestibility of DM and organic matter, and higher microbial protein production, with improved fermentation characteristics.
Uranium kernel formation via internal gelation

International Nuclear Information System (INIS)

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

2004-01-01

In the 1970s and 1980s, U.S. Department of Energy (DOE) conducted numerous studies on the fabrication of nuclear fuel particles using the internal gelation process. These amorphous kernels were prone to flaking or breaking when gases tried to escape from the kernels during calcination and sintering. These earlier kernels would not meet today's proposed specifications for reactor fuel. In the interim, the internal gelation process has been used to create hydrous metal oxide microspheres for the treatment of nuclear waste. With the renewed interest in advanced nuclear fuel by the DOE, the lessons learned from the nuclear waste studies were recently applied to the fabrication of uranium kernels, which will become tri-isotropic (TRISO) fuel particles. These process improvements included equipment modifications, small changes to the feed formulations, and a new temperature profile for the calcination and sintering. The modifications to the laboratory-scale equipment and its operation as well as small changes to the feed composition increased the product yield from 60% to 80%-99%. The new kernels were substantially less glassy, and no evidence of flaking was found. Finally, key process parameters were identified, and their effects on the uranium microspheres and kernels are discussed. (orig.)
Effects of irradiated Bothropstoxin-1 and Bothrops jararacussu crude venom on the immune system

International Nuclear Information System (INIS)

Caproni, Priscila

2009-01-01

Ionizing radiation has been successfully employed to modify the immunological properties of biomolecules and has been proven to be a powerful tool to attenuate snake venoms toxicity without affecting and even increasing their immunogenic properties. Very promising results were obtained when crude animal venoms, as well as isolated toxins, were treated with 60 Co gamma rays, yielding toxoids with good immunogenicity, however, little is known about the modifications that irradiated molecules undergo and even less about the immunological response that such antigens elicit. At the present work, we have evaluated the effects on immune system of B10.PL and BALB/c mice of Bothrops jararacussu crude venom and isolated bothropstoxin-1 (Bthx-1), before and after gamma radiation exposition. According to our data, irradiation process promoted structural modifications on both isolated toxin and crude venom, characterized by higher molecular weight protein (aggregates and oligomers) formation. Irradiated samples were immunogenic and the antibodies elicited by them were able to recognize the native toxin in ELISA. These results indicate that irradiation of toxic proteins can promote significant modifications in their structures, but still retain many of the original antigenic and immunological properties. Also, our data indicate that the irradiated protein induced higher titers of IgG2b, suggesting that Th1 cells were predominantly involved. Results from Western blot assay showed that antibodies raised against irradiated bothropstoxin-1 recognize both native isolated toxin or crude venom. Cytotoxicity assay showed that irradiated toxin and crude venom were less toxic than their native counterpart. Thus, the viability of the macrophages cultured in the presence of irradiated Bthx-1 or crude venom was higher if compared with their native forms. LDH Assay showed that irradiated Bthx-1 promotes less muscular damage than the native form. Our data confirm a potential use of ionizing
Kernel learning at the first level of inference.

Science.gov (United States)

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

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

DEFF Research Database (Denmark)

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

2015-01-01

This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...
Quantum tomography, phase-space observables and generalized Markov kernels

International Nuclear Information System (INIS)

Pellonpaeae, Juha-Pekka

2009-01-01

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

Indian Academy of Sciences (India)

paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.
RHAGOLETIS COMPLETA (DIPTERA; TEPHRITIDAE) DISTRIBUTION, FLIGHT DYNAMICS AND INFLUENCE ON WALNUT KERNEL QUALITY IN THE CONTINENTAL CROATIA

OpenAIRE

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

2015-01-01

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

International Nuclear Information System (INIS)

Boyer, A.L.

1988-01-01

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

Data.gov (United States)

National Aeronautics and Space Administration — This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian...
Integral equations with contrasting kernels

Directory of Open Access Journals (Sweden)

Theodore Burton

2008-01-01

Full Text Available In this paper we study integral equations of the form $x(t=a(t-\\int^t_0 C(t,sx(sds$ with sharply contrasting kernels typified by $C^*(t,s=\\ln (e+(t-s$ and $D^*(t,s=[1+(t-s]^{-1}$. The kernel assigns a weight to $x(s$ and these kernels have exactly opposite effects of weighting. Each type is well represented in the literature. Our first project is to show that for $a\\in L^2[0,\\infty$, then solutions are largely indistinguishable regardless of which kernel is used. This is a surprise and it leads us to study the essential differences. In fact, those differences become large as the magnitude of $a(t$ increases. The form of the kernel alone projects necessary conditions concerning the magnitude of $a(t$ which could result in bounded solutions. Thus, the next project is to determine how close we can come to proving that the necessary conditions are also sufficient. The third project is to show that solutions will be bounded for given conditions on $C$ regardless of whether $a$ is chosen large or small; this is important in real-world problems since we would like to have $a(t$ as the sum of a bounded, but badly behaved function, and a large well behaved function.
Kernel methods in orthogonalization of multi- and hypervariate data

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

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

DEFF Research Database (Denmark)

Ohlsson, C; Houmøller, L P; Weisbjerg, Martin Riis

2007-01-01

The objective of the present study was to examine if near infrared reflectance spectroscopy (NIRS) could be used to predict degradation parameters and effective degradation from scans of original forage samples. Degradability of dry matter (DM), crude protein (CP) and neutral detergent fibre (NDF......) of 61 samples of perennial ryegrass (Lolium perenne L.) and orchardgrass (Dactylis glomerata L.) was tested by using the in situ technique. The grass samples were harvested at three different stages, early vegetative growth, early reproductive growth and late reproductive growth. Degradability...
Influence of pre-sowing irradiation of soya seeds with low doses of gamma rays on the yields of grain and on the content of crude protein in the grain

International Nuclear Information System (INIS)

Nikolov, Ch.V.

1985-01-01

Pre-sowing irradiation of air-dry soya seeds of the Hodson variety, calibrated in size and humidity (12%), with gamma rays in the range of relatively low intensities of irradiation of 0.27 to 5 Gy/min and doses of 10 to 20 Gy increases both the yield of grain and the content of crude protein in the grain in relation to the absolute dry matter. The dependence of radiostimulation effect on the factors of the environment cannot be reason for neglecting it as a posssible reserve for increasing the yield of grain from soya and the content of crude protein in the grain. Possible results are exspected from production experiments with pre-sowing irradiation of seeds of Hodson variety using gamma rays in the range of the above intensities and doses

Kernel based subspace projection of near infrared hyperspectral images of maize kernels

DEFF Research Database (Denmark)

Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben

2009-01-01

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

Science.gov (United States)

2016-01-05

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

Science.gov (United States)

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

2018-01-01

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

NARCIS (Netherlands)

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

2016-01-01

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

Directory of Open Access Journals (Sweden)

Wang Qin

2015-11-01

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Science.gov (United States)

Zhou, Hong; Liu, Shihang; Liu, Yujiao; Liu, Yaxi; You, Jing; Deng, Mei; Ma, Jian; Chen, Guangdeng; Wei, Yuming; Liu, Chunji; Zheng, Youliang

2016-09-13

Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.
A laser optical method for detecting corn kernel defects

Energy Technology Data Exchange (ETDEWEB)

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

1984-01-01

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

NARCIS (Netherlands)

Straalen, van W.M.; Salaün, C.; Veen, W.A.G.; Rypkema, Y.S.; Hof, G.; Boxem, T.J.

1994-01-01

Protein evaluation systems (crude protein (CP), digestible crude protein (DCP), protein digested in the intestine (PDI), amino acids truly absorbed in the small intestine (AAT), absorbed protein (AP), metabolizable protein (MP), crude protein flow at the duodenum (AAS) and digestible protein in
Kernel maximum autocorrelation factor and minimum noise fraction transformations

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2010-01-01

in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...
Market potential for Canadian crude oil

International Nuclear Information System (INIS)

Heath, M.; Fisher, L.; Golosinski, D.; Luthin, A.; Gill, L.; Raggett, C.

1997-01-01

Future key markets for Canadian crude were evaluated, and probable flow volumes and prices were identified. Key concerns of market participants such as pricing, alternative crude sources, pipeline tariffs and crude quality, were examined. An overview of the competition faced by Canadian crude supply in global markets was presented. World crude oil supply and demand was discussed. US and Canadian crude oil supply (2000 to 2010), refinery demand for light and heavy crudes, existing future crude oil and refined product pipeline infrastructure, and pricing implications of changing crude oil flows were analyzed. The general conclusion was that the US market will continue to provide growing markets for Canadian crude oil, and that the Canadian supply to fulfill increased export requirements will be available due to the combined effects of increasing heavy crude supply, growing production from the east coast offshore, and recent and ongoing pipeline expansions and additions. 20 refs., 64 tabs., 42 figs
Identification of Fusarium damaged wheat kernels using image analysis

Directory of Open Access Journals (Sweden)

Ondřej Jirsa

2011-01-01

Full Text Available Visual evaluation of kernels damaged by Fusarium spp. pathogens is labour intensive and due to a subjective approach, it can lead to inconsistencies. Digital imaging technology combined with appropriate statistical methods can provide much faster and more accurate evaluation of the visually scabby kernels proportion. The aim of the present study was to develop a discrimination model to identify wheat kernels infected by Fusarium spp. using digital image analysis and statistical methods. Winter wheat kernels from field experiments were evaluated visually as healthy or damaged. Deoxynivalenol (DON content was determined in individual kernels using an ELISA method. Images of individual kernels were produced using a digital camera on dark background. Colour and shape descriptors were obtained by image analysis from the area representing the kernel. Healthy and damaged kernels differed significantly in DON content and kernel weight. Various combinations of individual shape and colour descriptors were examined during the development of the model using linear discriminant analysis. In addition to basic descriptors of the RGB colour model (red, green, blue, very good classification was also obtained using hue from the HSL colour model (hue, saturation, luminance. The accuracy of classification using the developed discrimination model based on RGBH descriptors was 85 %. The shape descriptors themselves were not specific enough to distinguish individual kernels.
1999 Crude oil market outlook

International Nuclear Information System (INIS)

Cochener, J.

1998-01-01

Baseline projection handling of crude oil prices was discussed, based on actual crude oil price trends from 1992 to 1998. Attention was drawn to the lack of correlation between crude oil and natural gas prices. Predictions for crude oil production were extended to the year 2015. As far as the immediate future is concerned the crude oil price for 1999 was predicted to continue to be sluggish due to competitive pressure from refined products at burner tip. tabs., figs
Degradability of dry matter and crude protein of dry grains and wet grain silages from different processing corn hybrids (Zea mays)

OpenAIRE

Wagner dos Reis; Ciniro Costa; Paulo Roberto de Lima Meirelles; Marina Gabriela Berchiol da Silva; Marco Aurélio Factori; Janaína Conte Hadlich; Kátia de Oliveira; Erikelly Aline Ribeiro de Santana; Cristiano Magalhães Pariz; Josineudson Augusto II de Vasconcelos Silva

2013-01-01

The objective of this work was to evaluate the effect of processing two corn hybrids conserved, dry and humid grains, the dry matter (DM) and crude protein (CP) degradability in situ. The particle size was determined and difference was verified in MGD (Medium Geometric Diameter) of processed ingredients. Three sheep were used with rumen canulated, in a completely randomized design, using a factorial outline 2 x 2 x 3, being two corn hybrid, two conservation methods and three processing forms ...
Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

Science.gov (United States)

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

2015-05-01

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

CERN Document Server

Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

2018-01-01

A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...
Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

African Journals Online (AJOL)

In this paper, we shall use higher-order hybrid Gaussian kernel in a meshsize boosting algorithm in kernel density estimation. Bias reduction is guaranteed in this scheme like other existing schemes but uses the higher-order hybrid Gaussian kernel instead of the regular fixed kernels. A numerical verification of this scheme ...
Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...

African Journals Online (AJOL)

This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...
Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws

Directory of Open Access Journals (Sweden)

Mohammed D. ABDULMALIK

2008-06-01

Full Text Available Microsoft has made substantial enhancements to the kernel of the Microsoft Windows Vista operating system. Kernel improvements are significant because the kernel provides low-level operating system functions, including thread scheduling, interrupt and exception dispatching, multiprocessor synchronization, and a set of routines and basic objects.This paper describes some of the kernel security enhancements for 64-bit edition of Windows Vista. We also point out some weakness areas (flaws that can be attacked by malicious leading to compromising the kernel.
Lactic acid fermentation of crude sorghum extract

Energy Technology Data Exchange (ETDEWEB)

Samuel, W.A.; Lee, Y.Y.; Anthony, W.B.

1980-04-01

Crude extract from sweet sorghum supplemented with vetch juice was utilized as the carbohydrate source for fermentative production of lactic acid. Fermentation of media containing 7% (w/v) total sugar was completed in 60-80 hours by Lactobacillus plantarum, product yield averaging 85%. Maximum acid production rates were dependent on pH, initial substrate distribution, and concentration, the rates varying from 2 to 5 g/liter per hour. Under limited medium supplementation the lactic acid yield was lowered to 67%. The fermented ammoniated product contained over eight times as much equivalent crude protein (N x 6.25) as the original medium. Unstructured kinetic models were developed for cell growth, lactic acid formation, and substrate consumption in batch fermentation. With the provision of experimentally determined kinetic parameters, the proposed models accurately described the fermentation process. 15 references.

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

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

2016-05-01

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

Science.gov (United States)

Tezuka, Taro

2018-06-01

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

Directory of Open Access Journals (Sweden)

João Sérgio Oliveira Carvalho

2012-03-01

Full Text Available This study was conducted to evaluate performance and body composition of tilapia (Oreochromis niloticus fed diets containing byproducts aerial parts of cassava meal (Manihot esculenta, mesquite pod meal (Prosopis juliflora, cocoa meal (Theobroma cacao and palm kernel cake (Elaeis guineensis and to analyze the economic viability of the feed. A total of 1,350 juvenile males (100 g were distributed in 15 cages (1 m³ in completely randomized design with five treatments (basal diet and four test diets and three replicates. The following aspects were evaluated: final weight, total feed intake, total weight gain, feed conversion, specific growth rate, protein efficiency ratio and survival rate, dry matter, crude protein, fat and ash body, the average cost of feed per kilogram of weight gain and economic efficiency rate. No differences were observed for total consumption of food or survival rate. For other variables, the inclusion of cocoa and cassava meal impaired fish performance. No differences were observed for dry matter, crude protein and body ash. The lower body fat accumulation was recorded for the tilapia fed palm kernel cake. The best economic indicators were found to diets containing palm kernel cake. The byproducts evaluated can be used up to 150 g/kg in feed formulation, providing good performance and economic rate for Nile tilapia.
An analysis of 1-D smoothed particle hydrodynamics kernels

International Nuclear Information System (INIS)

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

1996-01-01

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

Science.gov (United States)

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

2004-01-01

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

Energy Technology Data Exchange (ETDEWEB)

Bartels, J. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fadin, V.S. [Budker Institute of Nuclear Physics, Novosibirsk (Russian Federation); Novosibirskij Gosudarstvennyj Univ., Novosibirsk (Russian Federation); Lipatov, L.N. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Petersburg Nuclear Physics Institute, Gatchina, St. Petersburg (Russian Federation); Vacca, G.P. [INFN, Sezione di Bologna (Italy)

2012-10-02

We present results for the NLO kernel of the BKP equations for composite states of three reggeized gluons in the Odderon channel, both in QCD and in N=4 SYM. The NLO kernel consists of the NLO BFKL kernel in the color octet representation and the connected 3{yields}3 kernel, computed in the tree approximation.
A Fast and Simple Graph Kernel for RDF

NARCIS (Netherlands)

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

2013-01-01

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

Science.gov (United States)

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

2017-12-01

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

DEFF Research Database (Denmark)

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

2010-01-01

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

Science.gov (United States)

Wang, Zhe; Lu, MingZhe; Gao, Daqi

2015-02-01

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

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Morton, J.C.

2008-01-01

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

International Nuclear Information System (INIS)

Halford, T.L.; McIntosh, A.P.; Rasmussen

1997-01-01

Some of the factors affecting a refiner's choice of crude oil include refinery hardware, particularly gas oil crackers, products slate and product specifications, crude availability, relative crude price and crude quality. An overview of synthetic crude, the use of synthetic crude combined with other crudes and a comparison of synthetic crude with conventional crude oil was given. The two main users of synthetic crude are basically two groups of refiners, those large groups who use synthetic crude combined with other crudes, and a smaller group who run synthetic crude on specially designed units as a sole feed. The effects of changes in fuel legislation were reviewed. It was predicted that the changes will have a mixed impact on the value of synthetic crude, but low sulphur diesel regulations and gasoline sulphur regulations will make current synthetic crudes attractive. The big future change with a negative impact will be diesel cetane increases to reduce engine emissions. This will reduce synthetic crude attractiveness due to distillate yields and quality and high gas oil yields. Similarly, any legislation limiting aromatics in diesel fuel will also make synthetic crudes less attractive. Problems experienced by refiners with hardware dedicated to synthetic crude (salt, naphthenic acid, fouling, quality variations) were also reviewed. 3 tabs
Enhanced gluten properties in soft kernel durum wheat

Science.gov (United States)

Soft kernel durum wheat is a relatively recent development (Morris et al. 2011 Crop Sci. 51:114). The soft kernel trait exerts profound effects on kernel texture, flour milling including break flour yield, milling energy, and starch damage, and dough water absorption (DWA). With the caveat of reduce...
7 CFR 981.61 - Redetermination of kernel weight.

Science.gov (United States)

2010-01-01

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

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

2000-01-01

Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...
Consistent Estimation of Pricing Kernels from Noisy Price Data

OpenAIRE

Vladislav Kargin

2003-01-01

If pricing kernels are assumed non-negative then the inverse problem of finding the pricing kernel is well-posed. The constrained least squares method provides a consistent estimate of the pricing kernel. When the data are limited, a new method is suggested: relaxed maximization of the relative entropy. This estimator is also consistent. Keywords: $\\epsilon$-entropy, non-parametric estimation, pricing kernel, inverse problems.
The role of Tre6P and SnRK1 in maize early kernel development and events leading to stress-induced kernel abortion.

