A heat kernel proof of the index theorem for deformation quantization

Science.gov (United States)

Karabegov, Alexander

2017-11-01

We give a heat kernel proof of the algebraic index theorem for deformation quantization with separation of variables on a pseudo-Kähler manifold. We use normalizations of the canonical trace density of a star product and of the characteristic classes involved in the index formula for which this formula contains no extra constant factors.

A heat kernel proof of the index theorem for deformation quantization

OpenAIRE

Karabegov, Alexander

2017-01-01

We give a heat kernel proof of the algebraic index theorem for deformation quantization with separation of variables on a pseudo-Kahler manifold. We use normalizations of the canonical trace density of a star product and of the characteristic classes involved in the index formula for which this formula contains no extra constant factors.

Calculation of heat-kernel coefficients and usage of computer algebra

International Nuclear Information System (INIS)

Bel'kov, A.A.; Lanev, A.V.; Schaale, A.

1995-01-01

The calculation of heat-kernel coefficients with the classical De Witt algorithm has been discussed. We present the explicit form of the coefficients up to h 5 in the general case and up to h 7 min for the minimal parts. The results are compared with the expressions in other papers. A method to optimize the usage of memory for working with large expressions on universal computer algebra systems has been proposed. 20 refs

Observing integrals of heat kernels from a distance

DEFF Research Database (Denmark)

Heat kernels have integrals such as Brownian motion mean exit time, potential capacity, and torsional rigidity. We show how to obtain bounds on these values - essentially by observing their behaviour in terms of the distance function from a point and then comparing with corresponding values in ta...... and discussed as test cases. The talk is based on joint work with Vicente Palmer....... in tailor-made warped product spaces. The results will be illustrated by applications to the so-called 'type' problem: How to decide if a given manifold or surface is transient (hyperbolic) or recurrent (parabolic). Specific examples of minimal surfaces and constant pressure dry foams will be shown...

A new fractional derivative without singular kernel: Application to the modelling of the steady heat flow

Directory of Open Access Journals (Sweden)

Yang Xiao-Jun

2016-01-01

Full Text Available In this article we propose a new fractional derivative without singular kernel. We consider the potential application for modeling the steady heat-conduction problem. The analytical solution of the fractional-order heat flow is also obtained by means of the Laplace transform.

Some results from a Mellin transform expansion for the heat Kernel

International Nuclear Information System (INIS)

Malbouisson, A.P.C.; Simao, F.R.A.; Camargo Filho, A.F. de.

1988-01-01

The coefficients of a new Heat Kernel expansion, in the case of a differential operator containing a gauge field. The meromorphic structure of the generalized zeta-function obtained by that expansion is compared with the one obtained in a proceeding paper. The expansion is applied to anomalies, obtaining a general formula for arbitrary dimension D. The special cases D=2 and D=3 are investigated. (author) [pt

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...

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...

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

Science.gov (United States)

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

2018-05-07

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

The use of near infrared transmittance kernel sorting technology to salvage high quality grain from grain downgraded due to Fusarium damage

Directory of Open Access Journals (Sweden)

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.

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...

Heat kernel expansion in the background field formalism

CERN Document Server

Barvinsky, Andrei

2015-01-01

Heat kernel expansion and background field formalism represent the combination of two calculational methods within the functional approach to quantum field theory. This approach implies construction of generating functionals for matrix elements and expectation values of physical observables. These are functionals of arbitrary external sources or the mean field of a generic configuration -- the background field. Exact calculation of quantum effects on a generic background is impossible. However, a special integral (proper time) representation for the Green's function of the wave operator -- the propagator of the theory -- and its expansion in the ultraviolet and infrared limits of respectively short and late proper time parameter allow one to construct approximations which are valid on generic background fields. Current progress of quantum field theory, its renormalization properties, model building in unification of fundamental physical interactions and QFT applications in high energy physics, gravitation and...

Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt Seed Viability with Multivariate Data Analysis

Directory of Open Access Journals (Sweden)

Guangjun Qiu

2018-03-01

Full Text Available The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR spectroscopy with a wavelength range of 1000–2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

Single-Kernel FT-NIR Spectroscopy for Detecting Supersweet Corn (Zea mays L. Saccharata Sturt) Seed Viability with Multivariate Data Analysis.

Science.gov (United States)

Qiu, Guangjun; Lü, Enli; Lu, Huazhong; Xu, Sai; Zeng, Fanguo; Shui, Qin

2018-03-28

The viability and vigor of crop seeds are crucial indicators for evaluating seed quality, and high-quality seeds can increase agricultural yield. The conventional methods for assessing seed viability are time consuming, destructive, and labor intensive. Therefore, a rapid and nondestructive technique for testing seed viability has great potential benefits for agriculture. In this study, single-kernel Fourier transform near-infrared (FT-NIR) spectroscopy with a wavelength range of 1000-2500 nm was used to distinguish viable and nonviable supersweet corn seeds. Various preprocessing algorithms coupled with partial least squares discriminant analysis (PLS-DA) were implemented to test the performance of classification models. The FT-NIR spectroscopy technique successfully differentiated viable seeds from seeds that were nonviable due to overheating or artificial aging. Correct classification rates for both heat-damaged kernels and artificially aged kernels reached 98.0%. The comprehensive model could also attain an accuracy of 98.7% when combining heat-damaged samples and artificially aged samples into one category. Overall, the FT-NIR technique with multivariate data analysis methods showed great potential capacity in rapidly and nondestructively detecting seed viability in supersweet corn.

Palm kernel cake extract exerts hepatoprotective activity in heat-induced oxidative stress in chicken hepatocytes.

Science.gov (United States)

Oskoueian, Ehsan; Abdullah, Norhani; Idrus, Zulkifli; Ebrahimi, Mahdi; Goh, Yong Meng; Shakeri, Majid; Oskoueian, Armin

2014-10-02

Palm kernel cake (PKC), the most abundant by-product of oil palm industry is believed to contain bioactive compounds with hepatoprotective potential. These compounds may serve as hepatoprotective agents which could help the poultry industry to alleviate adverse effects of heat stress on liver function in chickens. This study was performed to evaluate the hepatoprotective potential of PKC extract in heat-induced oxidative stress in chicken hepatocytes. The nature of the active metabolites and elucidation of the possible mechanism involved were also investigated. The PKC extract possessed free radical scavenging activity with values significantly (p < 0.05) lower than silymarin as the reference antioxidant. Heat-induced oxidative stress in chicken hepatocyte impaired the total protein, lipid peroxidation and antioxidant enzymes activity significantly (p < 0.05). Treatment of heat-induced hepatocytes with PKC extract (125 μg/ml) and silymarin as positive control increased these values significantly (p < 0.05). The real time PCR and western blot analyses revealed the significant (p < 0.05) up-regulation of oxidative stress biomarkers including TNF-like, IFN-γ and IL-1β genes; NF-κB, COX-2, iNOS and Hsp70 proteins expression upon heat stress in chicken hepatocytes. The PKC extract and silymarin were able to alleviate the expression of all of these biomarkers in heat-induced chicken hepatocytes. The gas chromatography-mass spectrometry analysis of PKC extract showed the presence of fatty acids, phenolic compounds, sugar derivatives and other organic compounds such as furfural which could be responsible for the observed hepatoprotective activity. Palm kernel cake extract could be a potential agent to protect hepatocytes function under heat induced oxidative stress.

The Effect of Moisture Content and Temperature on the Specific Heat Capacity of Nut and Kernel of Two Iranian Pistachio Varieties

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A.R Salari Kia

2014-04-01

Full Text Available Pistachio has a special ranking among Iranian agricultural products. Iran is known as the largest producer and exporter of pistachio in the world. Agricultural products are imposed under different thermal treatments during storage and processing. Designing all these processes requires thermal parameters of the products such as specific heat capacity. Regarding the importance of pistachio processing as an exportable product, in this study the specific heat capacity of nut and kernel of two varieties of Iranian pistachio (Kalle-Ghochi and Badami were investigated at four levels of moisture content (initial moisture content (5%, 15%, 25% and 40% w.b. and three levels of temperature (40, 50 and 60°C. In both varieties, the differences between the data were significant at the 1% of probability; however, the effect of moisture content was greater than that of temperature. The results indicated that the specific heat capacity of both nuts and kernels increase logarithmically with increase of moisture content and also increase linearly with increase of temperature. This parameter has altered for nut and kernel of Kalle-Ghochi and Badami varieties within the range of 1.039-2.936 kJ kg-1 K-1, 1.236-3.320 kJ kg-1 K-1, 0.887-2.773 kJ kg-1 K-1 and 0.811-2.914 kJ kg-1 K-1, respectively. Moreover, for any given level of temperature, the specific heat capacity of kernels was higher than that of nuts. Finally, regression models with high R2 values were developed to predict the specific heat capacity of pistachio varieties as a function of moisture content and temperature

Free energy on a cycle graph and trigonometric deformation of heat kernel traces on odd spheres

Science.gov (United States)

Kan, Nahomi; Shiraishi, Kiyoshi

2018-01-01

We consider a possible ‘deformation’ of the trace of the heat kernel on odd dimensional spheres, motivated by the calculation of the free energy of a scalar field on a discretized circle. By using an expansion in terms of the modified Bessel functions, we obtain the values of the free energies after a suitable regularization.

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

Science.gov (United States)

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Moisture Dependence of physical Properties and Specific Heat Capacity of Neem (Azadirachta Indica A. Juss Kernels

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A. Dauda

2017-02-01

Full Text Available This study investigated the effect of moisture content on the physical properties and specific heat capacity of Neem (Azadirachta Indica A. Juss nut kernels. The major, intermediate and minor axial dimensions of the kernels increased from 1.04 to 1.23cm, 0.42 to 0.6cm, and 0.32 to 0.45cm respectively, as the moisture content increased from 5.2 to 44.9 % (db. The arithmetic and geometric mean diameters determined at the same moisture level were significantly different from each other, with the arithmetic mean diameter being higher. In the above moisture range, one thousand kernel weight, true density, porosity, sphericity, roundness and surface area all increased linearly from 0.0987 to 0.1755kg, 632 to 733kgm-3, 6.42 to 32.14%, 41.3 to 47.5%, 22 to 36% and 13 to 24cm2 respectively, while bulk density decreased from 591.4 to 497.4kgm-3 with increase in moisture content. Angle of repose increased from 21.22 to 29.8o with increase in moisture content. The Static coefficient of friction on ply wood with grains parallel to the direction of movement ranged from 0.41 to 0.61, it ranged from 0.19 to 0.24 on on fiber glass, 0.28 to .038 on hessian bag material and 0.25 to 0.33 on galvanized steel sheet. The specific heat of the seed varied from 2738.1- 4345.4J/kg/oC in the above moisture range.

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...

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

Science.gov (United States)

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

2017-11-01

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

One loop partition function of six dimensional conformal gravity using heat kernel on AdS

Energy Technology Data Exchange (ETDEWEB)

Lovreković, Iva [Institute for Theoretical Physics, Technische Universität Wien,Wiedner Hauptstrasse 8-10/136, A-1040 Vienna (Austria)

2016-10-13

We compute the heat kernel for the Laplacians of symmetric transverse traceless fields of arbitrary spin on the AdS background in even number of dimensions using the group theoretic approach introduced in http://dx.doi.org/10.1007/JHEP11(2011)010 and apply it on the partition function of six dimensional conformal gravity. The obtained partition function consists of the Einstein gravity, conformal ghost and two modes that contain mass.

Heat kernel expansion for fermionic billiards in an external magnetic field

International Nuclear Information System (INIS)

Antoine, M.; Comtet, A.; Knecht, M.

1989-05-01

Using Seeley's heat kernel expansion, we compute the asymptotic density of states of the Dirac operator coupled to a magnetic field on a two dimensional manifold with boundary (fermionic billiard). Local boundary conditions compatible with vector current conservation depend on a free parameter α. It is shown that the perimeter correction identically vanishes for α = 0. In that case, the next order constant term is found to be proportional to the Euler characteristic of the manifold. These results are independent of the external magnetic field and of the shape of the billiard, provided the boundary is sufficiently smooth. For the flat circular billiard, the constant term is found to be - 1/12, in agreement with a numerical result by M.V. BERRY and R.J. MONDRAGON (1987)

Probing interaction of Gram-positive and Gram-negative bacterial cells with ZnO nanorods

Energy Technology Data Exchange (ETDEWEB)

Jain, Aanchal; Bhargava, Richa; Poddar, Pankaj, E-mail: p.poddar@ncl.res.in

2013-04-01

In the present work, the physiological effects of the ZnO nanorods on the Gram positive (Staphylococcus aureus and Bacillus subtilis) and Gram-negative (Escherichia coli and Aerobacter aerogenes) bacterial cells have been studied. The analysis of bacterial growth curves for various concentrations of ZnO nanorods indicates that Gram positive and Gram negative bacterial cells show inhibition at concentrations of ∼ 64 and ∼ 256 μg/mL respectively. The marked difference in susceptibility towards nanorods was also validated by spread plate and disk diffusion methods. In addition, the scanning electron micrographs show a clear damage to the cells via changed morphology of the cells from rod to coccoid etc. The confocal optical microscopy images of these cells also demonstrate the reduction in live cell count in the presence of ZnO nanorods. These, results clearly indicate that the antibacterial activity of ZnO nanorods is higher towards Gram positive bacterium than Gram negative bacterium which indicates that the structure of the cell wall might play a major role in the interaction with nanostructured materials and shows high sensitivity to the particle concentration. Highlights: ► Effect of ZnO nanorods on the growth cycles of four bacterial strains. ► A relation has been established between growth rate of bacteria and concentration. ► Serious damage in the morphology of bacterial cells in the presence of ZnO nanorods. ► Microscopic studies to see the time dependent effect on bacterial cells.

Heat Damaged Forages: Effects on Forage Quality

Science.gov (United States)

Traditionally, heat damage in forages has been associated with alterations in forage protein quality as a result of Maillard reactions, and most producers and nutritionists are familiar with this concept. However, this is not necessarily the most important negative consequence of spontaneous heating...

Quantum Einstein gravity. Advancements of heat kernel-based renormalization group studies

Energy Technology Data Exchange (ETDEWEB)

Groh, Kai

2012-10-15

The asymptotic safety scenario allows to define a consistent theory of quantized gravity within the framework of quantum field theory. The central conjecture of this scenario is the existence of a non-Gaussian fixed point of the theory's renormalization group flow, that allows to formulate renormalization conditions that render the theory fully predictive. Investigations of this possibility use an exact functional renormalization group equation as a primary non-perturbative tool. This equation implements Wilsonian renormalization group transformations, and is demonstrated to represent a reformulation of the functional integral approach to quantum field theory. As its main result, this thesis develops an algebraic algorithm which allows to systematically construct the renormalization group flow of gauge theories as well as gravity in arbitrary expansion schemes. In particular, it uses off-diagonal heat kernel techniques to efficiently handle the non-minimal differential operators which appear due to gauge symmetries. The central virtue of the algorithm is that no additional simplifications need to be employed, opening the possibility for more systematic investigations of the emergence of non-perturbative phenomena. As a by-product several novel results on the heat kernel expansion of the Laplace operator acting on general gauge bundles are obtained. The constructed algorithm is used to re-derive the renormalization group flow of gravity in the Einstein-Hilbert truncation, showing the manifest background independence of the results. The well-studied Einstein-Hilbert case is further advanced by taking the effect of a running ghost field renormalization on the gravitational coupling constants into account. A detailed numerical analysis reveals a further stabilization of the found non-Gaussian fixed point. Finally, the proposed algorithm is applied to the case of higher derivative gravity including all curvature squared interactions. This establishes an improvement

Quantum Einstein gravity. Advancements of heat kernel-based renormalization group studies

International Nuclear Information System (INIS)

Groh, Kai

2012-10-01

The asymptotic safety scenario allows to define a consistent theory of quantized gravity within the framework of quantum field theory. The central conjecture of this scenario is the existence of a non-Gaussian fixed point of the theory's renormalization group flow, that allows to formulate renormalization conditions that render the theory fully predictive. Investigations of this possibility use an exact functional renormalization group equation as a primary non-perturbative tool. This equation implements Wilsonian renormalization group transformations, and is demonstrated to represent a reformulation of the functional integral approach to quantum field theory. As its main result, this thesis develops an algebraic algorithm which allows to systematically construct the renormalization group flow of gauge theories as well as gravity in arbitrary expansion schemes. In particular, it uses off-diagonal heat kernel techniques to efficiently handle the non-minimal differential operators which appear due to gauge symmetries. The central virtue of the algorithm is that no additional simplifications need to be employed, opening the possibility for more systematic investigations of the emergence of non-perturbative phenomena. As a by-product several novel results on the heat kernel expansion of the Laplace operator acting on general gauge bundles are obtained. The constructed algorithm is used to re-derive the renormalization group flow of gravity in the Einstein-Hilbert truncation, showing the manifest background independence of the results. The well-studied Einstein-Hilbert case is further advanced by taking the effect of a running ghost field renormalization on the gravitational coupling constants into account. A detailed numerical analysis reveals a further stabilization of the found non-Gaussian fixed point. Finally, the proposed algorithm is applied to the case of higher derivative gravity including all curvature squared interactions. This establishes an improvement of

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...

Rational kernels for Arabic Root Extraction and Text Classification

Directory of Open Access Journals (Sweden)

Attia Nehar

2016-04-01

Full Text Available In this paper, we address the problems of Arabic Text Classification and root extraction using transducers and rational kernels. We introduce a new root extraction approach on the basis of the use of Arabic patterns (Pattern Based Stemmer. Transducers are used to model these patterns and root extraction is done without relying on any dictionary. Using transducers for extracting roots, documents are transformed into finite state transducers. This document representation allows us to use and explore rational kernels as a framework for Arabic Text Classification. Root extraction experiments are conducted on three word collections and yield 75.6% of accuracy. Classification experiments are done on the Saudi Press Agency dataset and N-gram kernels are tested with different values of N. Accuracy and F1 report 90.79% and 62.93% respectively. These results show that our approach, when compared with other approaches, is promising specially in terms of accuracy and F1.

Acceleration of the universe, vacuum metamorphosis, and the large-time asymptotic form of the heat kernel

International Nuclear Information System (INIS)

Parker, Leonard; Vanzella, Daniel A.T.

2004-01-01

We investigate the possibility that the late acceleration observed in the rate of expansion of the Universe is due to vacuum quantum effects arising in curved spacetime. The theoretical basis of the vacuum cold dark matter (VCDM), or vacuum metamorphosis, cosmological model of Parker and Raval is reexamined and improved. We show, by means of a manifestly nonperturbative approach, how the infrared behavior of the propagator (related to the large-time asymptotic form of the heat kernel) of a free scalar field in curved spacetime leads to nonperturbative terms in the effective action similar to those appearing in the earlier version of the VCDM model. The asymptotic form that we adopt for the propagator or heat kernel at large proper time s is motivated by, and consistent with, particular cases where the heat kernel has been calculated exactly, namely in de Sitter spacetime, in the Einstein static universe, and in the linearly expanding spatially flat Friedmann-Robertson-Walker (FRW) universe. This large-s asymptotic form generalizes somewhat the one suggested by the Gaussian approximation and the R-summed form of the propagator that earlier served as a theoretical basis for the VCDM model. The vacuum expectation value for the energy-momentum tensor of the free scalar field, obtained through variation of the effective action, exhibits a resonance effect when the scalar curvature R of the spacetime reaches a particular value related to the mass of the field. Modeling our Universe by an FRW spacetime filled with classical matter and radiation, we show that the back reaction caused by this resonance drives the Universe through a transition to an accelerating expansion phase, very much in the same way as originally proposed by Parker and Raval. Our analysis includes higher derivatives that were neglected in the earlier analysis, and takes into account the possible runaway solutions that can follow from these higher-derivative terms. We find that the runaway solutions do

[Scanning electron microscopy of heat-damaged bone tissue].

Science.gov (United States)

Harsanyl, L

1977-02-01

Parts of diaphyses of bones were exposed to high temperature of 200-1300 degrees C. Damage to the bone tissue caused by the heat was investigated. The scanning electron microscopic picture seems to be characteristic of the temperature applied. When the bones heated to the high temperature of 700 degrees C characteristic changes appear on the periostal surface, higher temperatura on the other hand causes damage to the compact bone tissue and can be observed on the fracture-surface. Author stresses the importance of this technique in the legal medicine and anthropology.

Survival rate of Plodia interpunctella (Lepidoptera: Pyralidae: On different states of wheat and rye kernels previously infested by beetle pests

Directory of Open Access Journals (Sweden)

Vukajlović Filip N.

2017-01-01

Full Text Available The present study was undertaken to determine survival rate of Plodia interpunctella (Hübner, 1813, reared on different mechanical states of Vizija winter wheat cultivar and Raša winter rye cultivar, previously infested with different beetle pests. Wheat was previously infested with Rhyzopertha dominica, Sitophilus granarius, Oryzaephilus surinamensis and Cryptolestes ferrugineus, while rye was infested only with O. surinamensis. Kernels were tested in three different mechanical states: (A whole undamaged kernels; (B kernels already damaged by pests and (C original storage kernels (mixture of B and C type. No P. interpunctella adult emerged on wheat kernels, while 36 adults developed on rye kernels. The highest abundance reached beetle species who fed with a mixture of kernels damaged by pests and whole undamaged kernels. Development and survival rate of five different storage insect pests depends on type of kernels and there exist significant survivorship correlations among them.

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

Countermeasures for heat damage in rice grain quality under climate change

Directory of Open Access Journals (Sweden)

Satoshi Morita

2016-01-01

Full Text Available Climate change has been an increasingly significant factor behind fluctuations in the yield and quality of rice (Oryza sativa L., particularly regarding chalky (white-back, basal-white, and milky-white grain, immature thin grain, and cracked grain. The development and use of heat-tolerant varieties is an effective way to reduce each type of grain damage based on the existence of each varietal difference. Cultivation methods that increase the available assimilate supply per grain, such as deep-flood irrigation, are effective for diminishing the occurrence of milky-white grains under high temperature and low solar radiation conditions. The application of sufficient nitrogen during the reproductive stage is important to reduce the occurrence of most heat damage with the exception of milky-white grain. In regard to developing measures for heat-induced poor palatability of cooked rice, a sensory parameter, the hardness/adhesion ratio may be useful as an indicator of palatability within a relatively wide air–temperature range during ripening. Methods for heat damage to rice can be classified as either avoidance or tolerance measures. The timing of the measures is further divided into preventive and prompt types. The use of heat-tolerant varieties and late transplanting are preventive measures, whereas the application of sufficient nitrogen as a top dressing and irrigation techniques during the reproductive stage are prompt types which may function to lower the canopy temperature by enhancing evapotranspiration. Trials combining the different types of techniques will contribute towards obtaining more efficient and steady countermeasures against heat damage under conditions of climate change.

Effects of Defatting Combined or not to Heating of Jatropha curcas Kernel Meal on Feed Intake and Growth Performance in Broiler Chickens and Chicks in Senegal

Directory of Open Access Journals (Sweden)

Nesseim, TDT.

2017-01-01

Full Text Available Jatropha curcas is a tropical plant belonging to the Euphorbiaceae family whose cultivation has been largely promoted in recent years for the production of biofuels. The kernel of the seed contains approximately 55% lipid in dry matter and the meal obtained could be an exceptional source of proteins for family poultry farming, after treatments to remove toxic and anti-nutritional compounds. The ingestion and the growth performance of J. curcas kernel meal (JKM, obtained after partial physico-chemical de-oiling combined or not with heating was evaluated in broiler chickens and chicks. Sixty unsexed broiler chickens, 30 day-old, divided into three groups as well as twenty broiler chicks, 1 day-old, divided into two groups were used in two experiments. In experiment 1, jatropha kernel was de-oiled and incorporated into a control fattening feed at 40 and 80g/kg (diets 4JKM1 and 8JM1. In experiment 2, jatropha kernel meal obtained in experiment 1 was heat treated and incorporated into a growing diet at 80g/kg (diet 8JKM2. Daily dietary intakes as well as weight gain of the animals were affected by the incorporation of jatropha kernel meal in the ration. In experiment 1, average daily feed intake (ADFI1 of 139.2, 55.2 and 23.4g/day/animal and also average daily weight gain (ADWG1 of 61.9, 18.5 and -7.7g/animal were obtained respectively for the groups fed with diets 0JKM1, 4JKM1 and 8JKM1. In experiment 2, Average daily feed intake (ADFI2 of 18.7 and 3.1g/day/animal and also average daily weight gain (ADWG2 of 7.1 and 1.9g/animal were obtained respectively for the groups fed with diets 0JKM2 and 8JKM2. In both experiment, feed conversion ratio (FCR was also affected by the dietary treatments and the overall mortality rate showed an increase according to levels of jatropha kernel meal in diet.

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...

Migration of the ThO2 kernels under the influence of a temperature gradient

International Nuclear Information System (INIS)

Smith, C.L.

1977-01-01

Biso-coated ThO 2 fertile fuel kernels will migrate up the thermal gradients imposed across coated particles during high-temperature gas-cooled reactor (HTGR) operation. Thorium dioxide kernel migration has been studied as a function of temperature (1290 to 1705 0 C) (1563 to 1978 K) 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

An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel

Directory of Open Access Journals (Sweden)

Senyue Zhang

2016-01-01

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

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

Heat damaged forages: effects on forage energy content

Science.gov (United States)

Traditionally, educational materials describing the effects of heat damage within baled hays have focused on reduced bioavailability of crude protein as a result of Maillard reactions. These reactions are not simple, but actually occur in complex, multi-step pathways. Typically, the initial step inv...

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.

A Comparison of Heat versus Methanol Fixation for Gram Staining Bacteria

Science.gov (United States)

Minnerath, Jeanne M.; Roland, Jenna M.; Rossi, Lucas C.; Weishalla, Steven R.; Wolf, Melissa M.

2009-01-01

Gram staining bacteria is a fundamental technique introduced in general biology and microbiology laboratory courses. Two common problems students encounter when Gram staining bacteria are (1) having a difficult time locating bacterial cells on the microscope slide and (2) over-decolorizing bacterial cells during the staining procedure such that…

Excision of x-ray-induced thymine damage in chromatin from heated cells

International Nuclear Information System (INIS)

Warters, R.L.; Roti Roti, J.L.

1979-01-01

Experiments were performed to distinguish between two possible modes of hyperthermia-induced inhibition of thymine base damage excision from the DNA of CHO cells: (1) heat denaturation of excision enzyme(s) or (2) heat-induced alteration of the substrate for damage excision (chromatin). While hyperthermia (45 0 C, 15 min) had no apparent effect on the capacity of the excision enzymes to excise damage from DNA it had a dramatic effect (ca. 80% inhibition) on the ability of chromatin to serve as a substrate for unheated enzymes. These results suggest that hyperthermia-induced radiosensitization of CHO cells may be due primarily to lesions in the cellular chromatin

Inactivation dynamics of 222 nm krypton-chlorine excilamp irradiation on Gram-positive and Gram-negative foodborne pathogenic bacteria.

Science.gov (United States)

Kang, Jun-Won; Kim, Sang-Soon; Kang, Dong-Hyun

2018-07-01

The object of this study was to elucidate the bactericidal mechanism of a 222 nm Krypton Chlorine (KrCl) excilamp compared with that of a 254 nm Low Pressure mercury (LP Hg) lamp. The KrCl excilamp had higher bactericidal capacity against Gram-positive pathogenic bacteria (Staphylococcus aureus and L. monocytogenes) and Gram-negative pathogenic bacteria (S. Typhimurium and E. coli O157:H7) than did the LP Hg lamp when cell suspensions in PBS were irradiated with each type of UV lamp. It was found out that the KrCl excilamp induced cell membrane damage as a form of depolarization. From the study of respiratory chain dehydrogenase activity and the lipid peroxidation assay, it was revealed that cell membrane damage was attributed to inactivation of enzymes related to generation of membrane potential and occurrence of lipid peroxidation. Direct absorption of UV radiation which led to photoreaction through formation of an excited state was one of the causes inducing cell damage. Additionally, generation of ROS and thus occurrence of secondary damage can be another cause. The LP Hg lamp only induced damage to DNA but not to other components such as lipids or proteins. This difference was derived from differences of UV radiation absorption by cellular materials. Copyright © 2018 Elsevier Ltd. All rights reserved.

The assessment of bond strength between heat damaged concrete and high strength fibre reinforced concrete

Science.gov (United States)

Zahid, M. Z. A. Mohd; Muhamad, K.

2017-09-01

The aim of this study is to assess the bond strength between heat damaged concrete and high strength fibre reinforced concrete (HPFRC). Firstly, this paper presents the various steps taken to prepare the HPFRC with self-compacting property. The minimum targeted slump flow is 600 mm and minimum targeted compressive strength is 80 MPa. The key mix variables considered are such as type of superplasticizer, water cement ratio and silica fume content. Then, the bond strength between the heat damaged concrete with HPFRC was examined. The experimental parameters are heating temperature, surface treatment technique and curing method and the results show that, all experimental parameters are significantly affected the bond strength between heat damaged concrete and HPFRC.

Fretting-wear damage of heat exchanger tubes: a proposed damage criterion based on tube vibration response

International Nuclear Information System (INIS)

Yetisir, M.; McKerrow, E.; Pettigrew, M.J.

1997-01-01

A simple criterion is proposed to estimate fretting-wear damage in heat exchanger tubes with clearance supports. The criterion is based on parameters such as vibration frequency, mid-span vibration amplitude, span length, tube mass and an empirical wear coefficient. It is generally accepted that fretting-wear damage is proportional to a parameter called work-rate. Work-rate is a measure of the dynamic interaction between a vibrating tube and its supports. Due to the complexity of the impact-sliding behavior at the clearance-supports, work-rate calculations for heat exchanger tubes require specialized non-linear finite element codes. These codes include contact models for various clearance-support geometries. Such non-linear finite element analyses are complex, expensive and time consuming. The proposed criterion uses the results of linear vibration analysis (i.e., vibration frequency and mid-span vibration amplitude due to turbulence) and does not require a non-linear analysis. It can be used by non-specialists for a quick evaluation of the expected work-rate, and hence, the fretting-wear damage of heat exchanger tubes. The proposed criterion was obtained from an extensive parametric study that was conducted using a non-linear finite element program. It is shown that, by using the proposed work-rate criteria, work-rate can be estimated within a factor of two. This result, however, requires further testing with more complicated flow patterns. (author)

Supersymmetry of noncompact MQCD-like membrane instantons and heat kernel asymptotics

International Nuclear Information System (INIS)

Belani, Kanishka; Kaura, Payal; Misra, Aalok

2006-01-01

We perform a heat kernel asymptotics analysis of the nonperturbative superpotential obtained from wrapping of an M2-brane around a supersymmetric noncompact three-fold embedded in a (noncompact) G 2 -manifold as obtained, the three-fold being the one relevant to domain walls in Witten's MQCD, in the limit of small 'ζ', a complex constant that appears in the Riemann surfaces relevant to defining the boundary conditions for the domain wall in MQCD. The MQCD-like configuration is interpretable, for small but non-zero ζ as a noncompact/'large open membrane instanton, and for vanishing ζ, as the type IIA D0-brane (for vanishing M-theory circle radius). We find that the eta-function Seeley de-Witt coefficients vanish, and we get a perfect match between the zeta-function Seeley de-Witt coefficients (up to terms quadratic in ζ) between the Dirac-type operator and one of the two Laplace-type operators figuring in the superpotential. Given the dissimilar forms of the bosonic and the square of the fermionic operators, this is an extremely nontrivial check, from a spectral analysis point of view, of the expected residual supersymmetry for the nonperturbative configurations in M-theory considered in this work

Use of magnetic beads for Gram staining of bacteria in aqueous suspension.

Science.gov (United States)

Yazdankhah, S P; Sørum, H; Larsen, H J; Gogstad, G

2001-12-01

A Gram staining technique was developed using monodisperse magnetic beads in concentrating bacteria in suspension for downstream application. The technique does not require heat fixation of organisms, electrical power, or a microscope. Gram-negative and Gram-positive bacteria were identified macroscopically based on the colour of the suspension. The bacteria concentrated on magnetic beads may also be identified microscopically.

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

7 CFR 51.1414 - Serious damage.

Science.gov (United States)

2010-01-01

... as serious damage: (a) Adhering hull material or dark stains affecting an aggregate of more than 20...) Decay affecting any portion of the kernel; (g) Insect injury when the insect, web or frass is present... than three dark spots on either half of the kernel, or when any spot or the aggregate of two or more...

Dielectric properties of almond kernels associated with radio frequency and microwave pasteurization

Science.gov (United States)

Li, Rui; Zhang, Shuang; Kou, Xiaoxi; Ling, Bo; Wang, Shaojin

2017-02-01

To develop advanced pasteurization treatments based on radio frequency (RF) or microwave (MW) energy, dielectric properties of almond kernels were measured by using an open-ended coaxial-line probe and impedance analyzer at frequencies between 10 and 3000 MHz, moisture contents between 4.2% to 19.6% w.b. and temperatures between 20 and 90 °C. The results showed that both dielectric constant and loss factor of the almond kernels decreased sharply with increasing frequency over the RF range (10-300 MHz), but gradually over the measured MW range (300-3000 MHz). Both dielectric constant and loss factor of almond kernels increased with increasing temperature and moisture content, and largely enhanced at higher temperature and moisture levels. Quadratic polynomial equations were developed to best fit the relationship between dielectric constant or loss factor at 27, 40, 915 or 2450 MHz and sample temperature/moisture content with R2 greater than 0.967. Penetration depth of electromagnetic wave into samples decreased with increasing frequency (27-2450 MHz), moisture content (4.2-19.6% w.b.) and temperature (20-90 °C). The temperature profiles of RF heated almond kernels under three moisture levels were made using experiment and computer simulation based on measured dielectric properties. Based on the result of this study, RF treatment has potential to be practically used for pasteurization of almond kernels with acceptable heating uniformity.

Effect of Temperature and Moisture on the Development of Concealed Damage in Raw Almonds (Prunus dulcis).

Science.gov (United States)

Rogel-Castillo, Cristian; Zuskov, David; Chan, Bronte Lee; Lee, Jihyun; Huang, Guangwei; Mitchell, Alyson E

2015-09-23

Concealed damage (CD) is a brown discoloration of nutmeat that appears only after kernels are treated with moderate heat (e.g., roasting). Identifying factors that promote CD in almonds is of significant interest to the nut industry. Herein, the effect of temperature (35 and 45 °C) and moisture (almonds (Prunus dulcis var. Nonpareil) was studied using HS-SPME-GC/MS. A CIE LCh colorimetric method was developed to identify raw almonds with CD. A significant increase in CD was demonstrated in almonds exposed to moisture (8% kernel moisture content) at 45 °C as compared to 35 °C. Elevated levels of volatiles related to lipid peroxidation and amino acid degradation were observed in almonds with CD. These results suggest that postharvest moisture exposure resulting in an internal kernel moisture ≥ 8% is a key factor in the development of CD in raw almonds and that CD is accelerated by temperature.

Influence of food matrix on outgrowth heterogeneity of heat damaged Bacillus cereus spores.

Science.gov (United States)

Warda, Alicja K; den Besten, Heidy M W; Sha, Na; Abee, Tjakko; Nierop Groot, Masja N

2015-05-18

Spoilage of heat treated foods can be caused by the presence of surviving spore-formers. It is virtually impossible to prevent contamination at the primary production level as spores are ubiquitous present in the environment and can contaminate raw products. As a result spore inactivation treatments are widely used by food producing industries to reduce the microbial spore loads. However consumers prefer mildly processed products that have less impact on its quality and this trend steers industry towards milder preservation treatments. Such treatments may result in damaged instead of inactivated spores, and these spores may germinate, repair, and grow out, possibly leading to quality and safety issues. The ability to repair and grow out is influenced by the properties of the food matrix. In the current communication we studied the outgrowth from heat damaged Bacillus cereus ATCC 14579 spores on Anopore membrane, which allowed following outgrowth heterogeneity of individual spores on broccoli and rice-based media as well as standard and mildly acidified (pH 5.5) meat-based BHI. Rice, broccoli and BHI pH 5.5 media resulted in delayed outgrowth from untreated spores, and increased heterogeneity compared to BHI pH 7.4, with the most pronounced effect in rice media. Exposure to wet heat for 1 min at 95 °C caused 2 log inactivation and approximately 95% of the spores in the surviving fraction were damaged resulting in substantial delay in outgrowth based on the time required to reach a maximum microcolony size of 256 cells. The delay was most pronounced for heat-treated spores on broccoli medium followed by spores on rice media (both untreated and treated). Interestingly, the increase in outgrowth heterogeneity of heat treated spores on BHI pH 7.4 was more pronounced than on rice, broccoli and BHI pH 5.5 conceivably reflecting that conditions in BHI pH 7.4 better support spore damage repair. This study compares the effects of three main factors, namely heat treatment, p

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

Lévy matters VI Lévy-type processes moments, construction and heat kernel estimates

CERN Document Server

Kühn, Franziska

2017-01-01

Presenting some recent results on the construction and the moments of Lévy-type processes, the focus of this volume is on a new existence theorem, which is proved using a parametrix construction. Applications range from heat kernel estimates for a class of Lévy-type processes to existence and uniqueness theorems for Lévy-driven stochastic differential equations with Hölder continuous coefficients. Moreover, necessary and sufficient conditions for the existence of moments of Lévy-type processes are studied and some estimates on moments are derived. Lévy-type processes behave locally like Lévy processes but, in contrast to Lévy processes, they are not homogeneous in space. Typical examples are processes with varying index of stability and solutions of Lévy-driven stochastic differential equations. This is the sixth volume in a subseries of the Lecture Notes in Mathematics called Lévy Matters. Each volume describes a number of important topics in the theory or applicati ons of Lévy processes and pays ...

Application of Laser Pulse Heating to Simulate Thermomechanical Damage at Gun Bore Surfaces

National Research Council Canada - National Science Library

Cote, Paul

2003-01-01

Laser pulse heating experiments were performed to provide insights into the thermomechanical damage effects that occur at the surface of coated and uncoated gun steel under cyclic rapid heating and cooling...

7 CFR 51.2294 - Very serious damage.

Science.gov (United States)

2010-01-01

... serious damage. Very serious damage means any defect, other than color, which very seriously affects the... than one-fourth of the surface of the portion of kernel in the aggregate; (c) Discoloration of the meat...

Effects of propofol on damage of rat intestinal epithelial cells induced by heat stress and lipopolysaccharides

Energy Technology Data Exchange (ETDEWEB)

Tang, J.; Jiang, Y. [Southern Medical University, Nanfang Hospital, Department of Anesthesia, Guangzhou, China, Department of Anesthesia, Nanfang Hospital, Southern Medical University, Guangzhou (China); Tang, Y.; Chen, B. [Guangzhou General Hospital of Guangzhou Military Command, Department of Intensive Care Unit, Guangzhou, China, Department of Intensive Care Unit, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou (China); Sun, X. [Laboratory of Traditional Chinese Medicine Syndrome, School of Traditional Chinese Medicine, Southern Medical University, Guangzhou (China); Su, L.; Liu, Z. [Guangzhou General Hospital of Guangzhou Military Command, Department of Intensive Care Unit, Guangzhou, China, Department of Intensive Care Unit, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou (China)

2013-06-25

Gut-derived endotoxin and pathogenic bacteria have been proposed as important causative factors of morbidity and death during heat stroke. However, it is still unclear what kind of damage is induced by heat stress. In this study, the rat intestinal epithelial cell line (IEC-6) was treated with heat stress or a combination of heat stress and lipopolysaccharide (LPS). In addition, propofol, which plays an important role in anti-inflammation and organ protection, was applied to study its effects on cellular viability and apoptosis. Heat stress, LPS, or heat stress combined with LPS stimulation can all cause intestinal epithelial cell damage, including early apoptosis and subsequent necrosis. However, propofol can alleviate injuries caused by heat stress, LPS, or the combination of heat stress and LPS. Interestingly, propofol can only mitigate LPS-induced intestinal epithelial cell apoptosis, and has no protective role in heat-stress-induced apoptosis. This study developed a model that can mimic the intestinal heat stress environment. It demonstrates the effects on intestinal epithelial cell damage, and indicated that propofol could be used as a therapeutic drug for the treatment of heat-stress-induced intestinal injuries.

Effects of propofol on damage of rat intestinal epithelial cells induced by heat stress and lipopolysaccharides

International Nuclear Information System (INIS)

Tang, J.; Jiang, Y.; Tang, Y.; Chen, B.; Sun, X.; Su, L.; Liu, Z.

2013-01-01

Gut-derived endotoxin and pathogenic bacteria have been proposed as important causative factors of morbidity and death during heat stroke. However, it is still unclear what kind of damage is induced by heat stress. In this study, the rat intestinal epithelial cell line (IEC-6) was treated with heat stress or a combination of heat stress and lipopolysaccharide (LPS). In addition, propofol, which plays an important role in anti-inflammation and organ protection, was applied to study its effects on cellular viability and apoptosis. Heat stress, LPS, or heat stress combined with LPS stimulation can all cause intestinal epithelial cell damage, including early apoptosis and subsequent necrosis. However, propofol can alleviate injuries caused by heat stress, LPS, or the combination of heat stress and LPS. Interestingly, propofol can only mitigate LPS-induced intestinal epithelial cell apoptosis, and has no protective role in heat-stress-induced apoptosis. This study developed a model that can mimic the intestinal heat stress environment. It demonstrates the effects on intestinal epithelial cell damage, and indicated that propofol could be used as a therapeutic drug for the treatment of heat-stress-induced intestinal injuries

Damage prediction of carbon fibre composite armoured actively cooled plasma-facing components under cycling heat loads

International Nuclear Information System (INIS)

Chevet, G; Schlosser, J; Courtois, X; Escourbiac, F; Missirlian, M; Herb, V; Martin, E; Camus, G; Braccini, M

2009-01-01

In order to predict the lifetime of carbon fibre composite (CFC) armoured plasma-facing components in magnetic fusion devices, it is necessary to analyse the damage mechanisms and to model the damage propagation under cycling heat loads. At Tore Supra studies have been launched to better understand the damage process of the armoured flat tile elements of the actively cooled toroidal pump limiter, leading to the characterization of the damageable mechanical behaviour of the used N11 CFC material and of the CFC/Cu bond. Up until now the calculations have shown damage developing in the CFC (within the zone submitted to high shear stress) and in the bond (from the free edge of the CFC/Cu interface). Damage is due to manufacturing shear stresses and does not evolve under heat due to stress relaxation. For the ITER divertor, NB31 material has been characterized and the characterization of NB41 is in progress. Finite element calculations show again the development of CFC damage in the high shear stress zones after manufacturing. Stresses also decrease under heat flux so the damage does not evolve. The characterization of the CFC/Cu bond is more complex due to the monoblock geometry, which leads to more scattered stresses. These calculations allow the fabrication difficulties to be better understood and will help to analyse future high heat flux tests on various mock-ups.

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.

Selection and properties of alternative forming fluids for TRISO fuel kernel production

Energy Technology Data Exchange (ETDEWEB)

Baker, M.P. [Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); King, J.C., E-mail: kingjc@mines.edu [Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Gorman, B.P. [Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Marshall, D.W. [Idaho National Laboratory, 2525 N. Fremont Avenue, P.O. Box 1625, Idaho Falls, ID 83415 (United States)

2013-01-15

Highlights: Black-Right-Pointing-Pointer Forming fluid selection criteria developed for TRISO kernel production. Black-Right-Pointing-Pointer Ten candidates selected for further study. Black-Right-Pointing-Pointer Density, viscosity, and surface tension measured for first time. Black-Right-Pointing-Pointer Settling velocity and heat transfer rates calculated. Black-Right-Pointing-Pointer Three fluids recommended for kernel production testing. - Abstract: Current Very High Temperature Reactor (VHTR) designs incorporate TRi-structural ISOtropic (TRISO) fuel, which consists of a spherical fissile fuel kernel surrounded by layers of pyrolytic carbon and silicon carbide. An internal sol-gel process forms the fuel kernel using wet chemistry to produce uranium oxyhydroxide gel spheres by dropping a cold precursor solution into a hot column of trichloroethylene (TCE). Over time, gelation byproducts inhibit complete gelation, and the TCE must be purified or discarded. The resulting TCE waste stream contains both radioactive and hazardous materials and is thus considered a mixed hazardous waste. Changing the forming fluid to a non-hazardous alternative could greatly improve the economics of TRISO fuel kernel production. Selection criteria for a replacement forming fluid narrowed a list of {approx}10,800 chemicals to yield ten potential replacement forming fluids: 1-bromododecane, 1-bromotetradecane, 1-bromoundecane, 1-chlorooctadecane, 1-chlorotetradecane, 1-iododecane, 1-iodododecane, 1-iodohexadecane, 1-iodooctadecane, and squalane. The density, viscosity, and surface tension for each potential replacement forming fluid were measured as a function of temperature between 25 Degree-Sign C and 80 Degree-Sign C. Calculated settling velocities and heat transfer rates give an overall column height approximation. 1-bromotetradecane, 1-chlorooctadecane, and 1-iodododecane show the greatest promise as replacements, and future tests will verify their ability to form satisfactory

The relative effects of fuel concentration, residual-gas fraction, gas motion, spark energy and heat losses to the electrodes on flame-kernel development in a lean-burn spark ignition engine

Energy Technology Data Exchange (ETDEWEB)

Aleiferis, P.G.; Taylor, A.M.K.P. [Imperial College of Science, Technology and Medicine, London (United Kingdom). Dept. of Mechanical Engineering; Ishii, K. [Honda International Technical School, Saitama (Japan); Urata, Y. [Honda R and D Co., Ltd., Tochigi (Japan). Tochigi R and D Centre

2004-04-01

The potential of lean combustion for the reduction in exhaust emissions and fuel consumption in spark ignition engines has long been established. However, the operating range of lean-burn spark ignition engines is limited by the level of cyclic variability in the early-flame development stage that typically corresponds to the 0-5 per cent mass fraction burned duration. In the current study, the cyclic variations in early flame development were investigated in an optical stratified-charge spark ignition engine at conditions close to stoichiometry [air-to-fuel ratio (A/F) = 15] and to the lean limit of stable operation (A/F = 22). Flame images were acquired through either a pentroof window ('tumble plane' of view) or the piston crown ('swirl plane' of view) and these were processed to calculate the intra-cycle flame-kernel radius evolution. In order to quantify the relative effects of local fuel concentration, gas motion, spark-energy release and heat losses to the electrodes on the flame-kernel growth rate, a zero-dimensional flame-kernel growth model, in conjunction with a one-dimensional spark ignition model, was employed. Comparison of the calculated flame-radius evolutions with the experimental data suggested that a variation in A/F around the spark plug of {delta}(A/F) {approx} 4 or, in terms of equivalence ratio {phi}, a variation in {delta}{phi} {approx} 0.15 at most was large enough to account for 100 per cent of the observed cyclic variability in flame-kernel radius. A variation in the residual-gas fraction of about 20 per cent around the mean was found to account for up to 30 per cent of the variability in flame-kernel radius at the timing of 5 per cent mass fraction burned. The individual effect of 20 per cent variations in the 'mean' in-cylinder velocity at the spark plug at ignition timing was found to account for no more than 20 per cent of the measured cyclic variability in flame kernel radius. An individual effect of

Damage and fatigue crack growth of Eurofer steel first wall mock-up under cyclic heat flux loads. Part 2: Finite element analysis of damage evolution

International Nuclear Information System (INIS)

You, Jeong-Ha

2014-01-01

Highlights: • The surface heat flux load of 3.5 MW/m 2 produced substantial stresses and inelastic strains in the heat-loaded surface region, especially at the notch root. • The notch root exhibited a typical notch effect such as stress concentration and localized inelastic yield leading to a preferred damage development. • The predicted damage evolution feature agrees well with the experimental observation. • The smooth surface also experiences considerable stresses and inelastic strains. However, the stress intensity and the amount of inelastic deformation are not high enough to cause any serious damage. • The level of maximum inelastic strain is higher at the notch root than at the smooth surface. On the other hand, the amplitude of inelastic strain variation is comparable at both positions. • The amount of inelastic deformation is significantly affected by the length of pulse duration time indicating the important role of creep. - Abstract: In the preceding companion article (part 1), the experimental results of the high-heat-flux (3.5 MW/m 2 ) fatigue tests of a Eurofer bare steel first wall mock-up was presented. The aim was to investigate the damage evolution and crack initiation feature. The mock-up used there was a simplified model having only basic and generic structural feature of an actively cooled steel FW component for DEMO reactor. In that study, it was found that microscopic damage was formed at the notch root already in the early stage of the fatigue loading. On the contrary, the heat-loaded smooth surface exhibited no damage up to 800 load cycles. In this paper, the high-heat-flux fatigue behavior is investigated with a finite element analysis to provide a theoretical interpretation. The thermal fatigue test was simulated using the coupled damage-viscoplastic constitutive model developed by Aktaa. The stresses, inelastic deformation and damage evolution at the notch groove and at the smooth surface are compared. The different damage

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.

Use of Near-Infrared Spectroscopy and Chemometrics for the Nondestructive Identification of Concealed Damage in Raw Almonds (Prunus dulcis).

Science.gov (United States)

Rogel-Castillo, Cristian; Boulton, Roger; Opastpongkarn, Arunwong; Huang, Guangwei; Mitchell, Alyson E

2016-07-27

Concealed damage (CD) is defined as a brown discoloration of the kernel interior (nutmeat) that appears only after moderate to high heat treatment (e.g., blanching, drying, roasting, etc.). Raw almonds with CD have no visible defects before heat treatment. Currently, there are no screening methods available for detecting CD in raw almonds. Herein, the feasibility of using near-infrared (NIR) spectroscopy between 1125 and 2153 nm for the detection of CD in almonds is demonstrated. Almond kernels with CD have less NIR absorbance in the region related with oil, protein, and carbohydrates. With the use of partial least squares discriminant analysis (PLS-DA) and selection of specific wavelengths, three classification models were developed. The calibration models have false-positive and false-negative error rates ranging between 12.4 and 16.1% and between 10.6 and 17.2%, respectively. The percent error rates ranged between 8.2 and 9.2%. Second-derivative preprocessing of the selected wavelength resulted in the most robust predictive model.

DNA damage-responsive Drosophila melanogaster gene is also induced by heat shock

International Nuclear Information System (INIS)

Vivino, A.A.; Smith, M.D.; Minton, K.W.