Science.gov (United States)

Bledsoe, Samuel W; Henry, Clémence; Griffiths, Cara A; Paul, Matthew J; Feil, Regina; Lunn, John E; Stitt, Mark; Lagrimini, L Mark

2017-04-12

Drought stress during flowering is a major contributor to yield loss in maize. Genetic and biotechnological improvement in yield sustainability requires an understanding of the mechanisms underpinning yield loss. Sucrose starvation has been proposed as the cause for kernel abortion; however, potential targets for genetic improvement have not been identified. Field and greenhouse drought studies with maize are expensive and it can be difficult to reproduce results; therefore, an in vitro kernel culture method is presented as a proxy for drought stress occurring at the time of flowering in maize (3 days after pollination). This method is used to focus on the effects of drought on kernel metabolism, and the role of trehalose 6-phosphate (Tre6P) and the sucrose non-fermenting-1-related kinase (SnRK1) as potential regulators of this response. A precipitous drop in Tre6P is observed during the first two hours after removing the kernels from the plant, and the resulting changes in transcript abundance are indicative of an activation of SnRK1, and an immediate shift from anabolism to catabolism. Once Tre6P levels are depleted to below 1 nmol∙g -1 FW in the kernel, SnRK1 remained active throughout the 96 h experiment, regardless of the presence or absence of sucrose in the medium. Recovery on sucrose enriched medium results in the restoration of sucrose synthesis and glycolysis. Biosynthetic processes including the citric acid cycle and protein and starch synthesis are inhibited by excision, and do not recover even after the re-addition of sucrose. It is also observed that excision induces the transcription of the sugar transporters SUT1 and SWEET1, the sucrose hydrolyzing enzymes CELL WALL INVERTASE 2 (INCW2) and SUCROSE SYNTHASE 1 (SUSY1), the class II TREHALOSE PHOSPHATE SYNTHASES (TPS), TREHALASE (TRE), and TREHALOSE PHOSPHATE PHOSPHATASE (ZmTPPA.3), previously shown to enhance drought tolerance (Nuccio et al., Nat Biotechnol (October 2014):1-13, 2015). The impact
Stable Kernel Representations as Nonlinear Left Coprime Factorizations

NARCIS (Netherlands)

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

1994-01-01

A representation of nonlinear systems based on the idea of representing the input-output pairs of the system as elements of the kernel of a stable operator has been recently introduced. This has been denoted the kernel representation of the system. In this paper it is demonstrated that the kernel
7 CFR 981.60 - Determination of kernel weight.

Science.gov (United States)

2010-01-01

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

Science.gov (United States)

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

Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Ling-Yu Duan

2010-01-01

Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.
Per-Sample Multiple Kernel Approach for Visual Concept Learning

Directory of Open Access Journals (Sweden)

Tian Yonghong

2010-01-01

Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.
Discrete non-parametric kernel estimation for global sensitivity analysis

International Nuclear Information System (INIS)

Senga Kiessé, Tristan; Ventura, Anne

2016-01-01

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

Science.gov (United States)

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.
Improved modeling of clinical data with kernel methods.

Science.gov (United States)

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

2012-02-01

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

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Canty, Morton J.

2010-01-01

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

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

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

KAUST Repository

Zhan, Ge; Schuster, Gerard T.

2012-01-01

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

DEFF Research Database (Denmark)

Walder, Christian; Henao, Ricardo; Mørup, Morten

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

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

1998-01-01

Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...
21 CFR 176.350 - Tamarind seed kernel powder.

Science.gov (United States)

2010-04-01

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

African Journals Online (AJOL)

ADOWIE PERE

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

OpenAIRE

Härdle, Wolfgang; Müller, Marlene

1997-01-01

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

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole E.

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

African Journals Online (AJOL)

Effects of bonny light crude oil on anti-oxidative enzymes and total proteins in Wistar rats. Christian E Odo, Okwesili FC Nwodo, Parker E Joshua, Chibuike S Ubani, Okon E Etim, Okechukwu PC Ugwu ...
The influence of straw meal on the crude protein and amino acid metabolism and the digestibility of crude nutrients in broiler hens. 3

International Nuclear Information System (INIS)

Gruhn, K.; Zander, R.

1987-01-01

In two experiments with colostomized broiler hens the influence of a straw meal supplement on the apparent digestibility of the amino acids of the ration and the 15 N-labelled basic amino acids in wheat was studied. In experiment 1 the animals received 120 g mixed feed plus 0, 20, 30 and 40 g straw meal per animal and day. The digestibility of the amino acids decreased on average from 86% to 83%, 80% and 79% with the growing straw intake. In contrast to the control variant, 20 g straw meal intake resulted in a singificant decrease of digestibility for lysine, histidine, glycine, tyrosine, phenylanaline, cystine and methionine. 30 and 40 g straw meal reduced significantly the digestibility of all amino acids with the exception of arginine. The amino acid composition of the crude protein in feces changed only very slightly due to the straw supplement. In experiment 2 15 N-labelled wheat was a component of the ration. Of the 15 N-labelled amino acids lysine, histidine and arginine, 88, 90 and 95% were apparently digested. The adaptation of the animals to straw meal intake did not change the digestibility of the amino acids. (author)
Consumo e digestibilidade aparente da matéria seca, proteína e energia bruta, e balanço de nitrogênio das silagens de cinco genótipos de milho Consumption and apparent digestibility of dry matter, crude protein and crude energy, and balance of nitrogen of silages of five maize genotypes

Directory of Open Access Journals (Sweden)

G.A.R. Freitas

2003-08-01

Full Text Available Quantificaram-se o consumo voluntário e a digestibilidade aparente da matéria seca, proteína bruta, energia bruta e balanço de nitrogênio das silagens de cinco genótipos de milho (HT01, HT47C, HT129, AG 5011 e BR 3123. Foram utilizados 15 carneiros alojados em gaiolas metabólicas para coleta total de fezes e urina. O delineamento experimental foi o inteiramente ao acaso com cinco tratamentos e seis repetições. Não foram observadas diferenças entre os genótipos quanto ao consumo e digestibilidade da MS, da EB e da PB (P>0,05. Os consumos de MS, EB e PB digestíveis e energia metabolizável também não foram diferentes entre os híbridos (P>0,05. Quanto às relações consumo de energia digestível/consumo de MS e consumo de energia metabolizável/consumo de MS, o genótipo AG5011 foi semelhante ao HT01 (P>0,05 e superior aos demais (P0,05. Todos os genótipos produziram silagens de bom valor nutritivo, entretanto o genótipo AG5011 apresentou maior eficiência na utilização da energia (PThe voluntary intake and the apparent digestibility of dry matter, crude protein and crude energy and the nitrogen balance, of silages of five maize genotypes (HT01, HT47C, HT129, AG5011 and BR3123 were quantified. Fifteen sheep were stored in metabolic cages for total collection of feces and urine. A complete randomized design, with five treatments and six repetitions was used. The intake and digestibility of dry matter, crude protein and crude energy did not differ (P>0.05 among treatments. The intake of digestible dry matter, crude protein, crude energy and metabolic energy did not differ (P>0.05 among the genotypes. The ratios of digestible energy intake/dry matter intake and metabolic energy intake/dry matter intake of the genotype AG5011 silage was similar (P>0.05 to HT01, and higher than the other genotypes (P<0.05. All genotypes showed similar and positive nitrogen balance, and all of them produced silages of good nutritional value
Calculation of the thermal neutron scattering kernel using the synthetic model. Pt. 2. Zero-order energy transfer kernel

International Nuclear Information System (INIS)

Drozdowicz, K.

1995-01-01

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

KAUST Repository

Kosinka, Jiří

2016-02-12

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

KAUST Repository

Kosinka, Jiří ; Barton, Michael

2016-01-01

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

Hadamard Kernel SVM with applications for breast cancer outcome predictions.

Science.gov (United States)

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

2017-12-21

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

NARCIS (Netherlands)

Brouwer, A.E.

1995-01-01

Our Kernel Korner series continues with an article describing the Linux keyboard driver. This article is not for "Kernel Hackers" only--in fact, it will be most useful to those who wish to use their own keyboard to its fullest potential, and those who want to write programs to take advantage of the
Determination of amino acid contents of manketti seeds (Schinziophyton rautanenii) by pre-column derivatisation with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate and RP-HPLC.

Science.gov (United States)

Gwatidzo, Luke; Botha, Ben M; McCrindle, Rob I

2013-12-01

Defatted kernel flour from manketti seed kernels (Schinziophyton rautanenii) is an underutilised natural product. The plant grows in the wild, on sandy soils little used for agriculture in Southern Africa. The kernels are rich in protein and have a great potential for improving nutrition. The protein content and amino acid profile of manketti seed kernel were studied, using a new analytical method, in order to evaluate the nutritional value. The crude protein content of the press cake and defatted kernel flour was 29.0% and 67.5%, respectively. Leucine and arginine were found to be the most abundant essential and non-essential amino acids, respectively. The seed kernel contained 4.77 g leucine and 12.34 g arginine/100 g of defatted seed kernel flour. Methionine and proline were the least abundant essential and non-essential amino acids to with 0.23 g methionine and 0.36 g proline/100 g of defatted seed kernel flour, respectively. Validation of the pre-column derivatisation procedure with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) for the determination of amino acids was carried out. The analytical parameters were determined: linearity (0.0025-0.20 mM), accuracy of the derivatisation procedure: 86.7-109.8%, precision (method: 0.72-5.04%, instrumental: 0.14-1.88% and derivatisation: 0.15-2.94% and 0.41-4.32% for intraday and interday, respectively). Limits of detection and quantification were 6.80-157 mg/100 g and 22.7-523 mg/100 g kernel flour, respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.
The heating of UO_2 kernels in argon gas medium on the physical properties of sintered UO_2 kernels

International Nuclear Information System (INIS)

Damunir; Sri Rinanti Susilowati; Ariyani Kusuma Dewi

2015-01-01

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

Science.gov (United States)

Cheng, Jun; Huang, Rui; Yu, Tao; Li, Tao; Zhou, Junhu; Cen, Kefa

2014-01-01

A cogeneration process of biodiesel and bio-crude was proposed to make full use of wet microalgae biomass. High-grade biodiesel was first produced from lipids in wet microalgae through extraction and transesterification with microwave irradiation. Then, low-grade bio-crude was produced from proteins and carbohydrates in the algal residue through hydrothermal liquefaction. The total yield (40.19%) and the total energy recovery (67.73%) of the cogenerated biodiesel and bio-crude were almost equal to those of the bio-oil obtained from raw microalgae through direct hydrothermal liquefaction. Upon microwave irradiation, proteins were partially hydrolyzed and the hydrolysates were apt for deaminization under the hydrothermal condition of the algal residue. Hence, the total remaining nitrogen (16.02%) in the cogenerated biodiesel and bio-crude was lower than that (27.06%) in the bio-oil. The cogeneration process prevented lipids and proteins from reacting to produce low-grade amides and other long-chain nitrogen compounds during the direct hydrothermal liquefaction of microalgae. Copyright © 2013 Elsevier Ltd. All rights reserved.
Mitigation of artifacts in rtm with migration kernel decomposition

KAUST Repository

Zhan, Ge

2012-01-01

The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.
Full replacement of menhaden fish meal protein by low-gossypol cottonseed flour protein in the diet of juvenile black sea bass Centropristis striata

Science.gov (United States)

Eight iso-nitrogeneous (46% crude protein) and iso-lipidic (14% crude lipid) diets were formulated and prepared to replace menhaden fish meal (FM) protein (59.5% CP) by low-gossypol glandless meal (GCSM) protein (50.4% CP), solvent-extracted cottonseed meal (SCSM) protein (53.8% protein) and high go...
Realized kernels in practice

DEFF Research Database (Denmark)

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

2009-01-01

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

Science.gov (United States)

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

2016-09-21

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

Science.gov (United States)

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

2005-12-01

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

Science.gov (United States)

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

2015-01-01

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

International Nuclear Information System (INIS)

Zielinska, S.

1985-03-01

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

DEFF Research Database (Denmark)

Williams, Paul; Kucheryavskiy, Sergey V.

2016-01-01

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

DEFF Research Database (Denmark)

van Gelderen, Laurens; Malmquist, L.M.V.; Jomaas, Grunde

2015-01-01

In order to improve predictions for the burning efficiency and the residue composition of in-situ burning of crude oil, the burning mechanism of crude oil was studied in relation to the composition of its hydrocarbon mixture, before, during and after the burning. The surface temperature, flame...... height, mass loss rate and residues of three hydrocarbon liquids (n-octane, dodecane and hexadecane), two crude oils (DUC and REBCO) and one hydrocarbon liquid mixture of the aforementioned hydrocarbon liquids were studied using the Crude Oil Flammability Apparatus. The experimental results were compared...... on the highest achievable oil slick temperature. Based on this mechanism, predictions can then be made depending on the hydrocarbon composition of the fuel and the measured surface temperature....
Methods of analyzing crude oil

Science.gov (United States)

Cooks, Robert Graham; Jjunju, Fred Paul Mark; Li, Anyin; Rogan, Iman S.

2017-08-15

The invention generally relates to methods of analyzing crude oil. In certain embodiments, methods of the invention involve obtaining a crude oil sample, and subjecting the crude oil sample to mass spectrometry analysis. In certain embodiments, the method is performed without any sample pre-purification steps.
7 CFR 29.3015 - Crude.

Science.gov (United States)

2010-01-01

... of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing... Crude. A subdegree of maturity. Crude leaves are usually hard and slick as a result of extreme immaturity. A similar condition may result from sunburn or sunscald. Any leaf which is crude to the extent of...
Benchmark West Texas Intermediate crude assayed

International Nuclear Information System (INIS)

Rhodes, A.K.

1994-01-01

The paper gives an assay of West Texas Intermediate, one of the world's market crudes. The price of this crude, known as WTI, is followed by market analysts, investors, traders, and industry managers around the world. WTI price is used as a benchmark for pricing all other US crude oils. The 41 degree API < 0.34 wt % sulfur crude is gathered in West Texas and moved to Cushing, Okla., for distribution. The WTI posted prices is the price paid for the crude at the wellhead in West Texas and is the true benchmark on which other US crudes are priced. The spot price is the negotiated price for short-term trades of the crude. And the New York Mercantile Exchange, or Nymex, price is a futures price for barrels delivered at Cushing
Modulation of platelet functions by crude rice (Oryza sativa) bran policosanol extract.

Science.gov (United States)

Wong, Wai-Teng; Ismail, Maznah; Imam, Mustapha Umar; Zhang, Yi-Da

2016-07-28

Rice bran is bioactive-rich and has proven health benefits for humans. Moreover, its source, the brown rice has antioxidant, hypolipidemic and other functional properties that are increasingly making it a nutritional staple especially in Asian countries. This study investigated the antiplatelet aggregation mechanisms of crude hexane/methanolic rice bran extract, in which policosanol was the targeted bioactive. Platelets play a vital role in pathogenesis of atherosclerosis and cardiovascular diseases, and their increased activities could potentially cause arterial thrombus formation or severe bleeding disorders. Thus, in this study, platelet aggregation and adhesion of platelets to major components of basal lamina were examined in vitro. In addition, cellular protein secretion was quantified as a measurement of platelet activation. Adenosine diphosphate (ADP), collagen, and arachidonic acid (AA)-induced aggregation were studied using the microtiter technique. Rat platelets were pre-treated with various concentrations of policosanol extract, and the adhesion of platelets onto collagen- and laminin-coated surface (extracellular matrix) was studied using the acid phosphatase assay. The effect of crude policosanol extract on released proteins from activated platelets was measured using modified Lowry determination method. Rice bran policosanol extract significantly inhibited in vitro platelet aggregation induced by different agonists in a dose dependent manner. The IC50 of ADP-, collagen-, and AA-induced platelet aggregation were 533.37 ± 112.16, 635.94 ± 78.45 and 693.86 ± 70.57 μg/mL, respectively. The present study showed that crude rice bran policosanol extract significantly inhibited platelet adhesion to collagen in a dose dependent manner. Conversely, at a low concentration of 15.625 μg/mL, the extract significantly inhibited platelet adhesion to laminin stimulated by different platelet agonists. In addition to the alteration of cell adhesive
Evolution kernel for the Dirac field

International Nuclear Information System (INIS)

Baaquie, B.E.

1982-06-01

The evolution kernel for the free Dirac field is calculated using the Wilson lattice fermions. We discuss the difficulties due to which this calculation has not been previously performed in the continuum theory. The continuum limit is taken, and the complete energy eigenfunctions as well as the propagator are then evaluated in a new manner using the kernel. (author)
Gradient-based adaptation of general gaussian kernels.

Science.gov (United States)

Glasmachers, Tobias; Igel, Christian

2005-10-01

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

Crude value management through pipeline systems

Energy Technology Data Exchange (ETDEWEB)

Segato, R. [Suncor Energy Marketing Inc., Calgary, AB (Canada)

2009-07-01

This presentation reviewed Suncor's integrated oil flow operations with particular focus on the best practices in crude oil quality management from source rocks to refineries. Suncor produces synthetic crude at its operations in Fort McMurray, Alberta. The crude reaches destinations across North America. The quality of injected and delivered crude varies because of pipeline and terminal logistics, which implies changes in valuation. Refinery planners, engineers and crude traders are faced with the challenge of maximizing profitability while minimizing risk. Refiners face a continuously changing landscape in terms of crude classifications, new commodity developments, batch interferences, shared tank bottoms and sampling limitations. tabs., figs.
15 CFR 754.2 - Crude oil.

Science.gov (United States)

2010-01-01

... processed through a crude oil distillation tower. Included are reconstituted crude petroleum, and lease... 15 Commerce and Foreign Trade 2 2010-01-01 2010-01-01 false Crude oil. 754.2 Section 754.2....2 Crude oil. (a) License requirement. As indicated by the SS notation in the “License Requirements...
Nonparametric Inference of Doubly Stochastic Poisson Process Data via the Kernel Method.

Science.gov (United States)

Zhang, Tingting; Kou, S C

2010-01-01

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.
Analog forecasting with dynamics-adapted kernels

Science.gov (United States)

Zhao, Zhizhen; Giannakis, Dimitrios

2016-09-01

Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog forecasting by combining ideas from kernel methods developed in harmonic analysis and machine learning and state-space reconstruction for dynamical systems. A key ingredient of our approach is to replace single-analog forecasting with weighted ensembles of analogs constructed using local similarity kernels. The kernels used here employ a number of dynamics-dependent features designed to improve forecast skill, including Takens’ delay-coordinate maps (to recover information in the initial data lost through partial observations) and a directional dependence on the dynamical vector field generating the data. Mathematically, our approach is closely related to kernel methods for out-of-sample extension of functions, and we discuss alternative strategies based on the Nyström method and the multiscale Laplacian pyramids technique. We illustrate these techniques in applications to forecasting in a low-order deterministic model for atmospheric dynamics with chaotic metastability, and interannual-scale forecasting in the North Pacific sector of a comprehensive climate model. We find that forecasts based on kernel-weighted ensembles have significantly higher skill than the conventional approach following a single analog.
Open Problem: Kernel methods on manifolds and metric spaces

DEFF Research Database (Denmark)

Feragen, Aasa; Hauberg, Søren

2016-01-01

Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....
Evaluation of nutritive value of palm kernel cake fermented with molds as source of protein in ruminant

Directory of Open Access Journals (Sweden)

Wisri Puastuti

2014-06-01

Full Text Available The objective of the research was to improve the nutritive value of PKC through fermentation and to evaluate its degradation characteristics in the rumen and post rumen digestibility as a protein feed source for ruminants. PKC was fermented using Aspergillus niger, Trichoderma viridae and Aspergillus oryzae. To evaluate the in sacco rumen degradability, 2 rumen fistulated females Fries Holstein 3.5 years old were used. Samples were incubated in the rumen for 0, 4, 8, 12, 16, 24, 48 and 72 hours. Determination of dry matter (DM degradation characteristics value and crude protein (CP in the rumen was calculated based on formula y = a + b (1 - e-ct. The experiments were conducted using a completely randomized design with four replicates. The results showed that fermentation increased protein content of the PKC by 79.21% with the highest increase from fermentation using Aspergillus oryzae (88.34%. DM and CP degradability in the rumen and post rumen of fermented PKC was affected by type of mold used for fermentation. Fermentation increased the amount of water soluble DM (a of fermented PKC with average of 46.7%, but the value of insoluble but degradable fraction in the rumen (b was decreased. Fermentation by molds resulited in the reduction of fraction of insoluble CP but degradable (b in the rumen by 50.42%. PKC fermentation by Aspergillus oryzae resulted in the higest CP degradability in the rumen and post rumen. It can be concluded that PKC has a high content of degradable CP in the rumen even without fermentation. Protein source from PKC fermented using Aspergillus oryzae categorized as the best source of feed protein in terms of increasing CP content and digestibility.
Genetic dissection of the maize kernel development process via conditional QTL mapping for three developing kernel-related traits in an immortalized F2 population.