1986-01-01

A gene isolated by screening Drosophila melanogaster tissue culture cells for DNA damage regulation was also found to be regulated by heat shock. After UV irradiation or heat shock, induction is at the transcriptional level and results in the accumulation of a 1.0-kilobase polyadenylated transcript. The restriction map of the clone bears no resemblance to the known heat shock genes, which are shown to be uninduced by UV irradiation

Spatial Patterns of Aflatoxin Levels in Relation to Ear-Feeding Insect Damage in Pre-Harvest Corn

Directory of Open Access Journals (Sweden)

Alisa Huffaker

2011-07-01

Full Text Available Key impediments to increased corn yield and quality in the southeastern US coastal plain region are damage by ear-feeding insects and aflatoxin contamination caused by infection of Aspergillus flavus. Key ear-feeding insects are corn earworm, Helicoverpa zea, fall armyworm, Spodoptera frugiperda, maize weevil, Sitophilus zeamais, and brown stink bug, Euschistus servus. In 2006 and 2007, aflatoxin contamination and insect damage were sampled before harvest in three 0.4-hectare corn fields using a grid sampling method. The feeding damage by each of ear/kernel-feeding insects (i.e., corn earworm/fall armyworm damage on the silk/cob, and discoloration of corn kernels by stink bugs, and maize weevil population were assessed at each grid point with five ears. The spatial distribution pattern of aflatoxin contamination was also assessed using the corn samples collected at each sampling point. Aflatoxin level was correlated to the number of maize weevils and stink bug-discolored kernels, but not closely correlated to either husk coverage or corn earworm damage. Contour maps of the maize weevil populations, stink bug-damaged kernels, and aflatoxin levels exhibited an aggregated distribution pattern with a strong edge effect on all three parameters. The separation of silk- and cob-feeding insects from kernel-feeding insects, as well as chewing (i.e., the corn earworm and maize weevil and piercing-sucking insects (i.e., the stink bugs and their damage in relation to aflatoxin accumulation is economically important. Both theoretic and applied ramifications of this study were discussed by proposing a hypothesis on the underlying mechanisms of the aggregated distribution patterns and strong edge effect of insect damage and aflatoxin contamination, and by discussing possible management tactics for aflatoxin reduction by proper management of kernel-feeding insects. Future directions on basic and applied research related to aflatoxin contamination are also

Spatial patterns of aflatoxin levels in relation to ear-feeding insect damage in pre-harvest corn.

Science.gov (United States)

Ni, Xinzhi; Wilson, Jeffrey P; Buntin, G David; Guo, Baozhu; Krakowsky, Matthew D; Lee, R Dewey; Cottrell, Ted E; Scully, Brian T; Huffaker, Alisa; Schmelz, Eric A

2011-07-01

Key impediments to increased corn yield and quality in the southeastern US coastal plain region are damage by ear-feeding insects and aflatoxin contamination caused by infection of Aspergillus flavus. Key ear-feeding insects are corn earworm, Helicoverpa zea, fall armyworm, Spodoptera frugiperda, maize weevil, Sitophilus zeamais, and brown stink bug, Euschistus servus. In 2006 and 2007, aflatoxin contamination and insect damage were sampled before harvest in three 0.4-hectare corn fields using a grid sampling method. The feeding damage by each of ear/kernel-feeding insects (i.e., corn earworm/fall armyworm damage on the silk/cob, and discoloration of corn kernels by stink bugs), and maize weevil population were assessed at each grid point with five ears. The spatial distribution pattern of aflatoxin contamination was also assessed using the corn samples collected at each sampling point. Aflatoxin level was correlated to the number of maize weevils and stink bug-discolored kernels, but not closely correlated to either husk coverage or corn earworm damage. Contour maps of the maize weevil populations, stink bug-damaged kernels, and aflatoxin levels exhibited an aggregated distribution pattern with a strong edge effect on all three parameters. The separation of silk- and cob-feeding insects from kernel-feeding insects, as well as chewing (i.e., the corn earworm and maize weevil) and piercing-sucking insects (i.e., the stink bugs) and their damage in relation to aflatoxin accumulation is economically important. Both theoretic and applied ramifications of this study were discussed by proposing a hypothesis on the underlying mechanisms of the aggregated distribution patterns and strong edge effect of insect damage and aflatoxin contamination, and by discussing possible management tactics for aflatoxin reduction by proper management of kernel-feeding insects. Future directions on basic and applied research related to aflatoxin contamination are also discussed.

Spatial Patterns of Aflatoxin Levels in Relation to Ear-Feeding Insect Damage in Pre-Harvest Corn

Science.gov (United States)

Ni, Xinzhi; Wilson, Jeffrey P.; Buntin, G. David; Guo, Baozhu; Krakowsky, Matthew D.; Lee, R. Dewey; Cottrell, Ted E.; Scully, Brian T.; Huffaker, Alisa; Schmelz, Eric A.

2011-01-01

Key impediments to increased corn yield and quality in the southeastern US coastal plain region are damage by ear-feeding insects and aflatoxin contamination caused by infection of Aspergillus flavus. Key ear-feeding insects are corn earworm, Helicoverpa zea, fall armyworm, Spodoptera frugiperda, maize weevil, Sitophilus zeamais, and brown stink bug, Euschistus servus. In 2006 and 2007, aflatoxin contamination and insect damage were sampled before harvest in three 0.4-hectare corn fields using a grid sampling method. The feeding damage by each of ear/kernel-feeding insects (i.e., corn earworm/fall armyworm damage on the silk/cob, and discoloration of corn kernels by stink bugs), and maize weevil population were assessed at each grid point with five ears. The spatial distribution pattern of aflatoxin contamination was also assessed using the corn samples collected at each sampling point. Aflatoxin level was correlated to the number of maize weevils and stink bug-discolored kernels, but not closely correlated to either husk coverage or corn earworm damage. Contour maps of the maize weevil populations, stink bug-damaged kernels, and aflatoxin levels exhibited an aggregated distribution pattern with a strong edge effect on all three parameters. The separation of silk- and cob-feeding insects from kernel-feeding insects, as well as chewing (i.e., the corn earworm and maize weevil) and piercing-sucking insects (i.e., the stink bugs) and their damage in relation to aflatoxin accumulation is economically important. Both theoretic and applied ramifications of this study were discussed by proposing a hypothesis on the underlying mechanisms of the aggregated distribution patterns and strong edge effect of insect damage and aflatoxin contamination, and by discussing possible management tactics for aflatoxin reduction by proper management of kernel-feeding insects. Future directions on basic and applied research related to aflatoxin contamination are also discussed. PMID

Gram staining.

Science.gov (United States)

Coico, Richard

2005-10-01

Named after Hans Christian Gram who developed the method in 1884, the Gram stain allows one to distinguish between Gram-positive and Gram-negative bacteria on the basis of differential staining with a crystal violet-iodine complex and a safranin counterstain. The cell walls of Gram-positive organisms retain this complex after treatment with alcohol and appear purple, whereas gram-negative organisms decolorize following such treatment and appear pink. The method described here is useful for assessing bacterial contamination of tissue culture samples or for examining the Gram stain status and morphological features of bacteria isolated from mixed or isolated bacterial cultures.

Testosterone Depletion by Castration May Protect Mice from Heat-Induced Multiple Organ Damage and Lethality

Directory of Open Access Journals (Sweden)

Ruei-Tang Cheng

2010-01-01

Full Text Available When the vehicle-treated, sham-operated mice underwent heat stress, the fraction survival and core temperature at +4 h of body heating were found to be 5 of 15 and 34.4∘C±0.3∘C, respectively. Castration 2 weeks before the start of heat stress decreased the plasma levels of testosterone almost to zero, protected the mice from heat-induced death (fraction survival, 13/15 and reduced the hypothermia (core temperature, 37.3∘C. The beneficial effects of castration in ameliorating lethality and hypothermia can be significantly reduced by testosterone replacement. Heat-induced apoptosis, as indicated by terminal deoxynucleotidyl- transferase- mediatedαUDP-biotin nick end-labeling staining, were significantly prevented by castration. In addition, heat-induced neuronal damage, as indicated by cell shrinkage and pyknosis of nucleus, to the hypothalamus was also castration-prevented. Again, the beneficial effects of castration in reducing neuronal damage to the hypothalamus as well as apoptosis in multiple organs during heatstroke, were significantly reversed by testosterone replacement. The data indicate that testosterone depletion by castration may protect mice from heatstroke-induced multiple organ damage and lethality.

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...

Damage behavior of REE-doped W-based material exposed to high-flux transient heat loads

International Nuclear Information System (INIS)

Shi, Jing; Luo, Lai–Ma; Lin, Jin–shan; Zan, Xiang; Zhu, Xiao–yong; Xu, Qiu; Wu, Yu–Cheng

2016-01-01

Pure W and W-Lu alloys were prepared by mechanical alloying (MA) and spark plasma sintering (SPS) technology. The performance and relevant damage mechanism of W-(0%, 2%, 5%, 10%) Lu alloys under transient heat loads were investigated using a laser beam heat load test to simulate the transient events in future nuclear fusion reactors. Scanning electron microscopy was used to observe the morphologies of the damaged surfaces and energy dispersive X-ray spectroscopy was used to conduct composition analysis. Damages to the surface such as cracks, pits, melting layers, Lu-rich droplets, and thermal ablation were observed. A mass of dense fuzz-like nanoparticles formed on the outer region of the laser-exposed area. Recrystallization, grain growth, increased surface roughness, and material erosion were also observed. W-Lu samples with low Lu content demonstrated better thermal performance than pure W, and the degree of damage significantly deteriorated under repetitive transient heat loads.

Analysis of Linux kernel as a complex network

International Nuclear Information System (INIS)

Gao, Yichao; Zheng, Zheng; Qin, Fangyun

2014-01-01

Operating system (OS) acts as an intermediary between software and hardware in computer-based systems. In this paper, we analyze the core of the typical Linux OS, Linux kernel, as a complex network to investigate its underlying design principles. It is found that the Linux Kernel Network (LKN) is a directed network and its out-degree follows an exponential distribution while the in-degree follows a power-law distribution. The correlation between topology and functions is also explored, by which we find that LKN is a highly modularized network with 12 key communities. Moreover, we investigate the robustness of LKN under random failures and intentional attacks. The result shows that the failure of the large in-degree nodes providing basic services will do more damage on the whole system. Our work may shed some light on the design of complex software systems

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

Structural Damage Detection using Frequency Response Function Index and Surrogate Model Based on Optimized Extreme Learning Machine Algorithm

Directory of Open Access Journals (Sweden)

R. Ghiasi

2017-09-01

Full Text Available Utilizing surrogate models based on artificial intelligence methods for detecting structural damages has attracted the attention of many researchers in recent decades. In this study, a new kernel based on Littlewood-Paley Wavelet (LPW is proposed for Extreme Learning Machine (ELM algorithm to improve the accuracy of detecting multiple damages in structural systems.  ELM is used as metamodel (surrogate model of exact finite element analysis of structures in order to efficiently reduce the computational cost through updating process. In the proposed two-step method, first a damage index, based on Frequency Response Function (FRF of the structure, is used to identify the location of damages. In the second step, the severity of damages in identified elements is detected using ELM. In order to evaluate the efficacy of ELM, the results obtained from the proposed kernel were compared with other kernels proposed for ELM as well as Least Square Support Vector Machine algorithm. The solved numerical problems indicated that ELM algorithm accuracy in detecting structural damages is increased drastically in case of using LPW kernel.

Preparation and characterization of active carbon using palm kernel ...

African Journals Online (AJOL)

Activated carbons were prepared from Palm kernel shells. Carbonization temperature was 6000C, at a residence time of 5 min for each process. Chemical activation was done by heating a mixture of carbonized material and the activating agents at a temperature of 700C to form a paste, followed by subsequent cooling and ...

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.

Clinical utility of an automated instrument for gram staining single slides.

Science.gov (United States)

Baron, Ellen Jo; Mix, Samantha; Moradi, Wais

2010-06-01

Gram stains of 87 different clinical samples were prepared by the laboratory's conventional methods (automated or manual) and by a new single-slide-type automated staining instrument, GG&B AGS-1000. Gram stains from either heat- or methanol-fixed slides stained with the new instrument were easy to interpret, and results were essentially the same as those from the methanol-fixed slides prepared as a part of the routine workflow. This instrument is well suited to a rapid-response laboratory where Gram stain requests are commonly received on a stat basis.

Creep-fatigue life prediction for different heats of Type 304 stainless steel by linear-damage rule, strain-range partitioning method, and damage-rate approach

International Nuclear Information System (INIS)

Maiya, P.S.

1978-07-01

The creep-fatigue life results for five different heats of Type 304 stainless steel at 593 0 C (1100 0 F), generated under push-pull conditions in the axial strain-control mode, are presented. The life predictions for the various heats based on the linear-damage rule, strain-range partitioning method, and damage-rate approach are discussed. The appropriate material properties required for computation of fatigue life are also included

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

Science.gov (United States)

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

2015-03-01

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

Human recombinant factor VIIa may improve heat intolerance in mice by attenuating hypothalamic neuronal apoptosis and damage.

Science.gov (United States)

Hsu, Chuan-Chih; Chen, Sheng-Hsien; Lin, Cheng-Hsien; Yung, Ming-Chi

2014-10-01

Intolerance to heat exposure is believed to be associated with hypothalamo-pituitary-adrenocortical (HPA) axis impairment [reflected by decreases in blood concentrations of both adrenocorticotrophic-hormone (ACTH) and corticosterone]. The purpose of this study was to determine the effect of human recombinant factor VIIa (rfVIIa) on heat intolerance, HPA axis impairment, and hypothalamic inflammation, ischemic and oxidative damage, and apoptosis in mice under heat stress. Immediately after heat stress (41.2 °C for 1 h), mice were treated with vehicle (1 mL/kg of body weight) or rfVIIa (65-270 µg/kg of body weight) and then returned to room temperature (26 °C). Mice still alive on day 4 of heat exposure were considered survivors. Cellular ischemia markers (e.g., glutamate, lactate-to-pyruvate ratio), oxidative damage markers (e.g., nitric oxide metabolite, hydroxyl radials), and pro-inflammatory cytokines (e.g., interleukin-6, interleukin-1β, tumor necrosis factor-α) in hypothalamus were determined. In addition, blood concentrations of both ACTH and corticosterone were measured. Hypothalamic cell damage was assessed by determing the neuronal damage scores, whereas the hypothalamic cell apoptosis was determined by assessing the numbers of cells stained with terminal deoxynucleotidyl transferase-mediated αUTP nick-end labeling, caspase-3-positive cells, and platelet endothelial cell adhesion molecula-1-positive cells in hypothalamus. Compared with vehicle-treated heated mice, rfVIIa-treated heated mice had significantly higher fractional survival (8/10 vs 1/10), lesser thermoregulatory deficit (34.1 vs 24.8 °C), lesser extents of ischemic, oxidative, and inflammatory markers in hypothalamus, lesser neuronal damage scores and apoptosis in hypothalamus, and lesser HPA axis impairment. Human recombinant factor VIIa appears to exert a protective effect against heatstroke by attenuating hypothalamic cell apoptosis (due to ischemic, inflammatory, and oxidative damage

Flow cytometric evaluation of physico-chemical impact on Gram-positive and Gram-negative bacteria

Science.gov (United States)

Fröhling, Antje; Schlüter, Oliver

2015-01-01

Since heat sensitivity of fruits and vegetables limits the application of thermal inactivation processes, new emerging inactivation technologies have to be established to fulfill the requirements of food safety without affecting the produce quality. The efficiency of inactivation treatments has to be ensured and monitored. Monitoring of inactivation effects is commonly performed using traditional cultivation methods which have the disadvantage of the time span needed to obtain results. The aim of this study was to compare the inactivation effects of peracetic acid (PAA), ozonated water (O3), and cold atmospheric pressure plasma (CAPP) on Gram-positive and Gram-negative bacteria using flow cytometric methods. E. coli cells were completely depolarized after treatment (15 s) with 0.25% PAA at 10°C, and after treatment (10 s) with 3.8 mg l−1 O3 at 12°C. The membrane potential of CAPP treated cells remained almost constant at an operating power of 20 W over a time period of 3 min, and subsequently decreased within 30 s of further treatment. Complete membrane permeabilization was observed after 10 s O3 treatment, but treatment with PAA and CAPP did not completely permeabilize the cells within 2 and 4 min, respectively. Similar results were obtained for esterase activity. O3 inactivates cellular esterase but esterase activity was detected after 4 min CAPP treatment and 2 min PAA treatment. L. innocua cells and P. carotovorum cells were also permeabilized instantaneously by O3 treatment at concentrations of 3.8 ± 1 mg l−1. However, higher membrane permeabilization of L. innocua and P. carotovorum than of E. coli was observed at CAPP treatment of 20 W. The degree of bacterial damage due to the inactivation processes is highly dependent on treatment parameters as well as on treated bacteria. Important information regarding the inactivation mechanisms can be obtained by flow cytometric measurements and this enables the definition of critical process parameters. PMID

Flow cytometric evaluation of physico-chemical impact on Gram-positive and Gram-negative bacteria

Directory of Open Access Journals (Sweden)

Antje eFröhling

2015-09-01

Full Text Available Since heat sensitivity of fruits and vegetables limits the application of thermal inactivation processes, new emerging inactivation technologies have to be established to fulfil the requirements of food safety without affecting the produce quality. The efficiency of inactivation treatments has to be ensured and monitored. Monitoring of inactivation effects is commonly performed using traditional cultivation methods which have the disadvantage of the time span needed to obtain results.The aim of this study was to compare the inactivation effects of peracetic acid (PAA, ozonated water (O3 and cold atmospheric pressure plasma (CAPP on Gram-positive and Gram-negative bacteria using flow cytometric methods. E. coli cells were completely depolarized after treatment (15 s with 0.25 % PAA at 10 °C, and after treatment (10 s with 3.8 mg l-1 O3 at 12°C. The membrane potential of CAPP treated cells remained almost constant at an operating power of 20 W over a time period of 3 min, and subsequently decreased within 30 s of further treatment. Complete membrane permeabilization was observed after 10 s O3 treatment, but treatment with PAA and CAPP did not completely permeabilize the cells within 2 min and 4 min, respectively. Similar results were obtained for esterase activity. O3 inactivates cellular esterase but esterase activity was detected after 4 min CAPP treatment and 2 min PAA treatment. L. innocua cells and P. carotovorum cells were also permeabilized instantaneously by O3 treatment at concentrations of 3.8 ± 1 mg l-1. However, higher membrane permeabilization of L. innocua and P. carotovorum than of E. coli was observed at CAPP treatment of 20 W. The degree of bacterial damage due to the inactivation processes is highly dependent on treatment parameters as well as on treated bacteria. Important information regarding the inactivation mechanisms can be obtained by flow cytometric measurements and this enables the definition of critical process

Heat kernel estimates for pseudodifferential operators, fractional Laplacians and Dirichlet-to-Neumann operators

DEFF Research Database (Denmark)

Gimperlein, Heiko; Grubb, Gerd

2014-01-01

The purpose of this article is to establish upper and lower estimates for the integral kernel of the semigroup exp(−t P) associated to a classical, strongly elliptic pseudodifferential operator P of positive order on a closed manifold. The Poissonian bounds generalize those obtained for perturbat......The purpose of this article is to establish upper and lower estimates for the integral kernel of the semigroup exp(−t P) associated to a classical, strongly elliptic pseudodifferential operator P of positive order on a closed manifold. The Poissonian bounds generalize those obtained...... for perturbations of fractional powers of the Laplacian. In the selfadjoint case, extensions to t∈C+  are studied. In particular, our results apply to the Dirichlet-to-Neumann semigroup....

The development of the production process for the thorium/uranium dicarbide fuel kernels for the first charge of the Dragon Reactor

International Nuclear Information System (INIS)

Burnett, R.C.; Hankart, L.J.; Horsley, G.W.

1965-05-01

The development of methods of producing spheroidal sintered porous kernels of hyperstoichiometric thorium/uranium dicarbide solid solution from thorium/uranium monocarbide/carbon and thoria/urania/carbon powder mixes is described. The work has involved study of (i) Methods of preparing green kernels from UC/Th/C powder mixes using the rotary sieve technique. (ii) Methods of producing green kernels from UO2/Th02/C powder mixes using the planetary mill technique. (iii) The conversion by appropriate heat treatment of green kernels produced by both routes to sintered porous kernels of thorium/uranium carbide. (iv) The efficiency of the processes. (author)

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

Directory of Open Access Journals (Sweden)

Maryam Asnaashari

2015-01-01

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

Organo-Selenium Coatings Inhibit Gram-Negative and Gram-Positive Bacterial Attachment to Ophthalmic Scleral Buckle Material.

Science.gov (United States)

Tran, Phat; Arnett, Avery; Jarvis, Courtney; Mosley, Thomas; Tran, Khien; Hanes, Rob; Webster, Dan; Mitchell, Kelly; Dominguez, Leo; Hamood, Abdul; Reid, Ted W

2017-09-01

Biofilm formation is a problem for solid and sponge-type scleral buckles. This can lead to complications that require removal of the buckle, and result in vision loss due to related ocular morbidity, primarily infection, or recurrent retinal detachment. We investigate the ability of a covalent organo-selenium coating to inhibit biofilm formation on a scleral buckle. Sponge and solid Labtican brand scleral buckles were coated with organo-selenium coupled to a silyation reagent. Staphylococcus aureus biofilm formation was monitored by a standard colony-forming unit assay and the confocal laser scanning microscopy, while Pseudomonas aeruginosa biofilm formation was examined by scanning electron microscopy. Stability studies were done, by soaking in phosphate buffer saline (PBS) at room temperature for 2 months. Toxicity against human corneal epithelial cell was examined by growing the cells in the presence of organo-selenium-coated scleral buckles. The organo-selenium coating inhibited biofilm formation by gram-negative and gram-positive bacteria. The buckle coatings also were shown to be fully active after soaking in PBS for 2 months. The organo-selenium coatings had no effect on the viability of human corneal epithelial cells. Organo-selenium can be used to covalently coat a scleral buckle, which is stable and inhibits biofilm formation for gram-negative and gram-positive bacteria. The organo-selenium buckle coating was stable and nontoxic to cell culture. This technology provides a means to inhibit bacterial attachment to devices attached to the eye, without damage to ocular cells.

Heat damage-free laser-microjet cutting achieves highest die fracture strength

Science.gov (United States)

Perrottet, Delphine; Housh, Roy; Richerzhagen, Bernold; Manley, John

2005-04-01

Unlike conventional laser-based technologies, the water jet guided laser does not generate heat damage and contamination is also very low. The negligible heat-affected zone is one reason why die fracture strength is higher than with sawing. This paper first presents the water jet guided laser technology and then explains how it differs from conventional dry laser cutting. Finally, it presents the results obtained by three recent studies conducted to determine die fracture strength after Laser-Microjet cutting.

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

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

Science.gov (United States)

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

2017-12-15

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

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] ...

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 ...

Clinical Utility of an Automated Instrument for Gram Staining Single Slides ▿

Science.gov (United States)

Baron, Ellen Jo; Mix, Samantha; Moradi, Wais

2010-01-01

Gram stains of 87 different clinical samples were prepared by the laboratory's conventional methods (automated or manual) and by a new single-slide-type automated staining instrument, GG&B AGS-1000. Gram stains from either heat- or methanol-fixed slides stained with the new instrument were easy to interpret, and results were essentially the same as those from the methanol-fixed slides prepared as a part of the routine workflow. This instrument is well suited to a rapid-response laboratory where Gram stain requests are commonly received on a stat basis. PMID:20410348

Evaluation of critical temperatures for heat damage in northern highbush blueberry

Science.gov (United States)

Overhead sprinklers are often used to cool blueberry fields in the Pacific Northwest, but more information is needed to determine exactly when cooling is needed. The objective of this study was to identify the critical temperatures for heat damage in northern highbush blueberry (Vaccinium corymbosum...

DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages.

Science.gov (United States)

He, Lifang; Kong, Xiangnan; Yu, Philip S; Ragin, Ann B; Hao, Zhifeng; Yang, Xiaowei

With advances in data collection technologies, tensor data is assuming increasing prominence in many applications and the problem of supervised tensor learning has emerged as a topic of critical significance in the data mining and machine learning community. Conventional methods for supervised tensor learning mainly focus on learning kernels by flattening the tensor into vectors or matrices, however structural information within the tensors will be lost. In this paper, we introduce a new scheme to design structure-preserving kernels for supervised tensor learning. Specifically, we demonstrate how to leverage the naturally available structure within the tensorial representation to encode prior knowledge in the kernel. We proposed a tensor kernel that can preserve tensor structures based upon dual-tensorial mapping. The dual-tensorial mapping function can map each tensor instance in the input space to another tensor in the feature space while preserving the tensorial structure. Theoretically, our approach is an extension of the conventional kernels in the vector space to tensor space. We applied our novel kernel in conjunction with SVM to real-world tensor classification problems including brain fMRI classification for three different diseases ( i.e ., Alzheimer's disease, ADHD and brain damage by HIV). Extensive empirical studies demonstrate that our proposed approach can effectively boost tensor classification performances, particularly with small sample sizes.

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...

Probable causes of damage of heat-exchange tubes of low-pressure-exchanges of PND-3 type and repair methods

Science.gov (United States)

Trifonov, N. N.; Esin, S. B.; Nikolaenkova, E. K.; Sukhorukov, Yu. G.; Svyatkin, F. A.; Sintsova, T. G.; Modestov, V. S.

2017-08-01

The structures of low-pressure heaters (LPH), which are installed at nuclear power plants with the K-1000-60/1500 type turbine plants are considered. It was revealed that only the PND-3 type low-pressure heaters have the damages of the heat exchange tubes. For a short operation life, the number of the damaged heat-exchange tubes of PND-3 is approximately 50 pcs for Kalinin NPP and 100-150 pcs for Balakovo NPP. The low-pressure heaters were manufactured at AO Ural Plant of Chemical Machine-Building "Uralkhimmash," OAO Taganrog Boiler-Making Works "Krasny Kotelshchik," and Vitkovice Machinery Group, but the damage nature of the heat-exchange tubes is identical for all PND-3. The damages occur in the place of passage of the heat exchange tubes through the first, the second, and the third partitions over the lower tube plate (the first path of the turbine condensate). Hydraulic shocks can be one of the possible causes of the damage of the heat-exchange tubes of PND-3. The analysis of the average thermal and dynamic loads of the tube systems of PND-1-PND-4 revealed that PND-3 by the thermal power are loaded 1.4-1.6 times and by the dynamic effects are loaded 1.8-2.0 times more than the remaining LPHs. Another possible cause of damage can be the cascaded drain of the separate into PND-4 and then through the drainage heat exchange into PND-3. An additional factor can be the structure of the condensate drainage unit. The advanced system of the heating steam flow and pumping scheme of the separate drain using the existing drainage pumps of PND-3 for K-1000-60/1500 turbine plants for Balakovo and Kalinin NPPs were proposed. The considered decisions make it possible to reduce the flow rate of the heating steam condensate from PND-3 into PND-4 and the speed of the heating steam in the tube space of PND-3 and eliminate the occurrence of hydraulic shocks and damages of the heat exchanger tubes.

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

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...

Revisiting the Fundamental Analytical Solutions of Heat and Mass Transfer: The Kernel of Multirate and Multidimensional Diffusion

Science.gov (United States)

Zhou, Quanlin; Oldenburg, Curtis M.; Rutqvist, Jonny; Birkholzer, Jens T.

2017-11-01

There are two types of analytical solutions of temperature/concentration in and heat/mass transfer through boundaries of regularly shaped 1-D, 2-D, and 3-D blocks. These infinite-series solutions with either error functions or exponentials exhibit highly irregular but complementary convergence at different dimensionless times, td. In this paper, approximate solutions were developed by combining the error-function-series solutions for early times and the exponential-series solutions for late times and by using time partitioning at the switchover time, td0. The combined solutions contain either the leading term of both series for normal-accuracy approximations (with less than 0.003 relative error) or the first two terms for high-accuracy approximations (with less than 10-7 relative error) for 1-D isotropic (spheres, cylinders, slabs) and 2-D/3-D rectangular blocks (squares, cubes, rectangles, and rectangular parallelepipeds). This rapid and uniform convergence for rectangular blocks was achieved by employing the same time partitioning with individual dimensionless times for different directions and the product of their combined 1-D slab solutions. The switchover dimensionless time was determined to minimize the maximum approximation errors. Furthermore, the analytical solutions of first-order heat/mass flux for 2-D/3-D rectangular blocks were derived for normal-accuracy approximations. These flux equations contain the early-time solution with a three-term polynomial in √td and the late-time solution with the limited-term exponentials for rectangular blocks. The heat/mass flux equations and the combined temperature/concentration solutions form the ultimate kernel for fast simulations of multirate and multidimensional heat/mass transfer in porous/fractured media with millions of low-permeability blocks of varying shapes and sizes.

Multiphysics model of thermomechanical and helium-induced damage of tungsten during plasma heat transients

Energy Technology Data Exchange (ETDEWEB)

Crosby, Tamer, E-mail: tcrosby@ucla.edu; Ghoniem, Nasr M., E-mail: ghoniem@ucla.edu

2013-11-15

A combination of transient heating and bombardment by helium and hydrogen atoms has been experimentally proven to lead to severe surface and sub-surface damage. We developed a computational model to determine the relationship between the thermomechanical loading conditions and the onset of damage and failure of tungsten surfaces. The model is based on a thermoelasticity fracture damage approach that was developed using the phase field method. The model simulates the distribution of helium bubbles inside the grains and on grain boundaries using space-dependent rate theory. In addition, the model is coupled with a transient heat conduction analysis for temperature distributions inside the material. The results show the effects of helium bubbles on reducing tungsten surface energy. Further, a temperature gradient in the material equals to 10 K/μm, resulted in deep cracks propagating from the tungsten surface.

Predicting TDN losses from heat damaged hays and haylages with NIR

Science.gov (United States)

During the storage of hay or haylage, heating damage may occur and lead to losses of available protein and digestible nutrients. Recent research indicates that losses of TDN may be more significant economically than losses of available protein. Our objectives for this study were to establish a near-...

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

UO{sub 2} Kernel Preparation by M-EG Process and Its Irradiation Test

Energy Technology Data Exchange (ETDEWEB)

Jeong, K. C.; Eom, S. H.; Kim, Y. K.; Yeo, S. H.; Kim, Y. M.; Kim, B. G.; Cho, M. S. [KAERI, Daejeon (Korea, Republic of)

2016-05-15

Kernels of KAERI TRISO fuels are prepared in the following steps: (1) preparation of a raw material solution(UN solution) by UO{sub 3} (or U{sub 3}O{sub 8}) powder dissolution in the concentrated HNO{sub 3}; (2) broth preparation and physical property control by mixing UN, THFA, PVA, and H{sub 2}O; (3) preparation of spherical liquid gel droplets and dried-ADU gels in sequence through a reaction between uranyl ions and ammonia ions in a gelation column; (4) ageing, washing, and drying processes of ADU gel using AWD equipment; (5) UO{sub 3} calcination by thermal decomposition of driedADU gel in the air; (6) fabrication of UO{sub 2} kernel by reducing the UO{sub 3} and sintering in the H{sub 2}. In this study, improved KAERI processes for UO{sub 2} kernel preparation were presented. ADU gel washing procedure in AWD processes and the heating mode in sintering process were modified and the internal structures of UO{sub 2} kernels are presented as a result.

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...

7 CFR 51.2960 - Damage.

Science.gov (United States)

2010-01-01

... defect, or any combination of defects which materially detracts from the appearance or the edible or... considered as damaged; and, (g) Insects when an insect or insect fragment, web or frass is present inside the shell, or the kernel shows distinct evidence of insect feeding. ...

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...

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. ...

DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages

Science.gov (United States)

He, Lifang; Kong, Xiangnan; Yu, Philip S.; Ragin, Ann B.; Hao, Zhifeng; Yang, Xiaowei

2015-01-01

With advances in data collection technologies, tensor data is assuming increasing prominence in many applications and the problem of supervised tensor learning has emerged as a topic of critical significance in the data mining and machine learning community. Conventional methods for supervised tensor learning mainly focus on learning kernels by flattening the tensor into vectors or matrices, however structural information within the tensors will be lost. In this paper, we introduce a new scheme to design structure-preserving kernels for supervised tensor learning. Specifically, we demonstrate how to leverage the naturally available structure within the tensorial representation to encode prior knowledge in the kernel. We proposed a tensor kernel that can preserve tensor structures based upon dual-tensorial mapping. The dual-tensorial mapping function can map each tensor instance in the input space to another tensor in the feature space while preserving the tensorial structure. Theoretically, our approach is an extension of the conventional kernels in the vector space to tensor space. We applied our novel kernel in conjunction with SVM to real-world tensor classification problems including brain fMRI classification for three different diseases (i.e., Alzheimer's disease, ADHD and brain damage by HIV). Extensive empirical studies demonstrate that our proposed approach can effectively boost tensor classification performances, particularly with small sample sizes. PMID:25927014

Down-regulation of miR-181a can reduce heat stress damage in PBMCs of Holstein cows.

Science.gov (United States)

Chen, Kun-Lin; Fu, Yuan-Yuan; Shi, Min-Yan; Li, Hui-Xia

2016-09-01

Heat stress can weaken the immune system and even increase livestock's susceptibility to disease. MicroRNA (miR) is short non-coding RNA that functions in post-transcriptional regulation of gene expression and some phenotypes. Our recent study found that miR-181a is highly expressed in the serum of heat-stressed Holstein cows, but the potential function of miR-181a is still not clarified. In this study, peripheral blood mononuclear cells (PBMCs), isolated from Holstein cows' peripheral blood, were used to investigate the effects of miR-181a inhibitor on heat stress damage. Our results showed that significant apoptosis and oxidative damage were induced by heat stress in PBMCs. However, with apoptosis, the levels of reactive oxygen species (ROS) and content of malondialdehyde (MDA) were reduced, while the content of glutathione (GSH) and the activity of superoxide dismutase (SOD) were increased even under heat stress conditions after transfecting miR-181a inhibitors to PBMCs. Meanwhile, mRNA expression of bax and caspase-3 was significantly decreased, but mRNA expression of bcl-2 was increased in transfected PBMCs. In conclusion, our results demonstrated that down-regulation of miR-181a can reduce heat stress damage in PBMCs of Holstein cows.

Damage process of high purity tungsten coatings by hydrogen beam heat loads

International Nuclear Information System (INIS)

Tamura, S.; Tokunaga, K.; Yoshida, N.; Taniguchi, M.; Ezato, K.; Sato, K.; Suzuki, S.; Akiba, M.; Tsunekawa, Y.; Okumiya, M.

2005-01-01

To investigate the synergistic effects of heat load and hydrogen irradiation, cyclic heat load tests with a hydrogen beam and a comparable electron beam were performed for high purity CVD-tungsten coatings. Surface modification was examined as a function of the peak temperature by changing the heat flux. Scanning Electron Microscopy analysis showed that the surface damage caused by the hydrogen beam was more severe than that by the electron beam. In the hydrogen beam case, cracking at the surface occurred at all peak temperatures examined from 300 deg. C to 1600 deg. C. These results indicate that the injected hydrogen induces embrittlement for the CVD-tungsten coating

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`.

The effect of creep-fatigue damage relationships upon HTGR heat exchanger design

International Nuclear Information System (INIS)

Kozina, M.M.; King, J.H.; Basol, M.

1984-01-01

Materials for heat exchangers in the high temperature gas-cooled reactor (HTGR) are subjected to cyclic loading, extending the necessity to design against fatigue failure into the temperature region where creep processes become significant. Therefore, the fatigue life must be considered in terms of creep-fatigue interaction. In addition, since HTGR heat exchangers are subjected to holds at constant strain levels or constant stress levels in high-temperature environments, the cyclic life is substantially reduced. Of major concern in the design and analysis of HTGR heat exchangers is the accounting for the interaction of creep and fatigue. The accounting is done in conformance to the American Society of Mechanical Engineers Boiler and Pressure Vessel Code, Code Case N-47, which allows the use of the linear damage criterion for interaction of creep and fatigue. This method separates the damage incurred in the material into two parts: one due to fatigue and one due to creep. The summation of the creep-fatigue damage must be less than 1.0. Recent material test data have indicated that the assumption of creep and fatigue damage equals unity at failure may not always be valid for materials like Alloy 800H, which is used in the higher temperature sections of HTGR steam generators. Therefore, a more conservative creep-fatigue damage relationship was postulated for Alloy 800H. This more conservative bilinear damage relationship consists of a design locus drawn from D F =1.0, D C =0 to D F =0.1, D C =0.1 to D F =0, D C =1.0. D F is the fatigue damage and D C is the creep damage. A more conservative damage relationship for 2-1/4 Cr-1 Mo material consisted of including factors that degrade the fatigue curves. These revised relationships were used in a structural evaluation of the HTGR steam cycle/cogeneration (SC/C) steam generator design. The HTGR-SC/C steam generator, a once-through type, is comprised of an economizer-evaporator-superheater (ESS) helical bundle of 2-1/4 Cr-1

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...

Initiation and propagation of damage in actively cooled CFC armoured high heat flux components in fusion machines

International Nuclear Information System (INIS)

Chevet, G.; Schlosser, J.; Martin, E.; Herb, V.; Camus, G.; Escourbiac, F.

2009-01-01

Plasma facing components (PFCs) in magnetic confinement controlled fusion machines are armoured with carbon fibre composite (CFC) bonded to a copper alloy heat sink. The manufacturing process induces high level of residual stresses due to the thermal expansion mismatch between CFC and copper and PFCs have to withstand strong stress ranges during operation. To study the initiation and propagation of damage in the CFC part, the ONERA damage model is used to describe the behaviour of the N11 material. The finite element simulations show that the damage is located near the interface and develops during the manufacturing of the PFCs as a consequence of the high amplitude of shear stresses. Under high heat flux, stresses decrease and the damage does not evolve. Further studies will take into account the damageable behaviour of the composite/copper interface, which will lead to geometrical optimisations and better knowledge of the link between damage and conductivity.

Umbilical Cord Blood-Derived Stem Cells Improve Heat Tolerance and Hypothalamic Damage in Heat Stressed Mice

Directory of Open Access Journals (Sweden)

Ling-Shu Tseng

2014-01-01

Full Text Available Heatstroke is characterized by excessive hyperthermia associated with systemic inflammatory responses, which leads to multiple organ failure, in which brain disorders predominate. This definition can be almost fulfilled by a mouse model of heatstroke used in the present study. Unanesthetized mice were exposed to whole body heating (41.2°C for 1 hour and then returned to room temperature (26°C for recovery. Immediately after termination of whole body heating, heated mice displayed excessive hyperthermia (body core temperature ~42.5°C. Four hours after termination of heat stress, heated mice displayed (i systemic inflammation; (ii ischemic, hypoxic, and oxidative damage to the hypothalamus; (iii hypothalamo-pituitary-adrenocortical axis impairment (reflected by plasma levels of both adrenocorticotrophic-hormone and corticosterone; (iv decreased fractional survival; and (v thermoregulatory deficits (e.g., they became hypothermia when they were exposed to room temperature. These heatstroke reactions can be significantly attenuated by human umbilical cord blood-derived CD34+ cells therapy. Our data suggest that human umbilical cord blood-derived stem cells therapy may improve outcomes of heatstroke in mice by reducing systemic inflammation as well as hypothalamo-pituitary-adrenocortical axis impairment.

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...

Procalcitonin levels in gram-positive, gram-negative, and fungal bloodstream infections.

Science.gov (United States)

Leli, Christian; Ferranti, Marta; Moretti, Amedeo; Al Dhahab, Zainab Salim; Cenci, Elio; Mencacci, Antonella

2015-01-01

Procalcitonin (PCT) can discriminate bacterial from viral systemic infections and true bacteremia from contaminated blood cultures. The aim of this study was to evaluate PCT diagnostic accuracy in discriminating Gram-positive, Gram-negative, and fungal bloodstream infections. A total of 1,949 samples from patients with suspected bloodstream infections were included in the study. Median PCT value in Gram-negative (13.8 ng/mL, interquartile range (IQR) 3.4-44.1) bacteremias was significantly higher than in Gram-positive (2.1 ng/mL, IQR 0.6-7.6) or fungal (0.5 ng/mL, IQR 0.4-1) infections (P Gram-negatives from Gram-positives at the best cut-off value of 10.8 ng/mL and an AUC of 0.944 (95% CI 0.919-0.969, P Gram-negatives from fungi at the best cut-off of 1.6 ng/mL. Additional results showed a significant difference in median PCT values between Enterobacteriaceae and nonfermentative Gram-negative bacteria (17.1 ng/mL, IQR 5.9-48.5 versus 3.5 ng/mL, IQR 0.8-21.5; P Gram-negative from Gram-positive and fungal bloodstream infections. Nevertheless, its utility to predict different microorganisms needs to be assessed in further studies.

EFFECT OF SILICATE ON GRAM STAINING AND VIABILITY OF PNEUMOCOCCI AND OTHER BACTERIA

Science.gov (United States)

MacLeod, Colin M.; Roe, Amy S.

1956-01-01

Application of silicate solutions to living or heat-killed pneumococci and to certain "viridans" streptococci causes their conversion from a Gram-positive to a Gram-negative state. The original staining properties can be restored by suspending the silicate-treated bacteria in alkaline solutions of various salts but not by simple washing in water. Living pneumococci and the strains of streptococci whose staining properties are similarly affected are killed when suspended in silicate solutions. In other Gram-positive species silicate causes conversion to Gram negativity but restoration to positivity occurs upon washing in water. In a third group of Gram-positive organisms silicate has no effect on the Gram reaction. The viability of organisms in these two groups is unaffected by silicate under the conditions employed. No effect on staining or viability of Gram-negative bacteria has been observed. The effects of silicate on staining and viability are inhibited by nutrient broth or whole serum but not by purified serum albumin. Lecithin, choline, and other substituted ammonium compounds also inhibit the effects of silicate on pneumococci. PMID:13306854

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.

On the Operator ⨁Bk Related to Bessel Heat Equation

Directory of Open Access Journals (Sweden)

Wanchak Satsanit

2010-01-01

Full Text Available We study the equation (∂/∂tu(x,t=c2⊕Bku(x,t with the initial condition u(x,0=f(x for x∈Rn+. The operator ⊕Bk is the operator iterated k-times and is defined by ⊕Bk=((∑i=1pBxi4-(∑j=p+1p+qBxi4k, where p+q=n is the dimension of the Rn+, Bxi=∂2/∂xi2+(2vi/xi(∂/∂xi, 2vi=2αi+1, αi>-1/2, i=1,2,3,…,n, and k is a nonnegative integer, u(x,t is an unknown function for (x,t=(x1,x2,…,xn,t∈Rn+×(0,∞, f(x is a given generalized function, and c is a positive constant. We obtain the solution of such equation, which is related to the spectrum and the kernel, which is so called Bessel heat kernel. Moreover, such Bessel heat kernel has interesting properties and also related to the kernel of an extension of the heat equation.

Shape-dependent bactericidal activity of copper oxide nanoparticle mediated by DNA and membrane damage

International Nuclear Information System (INIS)

Laha, Dipranjan; Pramanik, Arindam; Laskar, Aparna; Jana, Madhurya; Pramanik, Panchanan; Karmakar, Parimal

2014-01-01

Highlights: • Spherical and sheet shaped copper oxide nanoparticles were synthesized. • Physical characterizations of these nanoparticles were done by TEM, DLS, XRD, FTIR. • They showed shape dependent antibacterial activity on different bacterial strain. • They induced both membrane damage and ROS mediated DNA damage in bacteria. - Abstract: In this work, we synthesized spherical and sheet shaped copper oxide nanoparticles and their physical characterizations were done by the X-ray diffraction, fourier transform infrared spectroscopy, transmission electron microscopy and dynamic light scattering. The antibacterial activity of these nanoparticles was determined on both gram positive and gram negative bacterial. Spherical shaped copper oxide nanoparticles showed more antibacterial property on gram positive bacteria where as sheet shaped copper oxide nanoparticles are more active on gram negative bacteria. We also demonstrated that copper oxide nanoparticles produced reactive oxygen species in both gram negative and gram positive bacteria. Furthermore, they induced membrane damage as determined by atomic force microscopy and scanning electron microscopy. Thus production of and membrane damage are major mechanisms of the bactericidal activity of these copper oxide nanoparticles. Finally it was concluded that antibacterial activity of nanoparticles depend on physicochemical properties of copper oxide nanoparticles and bacterial strain

Shape-dependent bactericidal activity of copper oxide nanoparticle mediated by DNA and membrane damage

Energy Technology Data Exchange (ETDEWEB)

Laha, Dipranjan; Pramanik, Arindam [Department of Life Science and Biotechnology, Jadavpur University, 188, Raja S C Mallick Road, Kolkata 700032 (India); Laskar, Aparna [CSIR-Indian Institute of Chemical Biology, Kolkata 700032 (India); Jana, Madhurya [Department of Life Science and Biotechnology, Jadavpur University, 188, Raja S C Mallick Road, Kolkata 700032 (India); Pramanik, Panchanan [Department of Chemistry, Indian Institute of Technology, Kharagpur 721302 (India); Karmakar, Parimal, E-mail: pkarmakar_28@yahoo.co.in [Department of Life Science and Biotechnology, Jadavpur University, 188, Raja S C Mallick Road, Kolkata 700032 (India)

2014-11-15

Highlights: • Spherical and sheet shaped copper oxide nanoparticles were synthesized. • Physical characterizations of these nanoparticles were done by TEM, DLS, XRD, FTIR. • They showed shape dependent antibacterial activity on different bacterial strain. • They induced both membrane damage and ROS mediated DNA damage in bacteria. - Abstract: In this work, we synthesized spherical and sheet shaped copper oxide nanoparticles and their physical characterizations were done by the X-ray diffraction, fourier transform infrared spectroscopy, transmission electron microscopy and dynamic light scattering. The antibacterial activity of these nanoparticles was determined on both gram positive and gram negative bacterial. Spherical shaped copper oxide nanoparticles showed more antibacterial property on gram positive bacteria where as sheet shaped copper oxide nanoparticles are more active on gram negative bacteria. We also demonstrated that copper oxide nanoparticles produced reactive oxygen species in both gram negative and gram positive bacteria. Furthermore, they induced membrane damage as determined by atomic force microscopy and scanning electron microscopy. Thus production of and membrane damage are major mechanisms of the bactericidal activity of these copper oxide nanoparticles. Finally it was concluded that antibacterial activity of nanoparticles depend on physicochemical properties of copper oxide nanoparticles and bacterial strain.

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....

Design analysis and performance test of reduction furnace of kernel U3O8

International Nuclear Information System (INIS)

Moch Setyadji; Triyono; Dedy Husnurrofiq

2015-01-01

High Temperature Reactor (HTR) with coated particle fuel is a future reactor (generation IV) because it is not only having high efficiency but also release no fission product into the environment. It has a passive safety principles and negative reactivity. Coated particle fuel for high temperature reactor is made through Sol-Gel process followed by aging, drying, calcination, reduction, sintering and coating process. Research of design analysis of heating system, electrical system, and insulation systems continued construction and performance test of reduction furnace has been done. The aim of this research was to obtain a reduction furnace with adequate performance that can be used to reduce the kernel of U 3 O 8 into UO 2 . The results of the performance test of the reduction furnace showed that heating zones 1-3 can generate heat to a temperature of 900°C with operation time 144 minutes and heat rate of 5.979°C/min. The coefficient of convection in the outer wall of fireproof stone having 7 cm thick was around 30 W/m 2 C. UO 2 kernel resulting from the reduction process has a diameter of between 0.850 to 0.992 mm and qualify as feed sintering process. (author)

Bactericidal catechins damage the lipid bilayer.

Science.gov (United States)

Ikigai, H; Nakae, T; Hara, Y; Shimamura, T

1993-04-08

The mode of antibacterial action of, the green tea (Camellia sinensis) extracts, (-)-epigallocatechin gallate (EGCg) and (-)-epicatechin (EC) was investigated. Strong bactericidal EGCg caused leakage of 5,6-carboxyfluorescein from phosphatidylcholine liposomes (PC), but EC with very weak bactericidal activity caused little damage to the membrane. Phosphatidylserine and dicetyl phosphate partially protected the membrane from EGCg-mediated damage when reconstituted into the liposome membrane with PC. EGCg, but not EC, caused strong aggregation and NPN-fluorescence quenching of PC-liposomes and these actions were markedly lowered in the presence of negatively charged lipids. These results show that bactericidal catechins primarily act on and damage bacterial membranes. The observation that Gram-negative bacteria are more resistant to bactericidal catechins than Gram-positive bacteria can be explained to some extent by the presence of negatively charged lipopolysaccharide.

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...

Visualization of Heat Transfer and Core Damage With RGUI 1.5

International Nuclear Information System (INIS)

Mesina, George L.

2002-01-01

Graphical User Interfaces (GUI) have become an integral and essential part of computer software. In the ever-changing world of computing, they provide the user with a valuable means to learn, understand, and use the application software while also helping applications adapt to and span different computing paradigms, such as different operating systems. For these reasons, GUI development for nuclear plant analysis programs has been ongoing for a decade and a half and much progress has been made. With the development of codes such as RELAP5-3D [1] and SCDAP/RELAP5 that have multi-dimensional modeling capability, it has become necessary to represent three-dimensional, calculated data. The RELAP5-3D Graphical User Interface (RGUI) [4] was designed specifically for this purpose. It reduces the difficulty of analyzing complex three-dimensional models and enhances the analysts' ability to recognize plant behavior visually. Previous versions of RGUI [5] focused on visualizing reactor coolant behavior during a simulated transient or accident. Recent work has extended RGUI to display two other phenomena, heat transfer and core damage. Heat transfer is depicted through the visualization of RELAP5-3D heat structures. Core damage is visualized by displaying fuel rods and other core structures in a reactor vessel screen. Conditions within the core are displayed via numerical results and color maps. These new features of RGUI 1.5 are described and illustrated. (authors)

Procalcitonin Levels in Gram-Positive, Gram-Negative, and Fungal Bloodstream Infections

Directory of Open Access Journals (Sweden)

Christian Leli

2015-01-01

Full Text Available Procalcitonin (PCT can discriminate bacterial from viral systemic infections and true bacteremia from contaminated blood cultures. The aim of this study was to evaluate PCT diagnostic accuracy in discriminating Gram-positive, Gram-negative, and fungal bloodstream infections. A total of 1,949 samples from patients with suspected bloodstream infections were included in the study. Median PCT value in Gram-negative (13.8 ng/mL, interquartile range (IQR 3.4–44.1 bacteremias was significantly higher than in Gram-positive (2.1 ng/mL, IQR 0.6–7.6 or fungal (0.5 ng/mL, IQR 0.4–1 infections (P<0.0001. Receiver operating characteristic analysis showed an area under the curve (AUC for PCT of 0.765 (95% CI 0.725–0.805, P<0.0001 in discriminating Gram-negatives from Gram-positives at the best cut-off value of 10.8 ng/mL and an AUC of 0.944 (95% CI 0.919–0.969, P<0.0001 in discriminating Gram-negatives from fungi at the best cut-off of 1.6 ng/mL. Additional results showed a significant difference in median PCT values between Enterobacteriaceae and nonfermentative Gram-negative bacteria (17.1 ng/mL, IQR 5.9–48.5 versus 3.5 ng/mL, IQR 0.8–21.5; P<0.0001. This study suggests that PCT may be of value to distinguish Gram-negative from Gram-positive and fungal bloodstream infections. Nevertheless, its utility to predict different microorganisms needs to be assessed in further studies.