Science.gov (United States)

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

2016-02-01

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Science.gov (United States)

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

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

African Journals Online (AJOL)

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

DEFF Research Database (Denmark)

Möllers, Jan

2014-01-01

. The heat kernel is explicitly given in terms of a multivariable $I$-Bessel function on $Ω$. Its corresponding heat kernel transform defines a continuous linear operator between $L^p$-spaces. The unitary image of the $L^2$-space under the heat kernel transform is characterized as a weighted Bergmann space...
A multi-scale kernel bundle for LDDMM

DEFF Research Database (Denmark)

Sommer, Stefan Horst; Nielsen, Mads; Lauze, Francois Bernard

2011-01-01

The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...
Fish protein hydrolysate production from sardine solid waste by crude pepsin enzymatic hydrolysis in a bioreactor coupled to an ultrafiltration unit

International Nuclear Information System (INIS)

Benhabiles, M.S.; Abdi, N.; Drouiche, N.; Lounici, H.; Pauss, A.; Goosen, M.F.A.; Mameri, N.

2012-01-01

The aims of the study were to optimize the production a fish protein hydrolysate (FPH) by enzymatic hydrolysis of sardine solid waste using crude pepsin, and to scale up the process in a bioreactor coupled to an ultrafiltration unit for product recovery. Results showed that the crude pepsin prepared by autolysis of the mucous membranes of a sheep stomach at optimal conditions (i. e. pH = 1.5–2 and incubation time of 6 h) could be satisfactory used for the enzymatic hydrolysis of fish solid waste. The optimal conditions for enzymatic reaction were: temperature 48 °C, and pH 1.5. The scale up of the enzymatic hydrolysis and the coupling of the reactor an ultrafiltration unit to concentrate the hydrolysate gave good results with a rejection coefficient for the protein hydrolysate product in the range of 90%. The volumetric concentration factor was 2.5, with a permeate flux of 200 L m −2 bar −1 . However, the results also suggest that the ultrafiltration product concentration process may be operating beyond the critical flux at which point irreversible membrane fouling occurs. - Highlights: ► Evaluating to produce a (FPH) by enzymatic hydrolysis of sardine solid wastes was achieved. ► Investigation of key parameters for optimal conditions for enzymatic hydrolysis have been studied. ► Valorization of sardine waste was realized by enzymatic hydrolysis process. ► Performances of this enzyme gave comparable results to those obtained with commercial pepsin. ► The nutritional quality of the FPH produced appears to be satisfactory.
Comparison of crude oil interfacial behavior

Energy Technology Data Exchange (ETDEWEB)

Beetge, J.H.; Panchev, N. [Champion Technologies Inc., Fresno, TX (United States)

2008-07-01

The bulk properties of crude oil are used to predict its behaviour with regards to treatment, transport and processing. Surface active components, such as asphaltenes, are often used to study or explain critical interfacial behaviour of crude oil. This study investigated the differences and similarities in the interfacial behaviour of the collective surface active component in various crude oils from different sources. The properties of interfaces between crude oil and water were compared using a Teclis drop shape tensiometer. A portion of a crude oil sample was diluted in toluene and contacted with water in a rising drop configuration. Dynamic surface tension and interfacial rheology was examined as a function of time from the early stages of interface formation. Sinusoidal oscillation of the drop volume allowed for the evaluation of visco-elastic behaviour of the crude oil/water interface as it developed with time. The Gibbs elastic modulus, as well as its elastic and viscose components were calculated from the drop shape. The interfacial behaviour was expressed in terms of concentration, oscillation frequency and interface age. It was concluded that knowledge of crude oil interfacial character could be of value in the treatment, transport and processing of crude oils because the its behaviour may play a significant role in crude oil production and processing.
Uptake and utilization of nutrients by developing kernels of Zea mays L

International Nuclear Information System (INIS)

Lyznik, L.A.

1987-01-01

The mechanisms involved in amino acid and sugar uptake by developing maize kernels were investigated. In the pedicel region of maize kernel, the site of nutrient unloading from phloem terminals, amino acids are accumulated in considerable amounts and undergo significant interconversion. A wide spectrum of enzymatic activities involved in the metabolism of amino acids is observed in these tissues. Subsequently, amino acids are taken up by the endosperm tissue in processes which require energy and the presence of carrier proteins. Conversely, no evidence was found that energy and carriers are involved in sugar uptake. This process of sugar uptake is not inhibited by metabolic inhibitors and shows nonsaturable kinetics, but the uptake is pH-dependent. L-glucose is taken up at a significantly reduced rate in comparison to D-glucose uptake. Based on analysis of radioactivity distribution among sugar fractions after incubations of kernels with radiolabeled D-glucose, it seems that sucrose is not efficiently resynthesized from D-glucose in the endosperm tissue. Thus, the proposed mechanism of sucrose transport involving sucrose hydrolysis in the pedicel region and subsequent resynthesis in endosperm cells may not be the main pathway. The evidence that transfer cells play an active role in D-glucose transport is presented
Training Lp norm multiple kernel learning in the primal.

Science.gov (United States)

Liang, Zhizheng; Xia, Shixiong; Zhou, Yong; Zhang, Lei

2013-10-01

Some multiple kernel learning (MKL) models are usually solved by utilizing the alternating optimization method where one alternately solves SVMs in the dual and updates kernel weights. Since the dual and primal optimization can achieve the same aim, it is valuable in exploring how to perform Lp norm MKL in the primal. In this paper, we propose an Lp norm multiple kernel learning algorithm in the primal where we resort to the alternating optimization method: one cycle for solving SVMs in the primal by using the preconditioned conjugate gradient method and other cycle for learning the kernel weights. It is interesting to note that the kernel weights in our method can obtain analytical solutions. Most importantly, the proposed method is well suited for the manifold regularization framework in the primal since solving LapSVMs in the primal is much more effective than solving LapSVMs in the dual. In addition, we also carry out theoretical analysis for multiple kernel learning in the primal in terms of the empirical Rademacher complexity. It is found that optimizing the empirical Rademacher complexity may obtain a type of kernel weights. The experiments on some datasets are carried out to demonstrate the feasibility and effectiveness of the proposed method. Copyright © 2013 Elsevier Ltd. All rights reserved.
Coupling individual kernel-filling processes with source-sink interactions into GREENLAB-Maize.

Science.gov (United States)

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

2018-02-13

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

Science.gov (United States)

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.
Exports of crude oil, 1988

International Nuclear Information System (INIS)

1989-06-01

Effective June 1, 1985, licensing and charging of oil exports ended. The Board now issues export orders specifying neither volumes nor prices and covering an exportation period of up to 1 year for light crude oil and up to 2 years for heavy crude oil, available on request to both Canadian and foreign companies. The Board has assumed a monitoring role, and export prices and volumes are reported monthly by exporters. This annual report provides a review of the volumes and prices associated with the supply and disposition of Canadian crude oil during 1988. Highlights are given with detailed information on prices, both internationally, in Canada, and the Chicago posted price by light or heavy crude, and on volumes including capacity and disposition in both domestic and export markets. A short description of the import market is included. Comparisons are made with the previous year. Export volumes of light crude oil in 1988 increased by 13% to average 50,200 m 3 /d. Export volumes of heavy crude also increased by ca 13% to 62,600 m 3 /d. 15 figs., 2 tabs
RTOS kernel in portable electrocardiograph

Science.gov (United States)

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

2011-12-01

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

RTOS kernel in portable electrocardiograph

International Nuclear Information System (INIS)

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

2011-01-01

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

Science.gov (United States)

Grover, Satyajit; Khosravi, Hormuzd; Kolar, Divya; Moffat, Samuel; Kounavis, Michael E.

In this paper we address the problem of protecting computer systems against stealth malware. The problem is important because the number of known types of stealth malware increases exponentially. Existing approaches have some advantages for ensuring system integrity but sophisticated techniques utilized by stealthy malware can thwart them. We propose Runtime Kernel Rootkit Detection (RKRD), a hardware-based, event-driven, secure and inclusionary approach to kernel integrity that addresses some of the limitations of the state of the art. Our solution is based on the principles of using virtualization hardware for isolation, verifying signatures coming from trusted code as opposed to malware for scalability and performing system checks driven by events. Our RKRD implementation is guided by our goals of strong isolation, no modifications to target guest OS kernels, easy deployment, minimal infra-structure impact, and minimal performance overhead. We developed a system prototype and conducted a number of experiments which show that the per-formance impact of our solution is negligible.
Denoising by semi-supervised kernel PCA preimaging

DEFF Research Database (Denmark)

Hansen, Toke Jansen; Abrahamsen, Trine Julie; Hansen, Lars Kai

2014-01-01

Kernel Principal Component Analysis (PCA) has proven a powerful tool for nonlinear feature extraction, and is often applied as a pre-processing step for classification algorithms. In denoising applications Kernel PCA provides the basis for dimensionality reduction, prior to the so-called pre-imag...
Sentiment classification with interpolated information diffusion kernels

NARCIS (Netherlands)

Raaijmakers, S.

2007-01-01

Information diffusion kernels - similarity metrics in non-Euclidean information spaces - have been found to produce state of the art results for document classification. In this paper, we present a novel approach to global sentiment classification using these kernels. We carry out a large array of
Drug: D06769 [KEGG MEDICUS

Lifescience Database Archive (English)

Full Text Available D06769 Crude ... Drug Peach kernel (JP17); Powdered peach kernel (JP17); Peach kernel...tegory: 5100 ... Rosaceae (rose family) Peach kernel Major component: Amygdalin [CPD:C08325] ... PubChem: 47208420 ...
Effect of Dietary Crude Protein and Methionine on Egg Production and Egg Quality of Laying Hens During Phase II

Directory of Open Access Journals (Sweden)

H Mohammadi Emarat

2012-02-01

Full Text Available An experiment was conducted to evaluate the effect of dietary crude protein and methionine levels on quality and quantity of egg production. Fifteen diets formulated with 3 levels of protein (13, 14 and 15% and 5 levels of methionine (0.25, 0.28, 0.31, 0.34 and 0.37% and fed to 420 birds in a 3×5 factorial arrangement. Each diet was randomly fed to 4 replicates of 7 birds each and fed for 3 periods of 4 weeks (50-62wks of age each. Egg number and mortality was recorded daily, whereas feed consumption determined at the end of each period. The increased in dietary protein significantly increased egg production from 54 to 59.4 %. Egg weight, egg mass and feed intake increased by 1.7 g, 3.4 g, and 2.8 g, respectively during the whole experimental period. As the dietary protein increased, feed conversion, egg component (as a percent of whale egg and egg albumin percent were improved. However, the egg breaking, specific gravity and eggshell were significantly decreased with increased dietary protein. The egg yolk percent was not influenced by dietary protein levels. The increased in dietary methionine from 0.25% to 0.37% caused the overall egg production, egg weight, egg mass, feed intake and egg component to improve by about 8.2%, 4g, 6.6g, 8.7g, and 6.0g, respectively. Feed conversion, specific gravity, egg breakage, egg shell, and egg yolk and albumin percent were not influenced by dietary methionine levels.
Linear and kernel methods for multivariate change detection

DEFF Research Database (Denmark)

Canty, Morton J.; Nielsen, Allan Aasbjerg

2012-01-01

), as well as maximum autocorrelation factor (MAF) and minimum noise fraction (MNF) analyses of IR-MAD images, both linear and kernel-based (nonlinear), may further enhance change signals relative to no-change background. IDL (Interactive Data Language) implementations of IR-MAD, automatic radiometric...... normalization, and kernel PCA/MAF/MNF transformations are presented that function as transparent and fully integrated extensions of the ENVI remote sensing image analysis environment. The train/test approach to kernel PCA is evaluated against a Hebbian learning procedure. Matlab code is also available...... that allows fast data exploration and experimentation with smaller datasets. New, multiresolution versions of IR-MAD that accelerate convergence and that further reduce no-change background noise are introduced. Computationally expensive matrix diagonalization and kernel image projections are programmed...
Panel data specifications in nonparametric kernel regression

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

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

Science.gov (United States)

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

2018-01-25

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

International Nuclear Information System (INIS)

Brooks, E.D. III

1988-01-01

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

International Nuclear Information System (INIS)

Qi, Chengming; Wang, Yuping; Tian, Wenjie; Wang, Qun

2016-01-01

The performance of kernel-based method, such as support vector machine (SVM), is greatly affected by the choice of kernel function. Multiple kernel learning (MKL) is a promising family of machine learning algorithms and has attracted many attentions in recent years. MKL combines multiple sub-kernels to seek better results compared to single kernel learning. In order to improve the efficiency of SVM and MKL, in this paper, the Kullback–Leibler kernel function is derived to develop SVM. The proposed method employs an improved ensemble learning framework, named KLMKB, which applies Adaboost to learning multiple kernel-based classifier. In the experiment for hyperspectral remote sensing image classification, we employ feature selected through Optional Index Factor (OIF) to classify the satellite image. We extensively examine the performance of our approach in comparison to some relevant and state-of-the-art algorithms on a number of benchmark classification data sets and hyperspectral remote sensing image data set. Experimental results show that our method has a stable behavior and a noticeable accuracy for different data set.
Kernel Methods for Mining Instance Data in Ontologies

Science.gov (United States)

Bloehdorn, Stephan; Sure, York

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

International Nuclear Information System (INIS)

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

1983-01-01

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

Directory of Open Access Journals (Sweden)

Daniel Rabello Ituassú

2005-03-01

Full Text Available O objetivo deste trabalho foi avaliar o efeito de quatro níveis de proteína sobre o crescimento de juvenis de pirarucu, Arapaima gigas. O experimento foi conduzido em delineamento inteiramente casualizado, com de quatro tratamentos (32,7%, 39,3%, 43,4% e 48,6% de proteína bruta, três repetições cada. Foram utilizados 120 peixes, com peso médio inicial de 120,6±3,5 g, distribuídos homogeneamente em 12 tanques-rede de 1 m³ cada, contendo dez peixes por tanque. Após 45 dias, os resultados indicaram que as dietas com 48,6% de proteína resultaram em melhor ganho de peso, crescimento específico e composição corporal diferenciada. A conversão alimentar e a eficiência da ração não produziram diferenças entre os tratamentos. O nível de proteína na ração que produz máximo crescimento é de 48,6%.The objective of this work was to verify the effect of four protein levels on pirarucu, Arapaima gigas, growth performance. One hundred and twenty pirarucu juveniles, with an average weight of 120.6±3.5 g, were stocked into 12 floating cages with 1 m³ (ten fish per cage, in a complete randomized design with four treatments (32.7%, 39.3%, 43.4% and 48.6% crude protein, in three replicates each. After 45 days, results showed that diet with highest protein level (48.6% produced a better weight gain, specific growth rate, and differentiated body composition. Feed conversion and protein efficiency ratios did not show any differences among treatments. The dietary protein level required to produce maximum growth is 48.6%.
The integral first collision kernel method for gamma-ray skyshine analysis[Skyshine; Gamma-ray; First collision kernel; Monte Carlo calculation

Energy Technology Data Exchange (ETDEWEB)

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

2003-12-01

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

International Nuclear Information System (INIS)

Kausar, T.; Ali, S.; Javed, M.A.; Javad, M.A.

2004-01-01

Chemical composition of seven varieties of sunflower seeds and seed fractions i.e., kernels, hulls and meals was determined. Sunflower meals (SFM) contained 44.00 to 49.52% crude protein, 1.25 to 1.50% fat, 3.43 to 6.75% crude fibre, 7.50 to 8.51% ash, 27.30 to 36.09% nitrogen free extract, 3.12 to 3.51% phytic acid and 2.45 to 3.01% chlorogenic acid. Fatty acid profile of sunflower oil with respect to other vegetable oils (i.e., soybean, mustard, canola, cotton, corn oils) and protein solubility profile of sunflower meal as compared to soybean and mustard meals, indicate that its oil and meal have a great nutritional potential. (author)
A kernel adaptive algorithm for quaternion-valued inputs.

Science.gov (United States)

Paul, Thomas K; Ogunfunmi, Tokunbo

2015-10-01

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

Science.gov (United States)

Andersson, Björn; von Davier, Alina A.

2014-01-01

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

Directory of Open Access Journals (Sweden)

JO Oyedeji

2005-09-01

Full Text Available Five isocaloric (3200kcal/kg diets were used in an experiment designed to investigate the effects of dietary crude protein (CP and feeding regimens on broiler performance. Day-old broilers were randomly distributed into four groups using a completely randomized design. Each group was replicated three times with ten broiler chicks per replicate. The experiment lasted for eight weeks. Broilers in group 1 received 23% CP from 0 to 3 weeks, 20% CP from 3 to 6 weeks and 18% CP from 6 to 8 weeks, while broilers in group 2 received 23% CP between 0 and 6 weeks and 18% CP between 6 and 8 weeks. Besides, broilers in group 3 were fed 23% CP from 0 to 4 weeks and 16% CP from 4 to 8 weeks, whereas group 4 was given 18% CP from 0 to weeks. Water was supplied ad libitum for broilers in the different dietary groups. A metabolic trial was carried out on the third week of the experiment using a total collection method. Proximate analyses of diets and faecal samples were performed according to the methods outlined by the Association Of the Official Analytical Chemists. Results at market age showed that broiler performance with respect to feed intake, weight gain, feed to gain ratio and water intake were not significantly influenced by CP regimens (p>0.05. Furthermore, CP regimens did not significantly influence broilers liveability (p>0.05. Protein retention, fat utilization and available fiber were not significantly influenced among treatments (p> 0.05. Economic data showed that cost to benefit ratio of producing broilers was comparable among broilers for all CP regimens used in this trial (p>0.05. It was concluded that a single diet of 18% CP and 3200kcal/kg metabolizable energy would be most suitable and convenient for farmers who are engaged in on-farm feed production for broilers as compared with the standard feeding regimens of broiler starter and broiler finisher diets.
Point kernels and superposition methods for scatter dose calculations in brachytherapy

International Nuclear Information System (INIS)

Carlsson, A.K.

2000-01-01

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

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

Science.gov (United States)

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

2013-05-01

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

Indian Academy of Sciences (India)

2011-12-02

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

African Journals Online (AJOL)

PRECIOUS

2010-01-11

Jan 11, 2010 ... enzyme and non-enzyme pre-treated cassava peel. ... T. viride in the fermentor revealed that dry biomass increased in crude protein, true protein, crude fat, ... either directly for human food or indirectly by conversion to animal ...
Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

Energy Technology Data Exchange (ETDEWEB)

Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov

2016-02-25

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.
Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique

International Nuclear Information System (INIS)

Hao, Ming; Wang, Yanli; Bryant, Stephen H.