Analysis of genetic diversity among the maize inbred lines (Zea mays L. under heat stress condition

Directory of Open Access Journals (Sweden)

Manoj Kandel

2017-12-01

Full Text Available High temperature adversely affects the plant physiological processes: limits plant growth and reduction in grain yield. Heat stress is often encountered to spring sowing of maize in spring season. Twenty maize inbred lines were studied for days to 50 % anthesis and silking, anthesis–silking interval, leaf firing, tassel blast, SPAD reading and leaf senescence, plant and ear height, leaf area index, ear per plant, cob length and diameter, number of kernel/ear, number of kernel row/ear, number of kernel row, silk receptivity, shelling percentage, thousand kernel weight and grain yield in alpha lattice design at National Maize Research Program at Rampur, Chitwan,Nepal with the objective to identify superior heat stress tolerant lines. Analysis of variance showed significant difference for all the traits. Result of multivariable analysis revealed that twenty inbred lines formed four clusters. The resistance inbred lines and susceptible inbred lines formed different clusters. The members of cluster 4 were found to be tolerant to heat stress due to they had lowest value of tassel blast, leaf firing, and leaf area index with highest value of cob diameter and length, ear per plant, number of kernel row/ear, number of kernel/ear, number of kernel row, shelling percentage, silk receptivity and grain yield whereas as members of cluster 1were found most susceptible due to they had longer anthesis silking interval, with maximum tassel blast and leaf firing along with no grain yield under heat stress condition. From this study inbred lines RL-140, RML-76, RML-91 and RML-40 were found most tolerant to heat stress. These inbred lines belonging to superior cluster could be considered very useful in developing heat tolerant variety and other breeding activities.

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

A Experimental Study of the Growth of Laser Spark and Electric Spark Ignited Flame Kernels.

Science.gov (United States)

Ho, Chi Ming

1995-01-01

Better ignition sources are constantly in demand for enhancing the spark ignition in practical applications such as automotive and liquid rocket engines. In response to this practical challenge, the present experimental study was conducted with the major objective to obtain a better understanding on how spark formation and hence spark characteristics affect the flame kernel growth. Two laser sparks and one electric spark were studied in air, propane-air, propane -air-nitrogen, methane-air, and methane-oxygen mixtures that were initially at ambient pressure and temperature. The growth of the kernels was monitored by imaging the kernels with shadowgraph systems, and by imaging the planar laser -induced fluorescence of the hydroxyl radicals inside the kernels. Characteristic dimensions and kernel structures were obtained from these images. Since different energy transfer mechanisms are involved in the formation of a laser spark as compared to that of an electric spark; a laser spark is insensitive to changes in mixture ratio and mixture type, while an electric spark is sensitive to changes in both. The detailed structures of the kernels in air and propane-air mixtures primarily depend on the spark characteristics. But the combustion heat released rapidly in methane-oxygen mixtures significantly modifies the kernel structure. Uneven spark energy distribution causes remarkably asymmetric kernel structure. The breakdown energy of a spark creates a blast wave that shows good agreement with the numerical point blast solution, and a succeeding complex spark-induced flow that agrees reasonably well with a simple puff model. The transient growth rates of the propane-air, propane-air -nitrogen, and methane-air flame kernels can be interpreted in terms of spark effects, flame stretch, and preferential diffusion. For a given mixture, a spark with higher breakdown energy produces a greater and longer-lasting enhancing effect on the kernel growth rate. By comparing the growth

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...

Non-separable pairing interaction kernels applied to superconducting cuprates

International Nuclear Information System (INIS)

Haley, Stephen B.; Fink, Herman J.

2014-01-01

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

Gram-negative, but not Gram-positive, bacteria elicit strong PGE2 production in human monocytes.

Science.gov (United States)

Hessle, Christina C; Andersson, Bengt; Wold, Agnes E

2003-12-01

Gram-positive and Gram-negative bacteria induce different cytokine patterns in human mononuclear cells. We have seen that Gram-positives preferentially induce IL-12 and TNF-alpha, whereas Gram-negatives induce more IL-10, IL-6, and IL-8. In this study, we compared the capacity of these two groups of bacteria to induce PGE2. Monocytes stimulated with Gram-negative bacterial species induced much more PGE2 than did Gram-positive bacteria (5600 +/- 330 vs. 1700 +/- 670 pg/mL, p Gram-positive and Gram-negative bacteria. We suggest that Gram-positive and Gram-negative bacteria may stimulate different innate effector functions; Gram-positive bacteria promoting cell-mediated effector functions whereas Gram-negative bacteria inducing mediators inhibiting the same.

Testing Infrastructure for Operating System Kernel Development

DEFF Research Database (Denmark)

Walter, Maxwell; Karlsson, Sven

2014-01-01

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

7 CFR 51.1403 - Kernel color classification.

Science.gov (United States)

2010-01-01

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

Analysis of Advanced Fuel Kernel Technology

International Nuclear Information System (INIS)

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

2010-03-01

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

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.

Extremely low-frequency magnetic fields can impair spermatogenesis recovery after reversible testicular damage induced by heat.

Science.gov (United States)

Tenorio, Bruno Mendes; Ferreira Filho, Moisés Bonifacio Alves; Jimenez, George Chaves; de Morais, Rosana Nogueira; Peixoto, Christina Alves; Nogueira, Romildo de Albuquerque; da Silva Junior, Valdemiro Amaro

2014-06-01

Male infertility is often related to reproductive age couples experiencing fertility-related issues. Men may have fertility problems associated with reversible testicular damage. Considering that men have been increasingly exposed to extremely low-frequency magnetic fields generated by the production, distribution and use of electricity, this study analyzed whether 60 Hz and 1 mT magnetic field exposure may impair spermatogenesis recovery after reversible testicular damage induced by heat shock using rats as an experimental model. Adult male rats were subjected to a single testicular heat shock (HS, 43 °C for 12 min) and then exposed to the magnetic field for 15, 30 and 60 d after HS. Magnetic field exposure during the spermatogenesis recovery induced changes in testis components volume, cell ultrastructure and histomorphometrical parameters. Control animals had a reestablished and active spermatogenesis at 60 d after heat shock, while animals exposed to magnetic field still showed extensive testicular degeneration. Magnetic field exposure did not change the plasma testosterone. In conclusion, extremely low-frequency magnetic field may be harmful to fertility recovery in males affected by reversible testicular damage.

Damage to photosystem II due to heat stress without light-driven electron flow: involvement of enhanced introduction of reducing power into thylakoid membranes.

Science.gov (United States)

Marutani, Yoko; Yamauchi, Yasuo; Kimura, Yukihiro; Mizutani, Masaharu; Sugimoto, Yukihiro

2012-08-01

Under a moderately heat-stressed condition, the photosystems of higher plants are damaged in the dark more easily than they are in the presence of light. To obtain a better understanding of this heat-derived damage mechanism that occurs in the dark, we focused on the involvement of the light-independent electron flow that occurs at 40 °C during the damage. In various plant species, the maximal photochemical quantum yield of photosystem (PS) II (Fv/Fm) decreased as a result of heat treatment in the dark. In the case of wheat, the most sensitive plant species tested, both Fv/Fm and oxygen evolution rapidly decreased by heat treatment at 40 °C for 30 min in the dark. In the damage, specific degradation of D1 protein was involved, as shown by immunochemical analysis of major proteins in the photosystem. Because light canceled the damage to PSII, the light-driven electron flow may play a protective role against PSII damage without light. Light-independent incorporation of reducing power from stroma was enhanced at 40 °C but not below 35 °C. Arabidopsis mutants that have a deficit of enzymes which mediate the incorporation of stromal reducing power into thylakoid membranes were tolerant against heat treatment at 40 °C in the dark, suggesting that the reduction of the plastoquinone pool may be involved in the damage. In conclusion, the enhanced introduction of reducing power from stroma into thylakoid membranes that occurs around 40 °C causes over-reduction of plastoquinone, resulting in the damage to D1 protein under heat stress without linear electron flow.

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

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

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

Science.gov (United States)

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

2018-04-01

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

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 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

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

Methods for Confirming the Gram Reaction of Gram-variable Bacillus Species Isolated from Tobacco

Directory of Open Access Journals (Sweden)

Morin A

2014-12-01

Full Text Available Bacillus is a predominant genus of bacteria isolated from tobacco. The Gram stain is the most commonly used and most important of all diagnostic staining techniques in microbiology. In order to help confirm the Gram positivity of Bacillus isolates from tobacco, three methods using the chemical differences of the cell wall and membrane of Gram-positive and Gram-negative bacteria were investigated: the KOH (potassium hydroxide, the LANA (L-alanine-4-nitroanilide, and the vancomycin susceptibility tests. When colonies of Gram-negative bacteria are treated with 3% KOH solution, a slimy suspension is produced, probably due to destruction of the cell wall and liberation of deoxyribonucleic acid (DNA. Gram-positive cell walls resist KOH treatment. The LANA test reveals the presence of a cell wall aminopeptidase that hydrolyzes the L-alanine-4-nitroanilide in Gram-negative bacteria. This enzyme is absent in Gram-positive bacteria. Vancomycin is a glycopeptide antibiotic inhibiting the cell wall peptido-glycan synthesis of Gram-positive microorganisms. Absence of lysis with KOH, absence of hydrolysis of LANA, and susceptibility to vancomycin were used with the Gram reaction to confirm the Gram positivity of various Bacillus species isolated from tobacco. B. laevolacticus excepted, all Bacillus species tested showed negative reactions to KOH and LANA tests, and all species were susceptible to vancomycin (5 and 30 µg.

Markers of muscle damage and performance recovery after exercise in the heat.

Science.gov (United States)

Nybo, Lars; Girard, Olivier; Mohr, Magni; Knez, Wade; Voss, Sven; Racinais, Sebastien

2013-05-01

This study aimed to determine whether competitive intermittent exercise in the heat affects recovery, aggravates markers of muscle fiber damage, and delays the recovery of performance and muscle glycogen stores. Plasma creatine kinase, serum myoglobin, muscle glycogen, and performance parameters (sprint, endurance, and neuromuscular testing) were evaluated in 17 semiprofessional soccer players before, immediately after, and during 48 h of recovery from a match played in 43°C (HOT) and compared with a control match (21°C with similar turf and setup). Muscle temperature was ∼1°C higher (P recovery. Creatine kinase was significantly elevated both immediately and 24 h after the matches, but the response after HOT was reduced compared with control. Muscle glycogen responses were similar across trials and remained depressed for more than 48 h after both matches. Sprint performance and voluntary muscle activation were impaired to a similar extent after the matches (sprint by ∼2% and voluntary activation by ∼1.5%; P heat stress does not aggravate the recovery response from competitive intermittent exercise associated with elevated muscle temperatures and markers of muscle damage, delayed resynthesis of muscle glycogen, and impaired postmatch performance.

GRIM : Leveraging GPUs for Kernel integrity monitoring

NARCIS (Netherlands)

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

2016-01-01

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

7 CFR 51.2296 - Three-fourths half kernel.

Science.gov (United States)

2010-01-01

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

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

Science.gov (United States)

Cid, Jaime A; von Davier, Alina A

2015-05-01

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

Adaptive Kernel in Meshsize Boosting Algorithm in KDE ...

African Journals Online (AJOL)

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

A kernel version of multivariate alteration detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

2013-01-01

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

Implementing Kernel Methods Incrementally by Incremental Nonlinear Projection Trick.

Science.gov (United States)

Kwak, Nojun

2016-05-20

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

The Causes of Post-Operative Meningitis: The Comparison Of Gram-Negative and Gram-Positive Pathogens.

Science.gov (United States)

Kurtaran, Behice; Kuscu, Ferit; Ulu, Aslihan; Inal, Ayse Seza; Komur, Suheyla; Kibar, Filiz; Cetinalp, Nuri Eralp; Ozsoy, Kerem Mazhar; Arslan, Yusuf Kemal; Aksu, Hasan Salih; Tasova, Yesim

2017-06-20

In this study, we aim to determine the microbiological etiology in critically ill neurosurgical patients with nosocomial meningitis (NM) and show the impact of Gram-negative rods and differences of patient's characteristics, clinical and prognostic measures between Gram-negative and Gram-positive meningitis. In this prospective, one center study we reviewed all adult patients hospitalized during a 12-year period and identified pathogens isolated from post-neurosurgical cases of NM. Demographic, clinical, and treatment characteristics were noted from the medical records. Of the 134 bacterial NM patients, 78 were male and 56 were female, with a mean age of 46±15.9 and median age of 50 (18-80) years. 141 strains isolated; 82 (58.2%) were Gram negative, 59 (41.8%) were Gram positive. Most common isolated microorganism was Acinetobacter baumannii (%34.8). In comparison of mortality data shows that the patients who have meningitis with Gram-negative pathogens have higher mortality than with Gram positives (p=0.034). The duration between surgery and meningitis was shorter in Gram negative meningitis cases compared to others (p=0.045) but the duration between the diagnosis and death was shorter in Gram-positive meningitis cases compared to Gram negatives (p= 0.017). CSF protein and lactate level were higher and glucose level was lower in cases of NM with Gram negatives (p value were respectively, 0.022, 0.039 and 0.049). As conclusions; in NM, Gram-negative pathogens were seen more frequently; A.baumanni was the predominant pathogen; and NM caused by Gram negatives had worse clinical and laboratory characteristic and prognostic outcome than Gram positives.

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.

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.)

Assessment of gamma irradiation heating and damage in miniature neutron source reactor vessel using computational methods and SRIM - TRIM code

International Nuclear Information System (INIS)

Appiah-Ofori, F. F.

2014-07-01

The Effects of Gamma Radiation Heating and Irradiation Damage in the reactor vessel of Ghana Research Reactor 1, Miniature Neutron Source Reactor were assessed using Implicit Control Volume Finite Difference Numerical Computation and validated by SRIM - TRIM Code. It was assumed that 5.0 MeV of gamma rays from the reactor core generate heat which interact and absorbed completely by the interior surface of the MNSR vessel which affects it performance due to the induced displacement damage. This displacement damage is as result of lattice defects being created which impair the vessel through formation of point defect clusters such as vacancies and interstitiaIs which can result in dislocation loops and networks, voids and bubbles and causing changes in the layers in the thickness of the vessel. The microscopic defects produced in the vessel due to γ - radiation damage are referred to as radiation damage while the defects thus produced modify the macroscopic properties of the vessel which are also known as the radiation effects. These radiation damage effects are of major concern for materials used in nuclear energy production. In this study, the overall objective was to assess the effects of gamma radiation heating and damage in GHARR - I MNSR vessel by a well-developed Mathematical model, Analytical and Numerical solutions, simulating the radiation damage in the vessel. SRIM - TRIM Code was used as a computational tool to determine the displacement per atom (dpa) associated with radiation damage while implicit Control Volume Finite Difference Method was used to determine the temperature profile within the vessel due to γ - radiation heating respectively. The methodology adopted in assessing γ - radiation heating in the vessel involved development of the One-Dimensional Steady State Fourier Heat Conduction Equation with Volumetric Heat Generation both analytical and implicit Control Volume Finite Difference Method approach to determine the maximum temperature and

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...

Heat and power demands in babassu palm oil extraction industry in Brazil

International Nuclear Information System (INIS)

Teixeira, Marcos A.

2005-01-01

The objective of this paper is to analyze the energy use profile of the babassu (Orbignya ssp-Palmae) oil extraction industry in Brazil in order to establish the basis for a cogeneration study of this important part of the Brazilian Northeast region economy, which is still ignored by energetic biomass studies. The work used information from new equipment suppliers that was analyzed against field information from operating units. The data was used to establish a basis for the thermal and mechanical energy consumption for the two main basic unit profiles for the sector: a simple one with just oil extraction and the other, more vertically integrated with other secondary by-products. For the energetic demand taken from the only oil extraction unit profile study, the minimum pressure for the steam process was estimated at 1.4MPa, electric demand at 5.79kW/ton of processed kernel and heat consumption at 2071MJ/ton of processed kernel (829kg steam/ton of processed kernel). For the vertically integrated unit profile, the following values were found: minimum pressure for the steam process 1.4MPa, electric demand 6.22kW/ton of processed kernel and heat consumption 21,503MJ/ton of processed kernel (7600kg steam/ton of processed kernel)

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.

Characterization of power induced heating and damage in fiber optic probes for near-field scanning optical microscopy

Science.gov (United States)

Dickenson, Nicholas E.; Erickson, Elizabeth S.; Mooren, Olivia L.; Dunn, Robert C.

2007-05-01

Tip-induced sample heating in near-field scanning optical microscopy (NSOM) is studied for fiber optic probes fabricated using the chemical etching technique. To characterize sample heating from etched NSOM probes, the spectra of a thermochromic polymer sample are measured as a function of probe output power, as was previously reported for pulled NSOM probes. The results reveal that sample heating increases rapidly to ˜55-60°C as output powers reach ˜50nW. At higher output powers, the sample heating remains approximately constant up to the maximum power studied of ˜450nW. The sample heating profiles measured for etched NSOM probes are consistent with those previously measured for NSOM probes fabricated using the pulling method. At high powers, both pulled and etched NSOM probes fail as the aluminum coating is damaged. For probes fabricated in our laboratory we find failure occurring at input powers of 3.4±1.7 and 20.7±6.9mW for pulled and etched probes, respectively. The larger half-cone angle for etched probes (˜15° for etched and ˜6° for pulled probes) enables more light delivery and also apparently leads to a different failure mechanism. For pulled NSOM probes, high resolution images of NSOM probes as power is increased reveal the development of stress fractures in the coating at a taper diameter of ˜6μm. These stress fractures, arising from the differential heating expansion of the dielectric and the metal coating, eventually lead to coating removal and probe failure. For etched tips, the absence of clear stress fractures and the pooled morphology of the damaged aluminum coating following failure suggest that thermal damage may cause coating failure, although other mechanisms cannot be ruled out.

The influence of grinding oil viscosity on grinding heat and burn damage in creep-feed grinding{copyright}

Energy Technology Data Exchange (ETDEWEB)

Zhen-Change Liu [Shandong Univ. of Technology, Jinan (China); Abe, Satoshi; Noda, Masahiro [Yushiro Chemical Industry Co. Ltd., Kanagawa (Japan)

1995-08-01

Grinding oils are widely used in precision grinding, such as tool grinding, thread grinding and gear grinding, during which processes grinding burn is the most prevalent damage affecting the integrity of ground surface. This paper discusses the influence of oil viscosity on grinding heat and burn damage in creep-feed-grinding. Experimental results indicated that, under lighter grinding conditions, the effects of oil viscosity was not observed, but under heavy grinding conditions grinding burn occurred when using low viscosity oil. When the viscosity of the oil was increased, grinding heat and burn damage tended to be reduced. As the viscosity was increased to a certain level, grinding burn reduction, by further increasing the viscosity, became less while other problems such as much higher oil pump noise and reduced oil flow occurred. It is clear that a viscosity limit exists for given grinding conditions. 5 refs., 4 figs., 3 tabs.

Generation and development of damage in double forged tungsten in different combined regimes of irradiation with extreme heat loads

Science.gov (United States)

Paju, Jana; Väli, Berit; Laas, Tõnu; Shirokova, Veroonika; Laas, Katrin; Paduch, Marian; Gribkov, Vladimir A.; Demina, Elena V.; Prusakova, Marina D.; Pimenov, Valeri N.; Makhlaj, Vadym A.; Antonov, Maksim

2017-11-01

Armour materials in fusion devices, especially in the region of divertor, are exposed to a continuous heat and particle load. In addition, several off-normal events can reach the material during a work session. Calculations show that the effects of plasma and heat during such events can lead to cracking, erosion and detachment of the armour material. On the other hand, mutual and combined influences of different kinds of heat and particle loads can lead to the amplification of defects or vice versa, to the mitigation of damages. Therefore, the purpose of the study is to investigate the plasma induced damages on samples of double forged tungsten, which is considered a potential candidate for armour material of future tokamak's divertor. The combined effect of different kinds of plasma induced damages was investigated and analysed in this research. The study was conducted by irradiating the samples in various irradiation regimes twice, to observe the accumulation of the damages. Afterwards the analysis of micro-topography, scanning electron microscopy images and electrical conductivity measurements was used. Results indicate that double-forging improved the tungsten's durability to irradiation. Nevertheless, powerful pulses lead to significant damage of the sample, which will lead to further deterioration in the bulk. Although the average micro-roughness on the sample's surface does not change, the overall height/depth ratios can change.

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.

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

Science.gov (United States)

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

2017-01-01

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

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.

An optimized staining technique for the detection of Gram positive and Gram negative bacteria within tissue.

Science.gov (United States)

Becerra, Sandra C; Roy, Daniel C; Sanchez, Carlos J; Christy, Robert J; Burmeister, David M

2016-04-12

Bacterial infections are a common clinical problem in both acute and chronic wounds. With growing concerns over antibiotic resistance, treatment of bacterial infections should only occur after positive diagnosis. Currently, diagnosis is delayed due to lengthy culturing methods which may also fail to identify the presence of bacteria. While newer costly bacterial identification methods are being explored, a simple and inexpensive diagnostic tool would aid in immediate and accurate treatments for bacterial infections. Histologically, hematoxylin and eosin (H&E) and Gram stains have been employed, but are far from optimal when analyzing tissue samples due to non-specific staining. The goal of the current study was to develop a modification of the Gram stain that enhances the contrast between bacteria and host tissue. A modified Gram stain was developed and tested as an alternative to Gram stain that improves the contrast between Gram positive bacteria, Gram negative bacteria and host tissue. Initially, clinically relevant strains of Pseudomonas aeruginosa and Staphylococcus aureus were visualized in vitro and in biopsies of infected, porcine burns using routine Gram stain, and immunohistochemistry techniques involving bacterial strain-specific fluorescent antibodies as validation tools. H&E and Gram stain of serial biopsy sections were then compared to a modification of the Gram stain incorporating a counterstain that highlights collagen found in tissue. The modified Gram stain clearly identified both Gram positive and Gram negative bacteria, and when compared to H&E or Gram stain alone provided excellent contrast between bacteria and non-viable burn eschar. Moreover, when applied to surgical biopsies from patients that underwent burn debridement this technique was able to clearly detect bacterial morphology within host tissue. We describe a modification of the Gram stain that provides improved contrast of Gram positive and Gram negative microorganisms within host

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

Deep-Burn MHR Neutronic Analysis with a SiC-Gettered TRU Kernel

International Nuclear Information System (INIS)

Jo, Chang Keun; Noh, Jae Man; Kim, Yong Hee; Venneric, F.

2010-01-01

This paper is focused on the nuclear core design of a DB-MHR (Deep Burn-Modular Helium Reactor) core loaded with a SiC-gettered TRU fuel. The SiC oxygen getter is added to reduce the CO pressure in the buffer zone of TRISO. In the paper, the cycle length, reactivity swing, discharged burnup, and the burning rate of plutonium were calculated for the DB-MHR. Also, impacts of uranium addition to the TRU kernel were investigated. Recently, the decay heat of TRU fueled DB core was found to be highly dependent on the TRU loading: the higher the loading, the higher the decay heat. The high decay heat of TRU fuel may lead to unacceptably high peak fuel temperature during an LPCC (Low Pressure Conduction Cooling) accident. Thus, we tried to minimize the decay heat of the core for a minimal peak fuel temperature during LPCC

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.

Damage Assessment of Heat Resistant Steels through Electron BackScatter Diffraction Strain Analysis under Creep and Creep-Fatigue Conditions

Science.gov (United States)

Fujiyama, Kazunari; Kimachi, Hirohisa; Tsuboi, Toshiki; Hagiwara, Hiroyuki; Ogino, Shotaro; Mizutani, Yoshiki

EBSD(Electron BackScatter Diffraction) analyses were conducted for studying the quantitative microstructural metrics of creep and creep-fatigue damage for austenitic SUS304HTB boiler tube steel and ferritic Mod.9Cr piping steel. KAM(Kernel Average Misorientation) maps and GOS(Grain Orientation Spread) maps were obtained for these samples and the area averaged values KAMave and GOSave were obtained. While the increasing trends of these misorientation metrics were observed for SUS304HTB steel, the decreasing trends were observed for damaged Mod.9Cr steel with extensive recovery of subgrain structure. To establish more universal parameter representing the accumulation of damage to compensate these opposite trends, the EBSD strain parameters were introduced for converting the misorientation changes into the quantities representing accumulated permanent strains during creep and creep-fatigue damage process. As KAM values were dependent on the pixel size (inversely proportional to the observation magnification) and the permanent strain could be expressed as the shear strain which was the product of dislocation density, Burgers vector and dislocation movement distance, two KAM strain parameters MεKAMnet and MεδKAMave were introduced as the sum of product of the noise subtracted KAMnet and the absolute change from initial value δKAMave with dislocation movement distance divided by pixel size. MεδKAMave parameter showed better relationship both with creep strain in creep tests and accumulated creep strain range in creep-fatigue tests. This parameter can be used as the strain-based damage evaluation and detector of final failure.

n-Gram-Based Text Compression

Science.gov (United States)

Duong, Hieu N.; Snasel, Vaclav

2016-01-01

We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods. PMID:27965708

n-Gram-Based Text Compression

Directory of Open Access Journals (Sweden)

Vu H. Nguyen

2016-01-01

Full Text Available We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.

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.

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)

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...

Differential staining of bacteria: gram stain.

Science.gov (United States)

Moyes, Rita B; Reynolds, Jackie; Breakwell, Donald P

2009-11-01

In 1884, Hans Christian Gram, a Danish doctor, developed a differential staining technique that is still the cornerstone of bacterial identification and taxonomic division. This multistep, sequential staining protocol separates bacteria into four groups based on cell morphology and cell wall structure: Gram-positive cocci, Gram-negative cocci, Gram-positive rods, and Gram-negative rods. The Gram stain is useful for assessing bacterial contamination of tissue culture samples or for examining the Gram stain status and morphological features of bacteria isolated from mixed or isolated bacterial cultures. (c) 2009 by John Wiley & Sons, Inc.

Attenuating brain inflammation, ischemia, and oxidative damage by hyperbaric oxygen in diabetic rats after heat stroke

Directory of Open Access Journals (Sweden)

Kai-Li Lee

2013-08-01

Conclusion: Our results suggest that, in diabetic animals, HBO2 therapy may improve outcomes of HS in part by reducing heat-induced activated inflammation and ischemic and oxidative damage in the hypothalamus and other brain regions.

Digital signal processing with kernel methods

CERN Document Server

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

2018-01-01

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

Higher-Order Hybrid Gaussian Kernel in Meshsize Boosting Algorithm

African Journals Online (AJOL)

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

Adaptive Kernel In The Bootstrap Boosting Algorithm In KDE ...

African Journals Online (AJOL)

This paper proposes the use of adaptive kernel in a bootstrap boosting algorithm in kernel density estimation. The algorithm is a bias reduction scheme like other existing schemes but uses adaptive kernel instead of the regular fixed kernels. An empirical study for this scheme is conducted and the findings are comparatively ...

Windows Vista Kernel-Mode: Functions, Security Enhancements and Flaws

Directory of Open Access Journals (Sweden)

Mohammed D. ABDULMALIK

2008-06-01

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

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

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

2016-05-01

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

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

Science.gov (United States)

Tezuka, Taro

2018-06-01

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

An analysis of 1-D smoothed particle hydrodynamics kernels

International Nuclear Information System (INIS)

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

1996-01-01

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

Putting Priors in Mixture Density Mercer Kernels

Science.gov (United States)

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

2004-01-01

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

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...

The effect of a heated skate blade on the ice surface

Energy Technology Data Exchange (ETDEWEB)

Hache, A. [Moncton Univ., NB (Canada). Dept. of Physics and Astronomy

2007-05-15

A new hockey skate using a heated blade, called the Therma Blade, cuts ice friction by half, thereby improving skating performance but has created questions about melting and damage of the ice surface. This paper discussed the effect of the heated skate blade on the ice surface. The paper discussed the thermal power produced by the Therma Blade skate, the ice melting capacity of the therma blade, and the ice temperature profile around the heated blade. It also examined the power dissipation by friction comparing the cold versus the heated blade. Units and definitions as well as conversion factors were also presented in appendix format. Constants and technical specifications were listed in an appendix. It was concluded that the maximum melting capacity of the therma blade is 0.7 grams of ice per skate per minute. This is the upper limit as set by the laws of physics, and this requires the skate to be completely static over ice at 0 degrees Celsius and all the power drawn by the battery to reach the ice friction force. 5 refs., 1 tab., 2 figs.

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....

Mid-infrared spectroscopic assessment of nanotoxicity in gram-negative vs. gram-positive bacteria.

Science.gov (United States)

Heys, Kelly A; Riding, Matthew J; Strong, Rebecca J; Shore, Richard F; Pereira, M Glória; Jones, Kevin C; Semple, Kirk T; Martin, Francis L

2014-03-07

Nanoparticles appear to induce toxic effects through a variety of mechanisms including generation of reactive oxygen species (ROS), physical contact with the cell membrane and indirect catalysis due to remnants from manufacture. The development and subsequent increasing usage of nanomaterials has highlighted a growing need to characterize and assess the toxicity of nanoparticles, particularly those that may have detrimental health effects such as carbon-based nanomaterials (CBNs). Due to interactions of nanoparticles with some reagents, many traditional toxicity tests are unsuitable for use with CBNs. Infrared (IR) spectroscopy is a non-destructive, high throughput technique, which is unhindered by such problems. We explored the application of IR spectroscopy to investigate the effects of CBNs on Gram-negative (Pseudomonas fluorescens) and Gram-positive (Mycobacterium vanbaalenii PYR-1) bacteria. Two types of IR spectroscopy were compared: attenuated total reflection Fourier-transform infrared (ATR-FTIR) and synchrotron radiation-based FTIR (SR-FTIR) spectroscopy. This showed that Gram-positive and Gram-negative bacteria exhibit differing alterations when exposed to CBNs. Gram-positive bacteria appear more resistant to these agents and this may be due to the protection afforded by their more sturdy cell wall. Markers of exposure also vary according to Gram status; Amide II was consistently altered in Gram-negative bacteria and carbohydrate altered in Gram-positive bacteria. ATR-FTIR and SR-FTIR spectroscopy could both be applied to extract biochemical alterations induced by each CBN that were consistent across the two bacterial species; these may represent potential biomarkers of nanoparticle-induced alterations. Vibrational spectroscopy approaches may provide a novel means of fingerprinting the effects of CBNs in target cells.

Distribution of multi-resistant Gram-negative versus Gram-positive bacteria in the hospital inanimate environment.

Science.gov (United States)

Lemmen, S W; Häfner, H; Zolldann, D; Stanzel, S; Lütticken, R

2004-03-01

We prospectively studied the difference in detection rates of multi-resistant Gram-positive and multi-resistant Gram-negative bacteria in the inanimate environment of patients harbouring these organisms. Up to 20 different locations around 190 patients were surveyed. Fifty-four patients were infected or colonized with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant enterococci (VRE) and 136 with multi-resistant Gram-negative bacteria. The environmental detection rate for MRSA or VRE was 24.7% (174/705 samples) compared with 4.9% (89/1827 samples) for multi-resistant Gram-negative bacteria (PGram-positive bacteria were isolated more frequently than Gram-negatives from the hands of patients (PGram-positive and Gram-negative isolates. Our results suggest that the inanimate environment serves as a secondary source for MRSA and VRE, but less so for Gram-negative bacteria. Thus, strict contact isolation in a single room with complete barrier precautions is recommended for MRSA or VRE; however, for multi-resistant Gram-negative bacteria, contact isolation with barrier precautions for close contact but without a single room seems sufficient. This benefits not only the patients, but also the hospital by removing some of the strain placed on already over-stretched resources.

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...

Bruchid egg induced transcript dynamics in developing seeds of black gram (Vigna mungo.

Directory of Open Access Journals (Sweden)

Indrani K Baruah

Full Text Available Black gram (Vigna mungo seeds are a rich source of digestible proteins, however, during storage these seeds are severely damaged by bruchids (Callosobruchus spp., reducing seed quality and yield losses. Most of the cultivated genotypes of black gram are susceptible to bruchids, however, few tolerant genotypes have also been identified but the mechanism of tolerance is poorly understood. We employed Suppression Subtractive Hybridization (SSH to identify specifically, but rarely expressed bruchid egg induced genes in black gram. In this study, Suppression Subtractive Hybridization (SSH library was constructed to study the genes involved in defense response in black gram against bruchid infestation. An EST library of 277 clones was obtained for further analyses. Based on CAP3 assembly, 134 unigenes were computationally annotated using Blast2GOPRO software. In all, 20 defense related genes were subject to quantitative PCR analysis (qPCR out of which 12 genes showed up-regulation in developing seeds of the pods oviposited by bruchids. Few major defense genes like defensin, pathogenesis related protein (PR, lipoxygenase (LOX showed high expression levels in the oviposited population when compared with the non-oviposited plants. This is the first report on defense related gene transcript dynamics during the bruchid-black gram interaction using SSH library. This library would be useful to clone defense related gene(s such as defensin as represented in our library for crop improvement.

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.

Producing standard damaged DNA samples by heating: pitfalls and suggestions.

Science.gov (United States)

Fattorini, Paolo; Marrubini, Giorgio; Bonin, Serena; Bertoglio, Barbara; Grignani, Pierangela; Recchia, Elisa; Pitacco, Paola; Procopio, Francesca; Cantoni, Carolina; Pajnič, Irena Zupanič; Sorçaburu-Cigliero, Solange; Previderè, Carlo

2018-05-15

Heat-mediated hydrolysis of DNA is a simple and inexpensive method for producing damaged samples in vitro. Despite heat-mediated DNA hydrolysis is being widely used in forensic and clinical validation procedures, the lack of standardized procedures makes it impossible to compare the intra and inter-laboratory outcomes of the damaging treatments. In this work, a systematic approach to heat induced DNA hydrolysis was performed at 70 °C for 0-18 h to test the role both of the hydrolysis buffer and of the experimental conditions. Specifically, a trial DNA sample, resuspended in three different media (ultrapure water, 0.1% DEPC-water and, respectively, TE) was treated both in Eppendorf tubes ("Protocol P") and in Eppendorf tubes provided with screwcaps ("Protocol S"). The results of these comparative tests were assessed by normalization of the qPCR results. DEPC-water increased the degradation of the samples up to about 100 times when compared to the ultrapure water. Conversely, the TE protected the DNA from degradation whose level was about 1700 times lower than in samples treated in ultrapure water. Even the employment of the "Protocol S" affected the level of degradation, by consistently increasing it (up to about 180 times in DEPC-water). Thus, this comparative approach showed that even seemingly apparently trivial and often underestimated parameters modify the degradation level up to 2-3 orders of magnitude. The chemical-physical reasons of these findings are discussed together with the role of potential factors such as enhanced reactivity of CO 2 , ROS, NO x and pressure, which are likely to be involved. Since the intra and inter-laboratory comparison of the outcomes of the hydrolytic procedure is the first step toward its standardization, the normalization of the qPCR data by the UV/qPCR ratio seems to be the simplest and most reliable way to allow this. Finally, the supplying (provided with the commercial qPCR kits) of a DNA sample whose degree of

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

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...

Gram positive and Gram negative bacteria differ in their sensitivity to cold plasma

Science.gov (United States)

Mai-Prochnow, Anne; Clauson, Maryse; Hong, Jungmi; Murphy, Anthony B.

2016-12-01

Cold atmospheric-pressure plasma (CAP) is a relatively new method being investigated for antimicrobial activity. However, the exact mode of action is still being explored. Here we report that CAP efficacy is directly correlated to bacterial cell wall thickness in several species. Biofilms of Gram positive Bacillus subtilis, possessing a 55.4 nm cell wall, showed the highest resistance to CAP, with less than one log10 reduction after 10 min treatment. In contrast, biofilms of Gram negative Pseudomonas aeruginosa, possessing only a 2.4 nm cell wall, were almost completely eradicated using the same treatment conditions. Planktonic cultures of Gram negative Pseudomonas libanensis also had a higher log10 reduction than Gram positive Staphylococcus epidermidis. Mixed species biofilms of P. aeruginosa and S. epidermidis showed a similar trend of Gram positive bacteria being more resistant to CAP treatment. However, when grown in co-culture, Gram negative P. aeruginosa was more resistant to CAP overall than as a mono-species biofilm. Emission spectra indicated OH and O, capable of structural cell wall bond breakage, were present in the plasma. This study indicates that cell wall thickness correlates with CAP inactivation times of bacteria, but cell membranes and biofilm matrix are also likely to play a role.

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...

Probabilistic Representations of Solutions to the Heat Equation

Indian Academy of Sciences (India)

In this paper we provide a new (probabilistic) proof of a classical result in partial differential equations, viz. if is a tempered distribution, then the solution of the heat equation for the Laplacian, with initial condition , is given by the convolution of with the heat kernel (Gaussian density). Our results also extend the ...

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....

The comparison of pyrosequencing molecular Gram stain, culture, and conventional Gram stain for diagnosing orthopaedic infections.

Science.gov (United States)

Kobayashi, Naomi; Bauer, Thomas W; Tuohy, Marion J; Lieberman, Isador H; Krebs, Viktor; Togawa, Daisuke; Fujishiro, Takaaki; Procop, Gary W

2006-08-01

We have developed a combined real-time PCR and pyrosequencing assay that successfully differentiated the vast majority of gram-positive and gram-negative bacteria when bacterial isolates were tested. The purpose of this study was to evaluate this assay on clinical specimens obtained from orthopedic surgeries, and to prospectively compare the results of "molecular Gram stain" with culture and conventional direct Gram stain. Forty-five surgical specimens were obtained from patients who underwent orthopedic surgery procedures. The DNA was extracted and a set of broad-range PCR primers that targeted a part of the 16S rDNA gene was used for pan-bacterial PCR. The amplicons were submitted for pyrosequencing and the resulting molecular Gram stain characteristics were recorded. Culture and direct Gram staining were performed using standard methods for all cases. Surgical specimens were reviewed histologically for all cases that had a discrepancy between culture and molecular results. There was an 86.7% (39/45) agreement between the traditional and molecular methods. In 12/14 (85.7%) culture-proven cases of bacterial infection, molecular Gram stain characteristics were in agreement with the culture results, while the conventional Gram stain result was in agreement only for five cases (35.7%). In the 31 culture negative cases, 27 cases were also PCR negative, whereas 4 were PCR positive. Three of these were characterized as gram negative and one as gram positive by this molecular method. Molecular determination of the Gram stain characteristics of bacteria that cause orthopedic infections may be achieved, in most instances, by this method. Further studies are necessary to understand the clinical importance of PCR-positive/culture-negative results.

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.

Analysis of total hydrogen content in palm oil and palm kernel oil using thermal neutron moderation method

International Nuclear Information System (INIS)

Akaho, E.H.K.; Dagadu, C.P.K.; Maaku, B.T.; Anim-Sampong, S.; Kyere, A.W.K.; Jonah, S.A.

2001-01-01

A fast and non-destructive technique based on thermal neutron moderation has been used for determining the total hydrogen content in two types of red palm oil (dzomi and amidze) and palm kernel oil produced by traditional methods in Ghana. An equipment consisting of an 241 Am-Be neutron source and 3 He neutron detector was used in the investigation. The equipment was originally designed for detection of liquid levels in petrochemical and other process industries. Standards in the form of liquid hydrocarbons were used to obtain calibration lines for thermal neutron reflection parameter as a function of hydrogen content. Measured reflection parameters with respective hydrogen content with or without heat treatment of the three edible palm oils available on the market were compared with a brand cooking oil (frytol). The average total hydrogen content in the local oil samples prior to heating was measured to be 11.62 w% which compared well with acceptable value of 12 w% for palm oils in the sub-region. After heat treatment, the frytol oil (produced through bleaching process) had the least loss of hydrogen content of 0.26% in comparison with palm kernel oil of 0.44% followed by dzomi of 1.96% and by amidze of 3.22%. (author)

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.

Influent of Carbonization of Sol Solution at the External Gelation Process on the Quality of Uranium Oxide Kernel

International Nuclear Information System (INIS)

Damunir; Sukarsono

2007-01-01

The influent of carbonization of sol solution at the external gelation process on the quality of uranium oxide kernel was done. Variables observed are the influent of carbon, temperature and time of reduction process of U 3 O 8 kernel resulted from carbonization of sol solution. First of all, uranyl nitrate was reacted with 1 M NH 4 OH solution, producing the colloid of UO 3 . Then by mixing and heating up to the temperature of 60-80 °C, the colloid solution was reacted with PVA, mono sorbitol oleate and paraffin producing of uranium-PVA sol. Then sol solution was carbonized with carbon black of mol ratio of carbon to uranium =2.32-6.62, produce of carbide gel. Gel then washed, dried and calcined at 800 °C for 4 hours to produce of U 3 O 8 kernel containing carbon. Then the kernel was reduced by H 2 gas in the medium of N 2 gas at 500-800 °C, 50 mmHg pressure for 3 hours. The process was repeated at 700 °C, 50 mmHg pressure for 1-4 hours. The characterization of chemical properties of the gel grains and uranium oxide kernel using FTIR covering the analysis of absorption band of infra red spectrum of UO 3 , C-OH, NH 3 , C-C, C-H and OH functional group. The physical properties of uranium oxide covering specific surface area, void volume, mean diameter using surface area meter Nova-1000 and as N 2 gas an absorbent. And O/U ratio of uranium dioxide kernel by gravimetry method. The result of experiment showed that carbonization of sol solution at the external gelation process give influencing the quality of uranium oxide kernel. (author)

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

Science.gov (United States)

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

2017-07-01

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

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

Mitigation of artifacts in rtm with migration kernel decomposition

KAUST Repository

Zhan, Ge

2012-01-01

The migration kernel for reverse-time migration (RTM) can be decomposed into four component kernels using Born scattering and migration theory. Each component kernel has a unique physical interpretation and can be interpreted differently. In this paper, we present a generalized diffraction-stack migration approach for reducing RTM artifacts via decomposition of migration kernel. The decomposition leads to an improved understanding of migration artifacts and, therefore, presents us with opportunities for improving the quality of RTM images.

Realized kernels in practice

DEFF Research Database (Denmark)

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

2009-01-01

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

Anatomically-aided PET reconstruction using the kernel method.

Science.gov (United States)

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

2016-09-21

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

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.

Characterization of microstructure and local deformation in 316NG weld heat-affected zone and stress corrosion cracking in high temperature water

International Nuclear Information System (INIS)

Lu Zhanpeng; Shoji, Tetsuo; Meng Fanjiang; Xue He; Qiu Yubing; Takeda, Yoichi; Negishi, Koji

2011-01-01

Research highlights: → Away from the fusion line, kernel average misorientation and hardness decrease. → Away from the fusion line, the fraction of Σ3 boundaries increases. → Crack growth in high temperature water correlates to kernel average misorientation and hardness. → SCC along random boundaries as well as extensive intergranular branching near the fusion line. - Abstract: Microstructure and local deformation in 316NG weld heat-affected zones were measured by electron-back scattering diffraction and hardness measurements. With increasing the distance from the fusion line, kernel average misorientation decreases and the fraction of Σ3 boundaries increases. Stress corrosion cracking growth rates in high temperature water were measured at different locations in the heat-affected zones that correspond to different levels of strain-hardening represented by kernel average misorientation and hardness distribution. Intergranular cracking along random boundaries as well as extensive intergranular crack branching is observed in the heat-affected zone near the weld fusion line.

Kernel Temporal Differences for Neural Decoding

Science.gov (United States)

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

2015-01-01

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

Collision kernels in the eikonal approximation for Lennard-Jones interaction potential

International Nuclear Information System (INIS)

Zielinska, S.

1985-03-01

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

Classification of maize kernels using NIR hyperspectral imaging

DEFF Research Database (Denmark)

Williams, Paul; Kucheryavskiy, Sergey V.

2016-01-01

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

Influence of wheat kernel physical properties on the pulverizing process.

Science.gov (United States)

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

2014-10-01

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

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.

Markers of muscle damage and performance recovery following exercise in the heat

DEFF Research Database (Denmark)

Nybo, Lars; Girard, Olivier; Mohr, Magni

2013-01-01

PURPOSE: To determine whether competitive intermittent exercise in the heat affects recovery, aggravates markers of muscle fiber damage, and delay the recovery of performance and muscle glycogen stores. METHODS: Plasma creatine kinase, serum myoglobin, muscle glycogen and performance parameters...... (sprint, endurance and neuromuscular testing) were evaluated in 17 semiprofessional soccer players before, immediately after and during 48 h of recovery from a match played in 43°C (HOT) and compared to a control match (21°C with similar turf and set-up). RESULTS: Muscle temperature was ~ 1°C higher (P...

Influenced prior loading on the creep fatigue damage accumulation of heat resistant steels

International Nuclear Information System (INIS)

Kloos, K.H.; Granacher, J.; Scholz, A.

1990-01-01

On two heat resistant power plant steels the influence of prior strain cycling on the creep rupture behaviour and the influence of prior creep loading on the strain cycling behaviour is investigated. These influences concern the number of cycles to failure and the rupture time being the reference values of the generalized damage accumulation rule and they are used for a creep fatigue analysis of the results of long term service-type strain cycling tests. (orig.) [de

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.

The effect of smelting time and composition of palm kernel shell charcoal reductant toward extractive Pomalaa nickel laterite ore in mini electric arc furnace

Science.gov (United States)

Sihotang, Iqbal Huda; Supriyatna, Yayat Iman; Ismail, Ika; Sulistijono

2018-04-01

Indonesia is a country that is rich in natural resources. Being a third country which has a nickel laterite ore in the world after New Caledonia and Philippines. However, the processing of nickel laterite ore to increase its levels in Indonesia is still lacking. In the processing of nickel laterite ore into metal, it can be processed by pyrometallurgy method that typically use coal as a reductant. However, coal is a non-renewable energy and have high enough levels of pollution. One potentially replace is the biomass, that is a renewable energy. Palm kernel shell are biomass that can be used as a reductant because it has a fairly high fix carbon content. This research aims to make nickel laterite ores become metal using palm kernel shell charcoal as reductant in mini electric arc furnace. The result show that the best smelting time of this research is 60 minutes with the best composition of the reductant is 2,000 gram.

Prognostic factors and monomicrobial necrotizing fasciitis: gram-positive versus gram-negative pathogens

Directory of Open Access Journals (Sweden)

Hsu Wei-Hsiu

2011-01-01

Full Text Available Abstract Background Monomicrobial necrotizing fasciitis is rapidly progressive and life-threatening. This study was undertaken to ascertain whether the clinical presentation and outcome for patients with this disease differ for those infected with a gram-positive as compared to gram-negative pathogen. Methods Forty-six patients with monomicrobial necrotizing fasciitis were examined retrospectively from November 2002 to January 2008. All patients received adequate broad-spectrum antibiotic therapy, aggressive resuscitation, prompt radical debridement and adjuvant hyperbaric oxygen therapy. Eleven patients were infected with a gram-positive pathogen (Group 1 and 35 patients with a gram-negative pathogen (Group 2. Results Group 2 was characterized by a higher incidence of hemorrhagic bullae and septic shock, higher APACHE II scores at 24 h post-admission, a higher rate of thrombocytopenia, and a higher prevalence of chronic liver dysfunction. Gouty arthritis was more prevalent in Group 1. For non-survivors, the incidences of chronic liver dysfunction, chronic renal failure and thrombocytopenia were higher in comparison with those for survivors. Lower level of serum albumin was also demonstrated in the non-survivors as compared to those in survivors. Conclusions Pre-existing chronic liver dysfunction, chronic renal failure, thrombocytopenia and hypoalbuminemia, and post-operative dependence on mechanical ventilation represent poor prognostic factors in monomicrobial necrotizing fasciitis. Patients with gram-negative monobacterial necrotizing fasciitis present with more fulminant sepsis.

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....

Gram staining for the treatment of peritonsillar abscess.

Science.gov (United States)

Takenaka, Yukinori; Takeda, Kazuya; Yoshii, Tadashi; Hashimoto, Michiko; Inohara, Hidenori

2012-01-01

Objective. To examine whether Gram staining can influence the choice of antibiotic for the treatment of peritonsillar abscess. Methods. Between 2005 and 2009, a total of 57 cases of peritonsillar abscess were analyzed with regard to cultured bacteria and Gram staining. Results. Only aerobes were cultured in 16% of cases, and only anaerobes were cultured in 51% of cases. Mixed growth of aerobes and anaerobes was observed in 21% of cases. The cultured bacteria were mainly aerobic Streptococcus, anaerobic Gram-positive cocci, and anaerobic Gram-negative rods. Phagocytosis of bacteria on Gram staining was observed in 9 cases. The bacteria cultured from these cases were aerobic Streptococcus, anaerobic Gram-positive cocci, and anaerobic Gram-negative rods. The sensitivity of Gram staining for the Gram-positive cocci and Gram-negative rods was 90% and 64%, respectively. The specificity of Gram staining for the Gram-positive cocci and Gram-negative rods was 62% and 76%, respectively. Most of the Gram-positive cocci were sensitive to penicillin, but some of anaerobic Gram-negative rods were resistant to penicillin. Conclusion. When Gram staining shows only Gram-positive cocci, penicillin is the treatment of choice. In other cases, antibiotics effective for the penicillin-resistant organisms should be used.

Production and detailed characterization of bio-oil from fast pyrolysis of palm kernel shell

International Nuclear Information System (INIS)

Asadullah, Mohammad; Ab Rasid, Nurul Suhada; Kadir, Sharifah Aishah Syed A.; Azdarpour, Amin

2013-01-01

Bio-oil has been produced from palm kernel shell in a fluidized bed reactor. The process conditions were optimized and the detailed characteristics of bio-oil were carried out. The higher feeding rate and higher gas flow rate attributed to higher bio-oil yield. The maximum mass fraction of biomass (57%) converted to bio-oil at 550 °C when 2 L min −1 of gas and 10 g min −1 of biomass were fed. The bio-oil produced up to 500 °C existed in two distinct phases, while it formed one homogeneous phase when it was produced above 500 °C. The higher heating value of bio-oil produced at 550 °C was found to be 23.48 MJ kg −1 . As GC–MS data shows, the area ratio of phenol is the maximum among the area ratio of identified compounds in 550 °C bio-oil. The UV–Fluorescence absorption, which is the indication of aromatic content, is also the highest in 550 °C bio-oil. -- Highlights: • Maximum 56 wt% yield of bio-oil was obtained at 550 °C from palm kernel shell. • Two layer of bio-oil was observed up to 500 °C, while it was one layer above 500 °C. • Bio-oil from palm kernel shell provides more than 40% area ratio of phenol in GC–MS analysis. • The calorific value of palm kernel shell bio-oil is higher than other bio-oil

Selective activation of human heat shock gene transcription by nitrosourea antitumor drugs mediated by isocyanate-induced damage and activation of heat shock transcription factor.