2016-01-01

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.
Crude oil market report

Energy Technology Data Exchange (ETDEWEB)

1985-01-01

Falling demand for refined products and an excess of production capacity are driving world oil prices down further. Competitive price cutting, notably by Mexico, Britain, and the Soviet Union, has left Saudi Arabia the only guardian of a costly pricing discipline in terms of crude oil sales. The current crisis is limited to the producers of crude oil. Refineries are now deciding what, where, and how to buy crude in order to meet the requirements of a slack market place. Saudi Arabia could precipitate a price collapse below $20 per barrel by increasing production volume, but that seems unlikely. 1 figure, 2 tables.
Crude oil spot market pricing: Pearsonian analysis of crude oil spot market prices

International Nuclear Information System (INIS)

Akinnusi, Ayo

1994-01-01

This paper presents a brief overview of crude oil pricing before describing a study of sets of 1991 spot market prices, and examining Pearson's model. Empirical distribution characteristics for 14 crude oils are tabulated, and skewness-kurtosis relationship and implication are considered. (UK)
A multi-label learning based kernel automatic recommendation method for support vector machine.

Science.gov (United States)

Zhang, Xueying; Song, Qinbao

2015-01-01

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

Science.gov (United States)

Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier
Fish protein hydrolysate production from sardine solid waste by crude pepsin enzymatic hydrolysis in a bioreactor coupled to an ultrafiltration unit

Energy Technology Data Exchange (ETDEWEB)

Benhabiles, M.S.; Abdi, N. [National Polytechnic school of Algiers, B.P. 182-16200, El Harrach, Algiers (Algeria); Drouiche, N., E-mail: nadjibdrouiche@yahoo.fr [National Polytechnic school of Algiers, B.P. 182-16200, El Harrach, Algiers (Algeria); Silicon Technology Development Unit (UDTS) 2, Bd Frantz Fanon BP140, Alger-7 Merveilles, 16000 (Algeria); Lounici, H. [National Polytechnic school of Algiers, B.P. 182-16200, El Harrach, Algiers (Algeria); Pauss, A. [University of Technology of Compiegne, Departement Genie chimique,B.P. 20.509, 60205 Compiegne cedex (France); Goosen, M.F.A. [Alfaisal University, Riyadh (Saudi Arabia); Mameri, N. [University of Technology of Compiegne, Departement Genie chimique,B.P. 20.509, 60205 Compiegne cedex (France)

2012-05-01

The aims of the study were to optimize the production a fish protein hydrolysate (FPH) by enzymatic hydrolysis of sardine solid waste using crude pepsin, and to scale up the process in a bioreactor coupled to an ultrafiltration unit for product recovery. Results showed that the crude pepsin prepared by autolysis of the mucous membranes of a sheep stomach at optimal conditions (i. e. pH = 1.5-2 and incubation time of 6 h) could be satisfactory used for the enzymatic hydrolysis of fish solid waste. The optimal conditions for enzymatic reaction were: temperature 48 Degree-Sign C, and pH 1.5. The scale up of the enzymatic hydrolysis and the coupling of the reactor an ultrafiltration unit to concentrate the hydrolysate gave good results with a rejection coefficient for the protein hydrolysate product in the range of 90%. The volumetric concentration factor was 2.5, with a permeate flux of 200 L m{sup -2} bar{sup -1}. However, the results also suggest that the ultrafiltration product concentration process may be operating beyond the critical flux at which point irreversible membrane fouling occurs. - Highlights: Black-Right-Pointing-Pointer Evaluating to produce a (FPH) by enzymatic hydrolysis of sardine solid wastes was achieved. Black-Right-Pointing-Pointer Investigation of key parameters for optimal conditions for enzymatic hydrolysis have been studied. Black-Right-Pointing-Pointer Valorization of sardine waste was realized by enzymatic hydrolysis process. Black-Right-Pointing-Pointer Performances of this enzyme gave comparable results to those obtained with commercial pepsin. Black-Right-Pointing-Pointer The nutritional quality of the FPH produced appears to be satisfactory.
Unsupervised multiple kernel learning for heterogeneous data integration.

Science.gov (United States)

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

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

DEFF Research Database (Denmark)

Sommer, Stefan Horst; Lauze, Francois Bernard; Nielsen, Mads

2011-01-01

In the LDDMM framework, optimal warps for image registration are found as end-points of critical paths for an energy functional, and the EPDiff equations describe the evolution along such paths. The Large Deformation Diffeomorphic Kernel Bundle Mapping (LDDKBM) extension of LDDMM allows scale space...
Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.

Science.gov (United States)

Han, Yina; Yang, Kunde; Ma, Yuanliang; Liu, Guizhong

2014-01-01

Our objective is to train support vector machines (SVM)-based localized multiple kernel learning (LMKL), using the alternating optimization between the standard SVM solvers with the local combination of base kernels and the sample-specific kernel weights. The advantage of alternating optimization developed from the state-of-the-art MKL is the SVM-tied overall complexity and the simultaneous optimization on both the kernel weights and the classifier. Unfortunately, in LMKL, the sample-specific character makes the updating of kernel weights a difficult quadratic nonconvex problem. In this paper, starting from a new primal-dual equivalence, the canonical objective on which state-of-the-art methods are based is first decomposed into an ensemble of objectives corresponding to each sample, namely, sample-wise objectives. Then, the associated sample-wise alternating optimization method is conducted, in which the localized kernel weights can be independently obtained by solving their exclusive sample-wise objectives, either linear programming (for l1-norm) or with closed-form solutions (for lp-norm). At test time, the learnt kernel weights for the training data are deployed based on the nearest-neighbor rule. Hence, to guarantee their generality among the test part, we introduce the neighborhood information and incorporate it into the empirical loss when deriving the sample-wise objectives. Extensive experiments on four benchmark machine learning datasets and two real-world computer vision datasets demonstrate the effectiveness and efficiency of the proposed algorithm.
Control Transfer in Operating System Kernels

Science.gov (United States)

1994-05-13

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

Science.gov (United States)

Mazza, Angelo; Punzo, Antonio

2015-07-01

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

Science.gov (United States)

Zhang, Shuai; Stein, Hans Henrik; Zhao, Jinbiao; Li, Defa

2018-01-01

Objective An experiment was conducted to evaluate effects of inclusion level of palm kernel meal (PKM) and adaptation duration on the digestible energy (DE) and apparent total tract digestibility (ATTD) of chemical constituents in diets fed to growing-finishing pigs. Methods Thirty crossbred barrows (Duroc×Landrace×Large White) with an average initial body weight of 85.0±2.1 kg were fed 5 diets in a completely randomized design. The diets included a corn-soybean meal basal diet and 4 additional diets in which corn and soybean meal were partly replaced by 10%, 20%, 30%, or 40% PKM. After 7 d of adaptation to the experimental diets, feces were collected from d 8 to 12, d 15 to 19, d 22 to 26, and d 29 to 33, respectively. Results The DE and ATTD of gross energy (GE), dry matter (DM), ash, organic matter (OM), neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) in diets decreased linearly as the dietary PKM increased within each adaptation duration (p 0.05). Considering a stable determination, 21 days of adaptation to a diet containing 19.5% PKM is needed in pigs and a longer adaptation time is recommended as dietary PKM increases. PMID:28920411
A framework for optimal kernel-based manifold embedding of medical image data.

Science.gov (United States)

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

2015-04-01

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

International Nuclear Information System (INIS)

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

2011-01-01

The TRISO-coated fuel particle for the high temperature gas-cooled reactor (HTGR) is composed of a nuclear fuel kernel and outer coating layers. The coated particles are mixed with graphite matrix to make HTGR fuel element. The weight of fuel kernels in an element is generally measured by the chemical analysis or a gamma-ray spectrometer. Although it is accurate to measure the weight of kernels by the chemical analysis, the samples used in the analysis cannot be put again in the fabrication process. Furthermore, radioactive wastes are generated during the inspection procedure. The gamma-ray spectrometer requires an elaborate reference sample to reduce measurement errors induced from the different geometric shape of test sample from that of reference sample. X-ray computed tomography (CT) is an alternative to measure the weight of kernels in a compact nondestructively. In this study, X-ray CT is applied to measure the weight of kernels in a cylindrical compact containing simulated TRISO-coated particles with ZrO 2 kernels. The volume of kernels as well as the number of kernels in the simulated compact is measured from the 3-D density information. The weight of kernels was calculated from the volume of kernels or the number of kernels. Also, the weight of kernels was measured by extracting the kernels from a compact to review the result of the X-ray CT application
3-D waveform tomography sensitivity kernels for anisotropic media

KAUST Repository

Djebbi, Ramzi

2014-01-01

The complications in anisotropic multi-parameter inversion lie in the trade-off between the different anisotropy parameters. We compute the tomographic waveform sensitivity kernels for a VTI acoustic medium perturbation as a tool to investigate this ambiguity between the different parameters. We use dynamic ray tracing to efficiently handle the expensive computational cost for 3-D anisotropic models. Ray tracing provides also the ray direction information necessary for conditioning the sensitivity kernels to handle anisotropy. The NMO velocity and η parameter kernels showed a maximum sensitivity for diving waves which results in a relevant choice of those parameters in wave equation tomography. The δ parameter kernel showed zero sensitivity; therefore it can serve as a secondary parameter to fit the amplitude in the acoustic anisotropic inversion. Considering the limited penetration depth of diving waves, migration velocity analysis based kernels are introduced to fix the depth ambiguity with reflections and compute sensitivity maps in the deeper parts of the model.
A Fourier-series-based kernel-independent fast multipole method

International Nuclear Information System (INIS)

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

2011-01-01

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

Resummed memory kernels in generalized system-bath master equations

International Nuclear Information System (INIS)

Mavros, Michael G.; Van Voorhis, Troy

2014-01-01

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Energy Technology Data Exchange (ETDEWEB)

Black, R. [Canadian Occidental Petroleum Ltd., Calgary, AB (Canada)

1998-05-01

The effects of globalization on Canadian crude oil prices was discussed. Since deregulation in October 1985, Canadian crude oil has competed directly against international crude oil through the use of the NYMEX contract price for light sweet crude oil as the base for establishing the price for Canadian crudes. Prior to that date, Alberta crude was marketed by the Alberta Petroleum Marketing Commission using the old block matrix which was loosely tied to the world market price. In addition to world crude oil prices other factors that affect the price of Canadian crude oil include technology impacts and global integration. Also, when the Sarnia to Montreal pipeline (Line 9) is reversed to bring offshore crude oil into the Ontario refining community, Canadian producers can expect some adverse effects on the price they are paid for their products leading up to the reversal as refiners start to swing over to their alternate suppliers. The offshore supply is expected to be about 140,000 barrels/day of light sweet crude oil, but all grades of Canadian crude oil will be affected.
A new discrete dipole kernel for quantitative susceptibility mapping.

Science.gov (United States)

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

2018-09-01

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

Directory of Open Access Journals (Sweden)

Zhengbin Liu

2016-08-01

Full Text Available Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis. In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.
SU-E-T-154: Calculation of Tissue Dose Point Kernels Using GATE Monte Carlo Simulation Toolkit to Compare with Water Dose Point Kernel

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-15

Purpose: the objective of this study was to assess utilizing water dose point kernel (DPK)instead of tissue dose point kernels in convolution algorithms.to the best of our knowledge, in providing 3D distribution of absorbed dose from a 3D distribution of the activity, the human body is considered equivalent to water. as a Result tissue variations are not considered in patient specific dosimetry. Methods: In this study Gate v7.0 was used to calculate tissue dose point kernel. the beta emitter radionuclides which have taken into consideration in this simulation include Y-90, Lu-177 and P-32 which are commonly used in nuclear medicine. the comparison has been performed for dose point kernels of adipose, bone, breast, heart, intestine, kidney, liver, lung and spleen versus water dose point kernel. Results: In order to validate the simulation the Result of 90Y DPK in water were compared with published results of Papadimitroulas et al (Med. Phys., 2012). The results represented that the mean differences between water DPK and other soft tissues DPKs range between 0.6 % and 1.96% for 90Y, except for lung and bone, where the observed discrepancies are 6.3% and 12.19% respectively. The range of DPK difference for 32P is between 1.74% for breast and 18.85% for bone. For 177Lu, the highest difference belongs to bone which is equal to 16.91%. For other soft tissues the least discrepancy is observed in kidney with 1.68%. Conclusion: In all tissues except for lung and bone, the results of GATE for dose point kernel were comparable to water dose point kernel which demonstrates the appropriateness of applying water dose point kernel instead of soft tissues in the field of nuclear medicine.
SU-E-T-154: Calculation of Tissue Dose Point Kernels Using GATE Monte Carlo Simulation Toolkit to Compare with Water Dose Point Kernel

International Nuclear Information System (INIS)

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

2015-01-01

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

DEFF Research Database (Denmark)

Petersen, Annette

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

Czech Academy of Sciences Publication Activity Database

Vidnerová, Petra; Neruda, Roman

-, accepted 28.11. 2017 (2018) ISSN 2278-0149 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : single-layer neural networks * kernel methods * kernel function * optimisation Subject RIV: IN - Informatics, Computer Science http://www.ijmerr.com/
Broken rice kernels and the kinetics of rice hydration and texture during cooking.

Science.gov (United States)

Saleh, Mohammed; Meullenet, Jean-Francois

2013-05-01

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

Directory of Open Access Journals (Sweden)

Yan Song

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

Directory of Open Access Journals (Sweden)

Rafael Monteiro Araújo Teixeira

2010-11-01

Full Text Available Objetivou-se avaliar o efeito de níveis crescentes de concentrado e de proteína bruta em dietas sendo avaliadoo consumo de matéria seca e de nutrientes, coeficientes de digestibilidades, produção e composição do leite e eficiência de utilização de alimentos. Vinte vacas em lactação foram distribuídas em delineamento em blocos casualizados, com cinco repetições por dieta, definidas conforme a produção de leite. As dietas experimentais foram constituídas de silagem de sorgo como volumoso e concentrado nos níveis de 11,7; 23,3; 35,2; e 46,8%, com quatro níveis de proteína bruta (PB (11,0; 12,0; 14,0; e 16,0%, com base da MS da dieta. Aumentos nos níveis de concentrado e de proteína bruta levaram a maior aumento no consumo de matéria seca total. O coeficiente de digestibilidade da proteína bruta foi influenciado pelos maiores níveis de concentrado e proteína bruta da dieta. A produção de leite foi maior nas vacas alimentadas com as dietas com maior nível de concentrado e PB, mas não diferiu entre as vacas que receberam as dietas intermediárias. Para vacas Gir linhagem leiteira mantidas nas condições desta pesquisa, níveis de 23,3% de concentrado e 12,0% de proteína bruta na dieta proporcionam melhor resposta produtiva.The objective of this work was to evaluate the effect of increasing levels of concentrate and crude protein in the diets, in which intakes of dry matter and nutrients, coefficients of digestibility, milk production and composition and efficiency of food use were evaluated. Twenty cows in lactation were distributed in a random block design, with five replicates per diet, defined according to milk production. The experimental diets were constituted of sorghum silage as roughage and concentrate at the following levels: 11.7; 23.3; 35.2 and 46.8% with four levels of crude protein (CP (11.0; 12.0; 14.0 and 16.0% on diet dry matter basis. Increases in the levels of concentrate and crude protein caused a
Multivariate realised kernels

DEFF Research Database (Denmark)

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

We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...
Process for producing metal oxide kernels and kernels so obtained

International Nuclear Information System (INIS)

Lelievre, Bernard; Feugier, Andre.

1974-01-01

The process desbribed is for producing fissile or fertile metal oxide kernels used in the fabrication of fuels for high temperature nuclear reactors. This process consists in adding to an aqueous solution of at least one metallic salt, particularly actinide nitrates, at least one chemical compound capable of releasing ammonia, in dispersing drop by drop the solution thus obtained into a hot organic phase to gel the drops and transform them into solid particles. These particles are then washed, dried and treated to turn them into oxide kernels. The organic phase used for the gel reaction is formed of a mixture composed of two organic liquids, one acting as solvent and the other being a product capable of extracting the anions from the metallic salt of the drop at the time of gelling. Preferably an amine is used as product capable of extracting the anions. Additionally, an alcohol that causes a part dehydration of the drops can be employed as solvent, thus helping to increase the resistance of the particles [fr
Ideal Gas Resonance Scattering Kernel Routine for the NJOY Code

International Nuclear Information System (INIS)

Rothenstein, W.

1999-01-01

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

DEFF Research Database (Denmark)

Feragen, Aase; Lauze, François; Hauberg, Søren

2015-01-01

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

CERN Multimedia

CERN. Geneva

2018-01-01

SystemTap is a dynamic method of monitoring and tracing the operation of a running Linux kernel. In this talk I will present a few practical use cases where SystemTap allowed me to turn otherwise complex userland monitoring tasks in simple kernel probes.
Utilization of soya protein as an alternative protein source in ...

African Journals Online (AJOL)

STORAGESEVER

2009-01-05

Jan 5, 2009 ... For carcass trait, ash, crude fat, and energy varied significantly with soya protein ... high-protein content, relatively well-balanced amino acid profile ..... and organoleptic quality of flesh of brook char (Salvelinus fontinalis).
Comparative Analysis of Kernel Methods for Statistical Shape Learning

National Research Council Canada - National Science Library

Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

2006-01-01

.... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...
Semi-supervised learning for ordinal Kernel Discriminant Analysis.

Science.gov (United States)

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

2016-12-01

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

Gene ontology based transfer learning for protein subcellular localization

Directory of Open Access Journals (Sweden)

Zhou Shuigeng

2011-02-01

Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for
Ideal gas scattering kernel for energy dependent cross-sections

International Nuclear Information System (INIS)

Rothenstein, W.; Dagan, R.

1998-01-01

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

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

2012-01-01

Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....
On flame kernel formation and propagation in premixed gases

Energy Technology Data Exchange (ETDEWEB)

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

2010-12-15

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

Science.gov (United States)

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

2012-01-01

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

International Nuclear Information System (INIS)

Lelievre Bernard; Feugier, Andre.

1973-01-01

A method is described for manufacturing fissile or fertile metal oxide kernels, consisting in adding at least a chemical compound capable of releasing ammonia to an aqueous solution of actinide nitrates dispersing the thus obtained solution dropwise in a hot organic phase so as to gelify the drops and transform them into solid particles, washing drying and treating said particles so as to transform them into oxide kernels. Such a method is characterized in that the organic phase used in the gel-forming reactions comprises a mixture of two organic liquids, one of which acts as a solvent, whereas the other is a product capable of extracting the metal-salt anions from the drops while the gel forming reaction is taking place. This can be applied to the so-called high temperature nuclear reactors [fr
New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

Science.gov (United States)

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

2017-06-21

We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.
Quasi-Dual-Packed-Kerneled Au49 (2,4-DMBT)27 Nanoclusters and the Influence of Kernel Packing on the Electrochemical Gap.

Science.gov (United States)

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

2017-10-02

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

African Journals Online (AJOL)

Average daily gains (119-136g/day), dry matter intake (855.897g/day), feed efficiency (6.59-7.19) dry matter digestibility (70.56-77.23%) were not significantly affected by the treatments. However, crude protein digestibility (69.39-76.32%) was significantly (P< 0.01) affected by the treatment, with treatment 4 giving the ...
ANALISIS KEHILANGAN MINYAK PADA CRUDE PALM OIL (CPO DENGAN MENGGUNAKAN METODE STATISTICAL PROCESS CONTROL

Directory of Open Access Journals (Sweden)

Vera Devani

2014-06-01

Full Text Available PKS “XYZ” merupakan perusahaan yang bergerak di bidang pengolahan kelapa sawit. Produk yang dihasilkan adalah Crude Palm Oil (CPO dan Palm Kernel Oil (PKO. Tujuan penelitian ini adalah menganalisa kehilangan minyak (oil losses dan faktor-faktor penyebab dengan menggunakan metoda Statistical Process Control. Statistical Process Control adalah sekumpulan strategi, teknik, dan tindakan yang diambil oleh sebuah organisasi untuk memastikan bahwa strategi tersebut menghasilkan produk yang berkualitas atau menyediakan pelayanan yang berkualitas. Sampel terjadinya oil losses pada CPO yang diteliti adalah tandan kosong (tankos, biji (nut, ampas (fibre, dan sludge akhir. Berdasarkan Peta Kendali I-MR dapat disimpulkan bahwa kondisi keempat jenis oil losses CPO berada dalam batas kendali dan konsisten. Sedangkan nilai Cpk dari total oil losses berada di luar batas kendali rata-rata proses, hal ini berarti CPO yang diproduksi telah memenuhi kebutuhan pelanggan, dengan total oil losses kurang dari batas maksimum yang ditetapkan oleh perusahaan yaitu 1,65%.
Optimal kernel shape and bandwidth for atomistic support of continuum stress

International Nuclear Information System (INIS)

Ulz, Manfred H; Moran, Sean J

2013-01-01

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

Directory of Open Access Journals (Sweden)

Hjalmar Rosengren

2006-12-01

Full Text Available We study multivariable Christoffel-Darboux kernels, which may be viewed as reproducing kernels for antisymmetric orthogonal polynomials, and also as correlation functions for products of characteristic polynomials of random Hermitian matrices. Using their interpretation as reproducing kernels, we obtain simple proofs of Pfaffian and determinant formulas, as well as Schur polynomial expansions, for such kernels. In subsequent work, these results are applied in combinatorics (enumeration of marked shifted tableaux and number theory (representation of integers as sums of squares.
Effect of crude protein levels and organic selenium supplementation in the diets fed during the breeding season on reproductive parameters of red-winged tinamous (Rhynchotus rufescens)

OpenAIRE

Felipe, L. [UNESP; Santos, E. C.; Tavian, A. F.; Góes, P. A. A.; Moraes, V. M. B. [UNESP; Tonhati, Humberto [UNESP; Boleli, I. C. [UNESP; Malheiros, E. B. [UNESP; Barnabé, V. H.; Queiroz, S. A. [UNESP

2010-01-01

There is little information on the nutrition of red-winged tinamous (Rhynchotus rufescens) reared in captivity, and their nutritional requirements still need to be determined. This study aimed at determining dietary crude protein requirements and testing four organic selenium supplementation levels in the diet of red-winged tinamous during the breeding season. Birds were housed in a conventional broiler house divided in 16 boxes with one male and three females each. Iso-energy (2800kcal ME/kg...
A multi-resolution approach to heat kernels on discrete surfaces

KAUST Repository

Vaxman, Amir

2010-07-26

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

Science.gov (United States)

Wittek, Peter; Tan, Chew Lim

2011-10-01

Wavelet kernels have been introduced for both support vector regression and classification. Most of these wavelet kernels do not use the inner product of the embedding space, but use wavelets in a similar fashion to radial basis function kernels. Wavelet analysis is typically carried out on data with a temporal or spatial relation between consecutive data points. We argue that it is possible to order the features of a general data set so that consecutive features are statistically related to each other, thus enabling us to interpret the vector representation of an object as a series of equally or randomly spaced observations of a hypothetical continuous signal. By approximating the signal with compactly supported basis functions and employing the inner product of the embedding L2 space, we gain a new family of wavelet kernels. Empirical results show a clear advantage in favor of these kernels.
Optimization of crude protein in diets for Nile tilapia reared in net pens: performance, hematology, and water quality

Directory of Open Access Journals (Sweden)

Débora Del Puppo

Full Text Available ABSTRACT: Two experiments were conducted to evaluate the effects of reducing dietary crude protein (CP, based on the ideal protein concept for Nile tilapia reared in net pens. The experimental (isocaloric, isocalcium, and isophosphoric diets were formulated to contain 270, 300, 330, and 360g kg-1 CP. In experiment 1, 4320 Nile tilapia (13.5±0.82g were used to evaluate the performance and hematological parameters. The experimental design was completely randomized and the fish were distributed in 24 net pens (1.0m3, with four diets, six replicates, and 180 fishes per experimental unit. In experiment 2, 40 Nile tilapia (22.5±0.56g were used to evaluate the ammonia excretion. Fish were distributed in 40 aquaria (3.0L, with one fish per aquarium (n=10. No protein reduction effect was observed in feed intake and the hematocrit and hemoglobin values. Regarding the statistic models used in the present study, difference was observed between CP values. The optimal level estimated by the quadratic equation first interception with the linear response plateau (LRP as a response to CP changes in the diet was determined for weight gain (324.3g kg-1 and feed conversion (317.8g kg-1. After reduction in the CP levels, a linear reduction was observed in the ammonia excretion in water. Based on the ideal protein concept for Nile tilapia reared in net pens, reducing the CP levels in the diets is possible, without change in the performance and hematological parameters, and with a reduction in the levels of ammonia excretion in water, since amino acids are supplemented.
Apparent or Standardized Ileal Digestibility of Amino Acids of Diets Containing Different Protein Feedstuffs Fed at Two Crude Protein Levels for Growing Pigs

Directory of Open Access Journals (Sweden)

A. O. Adebiyi

2015-09-01

Full Text Available The current study determined the apparent or standardized ileal digestibility of amino acids (AID or SID of AA in growing pigs fed diets containing three protein feedstuffs with different fiber characteristics at two dietary crude protein (CP levels. Twenty boars (Yorkshire×Landrace with average initial body weight of 35 (±2.6 kg were fitted with a simple T-cannula at the distal ileum. These pigs were offered six diets containing soybean meal (SBM, canola meal (CM or corn distillers dried grains with solubles (corn-DDGS that were either adequate (19% or marginal (15% in CP using a triplicated 6×2 Youden Square Design. Except for Met, Trp, Cys, and Pro, AID of AA was greater (p<0.05 in the SBM diet compared with the CM diet. Apparent ileal digestibility for Gly and Asp was greater (p<0.05 in the SBM diet compared with the corn-DDGS diet. The AID of Ile, Leu, Phe, Val, Ala, Tyr, and Asp was greater (p<0.05 in the corn-DDGS diet compared with the CM diet. Standardized ileal digestibility of AA was greater (p<0.05 in the SBM diet compared with the CM diet for all AA except Trp and Pro. The SID of Ile, Leu, Val, Ala, Tyr, and Asp was greater (p<0.05 in the corn-DDGS diet compared with the CM diet. It was concluded that protein feedstuff affects ileal AA digestibility and is closely related to dietary fiber characteristics, and a 4-percentage unit reduction in dietary CP had no effect on ileal AA digestibility in growing pigs.
Genome-wide Association Analysis of Kernel Weight in Hard Winter Wheat

Science.gov (United States)

Wheat kernel weight is an important and heritable component of wheat grain yield and a key predictor of flour extraction. Genome-wide association analysis was conducted to identify genomic regions associated with kernel weight and kernel weight environmental response in 8 trials of 299 hard winter ...
Fumonisins in corn: correlation with Fusarium sp. count, damaged kernels, protein and lipid content

Directory of Open Access Journals (Sweden)

Elisabete Yurie Sataque Ono

2006-01-01

Full Text Available Natural fungal and fumonisin contamination were evaluated in 109 freshly harvested corn samples from Paraná State and correlated to damaged kernels (%. In addition, healthy and damaged kernels of 24 corn samples were selected in order to compare the mycoflora profile and fumonisin levels. The correlation among protein/lipid content and fumonisin levels was also analyzed in the 15 most frequently cultivated corn hybrids. Total fungal colony count in 109 freshly harvested corn samples ranged from 1.9x10(4 to 3.5x10(6 CFU/g, Fusarium sp. count from 1.0x10³ to 2.2x10(6 CFU/g, and fumonisin levels from 0.13 to 20.38 µg/g. Total fungal colony/Fusarium sp. count and fumonisin levels showed positive correlation (p A contaminação natural por fungos e fumonisinas foi avaliada em 109 amostras de milho recém-colhido do Estado do Paraná e correlacionada com grãos ardidos (%. Além disso, grãos sadios e ardidos de 24 amostras de milho foram selecionados a fim de comparar o perfil da microbiota fúngica e níveis de fumonisinas. A correlação entre os teores de proteínas/lipídios e os níveis de fumonisinas também foi analisada nos 15 híbridos de milho mais freqüentemente cultivados no Estado do Paraná. A contagem total de fungos em 109 amostras de milho recém-colhido variou de 1,9x10(4 a 3,5x10(6 UFC/g, Fusarium sp. de 1,0x10³ a 2,2x10(6 UFC/g e, níveis de fumonisinas de 0,13 a 20,38 µg/g. A contagem total de fungos/Fusarium spp. e níveis de fumonisinas apresentaram correlação positiva (p<0,05. Adicionalmente, houve uma correlação positiva entre grãos ardidos (% e a contagem total de fungos/ Fusarium spp. (p < 0,05. Os níveis de fumonisinas nos grãos sadios variaram de 0,57 a 20,38 µg/g, enquanto que nos grãos ardidos variaram de 68,96 a 336,38 µg/g. Não foi observada correlação significativa entre os níveis de fumonisinas e os teores de proteínas/lipídios. Esses resultados ratificam a importância do monitoramento
A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

DEFF Research Database (Denmark)

Li, Gang; Guan, Wei; Sierszecki, Krzysztof

2012-01-01

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

Generalized synthetic kernel approximation for elastic moderation of fast neutrons

International Nuclear Information System (INIS)

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

1975-01-01

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

International Nuclear Information System (INIS)

Devries, O.

2005-01-01

This paper provided an outline of crude oil production and supply in Canada. Details of oil sands projects in Athabasca, Cold Lake and Peace River were presented. A chart of oil sands growth by major project was provided. A list of new emerging oil sands crude types was also presented along with details of a synthetic bitumen blending synergy. Maps of Western Canadian crude oil markets were provided, along with details of refinery and market demand by crude type. Various pipeline alternatives to new markets were examined, with reference to Enbridge Pipeline's supply and capacity. Details of the Hardisty to U.S Gulf Coast Pipeline and the Edmonton to Prince Rupert Pipeline and its terminal and dock facilities were presented. It was concluded that pipeline capacity and seasonal factors will influence market demand, while linefill, crude types and the quality of the product will influence operational strategies. tabs., figs
Validation of Born Traveltime Kernels

Science.gov (United States)

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

2001-12-01

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

African Journals Online (AJOL)

A feeding trial which lasted for twelve weeks was conducted to study the performance of finisher pigs fed five different levels of palm kernel cake replacement for maize (0%, 40%, 40%, 60%, 60%) in a maize-palm kernel cake based ration with or without enzyme supplementation. It was a completely randomized design ...
EVALUATING THE SHORT RUN EFFECTS OF U.S. CRUDE OIL INVENTORY LEVELS ON WTI CRUDE OIL PRICE FROM 1993 - 2013

Directory of Open Access Journals (Sweden)

Tobi Olasojiand

2016-07-01

Full Text Available The focus of this research was to investigate the short-term influence of U.S. crude oil inventories on WTI crude oil prices from 1993 to 2013. This study is important for policy makers who wish to reduce the persistent and growing price volatility of crude oil and its related products as well as businesses such as airline companies who wish to make annual budgetary sales decisions. Using OLS multiple regression, cointegration, VECM and Ex-post forecast techniques; we provide evidence of an inelastic relationship in which a 1% increase in U.S. crude oil inventories is associated with 0.46% decrease in WTI crude oil prices; however this was only valid for 22% of WTI crude oil price variation. We also find that past data on U.S. crude oil inventories could be used to predict future WTI crude oil prices movement. Contrary to literature, the results of the VECM analysis indicate there is no short-run relationship between both variables over the trajectory.
How much crude oil can zooplankton ingest? Estimating the quantity of dispersed crude oil defecated by planktonic copepods

International Nuclear Information System (INIS)

Almeda, Rodrigo; Connelly, Tara L.; Buskey, Edward J.

2016-01-01

We investigated and quantified defecation rates of crude oil by 3 species of marine planktonic copepods (Temora turbinata, Acartia tonsa, and Parvocalanus crassirostris) and a natural copepod assemblage after exposure to mechanically or chemically dispersed crude oil. Between 88 and 100% of the analyzed fecal pellets from three species of copepods and a natural copepod assemblage exposed for 48 h to physically or chemically dispersed light crude oil contained crude oil droplets. Crude oil droplets inside fecal pellets were smaller (median diameter: 2.4–3.5 μm) than droplets in the physically and chemically dispersed oil emulsions (median diameter: 6.6 and 8.0 μm, respectively). This suggests that copepods can reject large crude oil droplets or that crude oil droplets are broken into smaller oil droplets before or during ingestion. Depending on the species and experimental treatments, crude oil defecation rates ranged from 5.3 to 245 ng-oil copepod"−"1 d"−"1, which represent a mean weight-specific defecation rate of 0.026 μg-oil μg-C_c_o_p_e_p_o_d"1 d"−"1. Considering a dispersed crude oil concentration commonly found in the water column after oil spills (1 μl L"−"1) and copepod abundances in high productive coastal areas, copepods may defecate ∼1.3–2.6 mg-oil m"−"3 d"−"1, which would represent ∼0.15%–0.30% of the total dispersed oil per day. Our results indicate that ingestion and subsequent defecation of crude oil by planktonic copepods has a small influence on the overall mass of oil spills in the short term, but may be quantitatively important in the flux of oil from surface water to sediments and in the transfer of low-solubility, toxic petroleum hydrocarbons into food webs after crude oil spills in the sea. - Highlights: • Copepods exposed to dispersed crude oil produced fecal pellets contained numerous small oil droplets (2.4 to 3.5 µm). • Copepods could reject large oil droplets or oil droplets are broken into
Efficient Online Subspace Learning With an Indefinite Kernel for Visual Tracking and Recognition

NARCIS (Netherlands)

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

2012-01-01

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

Science.gov (United States)

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

2017-10-01

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

African Journals Online (AJOL)

Influence of differently processed mango seed kernel meal on performance response of west African ... and TD( consisted spear grass and parboiled mango seed kernel meal with concentrate diet in a ratio of 35:30:35). ... HOW TO USE AJOL.
Fiber-bound nitrogen in gorilla diets: implications for estimating dietary protein intake of primates.

Science.gov (United States)

Rothman, Jessica M; Chapman, Colin A; Pell, Alice N

2008-07-01

Protein is essential for living organisms, but digestibility of crude protein is poorly understood and difficult to predict. Nitrogen is used to estimate protein content because nitrogen is a component of the amino acids that comprise protein, but a substantial portion of the nitrogen in plants may be bound to fiber in an indigestible form. To estimate the amount of crude protein that is unavailable in the diets of mountain gorillas (Gorilla beringei) in Bwindi Impenetrable National Park, Uganda, foods routinely eaten were analyzed to determine the amount of nitrogen bound to the acid-detergent fiber residue. The amount of fiber-bound nitrogen varied among plant parts: herbaceous leaves 14.5+/-8.9% (reported as a percentage of crude protein on a dry matter (DM) basis), tree leaves (16.1+/-6.7% DM), pith/herbaceous peel (26.2+/-8.9% DM), fruit (34.7+/-17.8% DM), bark (43.8+/-15.6% DM), and decaying wood (85.2+/-14.6% DM). When crude protein and available protein intake of adult gorillas was estimated over a year, 15.1% of the dietary crude protein was indigestible. These results indicate that the proportion of fiber-bound protein in primate diets should be considered when estimating protein intake, food selection, and food/habitat quality.
A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

Charara, Ali

2017-06-06

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

KAUST Repository

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

2017-01-01

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

International Nuclear Information System (INIS)

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

2008-01-01

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-06-24

We present an auto-tuning approach to optimize application performance on emerging multicore architectures. The methodology extends the idea of search-based performance optimizations, popular in linear algebra and FFT libraries, to application-specific computational kernels. Our work applies this strategy to Sparse Matrix Vector Multiplication (SpMV), the explicit heat equation PDE on a regular grid (Stencil), and a lattice Boltzmann application (LBMHD). We explore one of the broadest sets of multicore architectures in the HPC literature, including the Intel Xeon Clovertown, AMD Opteron Barcelona, Sun Victoria Falls, and the Sony-Toshiba-IBM (STI) Cell. Rather than hand-tuning each kernel for each system, we develop a code generator for each kernel that allows us to identify a highly optimized version for each platform, while amortizing the human programming effort. Results show that our auto-tuned kernel applications often achieve a better than 4X improvement compared with the original code. Additionally, we analyze a Roofline performance model for each platform to reveal hardware bottlenecks and software challenges for future multicore systems and applications.
7 CFR 30.20 - Crude.

Science.gov (United States)

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Crude. 30.20 Section 30.20 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing... unfinished as a result of extreme immaturity. Crude tobacco ordinarily has a characteristic green color. ...
Kernel Bayesian ART and ARTMAP.

Science.gov (United States)

Masuyama, Naoki; Loo, Chu Kiong; Dawood, Farhan

2018-02-01

Adaptive Resonance Theory (ART) is one of the successful approaches to resolving "the plasticity-stability dilemma" in neural networks, and its supervised learning model called ARTMAP is a powerful tool for classification. Among several improvements, such as Fuzzy or Gaussian based models, the state of art model is Bayesian based one, while solving the drawbacks of others. However, it is known that the Bayesian approach for the high dimensional and a large number of data requires high computational cost, and the covariance matrix in likelihood becomes unstable. This paper introduces Kernel Bayesian ART (KBA) and ARTMAP (KBAM) by integrating Kernel Bayes' Rule (KBR) and Correntropy Induced Metric (CIM) to Bayesian ART (BA) and ARTMAP (BAM), respectively, while maintaining the properties of BA and BAM. The kernel frameworks in KBA and KBAM are able to avoid the curse of dimensionality. In addition, the covariance-free Bayesian computation by KBR provides the efficient and stable computational capability to KBA and KBAM. Furthermore, Correntropy-based similarity measurement allows improving the noise reduction ability even in the high dimensional space. The simulation experiments show that KBA performs an outstanding self-organizing capability than BA, and KBAM provides the superior classification ability than BAM, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
Low-Resolution Tactile Image Recognition for Automated Robotic Assembly Using Kernel PCA-Based Feature Fusion and Multiple Kernel Learning-Based Support Vector Machine

Directory of Open Access Journals (Sweden)

Yi-Hung Liu

2014-01-01

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

African Journals Online (AJOL)

Design and construction of palm kernel cracking and separation machines. ... Username, Password, Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. Design and construction of palm kernel cracking and separation machines. JO Nordiana, K ...
Variable kernel density estimation in high-dimensional feature spaces

CSIR Research Space (South Africa)

Van der Walt, Christiaan M

2017-02-01

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

Energy Technology Data Exchange (ETDEWEB)

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

2004-03-15

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

Graphical analyses of connected-kernel scattering equations

International Nuclear Information System (INIS)

Picklesimer, A.