Science.gov (United States)

Kroes, R A; Abravaya, K; Seidenfeld, J; Morimoto, R I

1991-01-01

Treatment of cultured human tumor cells with the chloroethylnitrosourea antitumor drug 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) selectively induces transcription and protein synthesis of a subset of the human heat shock or stress-induced genes (HSP90 and HSP70) with little effect on other stress genes or on expression of the c-fos, c-myc, or beta-actin genes. The active component of BCNU and related compounds appears to be the isocyanate moiety that causes carbamoylation of proteins and nucleic acids. Transcriptional activation of the human HSP70 gene by BCNU is dependent on the heat shock element and correlates with the level of heat shock transcription factor and its binding to the heat shock element in vivo. Unlike activation by heat or heavy metals, BCNU-mediated activation is strongly dependent upon new protein synthesis. This suggests that BCNU-induced, isocyanate-mediated damage to newly synthesized protein(s) may be responsible for activation of the heat shock transcription factor and increased transcription of the HSP90 and HSP70 genes. Images PMID:2052560

Evaluation of spatial and temporal patterns of insect damage and aflatoxin level in the pre-harvest corn fields to improve management tactics.

Science.gov (United States)

Ni, Xinzhi; Wilson, Jeffrey P; Toews, Michael D; Buntin, G David; Lee, R Dewey; Li, Xin; Lei, Zhongren; He, Kanglai; Xu, Wenwei; Li, Xianchun; Huffaker, Alisa; Schmelz, Eric A

2014-10-01

Spatial and temporal patterns of insect damage in relation to aflatoxin contamination in a corn field with plants of uniform genetic background are not well understood. After previous examination of spatial patterns of insect damage and aflatoxin in pre-harvest corn fields, we further examined both spatial and temporal patterns of cob- and kernel-feeding insect damage, and aflatoxin level with two samplings at pre-harvest in 2008 and 2009. The feeding damage by each of the ear/kernel-feeding insects (i.e., corn earworm/fall armyworm damage on the silk/cob, and discoloration of corn kernels by stink bugs) and maize weevil population were assessed at each grid point with five ears. Sampling data showed a field edge effect in both insect damage and aflatoxin contamination in both years. Maize weevils tended toward an aggregated distribution more frequently than either corn earworm or stink bug damage in both years. The frequency of detecting aggregated distribution for aflatoxin level was less than any of the insect damage assessments. Stink bug damage and maize weevil number were more closely associated with aflatoxin level than was corn earworm damage. In addition, the indices of spatial-temporal association (χ) demonstrated that the number of maize weevils was associated between the first (4 weeks pre-harvest) and second (1 week pre-harvest) samplings in both years on all fields. In contrast, corn earworm damage between the first and second samplings from the field on the Belflower Farm, and aflatoxin level and corn earworm damage from the field on the Lang Farm were dissociated in 2009. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

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 ...

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...

Influence of heat processing on the bioaccessibility of zinc and iron from cereals and pulses consumed in India.

Science.gov (United States)

Hemalatha, Sreeramaiah; Platel, Kalpana; Srinivasan, Krishnapura

2007-01-01

Influence of heat processing on the bioaccessibility of zinc and iron from food grains consumed in India was evaluated. Cereals - rice (Oryza sativa), finger millet (Eleusine coracana), sorghum (Sorghum vulgare), wheat (Triticum aestivum), and maize (Zea mays), and pulses - chickpea (Cicer arietinum) - whole and decorticated, green gram (Phaseolus aureus) - whole and decorticated, decorticated black gram (Phaseolus mungo), decorticated red gram (Cajanus cajan), cowpea (Vigna catjang), and French bean (Phaseolus vulgaris) were examined for zinc and iron bioaccessibility by employing an in vitro dialysability procedure. Both pressure-cooking and microwave heating were tested for their influence on mineral bioaccessibility. Zinc bioaccessibility from food grains was considerably reduced upon pressure-cooking, especially in pulses. Among cereals, pressure-cooking decreased zinc bioaccessibility by 63% and 57% in finger millet and rice, respectively. All the pressure-cooked cereals showed similar percent zinc bioaccessibility with the exception of finger millet. Bioaccessibility of zinc from pulses was generally lower as a result of pressure-cooking or microwave heating. The decrease in bioaccessibility of zinc caused by microwave heating ranged from 11.4% in chickpea (whole) to 63% in cowpea. Decrease in zinc bioaccessibility was 48% in pressure-cooked whole chickpea, 45% and 55% in pressure-cooked or microwave-heated whole green gram, 32% and 22% in pressure-cooked or microwave-heated decorticated green gram, and 45% in microwave-heated black gram. Iron bioaccessibility, on the other hand, was significantly enhanced generally from all the food grains studied upon heat treatment. Thus, heat treatment of grains produced contrasting effect on zinc and iron bioaccessibility.

Modeling electro-magneto-hydrodynamic thermo-fluidic transport of biofluids with new trend of fractional derivative without singular kernel

Science.gov (United States)

Abdulhameed, M.; Vieru, D.; Roslan, R.

2017-10-01

This paper investigates the electro-magneto-hydrodynamic flow of the non-Newtonian behavior of biofluids, with heat transfer, through a cylindrical microchannel. The fluid is acted by an arbitrary time-dependent pressure gradient, an external electric field and an external magnetic field. The governing equations are considered as fractional partial differential equations based on the Caputo-Fabrizio time-fractional derivatives without singular kernel. The usefulness of fractional calculus to study fluid flows or heat and mass transfer phenomena was proven. Several experimental measurements led to conclusion that, in such problems, the models described by fractional differential equations are more suitable. The most common time-fractional derivative used in Continuum Mechanics is Caputo derivative. However, two disadvantages appear when this derivative is used. First, the definition kernel is a singular function and, secondly, the analytical expressions of the problem solutions are expressed by generalized functions (Mittag-Leffler, Lorenzo-Hartley, Robotnov, etc.) which, generally, are not adequate to numerical calculations. The new time-fractional derivative Caputo-Fabrizio, without singular kernel, is more suitable to solve various theoretical and practical problems which involve fractional differential equations. Using the Caputo-Fabrizio derivative, calculations are simpler and, the obtained solutions are expressed by elementary functions. Analytical solutions of the biofluid velocity and thermal transport are obtained by means of the Laplace and finite Hankel transforms. The influence of the fractional parameter, Eckert number and Joule heating parameter on the biofluid velocity and thermal transport are numerically analyzed and graphic presented. This fact can be an important in Biochip technology, thus making it possible to use this analysis technique extremely effective to control bioliquid samples of nanovolumes in microfluidic devices used for biological

Training Lp norm multiple kernel learning in the primal.

Science.gov (United States)

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

2013-10-01

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

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

Science.gov (United States)

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

2018-02-13

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

Stochastic subset selection for learning with kernel machines.

Science.gov (United States)

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

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

RTOS kernel in portable electrocardiograph

Science.gov (United States)

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

2011-12-01

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

RTOS kernel in portable electrocardiograph

International Nuclear Information System (INIS)

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

2011-01-01

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

RKRD: Runtime Kernel Rootkit Detection

Science.gov (United States)

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

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

Denoising by semi-supervised kernel PCA preimaging

DEFF Research Database (Denmark)

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

2014-01-01

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

Sentiment classification with interpolated information diffusion kernels

NARCIS (Netherlands)

Raaijmakers, S.

2007-01-01

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

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...

Kinetics of heat-damaged homologous erythrocytes

International Nuclear Information System (INIS)

Dimitriou, P.A.; Depascouale, A.K.; Germenis, A.E.; Antipas, S.E.P.

1990-01-01

A new theoretical five-compartmental model (5CM) was developed for analysis of the clearance of heat-damaged erythroctes (HDE) labelled with chronium 51. Besides the HDE-spleen interaction, this new model also takes into account the interaction between extrasplenic reticuloendothelial (RES) sites and HDE, i.e. the hepatic clearance of fragment erythrocytes (FE). Accordingly, HDE clearance curves are analysed into three exponential components, the fastest of which describes the RES-FE interaction, whereas the others describe the splenic clearance of spherocytes. Therefore, an estimation of the effective liver blood flow for HDE (ELBF) was achieved, along with a series of parameters describing splenic function. The 5CM proved to be more efficient than a previously proposed three-compartmental model (3CM) in the mathematical description of HDE clearance. Comparison was made by applying both models to 37 experimental curves obtained from 20 patients with congenital hemolytic anemias. The values for the splenic function parameters calculated by 5CM analysis and the strong correlations observed among them offer evidence that this model provides an adequate approximation to the real conditions under which HDE clearance takes place. Furthermore, a detailed quantitative analysis of the pooling of spherocytes within the spleen was attempted in this work, and this phenomenon was found to compete with splenic irreversible spherocyte trapping. The ELBF proved to be closely correlated with the hemodynamic splenic parameters, following first-order kinetics, as do low-dose colloids. (orig.)

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 .

Electron beam irradiation: a technology for quarantine disinfestation of green gram seeds against Callsobruchus maculatus

International Nuclear Information System (INIS)

Bhalla, Shashi; Srinivasan, K.; Singh, Subadas; Thakur, Manju; Sharma, S.K.; Pramod, R.; Dwivedi, J.; Bapna, S.C.

2010-01-01

Green gram (Vigna radiata (L.) Wilkzec) an important legume crop in India is grown in 33.4 lakh hectares. India accounts for ∼ 60% of the world's green gram area but contributes only 47% of its production. Major constraint in storage is the pulse beetle Callosobruchus maculatus Fab. (Coleoptera: Bruchidae), which may cause damage upto 100%. It is widespread throughout tropics and sub-tropics with wide host range and also has different strains. Fumigation with methyl bromide (MB) has been the most widely applied management practice for its control. However, the ozone depleting effect of MB has led to restrictions in its use. Therefore, there is a need for an alternative strategy for controlling the pests. Irradiation, an approved technology by International Plant Protection Convention, seems to be a viable non-chemical, residue-free strategy. Therefore, present studies were conducted to see the efficacy of electron beam (EB) irradiation as quarantine disinfestation treatment against green gram seeds infested with different stages of the target pest, C. maculatus

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

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.

Micro- and nano-scale damage on the surface of W divertor component during exposure to high heat flux loads with He

International Nuclear Information System (INIS)

Li, C.; Greuner, H.; Zhao, S.X.; Böswirth, B.; Luo, G.N.; Zhou, X.; Jia, Y.Z.; Liu, X.; Liu, W.

2015-01-01

Micro- and nano-scale surface damage on a W divertor component sample exposed to high heat flux loads generated with He atoms has been investigated through SEM, EBSD, AFM and FIB-SEM. The component sample was supplied by the Institute of Plasma Physics, Chinese Academy of Sciences (ASIPP) and AT&M company, China, and the loading experiment was performed in the GLADIS facility at IPP Garching, Germany. Two typical damage structures were observed on the surface: the first one is characterized by obvious blisters and some grooves formed from ruptured blisters, and the other one is a kind of porous structure accompanying with at least ∼25 nm surface material loss. As the grain orientation is further away from , the damage morphology gradually changes from the former structure to the latter. The possible damage mechanism is discussed. - Highlights: • Two damage structures were observed on W component surface under He beam heating. • Blistering was more obvious in near grains. • Porous structure appeared in the grains away from . • A loose layer caused by He aggregation was formed in near-surface region.

Comparative activity of ceftobiprole against Gram-positive and Gram-negative isolates from Europe and the Middle East: the CLASS study.

Science.gov (United States)

Rossolini, Gian M; Dryden, Matthew S; Kozlov, Roman S; Quintana, Alvaro; Flamm, Robert K; Läuffer, Jörg M; Lee, Emma; Morrissey, Ian; CLASS Study Group

2011-01-01

to assess the in vitro activity of ceftobiprole and comparators against a recent collection of Gram-positive and Gram-negative pathogens, in order to detect potential changes in susceptibility patterns, and to evaluate the Etest assay for ceftobiprole susceptibility testing. contemporary Gram-positive and Gram-negative isolates (excluding extended-spectrum β-lactamase-producing isolates) from across Europe and the Middle East were collected, and their susceptibility to ceftobiprole, vancomycin, teicoplanin, linezolid, ceftazidime and cefepime was assessed using the Etest method. Quality testing [using Etest and broth microdilution (BMD)] was conducted at a central reference laboratory. some 5041 Gram-positive and 4026 Gram-negative isolates were included. Against Gram-positive isolates overall, ceftobiprole had the lowest MIC50 (0.5 mg/L), compared with 1 mg/L for its comparators (vancomycin, teicoplanin and linezolid). Against methicillin-resistant Staphylococcus aureus, all four agents had a similar MIC90 (2 mg/L), but ceftobiprole had a 4-fold better MIC90 (0.5 mg/L) against methicillin-susceptible strains. Only 38 Gram-positive isolates were confirmed as ceftobiprole resistant. Among Gram-negative strains, 86.9%, 91.7% and 95.2% were susceptible to ceftobiprole, ceftazidime and cefepime, respectively. Pseudomonas aeruginosa was less susceptible to all three antimicrobials than any other Gram-negative pathogen. There was generally good agreement between local Etest results and those obtained at the reference laboratory (for ceftobiprole: 86.8% with Gram-negatives; and 94.7% with Gram-positives), as well as between results obtained by BMD and Etest methods (for ceftobiprole: 98.2% with Gram-negatives; and 98.4% with Gram-positives). ceftobiprole exhibits in vitro activity against a wide range of Gram-positive and Gram-negative pathogens, including multidrug-resistant strains. No changes in its known susceptibility profile were identified.

Protamine-induced permeabilization of cell envelopes of gram-positive and gram-negative bacteria

DEFF Research Database (Denmark)

Johansen, Charlotte; Verheul, A.; Gram, Lone

1997-01-01

carboxyfluorescein and ATP after 2 to 5 min. Maximum antibacterial activity was reached at alkaline pH and in the absence of divalent cations. The efficient permeabilization of cell envelopes of both gram-positive and gram-negative bacteria suggests that protamine causes a general disruption of the cell envelope...

Numerical Gram-Schmidt orthonormalization

International Nuclear Information System (INIS)

Werneth, Charles M; Dhar, Mallika; Maung, Khin Maung; Sirola, Christopher; Norbury, John W

2010-01-01

A numerical Gram-Schmidt orthonormalization procedure is presented for constructing an orthonormal basis function set from a non-orthonormal set, when the number of basis functions is large. This method will provide a pedagogical illustration of the Gram-Schmidt procedure and can be presented in classes on numerical methods or computational physics.

A kernel adaptive algorithm for quaternion-valued inputs.

Science.gov (United States)

Paul, Thomas K; Ogunfunmi, Tokunbo

2015-10-01

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

Improving the Bandwidth Selection in Kernel Equating

Science.gov (United States)

Andersson, Björn; von Davier, Alina A.

2014-01-01

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

Point kernels and superposition methods for scatter dose calculations in brachytherapy

International Nuclear Information System (INIS)

Carlsson, A.K.

2000-01-01

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

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

Science.gov (United States)

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

2013-05-01

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

A fractal image analysis methodology for heat damage inspection in carbon fiber reinforced composites

Science.gov (United States)

Haridas, Aswin; Crivoi, Alexandru; Prabhathan, P.; Chan, Kelvin; Murukeshan, V. M.

2017-06-01

The use of carbon fiber-reinforced polymer (CFRP) composite materials in the aerospace industry have far improved the load carrying properties and the design flexibility of aircraft structures. A high strength to weight ratio, low thermal conductivity, and a low thermal expansion coefficient gives it an edge for applications demanding stringent loading conditions. Specifically, this paper focuses on the behavior of CFRP composites under stringent thermal loads. The properties of composites are largely affected by external thermal loads, especially when the loads are beyond the glass temperature, Tg, of the composite. Beyond this, the composites are subject to prominent changes in mechanical and thermal properties which may further lead to material decomposition. Furthermore, thermal damage formation being chaotic, a strict dimension cannot be associated with the formed damage. In this context, this paper focuses on comparing multiple speckle image analysis algorithms to effectively characterize the formed thermal damages on the CFRP specimen. This would provide us with a fast method for quantifying the extent of heat damage in carbon composites, thus reducing the required time for inspection. The image analysis methods used for the comparison include fractal dimensional analysis of the formed speckle pattern and analysis of number and size of various connecting elements in the binary image.

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.

Correlation Between Intercritical Heat-Affected Zone and Type IV Creep Damage Zone in Grade 91 Steel

Science.gov (United States)

Wang, Yiyu; Kannan, Rangasayee; Li, Leijun

2018-04-01

A soft zone in Cr-Mo steel weldments has been reported to accompany the infamous Type IV cracking, the highly localized creep damage in the heat-affected zone of creep-resistant steels. However, the microstructural features and formation mechanism of this soft zone are not well understood. In this study, using microhardness profiling and microstructural verification, the initial soft zone in the as-welded condition was identified to be located in the intercritical heat-affected zone of P91 steel weldments. It has a mixed structure, consisting of Cr-rich re-austenitized prior austenite grains and fine Cr-depleted, tempered martensite grains retained from the base metal. The presence of these further-tempered retained grains, originating from the base metal, is directly responsible for the hardness reduction of the identified soft zone in the as-welded condition. The identified soft zone exhibits a high location consistency at three thermal stages. Local chemistry analysis and thermodynamic calculation show that the lower chromium concentrations inside these retained grains thermodynamically decrease their potentials for austenitic transformation during welding. Heterogeneous grain growth is observed in the soft zone during postweld heat treatment. The mismatch of strengths between the weak Cr-depleted grains and strong Cr-rich grains enhances the creep damage. Local deformation of the weaker Cr-depleted grains accelerates the formation of creep cavities.

Recovery and subsequent characterization of polyhydroxybutyrate from Rhodococcus equi cells grown on crude palm kernel oil

Directory of Open Access Journals (Sweden)

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.

Microwave heat treatment as a substitute for conventional treatment of palm oil fruits

International Nuclear Information System (INIS)

Mujahid H Al-Fayadh; Nor Azura Masabbir Ali

1996-01-01

Microwave energy has become a sound method of heat treatment because of its high penetration power, cleanliness and possible economic significance. In this research, microwave heat was used as a substitute for conventional blanching method of palm oil fruits. Microwave treatment at 2450 MHz and 800 watts gave very close color and frn,frying characteristics to oil of blanched fruits after one minute exposure time. However, five minutes of microwave heat gave severe husk oil discoloration after 49 hours of deep frying, compared to all oils extracted from fruits treated by either low, microwave exposure time or conventional steam treatment. Kernel oil, after five minutes of microwave treatment, was less discolored than both steam or microwave-treated fruits for one minute. More carotenes and discoloration compounds may be contributed to discoloration during microwave treatments. Oil chemical constants of both husk and kernel oils treated by microwave heat were close to those treated by conventional heat. Further research is needed to investigate detailed oil characteristics and evaluate the feasibility study for using microwave energy, as a substitute for conventional heat in palm oil industry

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.

Gram staining apparatus for space station applications

Science.gov (United States)

Molina, T. C.; Brown, H. D.; Irbe, R. M.; Pierson, D. L.

1990-01-01

A self-contained, portable Gram staining apparatus (GSA) has been developed for use in the microgravity environment on board the Space Station Freedom. Accuracy and reproducibility of this apparatus compared with the conventional Gram staining method were evaluated by using gram-negative and gram-positive controls and different species of bacteria grown in pure cultures. A subsequent study was designed to assess the performance of the GSA with actual specimens. A set of 60 human and environmental specimens was evaluated with the GSA and the conventional Gram staining procedure. Data obtained from these studies indicated that the GSA will provide the Gram staining capability needed for the microgravity environment of space.

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

Protein fold recognition using geometric kernel data fusion.

Science.gov (United States)

Zakeri, Pooya; Jeuris, Ben; Vandebril, Raf; Moreau, Yves

2014-07-01

Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for integrating heterogeneous data. Various methods have been proposed to fuse multiple kernels. Most techniques for multiple kernel learning focus on learning a convex linear combination of base kernels. In addition to the limitation of linear combinations, working with such approaches could cause a loss of potentially useful information. We design several techniques to combine kernel matrices by taking more involved, geometry inspired means of these matrices instead of convex linear combinations. We consider various sequence-based protein features including information extracted directly from position-specific scoring matrices and local sequence alignment. We evaluate our methods for classification on the SCOP PDB-40D benchmark dataset for protein fold recognition. The best overall accuracy on the protein fold recognition test set obtained by our methods is ∼ 86.7%. This is an improvement over the results of the best existing approach. Moreover, our computational model has been developed by incorporating the functional domain composition of proteins through a hybridization model. It is observed that by using our proposed hybridization model, the protein fold recognition accuracy is further improved to 89.30%. Furthermore, we investigate the performance of our approach on the protein remote homology detection problem by fusing multiple string kernels. The MATLAB code used for our proposed geometric kernel fusion frameworks are publicly available at http://people.cs.kuleuven.be/∼raf.vandebril/homepage/software/geomean.php?menu=5/. © The Author 2014. Published by Oxford University Press.

Unsupervised multiple kernel learning for heterogeneous data integration.

Science.gov (United States)

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

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

Kernel bundle EPDiff

DEFF Research Database (Denmark)

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

2011-01-01

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

Proteome analysis of the almond kernel (Prunus dulcis).

Science.gov (United States)

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

2016-08-01

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

Localized Multiple Kernel Learning Via Sample-Wise Alternating Optimization.

Science.gov (United States)

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

2014-01-01

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

Control Transfer in Operating System Kernels

Science.gov (United States)

1994-05-13

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

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.

Gram-positive bacteria as an antigen topically applied into gingival sulcus of immunized rat accelerates periodontal destruction.

Science.gov (United States)

Nagano, F; Kaneko, T; Yoshinaga, Y; Ukai, T; Kuramoto, A; Nakatsu, S; Oshino, K; Ichimura, I; Hara, Y

2013-08-01

Periodontitis is generally accepted to relate to gram-negative bacteria, and the host defense system influences its onset and progression. However, little is known about the relation between gram-positive bacteria and periodontitis. In this study, we topically applied gram-positive and gram-negative bacterial suspensions to the gingival sulcus in rats after immunization, and then histopathologically examined their influence on periodontal destruction. Rats previously immunized with heat-treated and sonicated Staphylococcus aureus or Aggregatibacter actinomycetemcomitans were used as immunized groups. The non-immunized group received only sterile phosphate-buffered saline. In each animal, S. aureus or A. actinomycetemcomitans suspension was applied topically to the palatal gingival sulcus of first molars every 24 h for 10 d. Blood samples were collected and the serum level of anti-S. aureus or anti-A. actinomycetemcomitans immunoglobulin G (IgG) antibodies was determined by enzyme-linked immunosorbent assay. The first molar regions were resected and observed histopathologically. Osteoclasts were stained with tartrate-resistant acid phosphatase (TRAP). The formation of immune complexes was confirmed by immunohistological staining of C1qB. Serum levels of anti-S. aureus and anti-A. actinomycetemcomitans IgG antibodies in the immunized groups were significantly higher than those in the non-immunized groups were. The loss of attachment, increase in apical migration of the junctional epithelium, and decreases in alveolar bone level and number of TRAP-positive multinuclear cells in each immunized group were significantly greater than in each non-immunized group. The presence of C1qB was observed in the junctional epithelium and adjacent connective tissue in the immunized groups. Heat-treated and sonicated S. aureus and A. actinomycetemcomitans induced attachment loss in rats immunized with their suspensions. Our results suggest that not only gram-negative but also gram

Antimicrobial Activity of Carbon Nanoparticles Isolated from Natural Sources against Pathogenic Gram-Negative and Gram-Positive Bacteria

International Nuclear Information System (INIS)

Varghese, S.; Jose, S.; Varghese, S.; Kuriakose, S.; Jose, S.

2013-01-01

This paper describes the isolation of carbon nanoparticles (CNPs) from kitchen soot, characterization of the CNPs by UV/visible spectroscopy, SEM and XRD, and their antimicrobial action. The antibacterial activity of the isolated carbon nanoparticles was tested against various pathogenic bacterial strains such as Gram-negative Proteus refrigere and Pseudomonas aeruginosa and Gram-positive Staphylococcus aureus and Streptococcus haemolyticus. The inhibition zones were measured, and it was found that the carbon nanoparticles isolated from natural sources are active against these Gram-negative and Gram-positive bacterial strains

Evaluation of palm kernel fibers (PKFs for production of asbestos-free automotive brake pads

Directory of Open Access Journals (Sweden)

K.K. Ikpambese

2016-01-01

Full Text Available In this study, asbestos-free automotive brake pads produced from palm kernel fibers with epoxy-resin binder was evaluated. Resins varied in formulations and properties such as friction coefficient, wear rate, hardness test, porosity, noise level, temperature, specific gravity, stopping time, moisture effects, surface roughness, oil and water absorptions rates, and microstructure examination were investigated. Other basic engineering properties of mechanical overload, thermal deformation fading behaviour shear strength, cracking resistance, over-heat recovery, and effect on rotor disc, caliper pressure, pad grip effect and pad dusting effect were also investigated. The results obtained indicated that the wear rate, coefficient of friction, noise level, temperature, and stopping time of the produced brake pads increased as the speed increases. The results also show that porosity, hardness, moisture content, specific gravity, surface roughness, and oil and water absorption rates remained constant with increase in speed. The result of microstructure examination revealed that worm surfaces were characterized by abrasion wear where the asperities were ploughed thereby exposing the white region of palm kernel fibers, thus increasing the smoothness of the friction materials. Sample S6 with composition of 40% epoxy-resin, 10% palm wastes, 6% Al2O3, 29% graphite, and 15% calcium carbonate gave better properties. The result indicated that palm kernel fibers can be effectively used as a replacement for asbestos in brake pad production.