1982-10-01

Simple graphical techniques are employed to obtain a new (simultaneous) derivation of a large class of connected-kernel scattering equations. This class includes the Rosenberg, Bencze-Redish-Sloan, and connected-kernel multiple scattering equations as well as a host of generalizations of these and other equations. The graphical method also leads to a new, simplified form for some members of the class and elucidates the general structural features of the entire class
How much crude oil can zooplankton ingest? Estimating the quantity of dispersed crude oil defecated by planktonic copepods

DEFF Research Database (Denmark)

Almeda, Rodrigo; Connelly, Tara L.; Buskey, Edward J.

2016-01-01

% of the analyzed fecal pellets from three species of copepods and a natural copepod assemblage exposed for 48 h to physically or chemically dispersed light crude oil contained crude oil droplets. Crude oil droplets inside fecal pellets were smaller (median diameter: 2.4-3.5 mu m) than droplets in the physically...
An Ensemble Approach to Building Mercer Kernels with Prior Information

Science.gov (United States)

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

2005-01-01

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

Science.gov (United States)

Sumarjaya, I. W.

2017-10-01

Copulas have been widely used to model nonlinear dependence structure. Main applications of copulas include areas such as finance, insurance, hydrology, rainfall to name but a few. The flexibility of copula allows researchers to model dependence structure beyond Gaussian distribution. Basically, a copula is a function that couples multivariate distribution functions to their one-dimensional marginal distribution functions. In general, there are three methods to estimate copula. These are parametric, nonparametric, and semiparametric method. In this article we survey kernel-type estimators for copula such as mirror reflection kernel, beta kernel, transformation method and local likelihood transformation method. Then, we apply these kernel methods to three stock indexes in Asia. The results of our analysis suggest that, albeit variation in information criterion values, the local likelihood transformation method performs better than the other kernel methods.
Strategic study on energy-protein requirements for local sheep: 5. Ewes during lactation phase

Directory of Open Access Journals (Sweden)

I-W Mathius

2004-03-01

Full Text Available Thirty-six Javanese thin-tail ewes in the end of late pregnancy phase were set out to study the energy and crude protein requirements during the first eight-week of lactation phase. The ewes were penned individually in doors and randomly assigned to a 3 x 3 factorial arrangement, consisting of three levels of energy (low, medium and high and three levels of crude protein (low, medium and high diets with four ewes per treatment. The diets were pelleted and offered four times daily in approximately equal amount. Feed intake, nutrient digestibility, body weight and milk production were recorded. Results showed that, total lamb birth weights was not affected, but protein content on the ration treatments significantly altered (P0.05, while crude protein content on the ration highly significantly affected (P<0.01. Based on data recorded, the energy and protein requirements for ewes during lactation phase are highly significantly depended on ewes’ live weight, milk production and the ratio of energy metabolism and crude protein of the ration. It was concluded that in order to fulfil the crude protein and energy needs of the ewes during lactation phase, the ration given should contain crude protein and energy as much as 16% (based on dry matter and 13.4 MJ/kg dry matter respectively.
Irradiation performance of coated fuel particles with fission product retaining kernel additives

International Nuclear Information System (INIS)

Foerthmann, R.

1979-10-01

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

Science.gov (United States)

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

2017-01-01

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

Science.gov (United States)

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

2017-01-01

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

International Nuclear Information System (INIS)

Ahnesjoe, A.

1991-01-01

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

Czech Academy of Sciences Publication Activity Database

Engliš, Miroslav

2015-01-01

Roč. 429, č. 1 (2015), s. 233-272 ISSN 0022-247X R&D Projects: GA AV ČR IAA100190802 Institutional support: RVO:67985840 Keywords : harmonic Bergman kernel * Poisson kernel * pseudodifferential boundary operators Subject RIV: BA - General Mathematics Impact factor: 1.014, year: 2015 http://www.sciencedirect.com/science/article/pii/S0022247X15003170
Optimal Bandwidth Selection in Observed-Score Kernel Equating

Science.gov (United States)

Häggström, Jenny; Wiberg, Marie

2014-01-01

The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…
7 CFR 29.1010 - Crude.

Science.gov (United States)

2010-01-01

... of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing... Type 92) § 29.1010 Crude. A subdegree of maturity. Crude leaves are usually hard and slick as a result of extreme immaturity. A similar condition may result from fire-kill, sunburn, or sunscald. Any leaf...
7 CFR 29.3512 - Crude.

Science.gov (United States)

2010-01-01

... of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing... Type 95) § 29.3512 Crude. A subdegree of maturity. Crude leaves are usually hard and slick as a result of extreme immaturity. A similar condition may result from firekill, sunburn, or sunscald. Any leaf...
7 CFR 29.2261 - Crude.

Science.gov (United States)

2010-01-01

... of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing.... A subdegree of maturity. Crude leaves are usually hard and slick as a result of extreme immaturity. A similar condition may result from fire-kill, sunburn, or sunscald. Any leaf which is crude to the...
Kernel structures for Clouds

Science.gov (United States)

Spafford, Eugene H.; Mckendry, Martin S.

1986-01-01

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

Indian Academy of Sciences (India)

Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 4. Commutators of Integral Operators with Variable Kernels on Hardy Spaces. Pu Zhang Kai Zhao. Volume 115 Issue 4 November 2005 pp 399-410 ... Keywords. Singular and fractional integrals; variable kernel; commutator; Hardy space.
Oven-drying reduces ruminal starch degradation in maize kernels

NARCIS (Netherlands)

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

2014-01-01

The degradation of starch largely determines the feeding value of maize (Zea mays L.) for dairy cows. Normally, maize kernels are dried and ground before chemical analysis and determining degradation characteristics, whereas cows eat and digest fresh material. Drying the moist maize kernels
Investigating the characteristic strength of flocs formed from crude and purified Hibiscus extracts in water treatment.

Science.gov (United States)

Jones, Alfred Ndahi; Bridgeman, John

2016-10-15

The growth, breakage and re-growth of flocs formed using crude and purified seed extracts of Okra (OK), Sabdariffa (SB) and Kenaf (KE) as coagulants and coagulant aids was assessed. The results showed floc size increased from 300 μm when aluminium sulphate (AS) was used as a coagulant to between 696 μm and 722 μm with the addition of 50 mg/l of OK, KE and SB crude samples as coagulant aids. Similarly, an increase in floc size was observed when each of the purified proteins was used as coagulant aid at doses of between 0.123 and 0.74 mg/l. The largest floc sizes of 741 μm, 460 μm and 571 μm were obtained with a 0.123 mg/l dose of purified Okra protein (POP), purified Sabdariffa (PSP) and purified Kenaf (PKP) respectively. Further coagulant aid addition from 0.123 to 0.74 mg/l resulted in a decrease in floc size and strength in POP and PSP. However, an increase in floc strength and reduced d50 size was observed in PKP at a dose of 0.74 mg/l. Flocs produced when using purified and crude extract samples as coagulant aids exhibited high recovery factors and strength. However, flocs exhibited greater recovery post-breakage when the extracts were used as a primary coagulant. It was observed that the combination of purified proteins and AS improved floc size, strength and recovery factors. Therefore, the applications of Hibiscus seeds in either crude or purified form increases floc growth, strength, recoverability and can also reduce the cost associated with the import of AS in developing countries. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.
Perspectives for practical application of the combined fuel kernels in VVER-type reactors

International Nuclear Information System (INIS)

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

2011-01-01

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

Energy Technology Data Exchange (ETDEWEB)

Lee, Dal Sok [Korea Energy Economics Institute, Euiwang (Korea)

1999-03-01

Since the second oil crisis, the government has operated the import diversification support program to reduce the risk of crude oil import from Middle-East region and to raise the ability of dealing with the risk. This study tried to seek policy trends in future through reviewing the market environment related to the crude oil import diversification policy and the goal, instrument and effect of the policy. The supply and demand of crude oil and the price are influenced by market system in the world oil market and there are various types of crude oil trading available to both sellers and buyers. There is a probability that the suspension of supply in a certain area could be led to the price issue rather than the physical use of crude oil. In addition, the advantage of price with long-term contract of crude oil was abolished since the price of crude oil imported by term contract has been linked to spot prices. As a result, it is shown that the potential benefit from crude oil import diversification policy is reduced although political and social insecurity still exists in Middle-East region. Therefore, it is desirable to maintain the existing support program until the amount of stored oil reaches the optimum level and to help private enterprises determine the import considering economical efficiency and risk. (author). 36 refs., 5 figs., 23 tabs.

Systemic toxicity of dermally applied crude oils in rats

Energy Technology Data Exchange (ETDEWEB)

Feuston, M.H.; Mackerer, C.R.; Schreiner, C.A.; Hamilton, C.E. [Stonybrook Labs., Inc., Princeton, NJ (United States)

1997-12-31

Two crude oils, differing in viscosity (V) and nitrogen (N) and sulfur (S) content, were evaluated for systemic toxicity, In the Crude I (low V, low N, low S) study, the material was applied to the clipped backs of rats at dose levels of 0, 30, 125, and 500 mg/kg. In the Crude II (high V, high N, moderate S) study, the oil was applied similarly at the same dose levels. The crude oils were applied for 13 wk, 5 d/wk. Exposure sites were not occluded. Mean body weight gain (wk 1-14) was significantly reduced in male rats exposed to Crude II; body weight gain of all other animals was not adversely affected by treatment. An increase in absolute (A) and relative (R) liver weights and a decrease in A and R thymus weights were observed in male and female rats exposed to Crude II at 500 mg/kg; only liver weights (A and R) were adversely affected in male and female rats exposed to Crude I. In general, there was no consistent pattern of toxicity for serum chemistry endpoints; however, more parameters were adversely affected in Crude II-exposed female rats than in the other exposed groups. A consistent pattern of toxicity for hematology endpoints was observed among male rats exposed to Crude I and male and female rats exposed to Crude II. Parameters affected included: Crudes I and II, red blood cell count, hemoglobin, and hematocrit, Crude II, platelet count. Microscopic evaluation of tissues revealed the following treatment-related findings: Crude I, treated skin, thymus, and thyroid; Crude II, bone marrow, treated skin, thymus, and thyroid. The LOEL (lowest observable effect level) for skin irritation and systemic toxicity (based on marginal effects on the thyroid) for both crude oils was 30 mg/kg; effects were more numerous and more pronounced in animals exposed to Crude II. Systemic effects are probably related to concentrations of polycyclic aromatic compounds (PAC) found in crude oil.
Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach

International Nuclear Information System (INIS)

Fan, Ying; Wei, Yi-Ming; Zhang, Yue-Jun; Tsai, Hsien-Tang

2008-01-01

Estimation has been carried out using GARCH-type models, based on the Generalized Error Distribution (GED), for both the extreme downside and upside Value-at-Risks (VaR) of returns in the WTI and Brent crude oil spot markets. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between the two oil markets. Results of an empirical study indicate that the GED-GARCH-based VaR approach appears more effective than the well-recognized HSAF (i.e. historical simulation with ARMA forecasts). Moreover, this approach is also more realistic and comprehensive than the standard normal distribution-based VaR model that is commonly used. Results reveal that there is significant two-way risk spillover effect between WTI and Brent markets. Supplementary study indicates that at the 99% confidence level, when negative market news arises that brings about a slump in oil price return, historical information on risk in the WTI market helps to forecast the Brent market. Conversely, it is not the case when positive news occurs and returns rise. Historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets. (author)
Occurrence of 'super soft' wheat kernel texture in hexaploid and tetraploid wheats

Science.gov (United States)

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

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie

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

DEFF Research Database (Denmark)

Exterkate, Peter; Groenen, Patrick J.F.; Heij, Christiaan

This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the predi...
Onset of grain filling is associated with a change in properties of linker histone variants in maize kernels

DEFF Research Database (Denmark)

Kalamajka, R.; Finnie, Christine; Grasser, K.D.

2010-01-01

) initiation of storage synthesis. Six linker histone gene products were identified by MALDI-TOF mass spectrometry. A marked shift of around 4 pH units was observed for the linker histone spot pattern after 2D-gel electrophoresis when comparing the proteins of 11 and 16 dap kernels. The shift from acidic...
Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.)

NARCIS (Netherlands)

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

2010-01-01

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-11-15

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

International Nuclear Information System (INIS)

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

2007-01-01

We construct classes of coherent states on domains arising from dynamical systems. An orthonormal family of vectors associated to the generating transformation of a Julia set is found as a family of square integrable vectors, and, thereby, reproducing kernels and reproducing kernel Hilbert spaces are associated to Julia sets. We also present analogous results on domains arising from iterated function systems
Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

Science.gov (United States)

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

2016-07-07

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

Science.gov (United States)

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

2017-11-01

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

Science.gov (United States)

Zeng, Hong; Cheung, Yiu-ming

2011-08-01

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

Science.gov (United States)

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

2013-01-01

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

Science.gov (United States)

Wei, Wei; Jia, Qingxuan

2016-01-01

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

Indian Academy of Sciences (India)

In the proposed classifier, we design a new multi-kernel function based on the fuzzy triangular membership function. Finally, a newly developed multi-kernel function is incorporated into the spherical support vector machine to enhance the performance significantly. The experimental results are evaluated and performance is ...
Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

Science.gov (United States)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.
DOE/DOT Crude Oil Characterization Research Study, Task 2 Test Report on Evaluating Crude Oil Sampling and Analysis Methods

Energy Technology Data Exchange (ETDEWEB)

Lord, David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Allen, Ray [Allen Energy Services, Inc., Longview, TX (United States); Rudeen, David [GRAM, Inc., Albuquerque, NM (United States)

2017-11-01

The Crude Oil Characterization Research Study is designed to evaluate whether crude oils currently transported in North America, including those produced from "tight" formations, exhibit physical or chemical properties that are distinct from conventional crudes, and how these properties associate with combustion hazards with may be realized during transportation and handling.
Effect of crude seaweed extracts on seed germination, seedling growth and some metabolic processes of Vicia faba L.

Science.gov (United States)

el-Sheekh, M M; el-Saied A el-D

2000-01-01

Crude extracts from three green seaweeds (Cladophora dalmatica, Enteromorpha intestinalis, Ulva lactuca) and the three red algae (Corallina mediterranea, Jania rubens, Pterocladia pinnate) were prepared. Their effects on germination, growth of seedlings, chlorophyll content and other metabolic activities of Vicia faba were investigated. The crude extract of C. dalmatica showed maximal activity, and it increased seed germination, length of main root and shoot systems and the number of lateral roots. All the crude extracts of seaweed increased protein content in both root and shoot systems, total soluble sugars and chlorophyll content in leaves. The cytokinin content of the green algae was higher than that in red algae. Growth of seedlings of V. faba was stimulated but to different degrees.
Modelling microwave heating of discrete samples of oil palm kernels

International Nuclear Information System (INIS)

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

2016-01-01

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

KAUST Repository

Djebbi, Ramzi

2013-08-19

Anisotropy is an inherent character of the Earth subsurface. It should be considered for modeling and inversion. The acoustic VTI wave equation approximates the wave behavior in anisotropic media, and especially it\\'s kinematic characteristics. To analyze which parts of the model would affect the traveltime for anisotropic traveltime inversion methods, especially for wave equation tomography (WET), we drive the sensitivity kernels for anisotropic media using the VTI acoustic wave equation. A Born scattering approximation is first derived using the Fourier domain acoustic wave equation as a function of perturbations in three anisotropy parameters. Using the instantaneous traveltime, which unwraps the phase, we compute the kernels. These kernels resemble those for isotropic media, with the η kernel directionally dependent. They also have a maximum sensitivity along the geometrical ray, which is more realistic compared to the cross-correlation based kernels. Focusing on diving waves, which is used more often, especially recently in waveform inversion, we show sensitivity kernels in anisotropic media for this case.

Finite frequency traveltime sensitivity kernels for acoustic anisotropic media: Angle dependent bananas

KAUST Repository

Djebbi, Ramzi; Alkhalifah, Tariq Ali

2013-01-01

Anisotropy is an inherent character of the Earth subsurface. It should be considered for modeling and inversion. The acoustic VTI wave equation approximates the wave behavior in anisotropic media, and especially it's kinematic characteristics. To analyze which parts of the model would affect the traveltime for anisotropic traveltime inversion methods, especially for wave equation tomography (WET), we drive the sensitivity kernels for anisotropic media using the VTI acoustic wave equation. A Born scattering approximation is first derived using the Fourier domain acoustic wave equation as a function of perturbations in three anisotropy parameters. Using the instantaneous traveltime, which unwraps the phase, we compute the kernels. These kernels resemble those for isotropic media, with the η kernel directionally dependent. They also have a maximum sensitivity along the geometrical ray, which is more realistic compared to the cross-correlation based kernels. Focusing on diving waves, which is used more often, especially recently in waveform inversion, we show sensitivity kernels in anisotropic media for this case.
Prediction of crude protein digestibility of animal by-product meals for dogs by the protein solubility in pepsin method.

Science.gov (United States)

Kawauchi, Iris M; Sakomura, Nilva K; Pontieri, Cristiana F F; Rebelato, Aline; Putarov, Thaila C; Malheiros, Euclides B; Gomes, Márcia de O S; Castrillo, Carlos; Carciofi, Aulus C

2014-01-01

Animal by-product meals have large variability in crude protein (CP) content and digestibility. In vivo digestibility procedures are precise but laborious, and in vitro methods could be an alternative to evaluate and classify these ingredients. The present study reports prediction equations to estimate the CP digestibility of meat and bone meal (MBM) and poultry by-product meal (PM) using the protein solubility in pepsin method (PSP). Total tract CP digestibility of eight MBM and eight PM samples was determined in dogs by the substitution method. A basal diet was formulated for dog maintenance, and sixteen diets were produced by mixing 70 % of the basal diet and 30 % of each tested meal. Six dogs per diet were used to determine ingredient digestibility. In addition, PSP of the MBM and PM samples was determined using three pepsin concentrations: 0·02, 0·002 and 0·0002 %. The CP content of MBM and PM ranged from 39 to 46 % and 57 to 69 %, respectively, and their mean CP digestibility by dogs was 76 (2·4) and 85 (2·6) %, respectively. The pepsin concentration with higher Pearson correlation coefficients with the in vivo results were 0·0002 % for MBM (r 0·380; P = 0·008) and 0·02 % for PM (r 0·482; P = 0·005). The relationship between the in vivo and in vitro results was better explained by the following equations: CP digestibility of MBM = 61·7 + 0·2644 × PSP at 0·0002 % (P = 0·008; R (2) 0·126); and CP digestibility of PM = 54·1 + 0·3833 × PSP at 0·02 % (P = 0·005; R (2) 0·216). Although significant, the coefficients of determination were low, indicating that the models were weak and need to be used with caution.
The influence of maize kernel moisture on the sterilizing effect of gamma rays

International Nuclear Information System (INIS)

Khanymova, T.; Poloni, E.

1980-01-01

The influence of 4 levels of maize kernel moisture (16, 20, 25 and 30%) on gamma-ray sterilizing effect was studied and the after-effect of radiation on the microorganisms at short term storage was followed up. Maize kernels of the hybrid Knezha-36 produced in 1975 were used. Gamma-ray treatment of the kernels was effected by GUBEh-4000 irradiator at doses of 0.2 and 0.3 Mrad and after that they were stored for a month at 12 deg and 25 deg C and controlled moisture conditions. Surface and subepidermal infection of the kernels was determined immediately post irradiation and at the end of the experiment. Non-irradiated kernels were used as controls. Results indicated that the initial kernel moisture has a considerable influence on the sterilizing effect of gamma-rays at the rates used in the experiment and affects to a considerable extent the post-irradiation recovery of organisms. The speed of recovery was highest in the treatment with 30% moisture and lowest in the treatment with 16% kernel moisture. Irradiation of the kernels causes pronounced changes on the surface and subepidermal infection. This was due to the unequal radio resistance to the microbial components and to the modifying effect of the moisture holding capacity. The useful effect of maize kernel irradiation was more prolonged at 12 deg C than at 25 deg C
Capturing option anomalies with a variance-dependent pricing kernel

NARCIS (Netherlands)

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

2013-01-01

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

Directory of Open Access Journals (Sweden)

Neur Eddine Askour

2002-07-01

Full Text Available We present a formula that relates the Kohn Laplacian on Heisenberg groups and the magnetic Laplacian. Then we obtain the resolvent kernel for the Kohn Laplacian and find its spectral density. We conclude by obtaining the Green kernel for fractional powers of the Kohn Laplacian.
Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population.

Science.gov (United States)

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.
Crude oil pipeline expansion summary

International Nuclear Information System (INIS)

2005-02-01

The Canadian Association of Petroleum Producers has been working with producers to address issues associated with the development of new pipeline capacity from western Canada. This document presents an assessment of the need for additional oil pipeline capacity given the changing mix of crude oil types and forecasted supply growth. It is of particular interest to crude oil producers and contributes to current available information for market participants. While detailed, the underlying analysis does not account for all the factors that may come into play when individual market participants make choices about which expansions they may support. The key focus is on the importance of timely expansion. It was emphasized that if pipeline expansions lags the crude supply growth, then the consequences would be both significant and unacceptable. Obstacles to timely expansion are also discussed. The report reviews the production and supply forecasts, the existing crude oil pipeline infrastructure, opportunities for new market development, requirements for new pipeline capacity and tolling options for pipeline development. tabs., figs., 1 appendix
A Heterogeneous Multi-core Architecture with a Hardware Kernel for Control Systems

DEFF Research Database (Denmark)

Li, Gang; Guan, Wei; Sierszecki, Krzysztof

2012-01-01

Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints....... This paper presents a multi-core architecture incorporating a hardware kernel on FPGAs, intended for high performance applications in control engineering domain. First, the hardware kernel is investigated on the basis of a component-based real-time kernel HARTEX (Hard Real-Time Executive for Control Systems...
Equação de predição da exigência de proteína bruta para aves reprodutoras pesadas na fase de produção Prediction equation of crude protein requirements for broiler breeders hens

Directory of Open Access Journals (Sweden)

Carlos Bôa-Viagem Rabello

2002-06-01

Full Text Available O objetivo do presente trabalho foi determinar as exigências de proteína para aves reprodutoras pesadas através do método fatorial. A exigência de proteína bruta para mantença (PBm foi determinada por intermédio da técnica do balanço de nitrogênio por meio de ensaio de metabolismo com aves submetidas a quatro dietas com níveis decrescentes de proteína, proporcionando balanço positivo, próximo a zero e negativo. Para determinar a exigência de proteína bruta para o ganho de peso (PBg dois experimentos foram conduzidos, sendo que em um, determinou-se as exigências líquidas de nitrogênio e no outro, a eficiência de utilização do nitrogênio para o ganho, por meio de abates semanais de aves no período de 26 a 33 semanas de idade. A exigência de proteína bruta para produção de ovos (PBo foi determinada através de análises semanais de proteína bruta dos ovos coletados, no período de 31 a 37 semanas de idade, considerando a eficiência de deposição da proteína no ovo. A exigência e eficiência de utilização da proteína para mantença foram 2.282 mg PB/kg0,75/dia e 60,79%; respectivamente. As exigências de PBg e PBo determinadas foram: 356 mg PB/g e 262 mg PB/g, respectivamente, e as eficiências de utilização do nitrogênio, 40 e 46,80%, respectivamente. A equação de predição elaborada para aves reprodutoras pesadas na fase de produção foi: PB=2,282.P0,75+0,356.G+0,262.MO, onde PB é a exigência de proteína bruta (g/ave/dia, P o peso corporal (kg, G o ganho de peso (g/dia e MO a massa de ovos (g/dia.The objective of this study was to determine the protein requirement for broiler breeder hens using factorial method. The requirement of crude protein for maintenance (CPm was determined using nitrogen balance technique in metabolism assay. The birds were fed with four protein levels in order to get a positive, a close to zero and a negative nitrogen balance. To determine the crude protein weight gain
Graphical analyses of connected-kernel scattering equations

International Nuclear Information System (INIS)

Picklesimer, A.

1983-01-01

Simple graphical techniques are employed to obtain a new (simultaneous) derivation of a large class of connected-kernel scattering equations. This class includes the Rosenberg, Bencze-Redish-Sloan, and connected-kernel multiple scattering equations as well as a host of generalizations of these and other equations. The basic result is the application of graphical methods to the derivation of interaction-set equations. This yields a new, simplified form for some members of the class and elucidates the general structural features of the entire class
The global kernel k-means algorithm for clustering in feature space.

Science.gov (United States)

Tzortzis, Grigorios F; Likas, Aristidis C

2009-07-01

Kernel k-means is an extension of the standard k -means clustering algorithm that identifies nonlinearly separable clusters. In order to overcome the cluster initialization problem associated with this method, we propose the global kernel k-means algorithm, a deterministic and incremental approach to kernel-based clustering. Our method adds one cluster at each stage, through a global search procedure consisting of several executions of kernel k-means from suitable initializations. This algorithm does not depend on cluster initialization, identifies nonlinearly separable clusters, and, due to its incremental nature and search procedure, locates near-optimal solutions avoiding poor local minima. Furthermore, two modifications are developed to reduce the computational cost that do not significantly affect the solution quality. The proposed methods are extended to handle weighted data points, which enables their application to graph partitioning. We experiment with several data sets and the proposed approach compares favorably to kernel k -means with random restarts.
Application of Markov Model in Crude Oil Price Forecasting

Directory of Open Access Journals (Sweden)

Nuhu Isah

2017-08-01

Full Text Available Crude oil is an important energy commodity to mankind. Several causes have made crude oil prices to be volatile. The fluctuation of crude oil prices has affected many related sectors and stock market indices. Hence, forecasting the crude oil prices is essential to avoid the future prices of the non-renewable natural resources to rise. In this study, daily crude oil prices data was obtained from WTI dated 2 January to 29 May 2015. We used Markov Model (MM approach in forecasting the crude oil prices. In this study, the analyses were done using EViews and Maple software where the potential of this software in forecasting daily crude oil prices time series data was explored. Based on the study, we concluded that MM model is able to produce accurate forecast based on a description of history patterns in crude oil prices.
Effects of forest fertilization on nitrate and crude protein content in some important reindeer forage species

Directory of Open Access Journals (Sweden)

Gustaf Åhman

1984-05-01

Full Text Available When forests are fertilized with ammonia nitrate it is possible that grazing reindeer ingest ammonia nitrate by eating grains of fertilizer from the ground or by drinking contaminated water. They can also get nitrate through plants that have absorbed and disposed nitrate. This latter factor is studied in this report. In addition the effect of fertilization on crude protein content in forage plants is investigated. Fertilizing trials were done within two different areas. One was a dry scotch pine forest and the other a humid scotch pine forest. Both were situated 10 to 15 km north west of Lycksele (northern Sweden. Three different rations (75, 150 and 250 kg N/ha of ammonianitrate and one (150 kg N/ha of urea was used. Fertilization was done at two occations, in June and in July. To investigate the effect of fertilization on nitrate and crude protein content in reindeer forage plants, samples were taken of reindeer lichens (Cladina spp., heather {Calluna vulgaris, crowberry (Empetrum spp., cowberry (Vaccinium vitis ideae, blueberry (Vaccinium myrtillus and hair-grass (Deschampsia flexuosa at different times after fertilization. In this trial we could not find any higher degree of contamination of nitrate in lichens. The highest value was 0.013% nitrate-N in dry matter (table 1. Nitrate accumulation was low in shrubs and grass (table 2. The highest value (0.05% was found in heather. The concentrations were definitly below the level that could be considered as injurious to the reindeer. The effect of fertilization on crude protein content in reindeer forage plants was obvious. It was most evident in hair-grass. Four weeks after fertilization with 150 kg N/ha, crude protein content was more than doubled and reached 20% in dry matter (figure 1 and 2. In withered hair-grass in the autumn the effect was very small. One year after fertilization a small rise in crude protein was registered in both grass and shrubs (table 3. Some effect still remained
On methods to increase the security of the Linux kernel

International Nuclear Information System (INIS)

Matvejchikov, I.V.

2014-01-01

Methods to increase the security of the Linux kernel for the implementation of imposed protection tools have been examined. The methods of incorporation into various subsystems of the kernel on the x86 architecture have been described [ru
Relationship between processing score and kernel-fraction particle size in whole-plant corn silage.

Science.gov (United States)

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
Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

Science.gov (United States)

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

2017-06-21

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

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Samarjit Das

2014-04-01

Full Text Available Kernelized Fuzzy C-Means clustering technique is an attempt to improve the performance of the conventional Fuzzy C-Means clustering technique. Recently this technique where a kernel-induced distance function is used as a similarity measure instead of a Euclidean distance which is used in the conventional Fuzzy C-Means clustering technique, has earned popularity among research community. Like the conventional Fuzzy C-Means clustering technique this technique also suffers from inconsistency in its performance due to the fact that here also the initial centroids are obtained based on the randomly initialized membership values of the objects. Our present work proposes a new method where we have applied the Subtractive clustering technique of Chiu as a preprocessor to Kernelized Fuzzy CMeans clustering technique. With this new method we have tried not only to remove the inconsistency of Kernelized Fuzzy C-Means clustering technique but also to deal with the situations where the number of clusters is not predetermined. We have also provided a comparison of our method with the Subtractive clustering technique of Chiu and Kernelized Fuzzy C-Means clustering technique using two validity measures namely Partition Coefficient and Clustering Entropy.
A relationship between Gel'fand-Levitan and Marchenko kernels

International Nuclear Information System (INIS)

Kirst, T.; Von Geramb, H.V.; Amos, K.A.

1989-01-01

An integral equation which relates the output kernels of the Gel'fand-Levitan and Marchenko inverse scattering equations is specified. Structural details of this integral equation are studied when the S-matrix is a rational function, and the output kernels are separable in terms of Bessel, Hankel and Jost solutions. 4 refs
Expanding U.S. markets for Canadian crude oil

International Nuclear Information System (INIS)

Heath, M.; Angevine, G.; Chan, K.; Renne, G.; Stariha, J.; MacKay, E.

1993-01-01

The quantities and types of Canadian, U.S. and competing foreign crudes flowing into U.S. market regions and the potential to retain and/or expand Canadian crude oil sales in each of those markets, was studied. The various pipeline system expansion/construction proposals were reviewed. Findings of the study with respect to prospects for crude oil sales into each of the U.S. market regions were presented. Opportunities and constraints with regard to the potential for incremental crude oil sales into each of the U.S. market regions were detailed. The study concluded that there was a substantial market in the U.S. for incremental sales of Canadian crudes. Most of the refineries in the U.S. market regions were more flexible in terms of their crude diet than they were before the rationalization and restructuring of the industry began. The market for crude oil in the U.S. was shown to be one of the most competitive in the world and the most volatile. The study also revealed that there were risks associated with large additions to the capacity to ship crude oil by pipeline from Western Canada, given the uncertainties surrounding future supply. 4 refs., figs., tabs
Migration of ThO2 kernels under the influence of a temperature gradient

International Nuclear Information System (INIS)

Smith, C.L.

1976-11-01

BISO coated ThO 2 fertile fuel kernels will migrate up the thermal gradients imposed across coated particles during HTGR operation. Thorium dioxide kernel migration has been studied as a function of temperature (1300 to 1700 0 C) and ThO 2 kernel burnup (0.9 to 5.8 percent FIMA) in out-of-pile, postirradiation thermal gradient heating experiments. The studies were conducted to obtain descriptions of migration rates that will be used in core design studies to evaluate the impact of ThO 2 migration on fertile fuel performance in an operating HTGR and to define characteristics needed by any comprehensive model describing ThO 2 kernel migration. The kinetics data generated in these postirradiation studies are consistent with in-pile data collected by investigators at Oak Ridge National Laboratory, which supports use of the more precise postirradiation heating results in HTGR core design studies. Observations of intergranular carbon deposits on the cool side of migrating kernels support the assumption that the kinetics of kernel migration are controlled by solid state diffusion within irradiated ThO 2 kernels. The migration is characterized by a period of no migration (incubation period) followed by migration at the equilibrium rate for ThO 2 . The incubation period decreases with increasing temperature and kernel burnup. The improved understanding of the kinetics of ThO 2 kernel migration provided by this work will contribute to an optimization of HTGR core design and an increased confidence in fuel performance predictions

Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

DEFF Research Database (Denmark)

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

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

DEFF Research Database (Denmark)

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

2011-01-01

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

DEFF Research Database (Denmark)

Tjernsbekk, M. T.; Tauson, A. H.; Kraugerud, O. F.

2017-01-01

Protein quality was evaluated for mechanically separated chicken meat (MSC) and salmon protein hydrolysate (SPH), and for extruded dog foods where MSC or SPH partially replaced poultry meal (PM). Apparent total tract digestibility (ATTD) of crude protein (CP) and amino acids (AA) in the protein...
Utilizing protein-lean coproducts from corn containing recombinant pharmaceutical proteins for ethanol production.

Science.gov (United States)

Paraman, Ilankovan; Moeller, Lorena; Scott, M Paul; Wang, Kan; Glatz, Charles E; Johnson, Lawrence A

2010-10-13

Protein-lean fractions of corn (maize) containing recombinant (r) pharmaceutical proteins were evaluated as a potential feedstock to produce fuel ethanol. The levels of residual r-proteins in the coproduct, distillers dry grains with solubles (DDGS), were determined. Transgenic corn lines containing recombinant green fluorescence protein (r-GFP) and a recombinant subunit vaccine of Escherichia coli enterotoxin (r-LTB), primarily expressed in endosperm, and another two corn lines containing recombinant human collagen (r-CIα1) and r-GFP, primarily expressed in germ, were used as model systems. The kernels were either ground and used for fermentation or dry fractionated to recover germ-rich fractions prior to grinding for fermentation. The finished beers of whole ground kernels and r-protein-spent endosperm solids contained 127-139 and 138-155 g/L ethanol concentrations, respectively. The ethanol levels did not differ among transgenic and normal corn feedstocks, indicating the residual r-proteins did not negatively affect ethanol production. r-Protein extraction and germ removal also did not negatively affect fermentation of the remaining mass. Most r-proteins were inactivated during the mashing process used to prepare corn for fermentation. No functionally active r-GFP or r-LTB proteins were found after fermentation of the r-protein-spent solids; however, a small quantity of residual r-CIα1 was detected in DDGS, indicating that the safety of DDGS produced from transgenic grain for r-protein production needs to be evaluated for each event. Protease treatment during fermentation completely hydrolyzed the residual r-CIα1, and no residual r-proteins were detectable in DDGS.
Reduction of Aflatoxins in Apricot Kernels by Electronic and Manual Color Sorting

Directory of Open Access Journals (Sweden)

Rosanna Zivoli

2016-01-01

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

African Journals Online (AJOL)

feed industry are the relationships between isoleucine, leucine, lysine and arginine with crude protein content. Equations to predict the content of these amino acids from the amount of crude protein in maize are given. The remaining amino acids can be estimated without loss of accuracy from their mean value expressed as ...
Effects of de-oiled palm kernel cake based fertilizers on sole maize ...

African Journals Online (AJOL)

A study was conducted to determine the effect of de-oiled palm kernel cake based fertilizer formulations on the yield of sole maize and cassava crops. Two de-oiled palm kernel cake based fertilizer formulations A and B were compounded from different proportions of de-oiled palm kernel cake, urea, muriate of potash and ...
Gaussian processes with optimal kernel construction for neuro-degenerative clinical onset prediction

Science.gov (United States)

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.

Science.gov (United States)

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.

Science.gov (United States)

Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

2017-06-19

A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.
Effect of substituting soybean meal and canola cake with dried distillers grains with solubles at 2 dietary crude protein levels on feed intake, milk production, and milk quality in dairy cows

DEFF Research Database (Denmark)

Gaillard, Charlotte; Sørensen, Martin Tang; Vestergaard, Mogens

2017-01-01

Dried distillers grain with solubles (DDGS) is an alternative source of feed protein for dairy cows. Previous studies found that DDGS, based on grains other than corn, can substitute for soybean meal and canola cake as a dietary protein source without reducing milk production or quality....... As societal concerns exist, and in many areas strict regulation, regarding nitrogen excretion from dairy cows, the dairy industry has focused on reducing dietary protein level and nitrogen excretion. In the present study, we investigated the use of DDGS as a protein source, at a marginally low dietary crude...... protein (CP) levels, in a grass-clover and corn silage-based ration. The experiment involved 24 Holstein cows and 2 protein sources (DDGS or soybean-canola mixture) fed at 2 levels of CP (14 or 16%) in a 4 × 4 Latin square design. The aim of this study was to evaluate the effect of both protein source...
Fluidization calculation on nuclear fuel kernel coating

International Nuclear Information System (INIS)

Sukarsono; Wardaya; Indra-Suryawan

1996-01-01

The fluidization of nuclear fuel kernel coating was calculated. The bottom of the reactor was in the from of cone on top of the cone there was a cylinder, the diameter of the cylinder for fluidization was 2 cm and at the upper part of the cylinder was 3 cm. Fluidization took place in the cone and the first cylinder. The maximum and the minimum velocity of the gas of varied kernel diameter, the porosity and bed height of varied stream gas velocity were calculated. The calculation was done by basic program
Use of wheat and maize protein mutants in breeding for improved protein quantity and quality

International Nuclear Information System (INIS)

Denic, M.; Dumanovic, J.; Misevic, D.; Konstantinov, K.; Fidler, D.; Stojanovic, Z.

1984-01-01

Selected offspring progenies (50 mutant lines) originating from mutation experiments with hexaploid wheat (cv. Bezostaya 1) were analysed for induced heritable variation in protein content, lysine content, grain yield and protein and lysine yields. Ten of these mutant lines were crossed with 11 local varieties. The protein and lysine contents were measured in the progenies of these crossings. The data showed better correlations of grain yield with protein and lysine yields than the protein and lysine contents with their corresponding yields. F 1 seeds showed higher lysine and protein contents than local varieties. Data with maize showed that: (1) the total endosperm protein content of modified opaque-2 types increases with an increase in the degree of normalization; (2) the lysine content in dry matter and protein in normalized o 2 kernels usually decreases with the increasing degree of normalization; (3) the lysine content in protein of modified o 2 kernels, is, in general, satisfactory up to the normalization of about 50% of endosperm. A desirable modification of o 2 endosperm within line A632o 2 was selected and crossed with o 2 lines. Most of the tested hybrids had a good protein quality, but endosperm modification was not evident in all hybrids. The o 2 gene was incorporated into high protein backgrounds. Besides a high protein content and quality, some of the hybrids tested had a comparable or higher yield than the o 2 check. (author)
Notes on a storage manager for the Clouds kernel

Science.gov (United States)

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.