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

Biochemical effects of heat shock and caffeine on post-irradiation oxic and anoxic damage in barley seeds of low and high water content

International Nuclear Information System (INIS)

Singh, S.P.; Kesavan, P.C.

1991-01-01

Wet heat shock (60 o C, 90s) and caffeine (3.8 x 10 -4 M) afford significant radioprotection against post-irradiation O 2 -dependent damage which develops in seeds of ∼ 3.5% moisture content. The damage was assessed in terms of seedling injury on the eighth day of growth. An increase in seedling injury is clearly seen, associated with a parallel increase in the peroxidase activity. There is a concomitant decrease in the content of total peroxides. Both these post-irradiation treatments potentiate the O 2 -independent component of seedling injury, irrespective of the seed moisture content. Analysis of the peroxidase activity in the seedlings using non-denaturing polyacrylamide gel electrophoresis reveals that two additional bands appear with the post-irradiation oxic damage. Radioprotection against this damage by caffeine, heat shock and O 2 -free post-irradiation hydration is accompanied by the disappearance of these two additional bands. (author)

The dipole form of the gluon part of the BFKL kernel

International Nuclear Information System (INIS)

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

2007-01-01

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

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

Science.gov (United States)

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

2018-02-19

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

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.

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

Exogenous Cytokinins Increase Grain Yield of Winter Wheat Cultivars by Improving Stay-Green Characteristics under Heat Stress.

Directory of Open Access Journals (Sweden)

Dongqing Yang

Full Text Available Stay-green, a key trait of wheat, can not only increase the yield of wheat but also its resistance to heat stress during active photosynthesis. Cytokinins are the most potent general coordinator between the stay-green trait and senescence. The objectives of the present study were to identify and assess the effects of cytokinins on the photosynthetic organ and heat resistance in wheat. Two winter wheat cultivars, Wennong 6 (a stay-green cultivar and Jimai 20 (a control cultivar, were subjected to heat stress treatment from 1 to 5 days after anthesis (DAA. The two cultivars were sprayed daily with 10 mg L-1 of 6-benzylaminopurine (6-BA between 1 and 3 DAA under ambient and elevated temperature conditions. We found that the heat stress significantly decreased the number of kernels per spike and the grain yield (P < 0.05. Heat stress also decreased the zeatin riboside (ZR content, but increased the gibberellin (GA3, indole-3-acetic acid (IAA, and abscisic acid (ABA contents at 3 to 15 DAA. Application of 6-BA significantly (P < 0.05 increased the grain-filling rate, endosperm cell division rate, endosperm cell number, and 1,000-grain weight under heated condition. 6-BA application increased ZR and IAA contents at 3 to 28 DAA, but decreased GA3 and ABA contents. The contents of ZR, ABA, and IAA in kernels were positively and significantly correlated with the grain-filling rate (P < 0.05, whereas GA3 was counter-productive at 3 to 15 DAA. These results suggest that the decrease in grain yield under heat stress was due to a lower ZR content and a higher GA3 content compared to that at elevated temperature during the early development of the kernels, which resulted in less kernel number and lower grain-filling rate. The results also provide essential information for further utilization of the cytokinin substances in the cultivation of heat-resistant wheat.

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.

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...

Thermotolerance, oxidative stress, apoptosis, heat-shock proteins and damages to reproductive cells of insecticide-susceptible and -resistant strains of the diamondback moth Plutella xylostella.

Science.gov (United States)

Zhang, L J; Chen, J L; Yang, B L; Kong, X G; Bourguet, D; Wu, G

2017-08-01

In this study, we investigated thermotolerance, several physiological responses and damage to reproductive cells in chlorpyrifos-resistant (Rc) and -susceptible (Sm) strains of the diamondback moth, Plutella xylostella subjected to heat stress. The chlorpyrifos resistance of these strains was mediated by a modified acetylcholinesterase encoded by an allele, ace1R, of the ace1 gene. Adults of the Rc strain were less heat resistant than those of the Sm strain; they also had lower levels of enzymatic activity against oxidative damage, higher reactive oxygen species contents, weaker upregulation of two heat shock protein (hsp) genes (hsp69s and hsp20), and stronger upregulation of two apoptotic genes (caspase-7 and -9). The damage to sperm and ovary cells was greater in Rc adults than in Sm adults and was temperature sensitive. The lower fitness of the resistant strain, compared with the susceptible strain, is probably due to higher levels of oxidative stress and apoptosis, which also have deleterious effects on several life history traits. The greater injury observed in conditions of heat stress may be due to both the stronger upregulation of caspase genes and weaker upregulation of hsp genes in resistant than in susceptible individuals.

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.

Biochemical effects of heat shock and caffeine on post-irradiation oxic and anoxic damage in barley seeds of low and high water content

Energy Technology Data Exchange (ETDEWEB)

Singh, S.P.; Kesavan, P.C. (Jawaharlal Nehru Univ., New Delhi (India). School of Life Sciences)

1991-05-01

Wet heat shock (60{sup o}C, 90s) and caffeine (3.8 x 10{sup -4}M) afford significant radioprotection against post-irradiation O{sub 2}-dependent damage which develops in seeds of {similar to} 3.5% moisture content. The damage was assessed in terms of seedling injury on the eighth day of growth. An increase in seedling injury is clearly seen, associated with a parallel increase in the peroxidase activity. There is a concomitant decrease in the content of total peroxides. Both these post-irradiation treatments potentiate the O{sub 2}-independent component of seedling injury, irrespective of the seed moisture content. Analysis of the peroxidase activity in the seedlings using non-denaturing polyacrylamide gel electrophoresis reveals that two additional bands appear with the post-irradiation oxic damage. Radioprotection against this damage by caffeine, heat shock and O{sub 2}-free post-irradiation hydration is accompanied by the disappearance of these two additional bands. (author).

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

Cellular and genetic effects and recovery of heat-damaged cells of Saccharomyces cerevisiae by low intensity electromagnetic radiation at 915 MHz

International Nuclear Information System (INIS)

Sheikh, I.H.

1984-01-01

Studies were conducted on two genetically well known strains of Saccharomyces cerevisiae (Wild Type) and repair deficient mutant (UVS). Results obtained showed clear genetic difference between normal and mutants based on UV sensitivity, percent survival at elevated temperatures and high intensity electromagnetic radiation. At the cellular level, both strains showed a consistent increase in the recovery rate of heat damaged cells when exposed to low intensity FMR as compared to sham (non irradiated cells) at 915 MHz. The percent recovery of wild type was higher than mutant. At the molecular level, the uptake of tritiated uridine into thermally damaged cells which were recovered by low level EMR was significantly higher than sham. Total RNA isolated from irradiated cells and sham showed visible differences in the intensity of RNA bands. Gross quantitative analyses suggest more RNA production in radiation recovered cells as compared to sham. Results presented in this dissertation provide conclusive evidence that low level microwave radiation can be used in the recovery of heat damaged cells

Veillonella, Firmicutes: Microbes disguised as Gram negatives

DEFF Research Database (Denmark)

Vesth, Tammi Camilla; Ozen, Asli; Andersen, Sandra Christine

2013-01-01

Negativicutes, including the genus Veillonella, stain Gram negative. Veillonella are among the most abundant organisms of the oral and intestinal microflora of animals and humans, in spite of being strict anaerobes. In this work, the genomes of 24 Negativicutes, including eight Veillonella spp., are compared......, with the exception of a shared LPS biosynthesis pathway. The clade within the class Negativicutes to which the genus Veillonella belongs exhibits unique properties, most of which are in common with Gram-positives and some with Gram negatives. They are only distantly related to Clostridia, but are even less closely...... related to Gram-negative species. Though the Negativicutes stain Gram-negative and possess two membranes, the genome and proteome analysis presented here confirm their place within the (mainly) Gram positive phylum of the Firmicutes. Further studies are required to unveil the evolutionary history...

Effect of Light-Activated Hypocrellin B on the Growth and Membrane Permeability of Gram-Negative Escherichia coli Cells

Directory of Open Access Journals (Sweden)

Yuan Jiang

2014-01-01

Full Text Available Aim. To investigate the effect of light-activated hypocrellin B on the growth and membrane permeability of Gram-negative bacteria. Methods. Escherichia coli (E. coli as a model bacterium of Gram-negative bacteria was incubated with various concentrations of hypocrellin B for 60 min and was subsequently irradiated by blue light with wavelength of 470 nm at the dose of 12 J/cm2. Colony forming units were counted and the growth inhibition rate of E. coli cells was calculated after light-activated hypocrellin B. Membrane permeability was measured using flow cytometry and confocal laser scanning microscopy (CLSM with propidium iodide (PI staining. Bacterial morphology was observed using transmission electron microscopy (TEM. Reactive oxygen species in bacterial cells were measured using flow cytometry with DCFH-DA staining. Results. Significant growth inhibition rate of E. coli cells was observed after photodynamic action of hypocrellin B. Remarkable damage to the ultrastructure of E. coli was also observed by TEM. Flow cytometry and CLSM observation showed that light-activated hypocrellin B markedly increased membrane permeability of E. coli. Flow cytometry showed the intracellular ROS increase in E. coli treated by photodynamic action of hypocrellin B. Conclusion. Light-activated hypocrellin B caused intracellular ROS increase and structural damages and inhibited the growth of Gram-negative E. coli cells.

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.

Enhancement of radiation damage in germinating wheat seeds by hyperthermia

International Nuclear Information System (INIS)

Guo Fangqing; Gu Ruiqi

1994-01-01

Enhancement of X-ray induced radiation damage in germinating wheat seeds by heat treatment (44 degree C or 41 degree C, 20 min) has been investigated. The enhancement effect of heat treatment after irradiation was more significant than that of heat treatment before irradiation at dose range of 4.3-8.6 Gy. It was observed that germinating wheat seeds were very sensitive to heat treatment within 15 min after irradiation, which indicated that the repair of radiation damage was very active and rapid in a short period after irradiation. The repair of radiation damage in interval of fractionated irradiation was severely inhibited by heat treatment. The sensitivity of seeds to heat treatment corresponded with the levels of their repair activities. The more active the repairs of the seeds are, the more sensitive to heat treatment the seeds show. It was assumed that the enhancement of radiation damage by heat treatment in germinating wheat seeds was attributed to the inhibition of radiation damage repair by heat treatment, which is similar to the results of animal experiments

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.

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)

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.

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.

Dustborne and airborne gram-positive and gram-negative bacteria in high versus low ERMI homes

Science.gov (United States)

The study aimed at investigating Gram-positive and Gram-negative bacteria in moldy and non-moldy homes, as defined by the home's Environmental Relative Moldiness Index (ERMI) value. The ERMI values were determined from floor dust samples in 2010 and 2011 and homes were classified...

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 ...

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...

Potential of plant materials for the management of cowpea bruchid callosobruchus analis (coleoptera: bruchidae) in gram cicer arietinum during storage

International Nuclear Information System (INIS)

Sarwar, M.; Ahmad, N.; Tofique, M.

2012-01-01

Present research was carried out to identify alternatives to synthetic insecticides to control cowpea weevil Callosobruchus analis (F.) population in gram seed (Cicer arietinum L.), during storage. The efficacies of three plant materials such as Nicotiana tabacum, Citrullus colocythis and Aloe vera were assessed to determine their insecticidal activities against survival of bruchid C. analis on seeds of gram varieties viz., CM-98 and Jubiha-1. These plant materials tested reduced weevil infestation and emergence as compared with untreated control seeds. Seeds treatment with A. vera followed by N. tabacum reduced maximum pest damage over C. colocythis, which proved least effective to control C. analis population. Consequently, the tested plant materials should be given due consideration for effective gram protection as a component of integrated pest management approach in storage. (author)

The interaction of parsing rules and argument – Predicate constructions: implications for the structure of the Grammaticon in FunGramKB

Directory of Open Access Journals (Sweden)

María del Carmen Fumero Pérez

2017-07-01

Full Text Available The Functional Grammar Knowledge Base (FunGramKB, (Periñán-Pascual and Arcas-Túnez 2010 is a multipurpose lexico-conceptual knowledge base designed to be used in different Natural Language Processing (NLP tasks. It is complemented with the ARTEMIS (Automatically Representing Text Meaning via an Interlingua–based System application, a parsing device linguistically grounded on Role and Reference Grammar (RRG that transduces natural language fragments into their corresponding grammatical and semantic structures. This paper unveils the different phases involved in its parsing routine, paying special attention to the treatment of argumental constructions. As an illustrative case, we will follow all the steps necessary to effectively parse a For-Benefactive structure within ARTEMIS. This methodology will reveal the necessity to distinguish between Kernel constructs and L1-constructions, since the latter involve a modification of the lexical template of the verb. Our definition of L1-constructions leads to the reorganization of the catalogue of FunGramKB L1-constructions, formerly based on Levin’s (1993 alternations. Accordingly, a rearrangement of the internal configuration of the L1-Constructicon within the Grammaticon is proposed.

Retention of data in heat-damaged SIM cards and potential recovery methods.

Science.gov (United States)

Jones, B J; Kenyon, A J

2008-05-02

Examination of various SIM cards and smart card devices indicates that data may be retained in SIM card memory structures even after heating to temperatures up to 450 degrees C, which the National Institute of Standards and Technology (NIST) has determined to be approximately the maximum average sustained temperature at desk height in a house fire. However, in many cases, and certainly for temperatures greater than 450 degrees C, the SIM card chip has suffered structural or mechanical damage that renders simple probing or rewiring ineffective. Nevertheless, this has not necessarily affected the data, which is stored as charge in floating gates, and alternative methods for directly accessing the stored charge may be applicable.

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.)

Diagnosing periprosthetic infection: false-positive intraoperative Gram stains.

Science.gov (United States)

Oethinger, Margret; Warner, Debra K; Schindler, Susan A; Kobayashi, Hideo; Bauer, Thomas W

2011-04-01

Intraoperative Gram stains have a reported low sensitivity but high specificity when used to help diagnose periprosthetic infections. In early 2008, we recognized an unexpectedly high frequency of apparent false-positive Gram stains from revision arthroplasties. The purpose of this report is to describe the cause of these false-positive test results. We calculated the sensitivity and specificity of all intraoperative Gram stains submitted from revision arthroplasty cases during a 3-month interval using microbiologic cultures of the same samples as the gold standard. Methods of specimen harvesting, handling, transport, distribution, specimen processing including tissue grinding/macerating, Gram staining, and interpretation were studied. After a test modification, results of specimens were prospectively collected for a second 3-month interval, and the sensitivity and specificity of intraoperative Gram stains were calculated. The retrospective review of 269 Gram stains submitted from revision arthroplasties indicated historic sensitivity and specificity values of 23% and 92%, respectively. Systematic analysis of all steps of the procedure identified Gram-stained but nonviable bacteria in commercial broth reagents used as diluents for maceration of periprosthetic membranes before Gram staining and culture. Polymerase chain reaction and sequencing showed mixed bacterial DNA. Evaluation of 390 specimens after initiating standardized Millipore filtering of diluent fluid revealed a reduced number of positive Gram stains, yielding 9% sensitivity and 99% specificity. Clusters of false-positive Gram stains have been reported in other clinical conditions. They are apparently rare related to diagnosing periprosthetic infections but have severe consequences if used to guide treatment. Even occasional false-positive Gram stains should prompt review of laboratory methods. Our observations implicate dead bacteria in microbiologic reagents as potential sources of false-positive Gram

Design, development and evaluation of a divergent roller sizer for almond kernels

Directory of Open Access Journals (Sweden)

D Ghanbarian

2015-09-01

, and Q at the 1% level of confidence. In this work, an increase in the slope of rollers led to a decrease in C ̅_R, whereas at the same time an increase in EW and Q was observed. It may be because at a higher level of slope the almond kernels slip more effectively on rollers surface. This condition restrains the aggregation of kernels on the first part of the gap between the rollers. So, they have enough time to drop through all of the gap. Experimental results show that as the feeding rate increases, C ̅_R and Q increase, whereas EW decreases. Based on the results of the experiments, with an increase of rotation speed of rollers from 50 to 110 rpm, the C ̅_R decreases up to %6.5, and EW decreases about %6. Study of interactions showed effects among which only the interaction of slope and rotation speed of rollers significantly affects all standard criterions. The results also showed that the operation capacity (Q was significantly affected (P≤0.01 by the interaction effects between the feeding rate and the slope of rollers, and the feeding rate and the rotation speed of the rollers. The mechanical damage to almond kernels in the form of external damage such as cracks and scuffing was almost zero, which is a very important advantage of this machine in comparison with the other sizing machines. Conclusions: In this research, a divergent roller sizer was designed, developed and evaluated for almond kernels.The results showed that the best machine operation is obtainedat a feeding rate of 1000 kg 8h-1, slope of 9 degrees and rotation speed of 110 rpm. In this situation, the prototype could reach weighted sorting efficiencies index of 80% and operation capacity of 830 kg in an 8 hour work shift with weighed sorting error index of 23%.

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 ...

Solutions of Cattaneo-Hristov model of elastic heat diffusion with Caputo-Fabrizio and Atangana-Baleanu fractional derivatives

Directory of Open Access Journals (Sweden)

Koca Ilknur

2017-01-01

Full Text Available Recently Hristov using the concept of a relaxation kernel with no singularity developed a new model of elastic heat diffusion equation based on the Caputo-Fabrizio fractional derivative as an extended version of Cattaneo model of heat diffusion equation. In the present article, we solve exactly the Cattaneo-Hristov model and extend it by the concept of a derivative with non-local and non-singular kernel by using the new Atangana-Baleanu derivative. The Cattaneo-Hristov model with the extended derivative is solved analytically with the Laplace transform, and numerically using the Crank-Nicholson scheme.

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

Science.gov (United States)

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.

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

NARCIS (Netherlands)

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

2012-01-01

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

Flour quality and kernel hardness connection in winter wheat

Directory of Open Access Journals (Sweden)

Szabó B. P.

2016-12-01

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

Deep kernel learning method for SAR image target recognition

Science.gov (United States)

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

2017-10-01

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

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

African Journals Online (AJOL)

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

A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

Charara, Ali

2017-06-06

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

A framework for dense triangular matrix kernels on various manycore architectures

KAUST Repository

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

2017-01-01

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

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...

Graphical analyses of connected-kernel scattering equations

International Nuclear Information System (INIS)

Picklesimer, A.

1982-10-01

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

An Ensemble Approach to Building Mercer Kernels with Prior Information

Science.gov (United States)

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

2005-01-01

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

Exploration of Shorea robusta (Sal seeds, kernels and its oil

Directory of Open Access Journals (Sweden)

Shashi Kumar C.

2016-12-01

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

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

Science.gov (United States)

Sumarjaya, I. W.

2017-10-01

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

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

International Nuclear Information System (INIS)

Foerthmann, R.

1979-10-01

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

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

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

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…

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

The gram-negative bacterial periplasm: Size matters.

Directory of Open Access Journals (Sweden)

Samuel I Miller

2018-01-01

Full Text Available Gram-negative bacteria are surrounded by two membrane bilayers separated by a space termed the periplasm. The periplasm is a multipurpose compartment separate from the cytoplasm whose distinct reducing environment allows more efficient and diverse mechanisms of protein oxidation, folding, and quality control. The periplasm also contains structural elements and important environmental sensing modules, and it allows complex nanomachines to span the cell envelope. Recent work indicates that the size or intermembrane distance of the periplasm is controlled by periplasmic lipoproteins that anchor the outer membrane to the periplasmic peptidoglycan polymer. This periplasm intermembrane distance is critical for sensing outer membrane damage and dictates length of the flagellar periplasmic rotor, which controls motility. These exciting results resolve longstanding debates about whether the periplasmic distance has a biological function and raise the possibility that the mechanisms for maintenance of periplasmic size could be exploited for antibiotic development.

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)

Multicenter Assessment of Gram Stain Error Rates.

Science.gov (United States)

Samuel, Linoj P; Balada-Llasat, Joan-Miquel; Harrington, Amanda; Cavagnolo, Robert

2016-06-01

Gram stains remain the cornerstone of diagnostic testing in the microbiology laboratory for the guidance of empirical treatment prior to availability of culture results. Incorrectly interpreted Gram stains may adversely impact patient care, and yet there are no comprehensive studies that have evaluated the reliability of the technique and there are no established standards for performance. In this study, clinical microbiology laboratories at four major tertiary medical care centers evaluated Gram stain error rates across all nonblood specimen types by using standardized criteria. The study focused on several factors that primarily contribute to errors in the process, including poor specimen quality, smear preparation, and interpretation of the smears. The number of specimens during the evaluation period ranged from 976 to 1,864 specimens per site, and there were a total of 6,115 specimens. Gram stain results were discrepant from culture for 5% of all specimens. Fifty-eight percent of discrepant results were specimens with no organisms reported on Gram stain but significant growth on culture, while 42% of discrepant results had reported organisms on Gram stain that were not recovered in culture. Upon review of available slides, 24% (63/263) of discrepant results were due to reader error, which varied significantly based on site (9% to 45%). The Gram stain error rate also varied between sites, ranging from 0.4% to 2.7%. The data demonstrate a significant variability between laboratories in Gram stain performance and affirm the need for ongoing quality assessment by laboratories. Standardized monitoring of Gram stains is an essential quality control tool for laboratories and is necessary for the establishment of a quality benchmark across laboratories. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

An estimation of core damage frequency of a pressurized water reactor during midloop operation due to loss of residual heat removal

International Nuclear Information System (INIS)

Chao, C.C.; Chen, C.T.; Lee, M.

1995-01-01

The core damage frequency caused by loss of residual heat removal (RHR) events was assessed during midloop operation of a Westinghouse-designed three-loop pressurized water reactor. The assessment considers two types of outages (refueling and drained maintenance) and uses failure data collected specifically for shutdown condition. Event trees were developed for five categories of loss of RHR events. Human actions to mitigate the loss of RHR events were identified and human error probabilities were quantified using the human cognitive reliability (HCR) and the technique for human error rate prediction (THERP) models. The results showed that the core damage frequency caused by loss of RHR events during midloop operation was 3.4 x 10 -5 per year. The results also showed that the core damage frequency can be reduced significantly by removing a pressurizer safety valve before entering midloop operation. The establishment of reflux cooling, i.e., decay heat removal through the steam generator secondary side, also plays an important role in mitigating the loss of RHR events during midloop operation

How bacterial cell division might cheat turgor pressure - a unified mechanism of septal division in Gram-positive and Gram-negative bacteria.

Science.gov (United States)

Erickson, Harold P

2017-08-01

An important question for bacterial cell division is how the invaginating septum can overcome the turgor force generated by the high osmolarity of the cytoplasm. I suggest that it may not need to. Several studies in Gram-negative bacteria have shown that the periplasm is isoosmolar with the cytoplasm. Indirect evidence suggests that this is also true for Gram-positive bacteria. In this case the invagination of the septum takes place within the uniformly high osmotic pressure environment, and does not have to fight turgor pressure. A related question is how the V-shaped constriction of Gram-negative bacteria relates to the plate-like septum of Gram-positive bacteria. I collected evidence that Gram-negative bacteria have a latent capability of forming plate-like septa, and present a model in which septal division is the basic mechanism in both Gram-positive and Gram-negative bacteria. © 2017 WILEY Periodicals, Inc.

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...

Propofol alleviate oxidative stress and mitochondrial damage in endothelial cells after heat stress

Directory of Open Access Journals (Sweden)

Li LI

2017-08-01

Full Text Available Objective To explore the protective effect of propofol on endothelial cells during heat stress and its protective effect to mitochondra. Methods Heat stress model of human umbilical vein endothelial cell was established when cells were incubated at 43℃ for 2h, then further incubted at 37℃, 5%CO2 for 6h. The experimental group was subdivided into six groups, including 37℃ group, 37℃ plus intralipid group (negative control group, 37℃ plus propofol group, 43℃ plus propofol group, 43℃ plus intralipid group, H2O2 plus propofol group (positive control group; Pretreated with 50μmol/L propofol, 0.2ml intralipid or 25μmol/L H2O2 before heat stress at 43℃, while the cells in the control group were incubated at 37℃. Cell viability was tested by CCK-8. ROS, mitochondrial membrane potential and the changes in mitochondrial permeability transition pore were determined by flow cytometry. The level of ATP was detected by fluorescein-luciferase. The changes of caspase-9 and caspase-3 were analyzed by Caspase Activity Assay Kit. Results HUVESs cell viability and damage of mitochondra were significantly decreased after heat stress. Compared with 43℃ heat stress group, pretreatment with propofol induced the recovery of cell viability and the ROS levels were significantly decreased in HUVEC cells (P<0.05. Meanwhile, the number of cells representing the decrease of mitochondrial membrane potential (the proportion of JC-1 monomer was significantly decreased (P<0.05 by propofol. The average fluorescence intensity of calcein which representing the MPTP changes and intracellular ATP content was significantly increased (P<0.05. In addition, the activation of mitochondrial apoptotic pathway mediated by caspase-9/3 was also inhibited. Conclusions Propofol have anti-oxidative, anti-apoptosis and mitochondria protective effect against endothelial cell injury during heat stress. DOI: 10.11855/j.issn.0577-7402.2017.06.04

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

NARCIS (Netherlands)

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

2010-01-01

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

Reproducing Kernels and Coherent States on Julia Sets

Energy Technology Data Exchange (ETDEWEB)

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

2007-11-15

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

Reproducing Kernels and Coherent States on Julia Sets

International Nuclear Information System (INIS)

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

2007-01-01

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

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

Science.gov (United States)

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

2017-10-01

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

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

Science.gov (United States)

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

2016-07-07

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