Science.gov (United States)

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.
Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel

International Nuclear Information System (INIS)

Zhang, Yao; Wang, Jianxue; Luo, Xu

2015-01-01

Highlights: • Quantitative information on the uncertainty of wind power generation. • Kernel density estimator provides non-Gaussian predictive distributions. • Logarithmic transformation reduces the skewness of wind power density. • Boundary kernel method eliminates the density leakage near the boundary. - Abstracts: Probabilistic wind power forecasting not only produces the expectation of wind power output, but also gives quantitative information on the associated uncertainty, which is essential for making better decisions about power system and market operations with the increasing penetration of wind power generation. This paper presents a novel kernel density estimator for probabilistic wind power forecasting, addressing two characteristics of wind power which have adverse impacts on the forecast accuracy, namely, the heavily skewed and double-bounded nature of wind power density. Logarithmic transformation is used to reduce the skewness of wind power density, which improves the effectiveness of the kernel density estimator in a transformed scale. Transformations partially relieve the boundary effect problem of the kernel density estimator caused by the double-bounded nature of wind power density. However, the case study shows that there are still some serious problems of density leakage after the transformation. In order to solve this problem in the transformed scale, a boundary kernel method is employed to eliminate the density leak at the bounds of wind power distribution. The improvement of the proposed method over the standard kernel density estimator is demonstrated by short-term probabilistic forecasting results based on the data from an actual wind farm. Then, a detailed comparison is carried out of the proposed method and some existing probabilistic forecasting methods
Kernel based pattern analysis methods using eigen-decompositions for reading Icelandic sagas

DEFF Research Database (Denmark)

Christiansen, Asger Nyman; Carstensen, Jens Michael

We want to test the applicability of kernel based eigen-decomposition methods, compared to the traditional eigen-decomposition methods. We have implemented and tested three kernel based methods methods, namely PCA, MAF and MNF, all using a Gaussian kernel. We tested the methods on a multispectral...... image of a page in the book 'hauksbok', which contains Icelandic sagas....
Influence of Kernel Age on Fumonisin B1 Production in Maize by Fusarium moniliforme

Science.gov (United States)

Warfield, Colleen Y.; Gilchrist, David G.

1999-01-01

Production of fumonisins by Fusarium moniliforme on naturally infected maize ears is an important food safety concern due to the toxic nature of this class of mycotoxins. Assessing the potential risk of fumonisin production in developing maize ears prior to harvest requires an understanding of the regulation of toxin biosynthesis during kernel maturation. We investigated the developmental-stage-dependent relationship between maize kernels and fumonisin B1 production by using kernels collected at the blister (R2), milk (R3), dough (R4), and dent (R5) stages following inoculation in culture at their respective field moisture contents with F. moniliforme. Highly significant differences (P ≤ 0.001) in fumonisin B1 production were found among kernels at the different developmental stages. The highest levels of fumonisin B1 were produced on the dent stage kernels, and the lowest levels were produced on the blister stage kernels. The differences in fumonisin B1 production among kernels at the different developmental stages remained significant (P ≤ 0.001) when the moisture contents of the kernels were adjusted to the same level prior to inoculation. We concluded that toxin production is affected by substrate composition as well as by moisture content. Our study also demonstrated that fumonisin B1 biosynthesis on maize kernels is influenced by factors which vary with the developmental age of the tissue. The risk of fumonisin contamination may begin early in maize ear development and increases as the kernels reach physiological maturity. PMID:10388675
System identification via sparse multiple kernel-based regularization using sequential convex optimization techniques

DEFF Research Database (Denmark)

Chen, Tianshi; Andersen, Martin Skovgaard; Ljung, Lennart

2014-01-01

Model estimation and structure detection with short data records are two issues that receive increasing interests in System Identification. In this paper, a multiple kernel-based regularization method is proposed to handle those issues. Multiple kernels are conic combinations of fixed kernels...
Differential metabolome analysis of field-grown maize kernels in response to drought stress

Science.gov (United States)

Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

kernel oil by lipolytic organisms

African Journals Online (AJOL)

USER

2010-08-02

Aug 2, 2010 ... Rancidity of extracted cashew oil was observed with cashew kernel stored at 70, 80 and 90% .... method of American Oil Chemist Society AOCS (1978) using glacial ..... changes occur and volatile products are formed that are.
Characterisation and final disposal behaviour of theoria-based fuel kernels in aqueous phases

International Nuclear Information System (INIS)

Titov, M.

2005-08-01

Two high-temperature reactors (AVR and THTR) operated in Germany have produced about 1 million spent fuel elements. The nuclear fuel in these reactors consists mainly of thorium-uranium mixed oxides, but also pure uranium dioxide and carbide fuels were tested. One of the possible solutions of utilising spent HTR fuel is the direct disposal in deep geological formations. Under such circumstances, the properties of fuel kernels, and especially their leaching behaviour in aqueous phases, have to be investigated for safety assessments of the final repository. In the present work, unirradiated ThO 2 , (Th 0.906 ,U 0.094 )O 2 , (Th 0.834 ,U 0.166 )O 2 and UO 2 fuel kernels were investigated. The composition, crystal structure and surface of the kernels were investigated by traditional methods. Furthermore, a new method was developed for testing the mechanical properties of ceramic kernels. The method was successfully used for the examination of mechanical properties of oxide kernels and for monitoring their evolution during contact with aqueous phases. The leaching behaviour of thoria-based oxide kernels and powders was investigated in repository-relevant salt solutions, as well as in artificial leachates. The influence of different experimental parameters on the kernel leaching stability was investigated. It was shown that thoria-based fuel kernels possess high chemical stability and are indifferent to presence of oxidative and radiolytic species in solution. The dissolution rate of thoria-based materials is typically several orders of magnitude lower than of conventional UO 2 fuel kernels. The life time of a single intact (Th,U)O 2 kernel under aggressive conditions of salt repository was estimated as about hundred thousand years. The importance of grain boundary quality on the leaching stability was demonstrated. Numerical Monte Carlo simulations were performed in order to explain the results of leaching experiments. (orig.)
Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

Directory of Open Access Journals (Sweden)

Yu Feng

2017-01-01

Full Text Available This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.
CLASS-PAIR-GUIDED MULTIPLE KERNEL LEARNING OF INTEGRATING HETEROGENEOUS FEATURES FOR CLASSIFICATION

Directory of Open Access Journals (Sweden)

Q. Wang

2017-10-01

Full Text Available In recent years, many studies on remote sensing image classification have shown that using multiple features from different data sources can effectively improve the classification accuracy. As a very powerful means of learning, multiple kernel learning (MKL can conveniently be embedded in a variety of characteristics. The conventional combined kernel learned by MKL can be regarded as the compromise of all basic kernels for all classes in classification. It is the best of the whole, but not optimal for each specific class. For this problem, this paper proposes a class-pair-guided MKL method to integrate the heterogeneous features (HFs from multispectral image (MSI and light detection and ranging (LiDAR data. In particular, the one-against-one strategy is adopted, which converts multiclass classification problem to a plurality of two-class classification problem. Then, we select the best kernel from pre-constructed basic kernels set for each class-pair by kernel alignment (KA in the process of classification. The advantage of the proposed method is that only the best kernel for the classification of any two classes can be retained, which leads to greatly enhanced discriminability. Experiments are conducted on two real data sets, and the experimental results show that the proposed method achieves the best performance in terms of classification accuracies in integrating the HFs for classification when compared with several state-of-the-art algorithms.
Omnibus risk assessment via accelerated failure time kernel machine modeling.

Science.gov (United States)

Sinnott, Jennifer A; Cai, Tianxi

2013-12-01

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

Science.gov (United States)

Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

2014-01-01

The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.
Valorization of crude glycerol from biodiesel production

Directory of Open Access Journals (Sweden)

Konstantinović Sandra S.

2016-01-01

Full Text Available The increased production of biodiesel as an alternative fuel involves the simultaneous growth in production of crude glycerol as its main by-product. Therefore, the feasibility and sustainability of biodiesel production requires the effective utilization of crude glycerol. This review describes various uses of crude glycerol as a potential green solvent for chemical reactions, a starting raw material for chemical and biochemical conversions into value-added chemicals, a substrate or co-substrate in microbial fermentations for synthesis of valuable chemicals and production of biogas and biohydrogen as well as a feedstuff for animal feed. A special attention is paid to various uses of crude glycerol in biodiesel production. [Projekat Ministarstva nauke Republike Srbije, br. III 45001
Enbridge system : crude types, transportation and handling systems

Energy Technology Data Exchange (ETDEWEB)

Anand, A. [Enbridge Corp., Edmonton, AB (Canada)

2009-07-01

The supply of crude oil from the Western Canada Sedimentary Basin is expected to increase by approximately 2.1 million barrels per day by 2015. The crudes that Enbridge handles range from 19 API to 40 API and 0.1 per cent sulphur to 4.7 per cent sulphur. The diverse supply of crude oil that the Enbridge system handles includes conventional heavy, synthetic heavy, heavy high tan, heavy low residual, medium, light sour, heavy sour, light sweet, light sweet synthetic, condensate and olefinic crudes. This presentation discussed Enbridge's plans for infrastructure expansion, crude types and quality assurance program. The company's infrastructure plans include the expansion of regional pipelines to bring more supplies to the mainline; expansion of the mainline capacity to existing markets; and providing pipeline access to new markets. Merchant storage terminals will be provided in some locations. The quality of various crude types will be maintained through judicious sequencing and tank bottoms crossings. tabs., figs.
The dynamics of crude oil price differentials

International Nuclear Information System (INIS)

Fattouh, Bassam

2010-01-01

Crude oil price differentials are modelled as a two-regime threshold autoregressive (TAR) process using the method proposed by Caner and Hansen [Caner, M., Hansen, B.E. Threshold autoregression with a unit root. Econometrica 2001; 69; 1555-1596.]. While standard unit root tests suggest that the prices of crude oil of different varieties move closely together such that their price differential is stationary, the TAR results indicate strong evidence of threshold effects in the adjustment process to the long-run equilibrium. These findings suggest that crude oil prices are linked and thus at the very general level, the oil market is 'one great pool' (Adelman, M.A. International oil agreements. The Energy Journal 1984; 5; 1-9.). However, differences in the dynamics of adjustment suggest that within this one pool, oil markets are not necessarily integrated in every time period and hence the dynamics of crude oil price differentials may not follow a stationary process at all times. Although the development of a liquid futures market around the crude oil benchmarks has helped make some distant markets more unified, arbitrage is not costless or risk-free and temporary breakdowns in the benchmarks can lead to decoupling of crude oil prices. (author)
Supervised Kernel Optimized Locality Preserving Projection with Its Application to Face Recognition and Palm Biometrics

Directory of Open Access Journals (Sweden)

Chuang Lin

2015-01-01

Full Text Available Kernel Locality Preserving Projection (KLPP algorithm can effectively preserve the neighborhood structure of the database using the kernel trick. We have known that supervised KLPP (SKLPP can preserve within-class geometric structures by using label information. However, the conventional SKLPP algorithm endures the kernel selection which has significant impact on the performances of SKLPP. In order to overcome this limitation, a method named supervised kernel optimized LPP (SKOLPP is proposed in this paper, which can maximize the class separability in kernel learning. The proposed method maps the data from the original space to a higher dimensional kernel space using a data-dependent kernel. The adaptive parameters of the data-dependent kernel are automatically calculated through optimizing an objective function. Consequently, the nonlinear features extracted by SKOLPP have larger discriminative ability compared with SKLPP and are more adaptive to the input data. Experimental results on ORL, Yale, AR, and Palmprint databases showed the effectiveness of the proposed method.
Introducing etch kernels for efficient pattern sampling and etch bias prediction

Science.gov (United States)

Weisbuch, François; Lutich, Andrey; Schatz, Jirka

2018-01-01

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

Directory of Open Access Journals (Sweden)

Wagner dos Reis

2013-03-01

Full Text Available The objective of this work was to evaluate the effect of processing two corn hybrids conserved, dry and humid grains, the dry matter (DM and crude protein (CP degradability in situ. The particle size was determined and difference was verified in MGD (Medium Geometric Diameter of processed ingredients. Three sheep were used with rumen canulated, in a completely randomized design, using a factorial outline 2 x 2 x 3, being two corn hybrid, two conservation methods and three processing forms (whole, coarsely and finely ground, with five times of incubation (3, 6, 12, 24 and 48 hours. The fraction A in SDC (silage of dent corn of DM was superior to GDC (grain of dent corn in all of the particles size. The ensiling process increased the DM solubility, reducing the fraction B in comparison to dry grain. The values regarding the fractions DP and DE the 5% per hour of the protein, were larger for SDC and GDC, it presents a decreasing when the incubation time advances. The fermentation rate was superior for SDC and GDC. The ensiling process has positive effect in the decreasing of DM and CP in comparison to GDC.
Multiple kernel learning using single stage function approximation for binary classification problems

Science.gov (United States)

Shiju, S.; Sumitra, S.

2017-12-01

In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.
Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

Science.gov (United States)

Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

2017-03-01

Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.
Propriedades funcionais das proteínas de amêndoas da faveleira (Cnidosculus phyllacanthus (Mart. Pax. et K. Hoffm. com e sem espinhos Functional properties of the seed kernel proteins of faveleira plant with or without thorns

Directory of Open Access Journals (Sweden)

Mônica Tejo Cavalcanti

2009-09-01

Full Text Available A faveleira possui amêndoas com potencial em óleos e proteínas alimentares e é encontrada em todos os estados do nordeste brasileiro, principalmente nas regiões do sertão e caatinga. Objetivando a sua aplicação em formulações alimentícias, as propriedades funcionais das proteínas de amêndoas da faveleira com espinhos (FCE, e sem espinhos (FSE foram estudadas. As amêndoas apresentaram, elevado conteúdo de lipídio (40,56 e 40,21% e proteína (33,00 e 35,77% e depois de desengordurada, apresentou 57,55 e 63,00% respectivamente. Na obtenção dos isolados proteicos, os índices em proteínas extraídas foram de 83,51% para a FCE e 80,57% para a FSE em pH 10,5. Os índices de proteínas recuperadas através da precipitação isoelétrica foram de 72,84 e 72,11% em pH 4,5. Os índices de proteínas solúveis e as propriedades de emulsificação mostraram-se dependentes do pH, com valores mínimos no ponto isoelétrico e mais elevados em pH ácido e básico ao pI. O isolado proteico da FSE apresentou melhor capacidade de absorção de água e de óleo em relação à FCE. Quando avaliadas através da atividade e da estabilidade de emulsão os isolados apresentaram performance apropriada tanto na região ácida quanto alcalina do pI.The seed kernel of faveleira plant is a potential source of edible oil and proteins. The plant grows in all the northeastern states of Brazil, mainlly in the sertão (backlands and caatinga regions. With an objective of its use in food formulations, the functional properties of the protein isolates of the kernel from the faveleira plants with (FCE or without thorns (FSE were studied. The kernels presented high lipid (40.56 and 40.21% and protein (33.0 and 35.77% content which increased to about 57.55 and 63.0% respectively after the lipid removal. In the preparation of protein isolates, the content of protein extraction was 83.5% for FCE and 80.57% for FSE at pH 10.5 while the protein recovery through
Improved Variable Window Kernel Estimates of Probability Densities

OpenAIRE

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

1995-01-01

Variable window width kernel density estimators, with the width varying proportionally to the square root of the density, have been thought to have superior asymptotic properties. The rate of convergence has been claimed to be as good as those typical for higher-order kernels, which makes the variable width estimators more attractive because no adjustment is needed to handle the negativity usually entailed by the latter. However, in a recent paper, Terrell and Scott show that these results ca...
Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

Science.gov (United States)

Pendergrass, Angeline G.; Conley, Andrew; Vitt, Francis M.

2018-02-01

Radiative kernels at the top of the atmosphere are useful for decomposing changes in atmospheric radiative fluxes due to feedbacks from atmosphere and surface temperature, water vapor, and surface albedo. Here we describe and validate radiative kernels calculated with the large-ensemble version of CAM5, CESM1.1.2, at the top of the atmosphere and the surface. Estimates of the radiative forcing from greenhouse gases and aerosols in RCP8.5 in the CESM large-ensemble simulations are also diagnosed. As an application, feedbacks are calculated for the CESM large ensemble. The kernels are freely available at https://doi.org/10.5065/D6F47MT6" target="_blank">https://doi.org/10.5065/D6F47MT6, and accompanying software can be downloaded from https://github.com/apendergrass/cam5-kernels" target="_blank">https://github.com/apendergrass/cam5-kernels.
Computing an element in the lexicographic kernel of a game

NARCIS (Netherlands)

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

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

NARCIS (Netherlands)

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

2002-01-01

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

Directory of Open Access Journals (Sweden)

Any Juliani

2016-06-01

Full Text Available Kegiatan penambangan minyak bumi tidak hanya dilakukan oleh perusahaan-perusahaan besar, tetapi juga oleh masyarakat secara tradisional. Potensi pencemaran lingkungan yang ditimbulkan oleh kegiatan penambangan rakyat ini menjadi lebih tinggi karena pengelolaannya yang tradisional. Salah satu jenis pencemaran yang ditimbulkannya misalnya adalah tanah atau perairan yang tercemar oleh minyak bumi (crude oil pada saat berlangsungnya kegiatan penambangan. Salah satu upaya untuk dapat mengatasinya adalah dengan bioremediasi. Bioremediasi merupakan teknologi pengolahan pencemar dengan memanfaatkan aktivitas mikroba, terutama dari golongan bakteri. Bioremediasi tersebut harus melibatkan bakteri yang memiliki kapasitas metabolic untuk melakukan biodegradasi terhadap crude oil tersebut. Crude oil sendiri pada dasarnya merupakan senyawa hidrokarbon yang merupakan sumber karbon yang kaya bagi mikroba. Namun demikian, biodegradasi crude oil relative lebih sulit dilakukan karena karakteristiknya yang merupakan senyawa dengan berat molekul dan ukuran yang besar. Oleh karena itu penambahan kosubstrat yang lebih sederhana dapat dilakukan untuk membantu biodegradasi terutama pada tahap awal proses. Penelitian ini dilakukan untuk mengetahui pengaruh penambahan kosubstrat dalam hal ini glukosa terhadap biodegradasi crude oil. Penelitian dilakukan dalam media cair dengan bioaugmentasi melalui penambahan inoculum bakteri yang diisolasi dari tanah yang dikondisikan terhadap crude oil dalam beberapa variasi reactor. Indikasi terjadinya biodegradasi diperiksa melalui pengukuran terhadap parameter Total Petroleum Hydrocarbon (TPH dan Total Plate Count (TPC. Hasil penelitian menunjukkan bahwa penambahan kosubstrat glukosa memberikan pengaruh positif terhadap penurunan TPH. Penurunan TPH tertinggi setelah 28 hari adalah sebesar 25,3 % yang diberikan oleh reactor dengan penambahan kosubstrat serta konsentrasi crude oil awal sebesar 8.1 %. Sementara itu reactor tanpa

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